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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
21

Hypothesis formulation in medical records space

Ba-Dhfari, Thamer Omer Faraj January 2017 (has links)
Patient medical records are a valuable resource that can be used for many purposes including managing and planning for future health needs as well as clinical research. Health databases such as the clinical practice research datalink (CPRD) and many other similar initiatives can provide researchers with a useful data source on which they can test their medical hypotheses. However, this can only be the case when researchers have a good set of hypotheses to test on the data. Conversely, the data may have other equally important areas that remain unexplored. There is a chance that some important signals in the data could be missed. Therefore, further analysis is required to make such hidden areas become more obvious and attainable for future exploration and investigation. Data mining techniques can be effective tools in discovering patterns and signals in large-scale patient data sets. These techniques have been widely applied to different areas in medical domain. Therefore, analysing patient data using such techniques has the potential to explore the data and to provide a better understanding of the information in patient records. However, the heterogeneity and complexity of medical data can be an obstacle in applying data mining techniques. Much of the potential value of this data therefore goes untapped. This thesis describes a novel methodology that reduces the dimensionality of primary care data, to make it more amenable to visualisation, mining and clustering. The methodology involves employing a combination of ontology-based semantic similarity and principal component analysis (PCA) to map the data into an appropriate and informative low dimensional space. The aim of this thesis is to develop a novel methodology that provides a visualisation of patient records. This visualisation provides a systematic method that allows the formulation of new and testable hypotheses which can be fed to researchers to carry out the subsequent phases of research. In a small-scale study based on Salford Integrated Record (SIR) data, I have demonstrated that this mapping provides informative views of patient phenotypes across a population and allows the construction of clusters of patients sharing common diagnosis and treatments. The next phase of the research was to develop this methodology and explore its application using larger patient cohorts. This data contains more precise relationships between features than small-scale data. It also leads to the understanding of distinct population patterns and extracting common features. For such reasons, I applied the mapping methodology to patient records from the CPRD database. The study data set consisted of anonymised patient records for a population of 2.7 million patients. The work done in this analysis shows that methodology scales as O(n) in ways that did not require large computing resources. The low dimensional visualisation of high dimensional patient data allowed the identification of different subpopulations of patients across the study data set, where each subpopulation consisted of patients sharing similar characteristics such as age, gender and certain types of diseases. A key finding of this research is the wealth of data that can be produced. In the first use case of looking at the stratification of patients with falls, the methodology gave important hypotheses; however, this work has barely scratched the surface of how this mapping could be used. It opens up the possibility of applying a wide range of data mining strategies that have not yet been explored. What the thesis has shown is one strategy that works, but there could be many more. Furthermore, there is no aspect of the implementation of this methodology that restricts it to medical data. The same methodology could equally be applied to the analysis and visualisation of many other sources of data that are described using terms from taxonomies or ontologies.
22

Perfil químico micromolecular e análise quimiotaxonômica dos gêneros Stevia Cav.E Mikania Willd.(Asteraceae,Eupatorieae) / Chemotaxonomy of genus mikania willd. (Asteraceae) based on chemical profile database and multivariate analysis

Alves, Tiago Luiz da Silva January 2009 (has links)
O gênero Mikania (Asteraceae, tribo Eupatorieae) apresenta aproximadamente 450 espécies, muitas delas especialmente importantes por seu uso em medicina tradicional. Para a análise quimiotaxonômica, um banco de dados acerca da composição micromolecular de Mikania foi criado. Foram elaboradas análises de agrupamento e de componentes principais, bem como o cálculo de parâmetros evolutivos usados em quimiotaxonomia. O perfil químico e a análise estatística multivariada demonstraram que diterpenóides, lactonas sesquiterpenoídicas e cumarinas são os marcadores químicos mais importantes para este gênero. A presença de dicotomia entre a produção de lactonas sesquiterpenoídicas e diterpenóides não foi estritamente confirmada para o gênero, embora esteja claro que a produção de um interfere negativamente na do outro. As relações SH/(AC+IPP) e FV/FL foram compatíveis com o posicionamento de Mikania na família Asteraceae. As análises de componentes principais (PCA) e de agrupamento forneceram informações que correlacionam caracteres morfológicos e geográficos com dados químicos. As espécies distribuídas predominantemente no Brasil são consideradas muito mais ricas em diterpenos do tipo kaurano, assim como tendem a apresentar inflorescências tirsóides. Por outro lado, espécies não-brasileiras tendem a acumular lactonas sesquiterpenoídicas e apresentar preferencialmente inflorescências do tipo corimbosa. / The genus Mikania (Asteraceae, tribe Eupatorieae) encompasses around 450 species, many of which especially important due to their use in folk medicine. A database of the micromolecular composition of Mikania was generated for a chemotaxonomic analysis. Clustering and Principal Components Analysis (PCA) were performed, as well the calculation of evolutive parameters used in chemotaxonomy. The chemical profile and the statistical multivariate analysis demonstrated that diterpenes, sesquiterpene lactones and coumarins are the most important chemical markers in this genus. The presence of dicotomy between the production of sesquiterpene lactones and diterpenes was not strictly confirmed for the genus, although it is clear that the production of one interferes negatively with the other. The SH/(AC+IPP) and FV/FL ratios are compatible with the positioning of Mikania in the Asteraceae family. The PCA and clustering analysis provided information correlating morphological characters and geographical patterns with chemical data. The species distributed predominantly in Brazil are considered very rich in kaurane diterpenes quite prone to present thyrsoid inflorescences. In contrast, non-Brazilian species trend to accumulate mostly sesquiterpene lactones, preferentially presenting the corymbose inflorescence type.
23

