In recent years, the rapid development of economy and industry in Xiamen Bay causes serious environmental problems, particularly poor air quality and visibility impairment. There are no large-scale industrial emission sources in Kinmen Island, however, its ambient air quality is always the poorest in Taiwan. Moreover, ambient air quality monitoring data showed that PM10 concentrations varied in daytime and at nighttime. Consequently, this study tired to ascertain the potential causes for this phenomenon. This study selected ten particulate matter (PM) sampling sites at Xiamen Bay, including five sites at Kinmen Island and five sites at metro Xiamen. Particulate matter sampling was conducted in daytime (8:00-17:00) and at nighttime (17:00-8:00), which included regular and intensive sampling. Regular sampling was conducted to collect PM10 with high-volume samplers three times a month from April 2009 to April 2010, while intensive sampling was conducted to collect fine (PM2.5) and coarse (PM2.5-10) particles with dichotomous samplers and particle size distribution with a MOUDI at site B2 for consecutive 5 days in the spring and winter of 2009~2010. After sampling, the physicochemical properties of PM, including mass concentrations, particle size distribution, water- soluble ionic species, metallic elements, and carbonaceous contents were further analyzed. The level of atmospheric PM is affected by meteorological condition, thus PM10 concentrations in winter and fall was much higher than those in spring and summer. Results from backward trajectories showed that the concentrations of PM10 blown from the north were generally higher than those from the south. Furthermore, t-test analysis indicated that PM10 concentrations in daytime and at nighttime at site B3 were significantly different (p-value<0.05). During the intensive sampling periods, PM10 concentrations were mainly affected by coarse particles compared to fine particles. The highest concentration for fine and coarse particle modes occurred at the size ranges of 0.32~0.56 £gm and 3.2~5.6 £gm, respectively. The most abundant water-soluble ionic species of PM10 were secondary inorganic aerosols (SO42-, NO3-, and NH4+) which accounted for 85% of total ions. The daytime and nighttime PM10 concentration ratios (D/N) for Mg, K, Ca, Cr, Mn, Fe, Zn, Al, Cu, As, and V were in the same order of magnitude, however, the D/N ratios of Cd, Pb, Ni, and Ti in spring and summer varied higher than an order of magnitude, indicating that the emission sources of PM were different in daytime and at nighttime. Correlation analysis of OC and EC showed that OC and EC at nighttime had a higher correlation than those in daytime, while OC and EC had a higher correlation in Kinmen Island than those in metro Xiamen, indicating carbonaceous sources must be different in summer and winter at Xiamen Bay. Enrichment factor analysis revealed that ceramic industry, stone processing, and cement industry had higher correlation with PM10 concentration than utility power plants. Crustal dusts consisted of road dusts, farmland dusts, and constructive dusts, while biomass burning was not a negligible sources. Results obtained from PCA and CMB receptor modeling showed that major sources of PM in Xiamen Bay were secondary inorganic aerosols, fuel and biomass burning, marine aerosols, vehicular exhansts, and soil dusts. Besides, stone processing, cement industry, ceramic industry, and utility power plants had the highest contribution in winter. Their contributions in daytime and at nighttime were 38% and 45%, respectively.

This thesis presents content-related and construct-related validity evidence for science sub-tests within Student Selection Test (SST) in Turkey via underlying the content, cognitive processes, item characteristics, factorial structure, and group differences based on high school type. A total number of 126,245 students were present in the research from six type of school in the data of SST 2006. Reliability Analysis, Item Analysis, Principle Component Analysis (PCA) and one-way ANOVA have been carried out to evaluate the content-related and construct-related evidence of validity of SST. SPSS and ITEMAN programs were used to conduct the above-mentioned analyses. According to the results of content analysis, science items in the SST 2006 found to be measuring various cognitive processes under knowledge, understanding and problem solving cognitive domains. Those items loaded under three factors according to PCA findings which were measuring very close dimensions. Moreover, a threat to validity was detected via one-way ANOVA due to significant mean difference across high school types.

