Measurement of Training Intensity and Work During Submaximal Isokinetic Progressive Resistance Training Protocols

Physical exercise programmes are routinely prescribed in clinical practice to treat impairments, improve activity and participation in daily life because of their known physiological, health and psychological benefits (RCP, 2009). Progressive resistance exercise is a type of exercise prescribed specifically to improve skeletal muscle strength (Latham et al., 2004). The effectiveness of progressive resistance exercise varies considerably between studies and populations. This thesis focuses on how training parameters influence the delivery of progressive resistance exercise. In order to appropriately evaluate the influence of training parameters, this thesis argues the need to record training performance and the total work completed by participants as prescribed by training protocols. In the first study, participants were taken through a series of protocols differentiated by the intensity and volume of training. Training intensity was defined as a proportion of the mean peak torque achieved during maximal voluntary contractions and was set at 80% and 40% respectively of the MVC mean peak torque. Training volume was defined as the total external work achieved over the training period. Measures of training performance were developed to accurately report the intensity, repetitions and work completed during the training period. A second study evaluated training performance of the training protocols over repeated sessions. These protocols were then applied to 3 stroke survivors. Study 1 found sedentary participants could achieve a differentiated training intensity. Participants completing the high and low intensity protocols trained at 80% and 40% respectively of the MVC mean peak torque. The total work achieved in the high intensity low repetition protocol was lower than the total work achieved in the low intensity high repetition protocol. With repeated practice, study 2 found participants were able to improve in their ability to perform manoeuvres as shown by a reduction in the variation of the mean training intensity achieving total work as specified by the protocol to a lower margin of error. When these protocols were applied to 3 stroke survivors, they were able to achieve the specified training intensity but they were not able to achieve the total work as expected for the protocol. This is likely to be due to an inability in achieving a consistent force throughout the contraction. These results demonstrate evaluation of training characteristics and support the need to record and report training performance characteristics during progressive resistance exercise, including the total work achieved, in order to elucidate the influence of training parameters on progressive resistance exercise. The lack of accurate training performance may partly explain the inconsistencies between studies on optimal training parameters for progressive resistance exercise.

A posteriori error estimation for discontinuous Galerkin discretizations of H(curl)-elliptic partial differential equations

We develop the a posteriori error estimation of interior penalty discontinuous Galerkin discretizations for H(curl)-elliptic problems that arise in eddy current models. Computable upper and lower bounds on the error measured in terms of a natural (mesh-dependent) energy norm are derived. The proposed a posteriori error estimator is validated by numerical experiments, illustrating its reliability and efficiency for a range of test problems.

Error correcting codes for visible light communication systems

Over the past few years, the number of wireless networks users has been increasing. Until now, Radio-Frequency (RF) used to be the dominant technology. However, the electromagnetic spectrum in these region is being saturated, demanding for alternative wireless technologies. Recently, with the growing market of LED lighting, the Visible Light Communications has been drawing attentions from the research community. First, it is an eficient device for illumination. Second, because of its easy modulation and high bandwidth. Finally, it can combine illumination and communication in the same device, in other words, it allows to implement highly eficient wireless communication systems. One of the most important aspects in a communication system is its reliability when working in noisy channels. In these scenarios, the received data can be afected by errors. In order to proper system working, it is usually employed a Channel Encoder in the system. Its function is to code the data to be transmitted in order to increase system performance. It commonly uses ECC, which appends redundant information to the original data. At the receiver side, the redundant information is used to recover the erroneous data. This dissertation presents the implementation steps of a Channel Encoder for VLC. It was consider several techniques such as Reed-Solomon and Convolutional codes, Block and Convolutional Interleaving, CRC and Puncturing. A detailed analysis of each technique characteristics was made in order to choose the most appropriate ones. Simulink models were created in order to simulate how diferent codes behave in diferent scenarios. Later, the models were implemented in a FPGA and simulations were performed. Hardware co-simulations were also implemented to faster simulation results. At the end, diferent techniques were combined to create a complete Channel Encoder capable of detect and correct random and burst errors, due to the usage of a RS(255,213) code with a Block Interleaver. Furthermore, after the decoding process, the proposed system can identify uncorrectable errors in the decoded data due to the CRC-32 algorithm.