Recognition of Infrastructure Events Using Principal Component Analysis

Broadbent, Lane David 01 December 2016 (has links)
Information Technology systems generate system log messages to allow for the monitoring of the system. In increasingly large and complex systems the volume of log data can overwhelm the analysts tasked with monitoring these systems. A system was developed that utilizes Principal Component Analysis to assist the analyst in the characterization of system health and events. Once trained, the system was able to accurately identify a state of heavy load on a device with a low false positive rate. The system was also able to accurately identify an error condition when trained on a single event. The method employed is able to assist in the real time monitoring of large complex systems, increasing the efficiency of trained analysts.
24

Principal Component Analysis of Gramicidin

Kurylowicz, Martin 13 August 2010 (has links)
Computational research making use of molecular dynamics (MD) simulations has begun to expand the paradigm of structural biology to include dynamics as the mediator between structure and function. This work aims to expand the utility of MD simulations by developing Principal Component Analysis (PCA) techniques to extract the biologically relevant information in these increasingly complex data sets. Gramicidin is a simple protein with a very clear functional role and a long history of experimental, theoretical and computational study, making it an ideal candidate for detailed quantitative study and the development of new analysis techniques. First we quantify the convergence of our PCA results to underwrite the scope and validity of three 64 ns simulations of gA and two covalently linked analogs (SS and RR) solvated in a glycerol mono-oleate (GMO) membrane. Next we introduce a number of statistical measures for identifying regions of anharmonicity on the free energy landscape and highlight the utility of PCA in identifying functional modes of motion at both long and short wavelengths. We then introduce a simple ansatz for extracting physically meaningful modes of collective dynamics from the results of PCA, through a weighted superposition of eigenvectors. Applied to the gA, SS and RR backbone, this analysis results in a small number of collective modes which relate structural differences among the three analogs to dynamic properties with functional interpretations. Finally, we apply elements of our analysis to the GMO membrane, yielding two simple modes of motion from a large number of noisy and complex eigenvectors. Our results demonstrate that PCA can be used to isolate covariant motions on a number of different length and time scales, and highlight the need for an adequate structural and dynamical account of many more PCs than have been conventionally examined in the analysis of protein motion.
25

Principal Component Analysis of Gramicidin

Kurylowicz, Martin 13 August 2010 (has links)
Computational research making use of molecular dynamics (MD) simulations has begun to expand the paradigm of structural biology to include dynamics as the mediator between structure and function. This work aims to expand the utility of MD simulations by developing Principal Component Analysis (PCA) techniques to extract the biologically relevant information in these increasingly complex data sets. Gramicidin is a simple protein with a very clear functional role and a long history of experimental, theoretical and computational study, making it an ideal candidate for detailed quantitative study and the development of new analysis techniques. First we quantify the convergence of our PCA results to underwrite the scope and validity of three 64 ns simulations of gA and two covalently linked analogs (SS and RR) solvated in a glycerol mono-oleate (GMO) membrane. Next we introduce a number of statistical measures for identifying regions of anharmonicity on the free energy landscape and highlight the utility of PCA in identifying functional modes of motion at both long and short wavelengths. We then introduce a simple ansatz for extracting physically meaningful modes of collective dynamics from the results of PCA, through a weighted superposition of eigenvectors. Applied to the gA, SS and RR backbone, this analysis results in a small number of collective modes which relate structural differences among the three analogs to dynamic properties with functional interpretations. Finally, we apply elements of our analysis to the GMO membrane, yielding two simple modes of motion from a large number of noisy and complex eigenvectors. Our results demonstrate that PCA can be used to isolate covariant motions on a number of different length and time scales, and highlight the need for an adequate structural and dynamical account of many more PCs than have been conventionally examined in the analysis of protein motion.
26

