The mechanical responses of the comminuted ceramic under impact is important in understanding penetration resistance of the target, modeling the penetration process, developing ceramic models and designing better armor systems. To determine the dynamic compressive responses of ceramic rubbles, a novel loading/reloading feature in SHPB experiments was developed to produce two consecutive loading pulses in a single dynamic experiment with two strikers and two shapers. The first pulse pulverizes the intact specimen into rubble after characterizing the intact material. After unloading of the first pulse, a second pulse loads the comminuted specimen and gives the dynamic constitutive behavior of the rubble.With this new experimental technique, several series of experiments were conducted on an oxide ceramic -- alumina AD995 and a non-oxide ceramic--hot pressed silicon carbide, SiC-N, with different strain rates, various volume dilatations and damaged levels under 26 MPa, 56 MPa and 104 MPa confinement. The results show that the strength of the damaged ceramic is not very sensitive to strain rates within this research range and the pulse separation once the damage attains a critical level. When slightly damaged far below a critical level, the specimen remains nearly elastic; when transitionally damaged, the specimen strength gradually decrease from the slight damage level to the heavy damage level. Increasing confinement increases the strength of the ceramics. The crack patterns were dominantly axial splitting for the slight damage, axial splitting and fragmentation for the intermediate damage, and fragmentation and comminution for the heavy damage. For SiC-N, the volume dilatation history shows a delayed failure. SEM observations indicated that microstructural failure mechanism is intergranular fracture for alumina and transgranular fracture for SiC-N.Mohr-Coulomb criterion was successfully employed to describe the damaged ceramic and the parameters were determined. JH-1 model was employed to describe the failed SiC-N in the linearly segmentation description of the strength and the parameters were also determined. Through the analysis of JH-1 model for SiC-N, the critical damage level can be taken as D = 1.0. JH-2 model was used to describe analytically the damaged AD995 and the parameters were obtained. The critical damage value is 0.88 for alumina determined directly from JH-2 model. The description of JH-1 model is equivalent to Mohr-Coulomb criterion while it is unsuitable for JH-2 model due to the non-linear description. Based on the analysis of existing models and current experimental data, an empirical constitutive material model was developed for the damaged ceramic, which well described the completely damaged ceramic, but was unable to model the partially damaged ceramic.

