7 resultados para High-performance computing hyperspectral imaging
em Brock University, Canada
Resumo:
The use of certain perfonnance enhancing substances and methods has been defined as a major ethical breach by parties involved in the governance of highperfonnance sport. As a result, elite athletes worldwide are subject to rules and regulations set out in international and national anti-doping policies. Existing literature on the development of policies such as the World Anti-Doping Code and The Canadian antiDoping Program suggests a sport system in which athletes are rarely meaningfully involved in policy development (Houlihan, 2004a). Additionally, it is suggested that this lack of involvement is reflective of a similar lack of involvement in other areas of governance concerning athletes' lives. The purpose ofthis thesis is to examine the history and current state of athletes' involvement in the anti-doping policy process in Canada's high-perfonnance sport system. It includes discussion and analysis of recently conducted interviews with those involved in the policy process as well as an analysis of relevant documents, including anti-doping policies. The findings demonstrate that Canadian athletes have not been significantly involved in the creation of recently developed antidoping policies and that a re-evaluation of current policies is necessary to more fully recognize the reality of athletes' lives in Canada's high-perfonnance sport system and their rights within that system.
Resumo:
With the 2010 Vancouver Winter Olympic Games quickly approaching, there has been a heightened interest in the performance of Canadian athletes at international competitions (Duffy, 2007; Fidlin, 2005; Longley, 2006). Two significant documents outline Canada's goal to become the number one sporting nation at the 2010 Olympic Games, and improve Canada's performance at the 2008 Olympic Games: Own the Podium and Road to Excellence (Priestner Allinger & Allinger, 2004; Road to Excellence, 2006). These two documents represent heightened interest in the performance of our elite athletes, in conjunction with Canada's hosting status of the Vancouver 2010 Winter Olympic Games. The requirements to train and compete at the international level have become more demanding both in terms of financial resources and time commitment. The need to financially assist athletes with their training and competition costs has been an important topic of debate over the past decades (Beamish & Borowy, 1987; Gatehouse, 2004; Macintosh, 1996; Munro, 1970; Owens, 2004). Two sources of fiinding for high performance athletes in Canada are the Athlete Assistance Program (AAP) provided by the Federal Government and the Canadian Olympic Excellence Fund provided by the Canadian Olympic Committee. The importance of these fiinds for athletes has been discussed in various forums (Ekos, 1992, 1997, 2005; Priestner Allinger & Allinger, 2004; Thibault «& Babiak, 2005). However, alternative sources of funds for high performance athletes have never been the object of research. As such the purpose of this study was to describe a group of athlete applicants from the time period of November 2004 to April 2006, and to contextualize these applications within the development of the Charitable Fund for Athletes.
Resumo:
Several automated reversed-phase HPLC methods have been developed to determine trace concentrations of carbamate pesticides (which are of concern in Ontario environmental samples) in water by utilizing two solid sorbent extraction techniques. One of the methods is known as on-line pre-concentration'. This technique involves passing 100 milliliters of sample water through a 3 cm pre-column, packed with 5 micron ODS sorbent, at flow rates varying from 5-10 mUmin. By the use of a valve apparatus, the HPLC system is then switched to a gradient mobile phase program consisting of acetonitrile and water. The analytes, Propoxur, Carbofuran, Carbaryl, Propham, Captan, Chloropropham, Barban, and Butylate, which are pre-concentrated on the pre-column, are eluted and separated on a 25 cm C-8 analytical column and determined by UV absorption at 220 nm. The total analytical time is 60 minutes, and the pre-column can be used repeatedly for the analysis of as many as thirty samples. The method is highly sensitive as 100 percent of the analytes present in the sample can be injected into the HPLC. No breakthrough of any of the analytes was observed and the minimum detectable concentrations range from 10 to 480 ng/L. The developed method is totally automated for the analysis of one sample. When the above mobile phase is modified with a buffer solution, Aminocarb, Benomyl, and its degradation product, MBC, can also be detected along with the above pesticides with baseline resolution for all of the analytes. The method can also be easily modified to determine Benomyl and MBC both as solute and as particulate matter. By using a commercially available solid phase extraction cartridge, in lieu of a pre-column, for the extraction and concentration of analytes, a completely automated method has been developed with the aid of the Waters Millilab Workstation. Sample water is loaded at 10 mL/min through a cartridge and the concentrated analytes are eluted from the sorbent with acetonitrile. The resulting eluate is blown-down under nitrogen, made up to volume with water, and injected into the HPLC. The total analytical time is 90 minutes. Fifty percent of the analytes present in the sample can be injected into the HPLC, and recoveries for the above eight pesticides ranged from 84 to 93 percent. The minimum detectable concentrations range from 20 to 960 ng/L. The developed method is totally automated for the analysis of up to thirty consecutive samples. The method has proven to be applicable to both purer water samples as well as untreated lake water samples.
