Modern web services can see well over a billion requests per day. Data and services at such scale require advanced software and large amounts of computational resources to process requests in reasonable time. Advancements in cloud computing now allow us to acquire additional resources faster than in traditional capacity planning scenarios. Companies can scale systems up and down as required, allowing them to meet the demand of their customers without having to purchase their own expensive hardware. Unfortunately, these, now routine, scaling operations remain a primarily manual task. To solve this problem, we present CRAFTS (Cloud Resource Anticipation For Timing Scaling), a system for automatically identifying application throughput and predictive scaling of cloud computing resources based on historical data. We also present ARTS (Automated Request Trace Simulator), a request based workload generation tool for constructing diverse and realistic request patterns for modern web applications. ARTS allows us to evaluate CRAFTS' algorithms on a wide range of scenarios. In this thesis, we outline the design and implementation of both ARTS and CRAFTS and evaluate the effectiveness of various prediction algorithms applied to real-world request data and artificial workloads generated by ARTS.

No description available.

Introduction: Dental implant abutments can be exposed to a variety of oral prophylaxis procedures. Instrumentation of restored dental implants could subject the apical collar of the implant restorative abutment to surface scratching. Scratched surfaces may pose a threat to the integrity of the soft-tissue seal around the apical portion of the abutment which eventually may compromise the alveolar support of the implant. The aim of this study was to objectively measure surface roughness on the apical collar of metal implant abutments induced by probing and scaling instruments. Materials and Methods: 14 standard transmucosal 3 in 1, 4.5 mm diameter abutments made of titanium alloy (BioHorizons, Atlanta, GA) and 4 instruments, UNC-15 metal probe, Periowise plastic probe, McCall SM 17/18 metal scaler and universal plastic scaler were used to conduct the study. 4 abutments were used for non-treated measures and 10 abutments were used for instrumentation measures. All abutments were divided into four sections. Abutments used for instrumentation were treated with one of the four indicated instruments, one instrument per each section. Surface roughness of untreated and treated surfaces was assessed using a contact profilometer. Analysis of variance (ANOVA) was used to compare surface roughness between untreated and treated surfaces. Results: ANOVA showed significant differences in surface roughness between the treated and untreated surfaces (p< 0.0001). Add hoc analysis using Tukey-Kramer HSD test showed no statistical differences between untreated measures and metal probe measures (p>0.05). On the other hand, statistical differences were noted between untreated measures with plastic probe measures (p= 0.05), plastic scaler measures (p=0.05) and metal scaler measures (p=0.05). The metal scaler measures were higher than plastic probe measures (p=0.05), and plastic scaler measures (p=0.05). Conclusions: Probing around implant abutments with a metal probe seems to have no relevant effect on abutment surfaces. In contrast, instrumentation with scalers (both metal and plastic) and plastic probe may cause adverse surface changes. It is not known if these changes have clinical relevance. / Oral Biology

<p> We look for time-dependent solutions to a general class of supergravity models in an arbitrary amount of dimensions. Previously, many static solutions of these models have been found and studied, of which a subclass of these solutions support membrane-like configurations. While many properties of these solutions are known, their dynamics - and therefore stability - are not. We follow this motivation, and investigate the possibility of time dependent solutions that will also support this membrane configuration. Under various conditions, it turns out this is the case, bringing a better understanding to the stability of these branes. In addition, the form of the time dependence found suggest possible applications of supergravity to cosmological models.</p> / Thesis / Master of Science (MSc)

Quantum chemical methods to predict experimental chiroptical properties by solving the time-dependent Schrödinger equation are useful in the assignment of absolute configurations. Chiroptical properties, being very sensitive to the electronic structure of the system, require highly-accurate methods on the one hand and on the other, need to be able to be computed with limited computational resources. The calculation of the optical rotation in the solution phase is complicated by solvent effects. In order to capture those solvent effects, we present a study that uses conformational averaging and time-dependent density functional theory calculations that incorporate solvent molecules explicitly in the quantum mechanical region. While considering several controllable parameters along which the system's optical rotation varies, we find that the sampling of the dynamical trajectory and the density functional chosen have the largest impact on the value of the rotation. In order to eliminate the arbitrariness of the choice of density functional, we would prefer to use coupled cluster theory, a robust and systematically improvable method. However, the high-order polynomial scaling of coupled cluster theory makes it intractable for numerous large calculations, including the conformational averaging required for optical rotation calculations in solution. We therefore attempt to reduce the scaling of a linear response coupled cluster singles and doubles (LR-CCSD) calculation via a perturbed pair natural orbital (PNO++) local correlation approach which uses an orbital space created using a perturbed density matrix. We find that by creating a "combined PNO++" space, incorporating a set of orbitals from the unperturbed pair natural orbital (PNO) space into the PNO++ space, we can obtain well-behaved convergence behavior for both CCSD correlation energies and linear response properties, including dynamic polarizabilities and optical rotations, for the small systems considered. The PNO++ and combined PNO++ methods require aggressive truncation to keep the computational cost low, due to an expensive two-electron integral transformation at the beginning of the calculation. We apply the methods to larger systems than previously studied and refine them for more aggressive truncation by exploring an alternative form of the perturbed density and a perturbation-including weak pair approximation. / Doctor of Philosophy / Theoretical chemistry attempts to provide connections between the structure of molecules and their observable properties. One such family of observables are chiroptical properties, or the effect of the medium on the light which passes through it. These properties include the scattering, absorption and change in polarization of light. Light being classically an electromagnetic field, chiroptical properties can be derived by treating molecules quantum mechanically and the light classically. The prediction of chiroptical properties on computers using the principles of quantum mechanics is still a growing field, being very sensitive to the method used, and requiring considerations of factors such as conformations and anharmonic corrections. Matching experimental properties is an important step in the creation of a reliable method of predicting properties of systems in order to provide more information than can be obtained through experimental observation. This work begins by addressing the problem of matching experimentally obtained quantities. Our results show that current time-intensive methods still fall short in the matching of experimental data. Thus, we then move on to approximating a more robust but computationally expensive method in order to be able to use a more accurate method on a larger scale than is currently possible. On obtaining positive results for small test systems, we test the new method on larger systems, and explore possible improvements to its accuracy and efficiency.