A study on the Revealed Patent Advantage and the R&D productivity of IC Design companies

Chou, Cheng-chieh 23 July 2010 (has links)
The Strategies of the firms in Patent are not only about the future, but also forming the barrier for competitor. For the sake, we should develop the patent strategies and technological position.This study goes to the discussion of technological position by the patent multivariate analysis, and suggest the patent strategy by the difference within and between the groups which were clustered from IC design companies. This study selects twenty gobal IC design companies,which are always on the top25 of the industry.In case1 ,we wonder figure out the technological postion and the path of technology shift.In case2,we can recognize the technological position as industrial position. In case 1, we got four clusters by cluster analysis.Cluster 1 is called SpecialistII,and cluster2 is called Strong Generalist, and cluster 3 is called Specialist I,and cluster 4 is called Weak Generalist. For further observation, the firms with technology shift will shift from cluster 1 to cluster 2 in the same direction.Others still maintain the same strategies in their clusters. In case 2 , we also got four clusters by the analysis. Cluster 1 is called Weak Generalist ,and cluster 2 is called Strong Generalist, and cluster 3 is called Specialist I,and cluster 4 is called Specialist III.As financial results , we got homogeneity within a cluster except cluster 4. Performance between clusters, we made and observed the line chart of trend in the selected financial ratio and we used the median of samples within a cluster. In case 2,it seems heterogeneous in ROA and Price-to-book ratio in the chart.In case1,it is also heterogeneous in ROA and price-to-book ratio.It¡¦s significant and positively correlated in R&D productivity(GrossMargin-to-R&D ratio) between others by the correlation coefficient matrix.It seems to be the proxy to the other financial ratio.
27

The relationships between ozone concentration and meterrological parameters in the urban area, Kaohsiung

Liao, Siou-yi 16 June 2005 (has links)
ABSTRACT The relationships between high ozone events and synoptic weather patterns were investigated based on the meteorological and air-quality data at four monitoring stations in Kaohsiung city during 1997 to 2004 in this study. The PCA (principal component analysis) and correlation studies show that ozone concentration exhibit positive correlations with the ambient temperature and sunshine duration, while negative correlation with the cloud cover. The frequency of high ozone events was highest under the weather patterns of northeast seasonal wind (B1 type), high-pressure system with recirculation (B3 type), high-pressure system with offshore type (B2 type), and in the warm core of approaching front (B4 type), most frequently in autumn, winter, and spring, and least frequently in summer. The above four weather patterns are primarily dominated by the high-pressure system from Mainland China, with relatively cold and dry weather and little rain in Taiwan. Since the high-pressure center is usually located north or northeast of Taiwan during autumn, winter, and spring such that the leeside areas of Central Mountain Ranges in the western coast of Taiwan are prone to high pollution events, particularly when the wind speed is low (< 4m/s) and duration of sunshine is long (> 5.5 hr). Or sometimes the meso-scale wind system, for example, the sea-land breeze or the combined flow caused by the detouring flow from the Henchun Peninsula and northeast wind tends to raise the pollutant concentrations. Keywords¡GHigh ozone event, Synoptic weather pattern, Principal component analysis.
28

Pagrindinių komponenčių metodo realizacijos neuroniniais tinklais tyrimas / Investigation of principal komponents realized by neurol networks

Umbražūnaitė, Jurgita 03 June 2005 (has links)
In this research paper have been examined the ability of artificial neuron network, to project multidimensional data into smaller measurement expanse, by using the idea of main components. Described the usage of artificial neuron network and educational algorithm for specific features extraction and multidimensional data projection. Analyzed classical research methods of main components, and program KOMPONENTĖ has been designed to accomplish this particular work. Also there have been analyzed the possibilities of artificial neuron network to project the multidimensional data into the straight and plane. There have been designed programs TIESĖ, OJA and SANGER for this research paper. There have been accomplished and presented the results of this research. The results, obtained using classical main components method, were compared with results, obtained by neuron network realizabled main components. Additional conclusions maid about multidimensional data visualization problems, using the Y.H.Oja ir T.D.Sanger regulations and dependance of these regulations from parameter of educational precision, and parameter of significance of educational rate. Software operated in this research paper: Free Pascal IDE for WIN32 and Microsoft Excel 2003.
29