Probabilistic Models for Scalable Knowledge Graph Construction

In the past decade, systems that extract information from millions of Internet documents have become commonplace. Knowledge graphs -- structured knowledge bases that describe entities, their attributes and the relationships between them -- are a powerful tool for understanding and organizing this vast amount of information. However, a significant obstacle to knowledge graph construction is the unreliability of the extracted information, due to noise and ambiguity in the underlying data or errors made by the extraction system and the complexity of reasoning about the dependencies between these noisy extractions. My dissertation addresses these challenges by exploiting the interdependencies between facts to improve the quality of the knowledge graph in a scalable framework. I introduce a new approach called knowledge graph identification (KGI), which resolves the entities, attributes and relationships in the knowledge graph by incorporating uncertain extractions from multiple sources, entity co-references, and ontological constraints. I define a probability distribution over possible knowledge graphs and infer the most probable knowledge graph using a combination of probabilistic and logical reasoning. Such probabilistic models are frequently dismissed due to scalability concerns, but my implementation of KGI maintains tractable performance on large problems through the use of hinge-loss Markov random fields, which have a convex inference objective. This allows the inference of large knowledge graphs using 4M facts and 20M ground constraints in 2 hours. To further scale the solution, I develop a distributed approach to the KGI problem which runs in parallel across multiple machines, reducing inference time by 90%. Finally, I extend my model to the streaming setting, where a knowledge graph is continuously updated by incorporating newly extracted facts. I devise a general approach for approximately updating inference in convex probabilistic models, and quantify the approximation error by defining and bounding inference regret for online models. Together, my work retains the attractive features of probabilistic models while providing the scalability necessary for large-scale knowledge graph construction. These models have been applied on a number of real-world knowledge graph projects, including the NELL project at Carnegie Mellon and the Google Knowledge Graph.

Generalized cluster states based on finite groups

We define generalized cluster states based on finite group algebras in analogy to the generalization of the toric code to the Kitaev quantum double models. We do this by showing a general correspondence between systems with CSS structure and finite group algebras, and applying this to the cluster states to derive their generalization. We then investigate properties of these states including their projected entangled pair state representations, global symmetries, and relationship to the Kitaev quantum double models. We also discuss possible applications of these states.

Econometric models in foreign exchange market

According to the significance of the econometric models in foreign exchange market, the purpose of this research is to give a closer examination on some important issues in this area. The research covers exchange rate pass-through into import prices, liquidity risk and expected returns in the currency market, and the common risk factors in currency markets. Firstly, with the significant of the exchange rate pass-through in financial economics, the first empirical chapter studies on the degree of exchange rate pass-through into import in emerging economies and developed countries in panel evidences for comparison covering the time period of 1970-2009. The pooled mean group estimation (PMGE) is used for the estimation to investigate the short run coefficients and error variance. In general, the results present that the import prices are affected positively, though incompletely, by the exchange rate. Secondly, the following study addresses the question whether there is a relationship between cross-sectional differences in foreign exchange returns and the sensitivities of the returns to fluctuations in liquidity, known as liquidity beta, by using a unique dataset of weekly order flow. Finally, the last study is in keeping with the study of Lustig, Roussanov and Verdelhan (2011), which shows that the large co-movement among exchange rates of different currencies can explain a risk-based view of exchange rate determination. The exploration on identifying a slope factor in exchange rate changes is brought up. The study initially constructs monthly portfolios of currencies, which are sorted on the basis of their forward discounts. The lowest interest rate currencies are contained in the first portfolio and the highest interest rate currencies are in the last. The results performs that portfolios with higher forward discounts incline to contain higher real interest rates in overall by considering the first portfolio and the last portfolio though the fluctuation occurs.

Validation of single photon absorptiometry for on-farm measurement of density and mineral content of tail bone in cattle

A validation study examined the accuracy of a purpose-built single photon absorptiometry (SPA) instrument for making on-farm in vivo measurements of bone mineral density (BMD) in tail bones of cattle. In vivo measurements were made at the proximal end of the ninth coccygeal vertebra (Cy9) in steers of two age groups (each n = 10) in adequate or low phosphorus status. The tails of the steers were then resected and the BMD of the Cy9 bone was measured in the laboratory with SPA on the resected tails and then with established laboratory procedures on defleshed bone. Specific gravity and ash density were measured on the isolated Cy9 vertebrae and on 5-mm2 dorso-ventral cores of bone cut from each defleshed Cy9. Calculated BMD determined by SPA required a measure of tail bone thickness and this was estimated as a fraction of total tail thickness. Actual tail bone thickness was also measured on the isolated Cy9 vertebrae. The accuracy of measurement of BMD by SPA was evaluated by comparison with the ash density of the bone cores measured in the laboratory. In vivo SPA measurements of BMD were closely correlated with laboratory measurements of core ash density (r = 0.92). Ash density and specific gravity of cores, and all SPA measures of BMD, were affected by phosphorus status of the steers, but the effect of steer age was only significant (P < 0.05) for steers in adequate phosphorus status. The accuracy of SPA to determine BMD of tail bone may be improved by reducing error associated with in vivo estimation of tail bone thickness, and also by adjusting for displacement of soft tissue by bone mineral. In conclusion a purpose-built SPA instrument could be used to make on-farm sequential non-invasive in vivo measurements of the BMD of tailbone in cattle with accuracy acceptable for many animal studies.