This study investigated the concentration distributions of polyclic aromatic hydrocarbons (PAHs) in the sediment cores collected from Fang-Liao submarine canyon. Chemical fingerprinting techniques and statistical analysis were applied to delineate the possible sources of the PAHs in deposited sediment core samples. It is noteworthy that all cores were not dated; therefore the deposition age could not estimate from the depth of deposition directly. The average concentrations of polyclic aromatic hydrocarbons (£U51PAHs) were found ranged from 229 to 638 (ng/g dry wt) in the sediment cores in Fang-Liao submarine canyon. In addition, the low molecular weight PAHs (2-3 ring PAHs) were found dominant in the PAH composition pattern of most samples. Total PAH concentrations were significantly correlated with total organic carbon (TOC) in all the sediment cores. Compared with sediment quality guidelines (SQGs), the PAH concentrations of all sediment samples were lower than those outlined in the criteria, that suggests no evident adverse biological effects caused by PAHs. Results also showed that total PAH concentration of surface sediments (0-2 cm) decreased with the water depth. Identification of PAHs sources suggests that all up-cores were dominated by petrogenic sources, but all down-cores except for S17 and S18 were dominated by pyrogenic sources or mixed sources. In contrast, biogenic sources were found dominant in S17 and S18 as they were characterized by higher ratio of perylene/£Upenta-PAHs(%). Compared with literature, the sediment cores of Fang-Liao submarine canyon were moderately polluted with PAHs. Analysis of diagnostic ratios and hierarchical cluster analysis (HCA) as well as principal component analysis (PCA) all indicate PAHs sources of Fang-Liao submarine canyon were mainly from petroleum and petroleum combustion sources for site of S3,S5,S7,S8 and S17; while pyrogenic or mixed sources for site of S1,S2,S9,S18 and S33.

Age related macular degeneration (AMD) is a public health concern in an aging society. The retinal pigment epithelium (RPE) layer of the eye is a principal site of pathogenesis for AMD. Morphological characteristics of the cells in the RPE layer can be used to discriminate age and disease status of individuals. In this thesis three genotypes of mice of various ages are used to study the predictive abilities of these characteristics. The disease state is represented by two mutant genotypes and the healthy state by the wild-type. Classification analysis is applied to the RPE morphology from the different spatial regions of the RPE layer. Variable reduction is accomplished by principal component analysis (PCA) and classification analysis by the k-nearest neighbor (k-NN) algorithm. In this way the differential ability of the spatial regions to predict age and disease status by cellular variables is explored.

This diploma thesis deals with using laser-induced breakdown plasma spectroscopy for determining the elemental structure of unknown samples. It was necessary to design an appropriate method to qualify material by laser-induced emission spectrum. Pretreatment of data and using a variety of chemometrics methods had to be done in order to qualify the structure of elements. We achieved a required solution by projecting the data to a new PCA space, creating clusters and computing the Euclidean distance between each cluster. The experiment in the practical part was set to detect an interface of two elements. We created a data file simulating the ablation on the interface. This data set was gradually processed applying a mathematical-chemical-physical view. Several data procedures have been compiled: approximation by Lorenz, Gauss and Voigt function and also a pretreatment method such as the detection of outliers, standardization by several procedures and subsequent use of principal components analysis. A summarization of processes for input data is fully described in the thesis.

Background: A problematic area in today’s large scale distributed systems is the exponential amount of growing log data. Finding anomalies by observing and monitoring this data with manual human inspection methods becomes progressively more challenging, complex and time consuming. This is vital for making these systems available around-the-clock. Aim: The main objective of this study is to determine which are the most suitable Machine Learning (ML) algorithms and if they can live up to needs and requirements regarding optimization and efficiency in the log data monitoring area. Including what specific steps of the overall problem can be improved by using these algorithms for anomaly detection and classification on different real provided data logs. Approach: Initial pre-study is conducted, logs are collected and then preprocessed with log parsing tool Drain and regular expressions. The approach consisted of a combination of K-Means + XGBoost and respectively Principal Component Analysis (PCA) + K-Means + XGBoost. These was trained, tested and with different metrics individually evaluated against two datasets, one being a Server data log and on a HTTP Access log. Results: The results showed that both approaches performed very well on both datasets. Able to with high accuracy, precision and low calculation time classify, detect and make predictions on log data events. It was further shown that when applied without dimensionality reduction, PCA, results of the prediction model is slightly better, by a few percent. As for the prediction time, there was marginally small to no difference for when comparing the prediction time with and without PCA. Conclusions: Overall there are very small differences when comparing the results for with and without PCA. But in essence, it is better to do not use PCA and instead apply the original data on the ML models. The models performance is generally very dependent on the data being applied, it the initial preprocessing steps, size and it is structure, especially affecting the calculation time the most.

No description available.