THE EFFECT OF HEALTHY AGING ON TRUNK NEUROMUSCULAR ACTIVATION PATTERNS DURING A CONTROLLED FUNCTIONAL TRANSFER TASK

Quirk, David Adam 25 March 2013 (has links)
Healthy aging is associated with an increased incidence of injuries such as low back pain and falling. Age-related changes in trunk neuromuscular activation patterns could potentially explain uncontrolled trunk motion, a risk factor for these injuries. The purpose of this study was two-fold: i) to establish if trunk neuromuscular activation patterns differ between older and younger adults, and ii) to identify if increased cognitive load can alter the activation patterns used by older adults. Participants performed a controlled dynamic transfer task known to challenge trunk musculature by continuously changing the external moment experienced by the spine. In this thesis, the transfer task was altered by increasing the external moment and cognitive load to address purpose i) and ii) respectively. Three dimensional trunk and pelvis motion and surface electromyograms for 24 trunk muscle sites were collected in two experiments. In the first experiment 26 younger adults, and 17 older adults, performed the transfer task at two physical task intensities. In a second experiment, eight of these older adults performed the dynamic transfer task while performing a simultaneous cognitive dual-task. An analysis of amplitude and temporal characteristics of EMG waveforms, using principal component analysis, showed that older adults had altered trunk neuromuscular activation patterns compared to younger adults. In particular, after accounting for physical task intensity, older adults have increased antagonist co-activation, less temporal variation to changing external moments, and changes in the synergistic relationships between trunk muscle sites. Increasing the cognitive load had no influence on the trunk neuromuscular activation patterns used by healthy active older adults. However, as cognitive performance was not measured in the dual-task it cannot be excluded that i) the cognitive task did not represent enough challenge to result in competition of cortical resources, or ii) the cognitive resources necessary for the successful completion of the transfer task were prioritized in older adults.
30

PRINCIPAL COMPONENT ANALYSES OF JOINT ANGLE CURVES TO EXAMINE LIFTING TECHNIQUE

SADLER, ERIN 18 August 2010 (has links)
The objectives of the present body of work were 1) to evaluate the Personal Lift-Assist Device (PLAD) in terms of its effect on lifting technique, interjoint coordination, and whether sex modulates these effects and 2) to explore the use of principal component analysis (PCA) as a method to investigate lifting waveforms. Thirty participants (15M, 15F) completed a freestyle, symmetrical lifting protocol during which three-dimensional kinematics of the ankle, knee, hip, and lumbar and thoracic spine were collected using a two-camera Optotrak 3020 system. There were four testing conditions: a) with and b) without wearing the PLAD; and c) 0% load and d) 10% of maximum back strength load. All data were evaluated using PCA. In the first analysis, the relationship between the PLAD and lifting technique under a loaded condition was explored. Results showed that 8 PCs were significantly different between the PLAD/No PLAD conditions yet there were no significant effects of sex on any of the PCs. It was concluded that wearing the PLAD encourages a lifting technique that is reflective of a squat lift, independent of sex. In the second analysis, the PLAD’s effect on interjoint coordination patterns under both loaded and unloaded conditions was examined using the relative phase angle (RPA). It was found that there were no significant differences between device, sex, or load conditions on any of the PCs retained in the model. A novel approach to enhance interpretability of PCs was developed during this study. Finally, when the PLAD was not worn, male and female differences were further investigated under loaded and unloaded conditions. It was determined that when the load is individualized to personal strength characteristics, sex differences in lifting technique are negligible. This is a contradictory finding from previous research. Overall, the major contributions of this research are: support for the use of the PLAD in industry; the recommendation that load be selected based on individual strength characteristics for lifting research experimental design; the use of PCA as a method to effectively evaluate lifting waveforms; and the development of a novel approach to aid in the interpretation of principal components. / Thesis (Master, Kinesiology & Health Studies) -- Queen's University, 2010-08-18 09:35:19.142

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