Measurement and Simulation of Suppression Effects in a Buoyant Turbulent Line Fire

An experimental and numerical study of turbulent fire suppression is presented. For this work, a novel and canonical facility has been developed, featuring a buoyant, turbulent, methane or propane-fueled diffusion flame suppressed via either nitrogen dilution of the oxidizer or application of a fine water mist. Flames are stabilized on a slot burner surrounded by a co-flowing oxidizer, which allows controlled delivery of either suppressant to achieve a range of conditions from complete combustion through partial and total flame quenching. A minimal supply of pure oxygen is optionally applied along the burner to provide a strengthened flame base that resists liftoff extinction and permits the study of substantially weakened turbulent flames. The carefully designed facility features well-characterized inlet and boundary conditions that are especially amenable to numerical simulation. Non-intrusive diagnostics provide detailed measurements of suppression behavior, yielding insight into the governing suppression processes, and aiding the development and validation of advanced suppression models. Diagnostics include oxidizer composition analysis to determine suppression potential, flame imaging to quantify visible flame structure, luminous and radiative emissions measurements to assess sooting propensity and heat losses, and species-based calorimetry to evaluate global heat release and combustion efficiency. The studied flames experience notable suppression effects, including transition in color from bright yellow to dim blue, expansion in flame height and structural intermittency, and reduction in radiative heat emissions. Still, measurements indicate that the combustion efficiency remains close to unity, and only near the extinction limit do the flames experience an abrupt transition from nearly complete combustion to total extinguishment. Measurements are compared with large eddy simulation results obtained using the Fire Dynamics Simulator, an open-source computational fluid dynamics software package. Comparisons of experimental and simulated results are used to evaluate the performance of available models in predicting fire suppression. Simulations in the present configuration highlight the issue of spurious reignition that is permitted by the classical eddy-dissipation concept for modeling turbulent combustion. To address this issue, simple treatments to prevent spurious reignition are developed and implemented. Simulations incorporating these treatments are shown to produce excellent agreement with the experimentally measured data, including the global combustion efficiency.

Estimating Population Trends in American Woodcock (Scolopax Minor) Using Population Reconstruction Models

The American woodcock (Scolopax minor) population index in North America has declined 0.9% a year since 1968 prompting managers to identify priority information and management needs for the species (Sauer et al 2008). Managers identified a need for a population model that better informs on the status of American woodcock populations (Case et al. 2010). Population reconstruction techniques use long-term age-at-harvest data and harvest effort to estimate abundances with error estimates. Four new models were successfully developed using survey data (1999 to 2013). The optimal model estimates sex specific harvest probability for adult females at 0.148 (SE = 0.017) and all other age-sex cohorts at 0.082 (SE = 0.008) for the most current year 2013. The model estimated a yearly survival rate of 0.528 (SE = 0.008). Total abundance ranged from 5,206,000 woodcock in 2007 to 6,075,800 woodcock in 1999. This study represents the first population estimates of woodcock populations.

Air-coupled ultrasonic tomographic imaging of concrete elements

Ultrasonic tomography is a powerful tool for identifying defects within an object or structure. This method can be applied on structures where x-ray tomography is impractical due to size, low contrast, or safety concerns. By taking many ultrasonic pulse velocity (UPV) readings through the object, an image of the internal velocity variations can be constructed. Air-coupled UPV can allow for more automated and rapid collection of data for tomography of concrete. This research aims to integrate recent developments in air-coupled ultrasonic measurements with advanced tomography technology and apply them to concrete structures. First, non-contact and semi-contact sensor systems are developed for making rapid and accurate UPV measurements through PVC and concrete test samples. A customized tomographic reconstruction program is developed to provide full control over the imaging process including full and reduced spectrum tomographs with percent error and ray density calculations. Finite element models are also used to determine optimal measurement configurations and analysis procedures for efficient data collection and processing. Non-contact UPV is then implemented to image various inclusions within 6 inch (152 mm) PVC and concrete cylinders. Although there is some difficulty in identifying high velocity inclusions, reconstruction error values were in the range of 1.1-1.7% for PVC and 3.6% for concrete. Based upon the success of those tests, further data are collected using non-contact, semi-contact, and full contact measurements to image 12 inch (305 mm) square concrete cross-sections with 1 inch (25 mm) reinforcing bars and 2 inch (51 mm) square embedded damage regions. Due to higher noise levels in collected signals, tomographs of these larger specimens show reconstruction error values in the range of 10-18%. Finally, issues related to the application of these techniques to full-scale concrete structures are discussed.