Biometrics includes the study of automatic methods for distinguishing human beings based on physical or behavioral traits. The problem of finding good biometric features and recognition methods has been researched extensively in recent years. Our research considers the use of ears as a biometric for human recognition. Researchers have not considered this biometric as much as others, which include fingerprints, irises, and faces. This thesis presents a novel approach to recognize individuals based on their outer ear images through spatial segmentation. This approach to recognizing is also good for dealing with occlusions. The study will present several feature extraction techniques based on spatial segmentation of the ear image. The study will also present a method for classifier fusion. Principal components analysis (PCA) is used in this research for feature extraction and dimensionality reduction. For classification, nearest neighbor classifiers are used. The research also investigates the use of ear images as a supplement to face images in a multimodal biometric system. Our base eigen-ear experiment results in an 84% rank one recognition rate, and the segmentation method yielded improvements up to 94%. Face recognition by itself, using the same approach, gave a 63% rank one recognition rate, but when complimented with ear images in a multimodal system improved to 94% rank one recognition rate. / Master of Science

L'huile d'olive est un élément important de l'alimentation méditerranéenne. Cependant lorsqu'une huile vieillit, elle se dégrade et perd ses propriétés. Il est donc important de connaitre l'évolution de la composition de l'huile en fonction de ses conditions de stockage et de fabrication. Ce suivi a été effectué sur deux huiles de fabrication différente, une huile fruité vert et une huile fruité noir, obtenue à partir d'olive à maturité que l'on a laissé fermenter quelques jours. De manière à obtenir rapidement des vieillissements poussés, ces deux huiles ont été vieillies artificiellement, par procédé thermique , et par procédé photochimique. Ces vieillissements ont été réalisés sur des volumes différents de manière à déterminer l'impact du rapport surface/masse. En parallèle, des échantillons de chacune des deux huiles ont été conservés durant 24 mois dans des conditions de stockage différentes déterminées à l'aide d'un plan d'expériences. Les paramètres influençant le plus la conservation de l'huile d'olive sont l'apport en oxygène, la luminosité et la température. Ces influences ont été déterminées à partir du suivi des principaux paramètres de qualité La réponse des plans a permis de mettre en évidence des interactions entre ces différents paramètres. L'analyse de la composition de l'huile ainsi que de tous les critères de qualité demande beaucoup de temps et consomme une grande quantité de solvant. Afin de pallier à ces désagréments, les résultats ont également été utilisés pour construire des modèles chimiométriques permettant de déterminer ces grandeurs à partir des spectres proche et moyen infrarouge des échantillons. / Olive oil is an important component of the Mediterranean diet. When oil ages, it deteriorates and loses its properties. It is therefore important to know the evolution of the oil composition according to the conditions of storage and manufacturing. This monitoring was carried out on two different oils manufacturing, green fruity oil obtained from olives harvested before maturity, and black fruit oil obtained from olives harvest at maturity and fermented for few days under controlled conditions. To obtain quickly pushed aging, these two oils were artificially aged by heat process (heated to 180 °C under supply of O2), and photochemical process (under an UV lamp and under supply of O2). These aging were performed on different volumes to determine the impact of surface/weight ratio. In parallel, samples of both oils were stored for 24 months under different storage conditions determined using an experimental design. The parameters affecting the most the conservation of olive oil are oxygen, light and temperature. These influences were determined from the monitoring of key quality criteria. Response of experimental design helped to highlight the interactions between these different parameters. The analysis of the oil composition as well as all the quality criteria requires a large amount of solvents and a lot of time consumer. To overcome these inconveniences, chemometric models has been built to determine these criteria from the near and mid-infrared spectra of samples. Natural aging is very little advanced in comparison to accelerated aging, so predictive models were established from the results of natural aging and accelerated separately.

