Modern storage systems are complex. Simple direct-attached storage devices are giving way to storage systems that are flexible, network-attached, consolidated and virtualized. Today, storage systems have their own administrators, who use specialized tools and expertise to configure and manage storage resources. As a result, database administrators are no longer in direct control of the design and configuration of their database systems' underlying storage resources. This introduces problems because database physical design and storage configuration are closely related tasks, and the separation makes it more difficult to achieve a good end-to-end design. For instance, the performance of a database system depends strongly on the storage layout of database objects, such as tables and indexes, and the separation makes it hard to design a storage layout that is tuned to the I/O workload generated by the database system. In this thesis we address this problem and attempt to close the information gap between database and storage tiers by addressing the problem of predicting the storage (I/O) workload that will be generated by a database management system. Specifically, we show how to translate a database workload description, together with a database physical design, into a characterization of the I/O workload that will result. Such a characterization can directly be used by a storage configuration tool and thus enables effective end-to-end design and configuration spanning both the database and storage tiers. We then introduce our storage layout optimization tool, which leverages such workload characterizations to generate an optimized layout for a given set of database objects. We formulate the layout problem as a non-linear programming (NLP) problem and use the I/O characterization as input to an NLP solver. We have incorporated our I/O estimation technique into the PostgreSQL database management system and our layout optimization technique into a database layout advisor. We present an empirical assessment of the cost of both tools as well as the efficacy and accuracy of their results.

A modern approach to the treatment of localized disease involves the use of advanced polymeric or ceramic implant materials for controlled-rate drug delivery. These implants are dynamic systems that maintain drug concentrations within the optimal therapeutic window via complex hydration, swelling, and degradation processes. To optimize the performance of these materials, however, requires a fundamental understanding of the mechanisms that govern drug release. Magnetic resonance imaging (MRI) provides a means of non-invasively characterizing the microstructure and transport properties in this type of material, and has proven to be an invaluable tool for their advancement. Calcium polyphosphate (CPP) is a biomaterial that has shown promise as a degradable matrix for drug delivery and bone defect repair. Release rates are potentially governed by hydrogelation, swelling, and polymer chain scission. CPP bioceramics have previously been studied using models for drug elution, but these tend to be simplistic and unable to explain the many interrelated mechanisms. Structural analysis techniques have also been applied, but these tend to be inherently destructive and unable to characterize the material in situ. With the aim of characterizing degradation/drug release mechanisms, a non-invasive approach based on MRI was developed and optimized for imaging two existing types of CPP device. Techniques included mapping of the T1 and T2 relaxation times and the apparent diffusion coefficient (ADC), which together provide sensitivity to local fluid transport parameters. The non-destructive nature of MRI permitted longitudinal observation, and structural degradation effects were investigated by correlation with concurrent drug elution measurements. Temporal variation in the release mechanisms was treated by analyzing elution in stages. Large variation between samples was found, but on average, drug elution that was controlled by a structural-relaxation mechanism appeared correlated with the gradual formation of a highly-mobile ``free'' water component within the disk. Other characteristics, such as swelling rate, did not appear to correlate with drug release at all. While the data did not implicate a singular, governing scheme for drug release from CPP bioceramics, the approach did yield an assessment of the relative importance of the various contributing mechanisms.

This thesis presents an experimental apparatus and methodology for measuring the interface conductance of thermal interface materials (TIMs) as a function of clamping pressure. The experimental apparatus is a steady state characterization device based on the basic premise presented in ASTM D5470 – 06. The setup is designed to develop an approximately one dimensional heat transfer through a TIM sample which is held between two meter bars. The temperature is measured along the meter bars using resistance temperature detectors (RTDs) and the temperature drop across the interface is extrapolated from these measurements and then used to calculate the conductance of the interface. This setup and methodology was used to characterize six commercial TIMs at pressures ranging from 0.17-2.76 MPa (25-400 psi). These TIMs included: Tgrease 880, Tflex 720, Tmate 2905c, Tpcm HP105, Cho-Therm 1671, and Cho-Therm T500. The measured conductance values for the various tests ranged from 0.19 to 5.7 W/cm2K. A three dimensional FEA model of the experimental setup was created in COMSOL Multiphysics 4.2a. This model was compared to the experimental data for a single data point and showed good correlation with the measured temperatures and conductance value.