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With the increasing demand for more wireless multimedia applications, it is desired to design a wireless system with higher data rate. Furthermore, the frequency spectrum has become a limited and valuable resource, making it necessary to utilize the available spectrum efficiently and coexist with other wireless systems. Orthogonal frequency division multiplexing (OFDM) modulation is widely used in communication systems to meet the demand for ever increasing data rates. The major advantage of OFDM over single-carrier transmission is its ability to deal with severe channel conditions without complex equalization. However, OFDM systems suffer from a high peak to average power ratio, and they are sensitive to carrier frequency offset and Doppler spread. This dissertation first focuses on the development of intercarrier interference (ICI) reduction and signal detection algorithms for OFDM systems over time-varying channels. Several ICI reduction algorithms are proposed for OFDM systems over doubly-selective channels. The OFDM ICI reduction problem over time-varying channels is formulated as a combinatorial optimization problem based on the maximum likelihood (ML) criterion. First, two relaxation methods are utilized to convert the ICI reduction problem into convex quadratic programming (QP) problems. Next, a low complexity ICI reduction algorithm applicable to $M$-QAM signal constellations for OFDM systems is proposed. This formulates the ICI reduction problem as a QP problem with non-convex constraints. A successive method is then utilized to deduce a sequence of reduced-size QP problems. For the proposed algorithms, the QP problems are solved by limiting the search in the 2-dimensional subspace spanned by its steepest-descent and Newton directions to reduce the computational complexity. Furthermore, a low-bit descent search (LBDS) is employed to improve the system performance. Performance results are given to demonstrate that the proposed ICI reduction algorithms provide excellent performance with reasonable computational complexity. A low complexity joint semiblind detection algorithm based on the channel correlation and noise variance is proposed which does not require channel state information. The detection problem is relaxed to a continuous non-convex quadratic programming problem. Then an iterative method is utilized to deduce a sequence of reduced-size quadratic programming problems. A LBDS method is also employed to improve the solution of the derived QP problems. Results are given which demonstrate that the proposed algorithm provides similar performance with lower computational complexity compared to that of a sphere decoder. A major challenge to OFDM systems is how to obtain accurate channel state information for coherent detection of the transmitted signals. Thus several channel estimation algorithms are proposed for OFDM systems over time-invariant channels. A channel estimation method is developed to utilize the noncircularity of the input signals to obtain an estimate of the channel coefficients. It takes advantage of the nonzero cyclostationary statistics of the transmitted signals, which in turn allows blind polynomial channel estimation using second-order statistics of the OFDM symbol. A set of polynomial equations are formulated based on the correlation of the received signal which can be used to obtain an estimate of the time domain channel coefficients. Performance results are presented which show that the proposed algorithm provides better performance than the least minimum mean-square error (LMMSE) algorithm at high signal to noise ratios (SNRs), with low computational complexity. Near-optimal performance can be achieved with large OFDM systems. Finally, a CS-based time-domain channel estimation method is presented for OFDM systems over sparse channels. The channel estimation problem under consideration is formulated as a small-scale $l_1$-minimization problem which is convex and admits fast and reliable solvers for the globally optimal solution. It is demonstrated that the magnitudes as well as delays of the significant taps of a sparse channel model can be estimated with satisfactory accuracy by using fewer pilot tones than the channel length. Moreover, it is shown that a fast Fourier transform (FFT) matrix of extended size can be used as a set of appropriate basis vectors to enhance the channel sparsity. This technique allows the proposed method to be applicable to less-sparse OFDM channels. In addition, a total-variation (TV) minimization based method is introduced to provide an alternative way to solve the original sparse channel estimation problem. The performance of the proposed method is compared to several established channel estimation algorithms. / Graduate

Summary Background The cementation of crowns to dental implant abutments is an accepted form of crown retention that requires consideration of the properties of available cements within the applied clinical context. Most current dental cements were developed primarily for use with natural tooth crowns, but must act in a different manner with implant components. Cements are exposed to a number of stressors that may reduce crown retention in vivo, not the least of which is occlusal loading. This study investigated the influence of compressive cyclic loading on the physical retention of cast crown copings cemented to implant abutments. Method Cast crown copings were cemented to Straumann synOcta titanium implant abutments with three different readily used and available cements. Specimens were placed in a humidifier, thermocycled and subjected to one of four quantities of compressive cyclic loading. The uniaxial tensile force required to remove the cast crown copings was then recorded. Data analysis was conducted using two-way ANOVA and paired post tests. Results Statistical analysis arising from post tests following two-way ANOVA testing revealed the mean retention values for crown copings cemented with Panavia-F cement (5.103, 2.681, 3.178, 2.986MPa) were statistically significantly greater than both KetacCem (0.646, 0.701, 1.083, 0.914MPa) and TempBond non–eugenol (0.074, 0.181, 0.190, 0.303MPa) cements at each compressive cyclic loading quantity. KetacCem and TempBond non–eugenol cements produced relatively low mean retention values that were not statistically significantly different at each quantity of compressive cyclic loading. Compressive cyclic loading had a statistically significant effect on Panavia-F specimens alone, but increased loading quantities produced no further statistically significant difference in mean retention. Compressive cyclic loading had no overriding statistically significant effect on the retention of all specimens as a population. Conclusions Within the limitations of the current in vitro conditions employed in this study, the retention of cast crown copings cemented to Straumann synOcta implant abutments with Panavia-F, KetacCem, and TempBond non-eugenol was significantly affected by cement type but not compressive cyclic loading. Panavia-F is the cement of choice for the definitive non-retrievable cementation of cast crown copings to Straumann synOcta implant abutments out of the three cements tested. The implications of these results relate to the choice of cement to provide the desired crown coping retention. / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1349966 / Thesis (D.Clin.Dent.) -- University of Adelaide, School of Dentistry, 2008