Tourism demand modelling and forecasting with artificial neural network models: the Mozambique case study

This study is aimed to model and forecast the tourism demand for Mozambique for the period from January 2004 to December 2013 using artificial neural networks models. The number of overnight stays in Hotels was used as representative of the tourism demand. A set of independent variables were experimented in the input of the model, namely: Consumer Price Index, Gross Domestic Product and Exchange Rates, of the outbound tourism markets, South Africa, United State of America, Mozambique, Portugal and the United Kingdom. The best model achieved has 6.5% for Mean Absolute Percentage Error and 0.696 for Pearson correlation coefficient. A model like this with high accuracy of forecast is important for the economic agents to know the future growth of this activity sector, as it is important for stakeholders to provide products, services and infrastructures and for the hotels establishments to adequate its level of capacity to the tourism demand.

The study of correlation between sea surface temperature (SST) by using the NOAA-AVHRR data and compare this data with temperature measurement in the Caspian Sea

The changes in time and location of surface temperature from a water body has an important effect on climate activities, marine biology, sea currents, salinity and other characteristics of the seas and lakes water. Traditional measurement of temperature is costly and time consumer due to its dispersion and instability. In recent years the use of satellite technology and remote sensing sciences for data acquiring and parameter and lysis of climatology and oceanography is well developed. In this research we used the NOAA’s Satellite images from its AVHRR system to compare the field surface temperature data with the satellite images information. Ten satellite images were used in this project. These images were calibrated with the field data at the exact time of satellite pass above the area. The result was a significant relation between surface temperatures from satellite data with the field work. As the relative error less than %40 between these two data is acceptable, therefore in our observation the maximum error is %21.2 that can be considered it as acceptable. In all stations the result of satellite measurements is usually less than field data that cores ponds with the global result too. As this sea has a vast latitude, therefore the different in the temperature is natural. But we know this factor is not the only cause for surface currents. The information of all satellites were images extracted by ERDAS software, and the “Surfer” software is used to plot the isotherm lines.

Energy norm a-posteriori error estimation for hp-adaptive discontinuous Galerkin methods for elliptic problems in three dimensions

We develop the energy norm a-posteriori error estimation for hp-version discontinuous Galerkin (DG) discretizations of elliptic boundary-value problems on 1-irregularly, isotropically refined affine hexahedral meshes in three dimensions. We derive a reliable and efficient indicator for the errors measured in terms of the natural energy norm. The ratio of the efficiency and reliability constants is independent of the local mesh sizes and weakly depending on the polynomial degrees. In our analysis we make use of an hp-version averaging operator in three dimensions, which we explicitly construct and analyze. We use our error indicator in an hp-adaptive refinement algorithm and illustrate its practical performance in a series of numerical examples. Our numerical results indicate that exponential rates of convergence are achieved for problems with smooth solutions, as well as for problems with isotropic corner singularities.

Some misspecfication problems in long-memory time series models

Doctor of Philosophy in Mathematics

Measurement of the magnetic field of small magnets with a smartphone: a very economical laboratory practice for introductory physics courses

In this work, we propose an inexpensive laboratory practice for an introductory physics course laboratory for any grade of science and engineering study. This practice was very well received by our students, where a smartphone (iOS, Android, or Windows) is used together with mini magnets (similar to those used on refrigerator doors), a 20 cm long school rule, a paper, and a free application (app) that needs to be downloaded and installed that measures magnetic fields using the smartphone's magnetic field sensor or magnetometer. The apps we have used are: Magnetometer (iOS), Magnetometer Metal Detector, and Physics Toolbox Magnetometer (Android). Nothing else is needed. Cost of this practice: free. The main purpose of the practice is that students determine the dependence of the component x of the magnetic field produced by different magnets (including ring magnets and sphere magnets). We obtained that the dependency of the magnetic field with the distance is of the form x-3, in total agreement with the theoretical analysis. The secondary objective is to apply the technique of least squares fit to obtain this exponent and the magnetic moment of the magnets, with the corresponding absolute error.