The physico-chemical characteristics of soymilk particles and the gelation properties of soymilk were investigated as a function of soymilk protein concentration, by preparing soymilk samples from different water-to-bean ratios. Particles from different soymilk protein concentrations showed similar protein composition and surface hydrophobicity, but different -potential, size and protein content. The particle voluminosity was derived using a relation between the effective refractive index of soymilk and the turbidity parameter determined experimentally. For the first time, experimental data was compared to theoretical models, drawing general conclusions about colloidal properties of soymilk particles. Protein concentration and the rate of acidification did not have a significant effect on the acid-induced gelation of soymilk. Results demonstrated that decreased charge is a prerequisite for particle aggregation, which is driven by hydrogen bridging. This thesis provides soymilk processors with general principles on the colloidal behaviour of soymilk, valuable information for new product development and better process design. / Soybean Growers of Ontario, Natural Sciences and Engineering Research Council of Canada

As part of a larger quantitative microbial risk assessment (QMRA) study, the raw water intakes of 8 different drinking water treatment plants in Ontario were sampled for rotavirus. Group A rotavirus was detected and semi-quantified via RT-qPCR. Rotavirus was detected in 6 of 8 drinking water treatment plant raw water intakes at various sampling times during a 2 year period at estimated quantities of 0 – 513 viral genome copies/L water. As hypothesized, the virus counts showed a seasonal tendency with significant detection most likely to occur during the spring months and a correlation with turbidity measurements. To our knowledge this is the first study exploring the presence of rotavirus in Ontario source waters. With new proposed changes to the Health Canada guidelines regarding the viruses in drinking water, data on the presence of rotavirus in source waters is required for assessment of risk to public health. / Kingsclear First Nation

Contractors and tunnelling engineers consistently seek to identify techniques and equipment to improve the efficiency and lower the cost of tunnelling projects. Based on the recent successes of rock slope characterization with laser scanning techniques, the author proposes 3D laser scanning (LiDAR) as a new tool for geotechnical assessment in drill and blast tunnels. It has been demonstrated that practical deployment of a phase-based LiDAR system at the face of an active tunnel heading is possible with a simple tripod setup. With data collection requiring only 5 minutes at the tunnel face, it was shown that this technique could be integrated into geotechnical evaluation without interruption of the excavation cycle. Following the successful scanning at two active tunnelling projects and two completed unlined tunnels, the research explored the applications of the data. With detailed geometric data of the heading as it advanced, the author identified applications of interest to the contractor/on-site engineer as well as the geotechnical engineer or geologist responsible for rockmass characterization. Operational applications included the extraction of information about tunnel geometry and installed support, while geomechanical information provided important elements of rockmass characterization. Building on the success of retrieving joint network information, the research investigated the potential for LiDAR-derived structural databases to be the basis for highly-representative 3D discrete element models. These representative models were found to be useful for back-analysis or as predictive tools for future tunnel design. The primary implications of the thesis are that a) LiDAR data collection at the face of a drill and blast tunnel operation is practical and potentially has great value, b) data extraction is possible for a wide range of applications, and c) that discontinuum stability analysis becomes a much more powerful tool with the integration of LiDAR data. The cumulative result of the work presented is a proposed workflow for integrating LiDAR into tunneling operations. / Thesis (Master, Geological Sciences & Geological Engineering) -- Queen's University, 2010-09-22 19:38:49.401

Plug-in hybrid electric vehicles (PHEV) with all-electric range (AER) combine battery driven electric motors with traditional internal combustion engines in order to reduce emissions emitted to the atmosphere, especially during short, repetitive driving cycles such as commuting to work. A PHEV utilizes grid energy to recharge the electrical energy storage device for use in the AER operation. This study focuses on battery systems as the electrical energy storage device and evaluates commercially available technologies for PHEV through scaled hardware-in-loop (HIL) testing. This project has three main goals: determine the state of technology for PHEV batteries through an extensive literature review, characterize commercially available batteries including simulated HIL response to a real-world PHEV simulation model, and finally, develop a tool to aid in choosing battery types for different vehicle styles (a battery decision matrix). The five different battery types tested are as follows: A123 Lithium Iron Phosphate (LiFePO4) Li-Ion, Genesis Pure Lead-Tin lead acid, generic absorbed glass mat (AGM) valve regulated lead acid (VRLA), SAFT Nickel-Metal Hydride (NiMH) and SAFT Nickel-Cadmium (NiCd). The batteries were characterized in terms of capacity and maximum power as well as tested on an individually scaled real-world duty cycle derived from a model developed by the University of Manitoba and the University of Winnipeg. When comparing the results of the characterization testing with the literature review and manufacturers’ data it was found that there are discrepancies between the batteries tested and the manufacturers’ specifications for mass and capacity. Furthermore, the response to duty cycle testing shows that it is imperative that the internal resistance of the batteries and their conductors should be considered when designing a vehicle, although the literature suggest that this is not commonly done. The results from testing were incorporated into a simple decision matrix factoring in vehicle design constraints, battery performance and cost. Through the duty cycle testing, the dynamic resistance of each of the batteries was determined by measuring the voltage response of the battery to variations in current draw. This resistance figure is important to include in simulations as it effectively reduces available energy the battery can supply due to increasing current demands, as voltage drops in response to a load. / Thesis (Master, Mechanical and Materials Engineering) -- Queen's University, 2011-02-28 15:17:31.209