The usefulness of watershed hydrological process models is considerably increased when they can be extrapolated across spatial and temporal scales. This scale transfer problem, meaning the description and prediction of characteristics and processes at a scale different from the one at which observations and measurements are made, and has become the subject of much current research in hydrology and other areas. Quantitative description of fractal scaling behavior of runoff and stream network morphometry in agricultural watersheds has not been previously reported. In the present study, fractal and multifractal scaling of daily runoff rate in four experimental agricultural watersheds and their associated sub-watersheds (32 in total) were investigated. The time series of daily runoff rate were obtained from the database (comprising about 16,600 station years of rainfall and runoff data for small agricultural watersheds across the U.S.) developed by the Hydrological and Remote Sensing Laboratory, Agricultural Research Service, US Department of Agriculture (HRSL/ARS/USDA). Fractal scaling patterns of the Digital Elevation Model (DEM)-extracted stream network morphometry for these four watersheds were also examined. The morphometry of stream networks of four watersheds were obtained by Geographic Information System (GIS) manipulation of digital elevation data downloaded from the most recent (July 2004) U.S. Geological Survey (USGS) National Elevation Dataset (NED). Several threshold values of contribution area for stream initiation were used to extract stream networks for each of the four watersheds. The principal measures of fractal scaling determined for the runoff series were the Hurst exponent obtained by rescaled range (R/S) analysis, the fractal dimension estimated by the shifted box-counting method, and the multifractal scaling function parameters (a and C1) of the Universal Multifractal Model (UMM). Corresponding measures for the DEM-extracted stream networks at each threshold value were the fractal dimension estimated using the box-counting technique and the Horton ratios of the network. Daily runoff rate exhibited strong long-term dependence and scale invariance over certain time scales. The same fractal dimensions and Hurst exponents were obtained for the sub-watersheds within each watershed. Runoff exhibited multifractal behavior that was well described by UMM. The multifractal parameters a (quantifies how far the process is from monofractality) and C1 (characterizes the sparseness or inhomogeneity of the mean of the process) were reasonably close to each other for sub-watersheds within a watershed and were generally similar among four watersheds. For the DEM-extracted networks, the morphometric attributes and Horton ratios as well as their fractal dimensions were dependent on the threshold values of contribution area used in the extraction process. The fractal dimensions were almost identical for DEM-extracted stream networks of the four watersheds. The DEM-extracted stream network displayed a single scaling pattern, rather than multifractal behavior. Explanation of the physical significance of fractal characteristics of the stream network in relation to runoff time series would require more data than were available in this study. / Ph. D.

Evaluated were correlated responses to 54-generations of divergent selection for 8-week body weight (BW) and of BW at other ages and reproductive traits. Evaluated first was the influence of scaling on phenotypic responses to selection, phenotypic correlations of means and standard deviations, and unadjusted vs. standardized responses. Measured was BW at 4 (BW4), 8 (BW8), 24 (BW24), and 38 (BW38) weeks of age. Correlations between means and standard deviations were positive and greater in the LWS than HWS. Scaling masked the degree more than the pattern of response and was line specific with the magnitude of response greater in the LWS than HWS. While BW ratios across ages were not influenced by scaling in LWS, they were evident in HWS. Also measured were correlated responses of reproductive traits in selected and relaxed lines. Traits were age at first egg (AFE), body weight at first egg (WFE), their ratio (WAFE), and hen-day normal egg production (HDP). Although sexual maturity was delayed, the effect was more pronounced in the low than high weight lines. Selection for low BW decreased WFE, WAFE and HDP. Selection for high BW resulted in lower HDP, while WFE and WAFE were generally higher. Minimum AFE, WFE and WAFE in relation to sexual maturity were line specific. Opposition between relaxed and artificial selection resulted in a higher reproductive performance and fitness with relaxed than artificial selection. Overall, results demonstrate that correlated responses to long-term divergent selection were masked by scaling and negative correlated reproductive responses. / Master of Science