Compressed sensing (CS) is an innovative approach of signal processing that facilitates sub-Nyquist processing of bio-signals, such as a neural signal, electrocardiogram (ECG), and electroencephalogram (EEG). This strategy can be used to lower the data rate to realize ultra-low-power performance, As the count of recording channels increases, data volume is increased resulting in impermissible transmitting power. This thesis work presents the implementation of a CMOS-based front-end design with the CS in the standard 180 nm CMOS process. A novel pseudo-random sequence generator is proposed, which consists of two different types of D flip-flops that are used for obtaining a completely random sequence. This thesis work also includes the (reverse electrowetting-on-dielectric) REWOD based energy harvesting model for self-powered bio-sensor which utilizes the electrical energy generated through the process of conversion of mechanical energy to electrical energy. This REWOD based energy harvesting model can be a good alternative to battery usage, particularly for the bio-wearable applications. The comparative analysis of the results generated for voltage, current and capacitance of the rough surface model is compared to that of results of planar surface REWOD.

Η παρούσα εργασία χωρίζεται σε δύο μέρη. Στο πρώτο μέρος μελετάμε το αντικείμενο της Συμπιεσμένης καταγραφής. Το κείμενο εστιάζει στα βασικότερα σημεία της θεωρίας γύρω από την ανακατασκευή αραιών σημάτων από λίγες μετρήσεις, ενώ γίνεται και μία ανασκόπηση των τεχνικών ανακατασκευής. Στο δεύτερο μέρος παρουσιάζονται τα αποτελέσματα της ερευνητικής προσπάθειας γύρω από συγκεκριμένα προβλήματα ανακατασκευής. / -

Early and accurate prediction of the compressive strength of concrete is important in the construction industry. Modeling the compressive strength of concrete to obtain a balance and equality between prediction accuracy, time and uncertainty of the prediction is a very difficult task due to the highly nonlinear nature of concrete. For structural engineering purposes, the 28- day compressive strength is the most relevant parameter. In this study, an attempt has been made to predict the 28-day compressive strength of concrete using Relevance Vector Machine (RVM). An RVM belongs to the class of sparse kernel classifiers, which are powerful tools in classification and regression. It has a model of identical functional form to the popular and state-of-the-art `Support Vector Machine (SVM)'. The benefits of using RVM include automatic estimation of nuisance parameters, probabilistic prediction and the ability to model complex data with little information. A total of 425 different data of high performance mix designs were collected from the University of California, Irvine repository. The data used to predict the compressive strength consisted of nine components. The RVM model was trained and tested using 395 and 30 data sets respectively. The model's performance was assessed at the end of the training and testing period using four performance measures; coefficient of determination, root-mean-square error, percentage of relevance vectors and residual plots. All the performance measures confirmed the accuracy of the model. The results of the study suggested that RVM is an effective tool for predicting the 28- day compressive strength of concrete from its mix ingredients.