Resumo:
This work includes two major parts. The first part of the work concentrated on the studies of the application of the highperfonnance liquid chromatography-particle beam interface-mass spectrometry system of some pesticides. Factors that have effects on the detection sensitivity were studied. The linearity ranges and detection limits of ten pesticides are also given in this work. The second part of the work concentrated on the studies of the reduction phenomena of nitro compounds in the HPLC-PB-MS system. Direct probe mass spectrometry and gas chromatography-mass spectrometry techniques were also used in the work. Factors that have effects on the reduction of the nitro compounds were studied, and the possible explanation is proposed. The final part of this work included the studies of reduction behavior of some other compounds in the HPLC-PB-MS system, included in them are: quinones, sulfoxides, and sulfones.
Resumo:
Variations in different types of genomes have been found to be responsible for a large degree of physical diversity such as appearance and susceptibility to disease. Identification of genomic variations is difficult and can be facilitated through computational analysis of DNA sequences. Newly available technologies are able to sequence billions of DNA base pairs relatively quickly. These sequences can be used to identify variations within their specific genome but must be mapped to a reference sequence first. In order to align these sequences to a reference sequence, we require mapping algorithms that make use of approximate string matching and string indexing methods. To date, few mapping algorithms have been tailored to handle the massive amounts of output generated by newly available sequencing technologies. In otrder to handle this large amount of data, we modified the popular mapping software BWA to run in parallel using OpenMPI. Parallel BWA matches the efficiency of multithreaded BWA functions while providing efficient parallelism for BWA functions that do not currently support multithreading. Parallel BWA shows significant wall time speedup in comparison to multithreaded BWA on high-performance computing clusters, and will thus facilitate the analysis of genome sequencing data.
Resumo:
This work investigates mathematical details and computational aspects of Metropolis-Hastings reptation quantum Monte Carlo and its variants, in addition to the Bounce method and its variants. The issues that concern us include the sensitivity of these algorithms' target densities to the position of the trial electron density along the reptile, time-reversal symmetry of the propagators, and the length of the reptile. We calculate the ground-state energy and one-electron properties of LiH at its equilibrium geometry for all these algorithms. The importance sampling is performed with a single-determinant large Slater-type orbitals (STO) basis set. The computer codes were written to exploit the efficiencies engineered into modern, high-performance computing software. Using the Bounce method in the calculation of non-energy-related properties, those represented by operators that do not commute with the Hamiltonian, is a novel work. We found that the unmodified Bounce gives good ground state energy and very good one-electron properties. We attribute this to its favourable time-reversal symmetry in its target density's Green's functions. Breaking this symmetry gives poorer results. Use of a short reptile in the Bounce method does not alter the quality of the results. This suggests that in future applications one can use a shorter reptile to cut down the computational time dramatically.
Resumo:
Remote sensing techniques involving hyperspectral imagery have applications in a number of sciences that study some aspects of the surface of the planet. The analysis of hyperspectral images is complex because of the large amount of information involved and the noise within that data. Investigating images with regard to identify minerals, rocks, vegetation and other materials is an application of hyperspectral remote sensing in the earth sciences. This thesis evaluates the performance of two classification and clustering techniques on hyperspectral images for mineral identification. Support Vector Machines (SVM) and Self-Organizing Maps (SOM) are applied as classification and clustering techniques, respectively. Principal Component Analysis (PCA) is used to prepare the data to be analyzed. The purpose of using PCA is to reduce the amount of data that needs to be processed by identifying the most important components within the data. A well-studied dataset from Cuprite, Nevada and a dataset of more complex data from Baffin Island were used to assess the performance of these techniques. The main goal of this research study is to evaluate the advantage of training a classifier based on a small amount of data compared to an unsupervised method. Determining the effect of feature extraction on the accuracy of the clustering and classification method is another goal of this research. This thesis concludes that using PCA increases the learning accuracy, and especially so in classification. SVM classifies Cuprite data with a high precision and the SOM challenges SVM on datasets with high level of noise (like Baffin Island).