Magnitude Scaling Factors (MSF) account for the durational effects of strong ground shaking on the inducement of liquefaction within the simplified liquefaction evaluation procedure which is the most commonly used approach for assessing liquefaction potential worldwide. Within the context of the simplified procedure, the spatial variation in the seismic demand imposed on the soil traditionally has been assumed to be solely a function of the spatial variation of the peak amplitude of the ground motions and the characteristics of the soil profile. Conversely, MSF have been solely correlated to earthquake magnitude. This assumption fails to appreciate the inverse correlation between the peak amplitude of ground motions and strong ground motion duration, and thus MSF would seemingly vary spatially. The combination of well-documented liquefaction response during the Darfield and Christchurch, New Zealand, earthquakes, densely-recorded ground motions for the events, and detailed subsurface characterization provides an unprecedented opportunity to investigate the significance of the spatial variation of MSF on the inducement of liquefaction. Towards this end, MSF were computed at 15 strong motion recording station sites across Christchurch and its surroundings using two established approaches. Trends in the site and spatial variation of the MSF computed for both the Darfield and Christchurch earthquakes are scrutinized and their implications on liquefaction evaluations are discussed. / Master of Science

As improving technology is making it easier to select or engineer DNA sequences that produce dangerous proteins, it is important to be able to predict whether a novel DNA sequence is potentially dangerous by determining its taxonomic identity and functional characteristics. These tasks can be facilitated by the ever increasing amounts of available biological data. Unfortunately, though, these growing databases can be difficult to take full advantage of due to the corresponding increase in computational and storage costs. Entropy scaling algorithms and data structures present an approach that can expedite this type of analysis by scaling with the amount of entropy contained in the database instead of scaling with the size of the database. Because sets of DNA and protein sequences are biologically meaningful instead of being random, they demonstrate some amount of structure instead of being purely random. As biological databases grow, taking advantage of this structure can be extremely beneficial. The entropy scaling sequence similarity search algorithm introduced here demonstrates this by accelerating the biological sequence search tools BLAST and DIAMOND. Tests of the implementation of this algorithm shows that while this approach can lead to improved query times, constructing the required entropy scaling indices is difficult and expensive. To improve performance and remove this bottleneck, I investigate several ideas for accelerating building indices that support entropy scaling searches. The results of these tests identify key tradeoffs and demonstrate that there is potential in using these techniques for sequence similarity searches. / Master of Science / As biological organisms are created and discovered, it is important to compare their genetic information to known organisms in order to detect possible harmful or dangerous properties. However, the collection of published genetic information from known organisms is huge and growing rapidly, making it difficult to search. This thesis shows that it might be possible to use the non-random properties of biological information to increase the speed and efficiency of searches; that is, because genetic sequences are not random but have common structures, the increase of known data does not mean a proportional increase in complexity, known as entropy. Specifically, when comparing a new sequence to a set of previously known sequences, it is important to choose the correct algorithms for comparing the similarity of two sequences, also known as the distance between them. This thesis explores the performance of entropy scaling algorithm compared to several conventional tools.

Dynamic voltage and frequency scaling (DVFS) is an extensively studied energy manage ment technique, which aims to reduce the energy consumption of computing platforms by dynamically scaling the CPU frequency. Real-Time DVFS (RT-DVFS) is a branch of DVFS, which reduces CPU energy consumption through DVFS, while at the same time ensures that task time constraints are satisfied by constructing appropriate real-time task schedules. The literature presents numerous RT-DVFS scheduling algorithms, which employ different techniques to utilize the CPU idle time to scale the frequency. Many of these algorithms have been experimentally studied through simulations, but have not been implemented on real hardware platforms. Though simulation-based experimental studies can provide a first-order understanding, implementation-based studies can reveal actual timeliness and energy consumption behaviours. This is particularly important, when it is difficult to devise accurate simulation models of hardware, which is increasingly the case with modern systems. In this thesis, we study the timeliness and energy consumption behaviours of fourteen state- of-the-art RT-DVFS schedulers by implementing and evaluating them on two hardware platforms. The schedulers include CC-EDF, LA-EDF, REUA, DRA andd AGR1 among others, and the hardware platforms include ASUS laptop with the Intel I5 processor and a mother- board with the AMD Zacate processor. We implemented these schedulers in the ChronOS real-time Linux kernel and measured their actual timeliness and energy behaviours under a range of workloads including CPU-intensive, memory-intensive, mutual exclusion lock-intensive, and processor-underloaded and overloaded workloads. Our studies reveal that measuring the CPU power consumption as the cube of CPU frequency can lead to incorrect conclusions. In particular, it ignores the idle state CPU power consumption, which is orders of magnitude smaller than the active power consumption. Consequently, power savings obtained by exclusively optimizing active power consumption (i.e., RT-DVFS) may be offset by completing tasks sooner by running them at the highest frequency and transitioning to the idle state earlier (i.e., no DVFS). Thus, the active power consumption savings of the RT-DVFS techniques' that we report are orders of magnitude smaller than their simulation-based savings reported in the literature. / Master of Science