Humic-based organic compounds containing phenol or benzoic acid groups strongly compete with phosphates for specific binding sites on the surface of these colloidal particles. To study the interactions between phenol groups and the surface binding sites of unmodified or modified colloidal particles, chemical force spectrometry (CFS) was used as a tool to measure the adhesion force between an atomic force microscopy (AFM) tip terminated with a phenol self-assembled monolayer and colloidal particles under varying pH conditions. Two modification methods, co-precipitation and post-precipitation, were used to simulate the naturally-occurring phosphate and humic-acid adsorption process. The pH dependence of adhesion forces between phenol-terminated tip and colloidal particles could be explained by an interplay of electrostatic forces, the surface loading of the modifying phosphate or humic acid species and ionic hydrogen bonding. Polydimethylsiloxane (PDMS) is a widely-used polymer in microfluidic devices. PDMS surfaces are commonly modified to make it suitable for specific microfluidic devices. We studied the surface modification of PDMS using four perfluoroalkyl-triethoxysilane molecules of differing length of perfluorinated alkyl chain. The results show that the length of fluorinated alkyl chain has important effects on the density of surface modifying molecules, surface topography and surface zeta potential. The perfluorinated overlayer makes PDMS more efficient at supporting electroosmotic flow, which has potential applications in microfluidic devices. The kinetic study of RNase A, lysozyme C, α-lactalbumin and myoglobin at different concentrations adsorbed on the self-assembled monolayers of 1-octanethiol (OT-Au) and 1H, 1H, 2H, 2H-perfluorooctyl-1-thiol (FOT-Au) has been carried out. The results show a positive relationship between the lower protein concentration and the increased adsorption rate constant (ka) on both surfaces. At low concentrations, the protein adsorption on an OT-Au surface has greater ka than it on a FOT-Au surface. Comparing ka values for four proteins on OT-Au and FOT-Au surface demonstrates that hard proteins (lysozyme and RNase A) have larger ka than soft proteins (α-lactalbumin and myoglobin) on both surfaces. The discussion is based on the hydrophobicity of OT-Au and FOT-Au surfaces, as well as average superficial hydrophobicity, flexibility, size, stability, and surface induced conformation change of proteins. / Thesis (Ph.D, Chemistry) -- Queen's University, 2011-10-14 21:08:31.617

Ultrasound-based tissue characterization has been an active eld of cancer detection in the past decades. The main concept behind various techniques is that the returning ultrasound echoes carry tissue-dependent information that can be used to distinguish tissue types. Recently, a new paradigm for tissue typing has been proposed which uses ultrasound Radio Frequency (RF) echoes, recorded continuously from a xed location of the tissue, to extract tissue-dependent information. This is hereafter referred to as RF time series. The source of tissue typing information in RF time series is not a well known concept in the literature. However, there are two main hypotheses that describe the informativeness of variations in RF time series. Such information could be partly due to heat induction as a result of consistent eradiation of tissue with ultrasound beams which results in a virtual displacement in RF echoes, and partly due to the acoustic radiation force of ultrasound beams resulting in micro-vibration inside tissue. In this thesis, we further investigate RF time series signals, collected at high frequencies, by analyzing the properties of the RF displacements. It will be shown that such displacements exhibit oscillatory behavior, emphasizing on the possible micro-vibrations inside tissue, as well as linear incremental trend, indicating the e ect of heat absorbtion of tissue. i The main focus of this thesis is to study the oscillatory behavior of RF displace- ments in order to extract tissue-dependent features based on which tissue classi ca- tion is performed. Using various linear and nonlinear tools, we study the properties of such displacements in both frequency and time domain. Nonlinear analysis, based on the theory of dynamical systems, is used to study the dynamical and geometrical properties of RF displacements in the time domain. Using Support Vector Machine (SVM), di erent tissue typing experiments are performed to investigate the capability of the proposed features in tissue classi ca- tion. It will be shown that the combination of such features can distinguish between di erent tissue types almost perfectly. In addition, a feature reduction algorithm, based on principle component analysis (PCA), is performed to reduce the number of features required for a successful tissue classi cation. / Thesis (Master, Electrical & Computer Engineering) -- Queen's University, 2012-03-29 13:52:10.874

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