Made available in DSpace on 2015-08-20T17:09:28Z (GMT). No. of bitstreams: 0 Previous issue date: 2014-06-27. Added 1 bitstream(s) on 2015-08-20T17:27:08Z : No. of bitstreams: 1 000844276.pdf: 29036188 bytes, checksum: 616a25863a975b7bbef55bbbb94efb03 (MD5) / O concreto celular, que se caracteriza por ter um peso próprio reduzido pela incorporação artificial de ar no concreto, pode constituir uma alternativa ao concreto armado nas estruturas de pequeno e médio porte. A baixa solicitação dos elementos estruturais permite aproveitar as principais vantagens do material: melhoria da isolação, economia de material para produzir o concreto e facilidade do transporte dos elementos pré-moldados. A fim de conhecer melhor o desempenho mecânico do material para aplicações estruturais, o presente trabalho trata da avaliação da aderência entre o concreto celular e as barras de aço. Para estudar esse fenômeno, foram realizados ensaios de arrancamento com barras de diâmetro igual a 4,2 mm, parcialmente imersas em corpos-de-prova de concreto cilíndrico. A variação da massa específica do concreto e a presença ou não de uma barra transversal dentro do cilindro constituem as variáveis da pesquisa. No total foram realizados três tipos de concreto, com massa específica aparente aos 28 dias de 2255, 1565 e 1510 kg/m 3 . Entre outros resultados, a pesquisa revelou, pelo arrancamento de barras simples de diâmetro igual a 4,2 mm, o forte decréscimo da tensão de aderência junto com o rebaixamento da massa específica aparente do concreto. Confrontando os resultados com trabalhos semelhantes, a elevada relação água/cimento parece ser o parâmetro que mais influenciou os resultados. Também, parâmetros que podem ter influenciado a tensão de aderência são a quantidade de agente espumígeno colocada nos concretos, a utilização de agregado graúdo e talvez o diâmetro das barras arrancadas. A introdução da barra transversal no meio do cilindro permitiu obter um ganho de resistência ao arrancamento da barra longitudinal, que cresceu junto com o rebaixamento da massa específica do concreto celular. Assim, a utilização de ancoragens especiais (não exclusivamente retas), que permite... / Cellular concrete is a lightweight concrete obtained by aerating agent, which produces air-voids into the mixture. Low loads acting on houses or small buildings permits to use cellular concrete advantages: good thermal insulation, lower concrete production costs and simplification of precast transportation. To improve the mechanical characteristic of structural cellular concrete knowledge, this work deals with bond between cellular concrete and steel rebars. Pull-out tests of 4,2 mm diameter rebars partly immersed into concrete cylinders were made. Concrete unit weight variation and setting of a transverse rebar into the concrete cylinder center constitute the variables of the work. Three types of mixture were prepared: one without aerating agent (with a dry unit weight of 2255 kg/m 3 ), and two with different aerating agent rates (with a dry unit weight equal to 1565 and 1510 kg/m 3 ). One of the conclusions of the study is the large decrease of bond stress between 4,2 diameter rebars and cellular concrete, due to concrete unit weight reduction. Comparison of results with others studies reveals that water/cement ratio could be the main variable which influences bond stress. Moreover, other variables like aerating agent quantity introduced into the mixture, coarse aggregate use or rebar diameter could influence the bond stress value. Transverse rebar introduced into concrete cylinder center increased the ultimate pull-out force of the test: the gain of bond produced by the transverse rebar grew up when the cellular concrete unit weight had been reduced. Therefore, special anchorages (not exclusively straight), permitting bond improvement between cellular concrete and 4,2 mm diameter rebar could be a solution to improve the mechanical performance of cellular concrete

abstract: As a promising solution to the problem of acquiring and storing large amounts of image and video data, spatial-multiplexing camera architectures have received lot of attention in the recent past. Such architectures have the attractive feature of combining a two-step process of acquisition and compression of pixel measurements in a conventional camera, into a single step. A popular variant is the single-pixel camera that obtains measurements of the scene using a pseudo-random measurement matrix. Advances in compressive sensing (CS) theory in the past decade have supplied the tools that, in theory, allow near-perfect reconstruction of an image from these measurements even for sub-Nyquist sampling rates. However, current state-of-the-art reconstruction algorithms suffer from two drawbacks -- They are (1) computationally very expensive and (2) incapable of yielding high fidelity reconstructions for high compression ratios. In computer vision, the final goal is usually to perform an inference task using the images acquired and not signal recovery. With this motivation, this thesis considers the possibility of inference directly from compressed measurements, thereby obviating the need to use expensive reconstruction algorithms. It is often the case that non-linear features are used for inference tasks in computer vision. However, currently, it is unclear how to extract such features from compressed measurements. Instead, using the theoretical basis provided by the Johnson-Lindenstrauss lemma, discriminative features using smashed correlation filters are derived and it is shown that it is indeed possible to perform reconstruction-free inference at high compression ratios with only a marginal loss in accuracy. As a specific inference problem in computer vision, face recognition is considered, mainly beyond the visible spectrum such as in the short wave infra-red region (SWIR), where sensors are expensive. / Dissertation/Thesis / Masters Thesis Electrical Engineering 2015