O presente trabalho tem como objetivo avaliar a influência das variáveis ambientais na mortalidade de idosos (acima de 65 anos) por doenças cardiovasculares (DCV) e respiratórias (RES), nos condados de Los Angeles, Orange e Santa Bárbara na Califórnia, através de análises estatísticas, em particular de componentes principais (ACP). Para isso foram utilizados dados diários das estações meteorológicas dos condados (temperatura, pressão, umidade e velocidade do vento), de poluição do ar (NO2, CO, SO2 e O3) e da mortalidade por DCV e RES, durante o período 1975-2005. Além disso, foram calculados 7 índices de conforto térmico e estabelecidas as zonas de conforto para diferentes graus de percepção térmica a partir do índice de Temperatura Efetiva (TE). Os resultados verificaram tendências diferentes na variação temporal das DCV e RES. Enquanto as doenças RES tiveram um aumento bastante leve em todos os condados, as DCV apresentaram uma ligeira diminuição nos condados de Orange e Santa Bárbara, e uma diminuição constante e acentuada no condado de Los Angeles. Também se verificou uma variação sazonal significativa, com evidente aumento do número de óbitos de ambas as doenças durante o inverno e queda durante o verão. Em relação aos poluentes, foram observadas muitas ultrapassagens dos padrões nacionais de qualidade do ar principalmente para o O3, com 1443 vezes para o condado de Los Angeles, 771 para o Orange e 114 para Santa Bárbara. A partir dos índices de conforto térmico notou-se que o mês mais estressante devido ao calor foi setembro principalmente para os condados de Los Angeles e Santa Bárbara, e julho e agosto para o condado de Orange. Analisando a média de óbitos por sensação térmica observou-se um aumento das doenças nos extremos, principalmente quando a sensação é Muito Frio, com médias por doenças RES de 16,42, 3,31 e 0,81 e por DCV de 77,32, 15,37 e 2,92 nos condados de Los Angeles, Orange e Santa Bárbara, respectivamente. Com base na análise de correlação entre as variáveis e as doenças, observaram-se as melhores correlações no condado de Los Angeles, tanto para as doenças RES quanto DCV, e as correlações mais baixas foram observadas no condado de Santa Bárbara. Os resultados da ACP nos condados de Los Angeles e Orange verificaram o aumento da mortalidade por DCV no inverno, associadas a correlações positivas com os níveis de poluição principalmente em Los Angeles e ao estresse por frio, umidade e vento (via índice de conforto térmico) em Orange. Por outro lado, a mortalidade por doenças RES esteve mais associada às variações meteorológicas do que às concentrações de poluentes, observando-se associações positivas com o índice de calor (IC). Neste sentido, o condado de Orange apresentou maiores correlações com IC do que o condado de Los Angeles, além de uma variância maior (11,36 % contra 9,89 %). Por último, no condado de Santa Bárbara os resultados foram muito diferentes, já que tanto episódios de frio quanto de calor não mostraram impactos claros na população idosa, com respeito a ambos os grupos de doenças. O distintivo foi que os níveis de SO2 tiveram a maior associação positiva à mortalidade principalmente por DCV (0,53), embora tiver o condado as concentrações mais baixas das estudadas (média de 0,29 ppb). Em suma, os condados possuem estruturas sociais diferentes, apesar da semelhança do clima, fazendo com que os resultados sejam bastante dispares entre os mesmos. As perspectivas destes estudos pretendem colocar estes resultados para climas futuros, pois diversos episódios de ondas de calor ocorreram após o ano de 2005. / The objective of this study was to evaluate the influence of environmental variables on the mortality of elderly patients (over 65 years) due to cardiovascular diseases (CD) and respiratory diseases (RD) in the counties of Los Angeles, Orange and Santa Bárbara, California; through statistical analyzes, in particular, principal components (PCA). For this purpose, daily data of the meteorological stations of the counties (temperature, pressure, humidity and wind speed), air pollution (NO2, CO, SO2 and O3) and mortality by CD and RD were used during the period 1975-2005. In addition, seven thermal comfort indexes were calculated and comfort zones were established for different degrees of thermal perception according to the Effective Temperature index (TE). The results showed different trends in the temporal variation of CD and RD. While RD diseases had a fairly mild increase in all counties, CD showed a slight decrease in Orange and Santa Barbara counties and a steady decline in Los Angeles county. There was also a significant seasonal variation, with an evident increase in the number of deaths from both diseases during the winter and fall during the summer. In relation to the pollutants, many national standards for air quality were exceeded, mainly for the O3, with 1443 times for Los Angeles, 771 for Orange and 114 for Santa Barbara. From the thermal comfort indexes it was noted that the most stressful month due to the heat was September, mainly for the counties of Los Angeles and Santa Barbara, and July and August for the county of Orange. Analyzing the average number of deaths due to thermal sensation, there was an increase of the illnesses in extreme, especially when the sensation is Very Cold, with RD averages of 16.42, 3.31 and 0.81 and CD average of 77.32, 15.37 and 2.92 in the counties of Los Angeles, Orange and Santa Barbara, respectively. Based on correlation analysis between variables and diseases, the best correlations were found in Los Angeles for both RD and CD, and the lowest correlations were observed in Santa Barbara. The results of PAC in the counties of Los Angeles and Orange showed the increase in CD mortality in winter associated to positive correlations with the levels of pollution mainly in Los Angeles and stress due to cold, humidity and wind (via thermal comfort index) in Orange. On the other hand, mortality due to RD diseases was more associated with meteorological variations than with pollutant concentrations, with positive associations with heat index (HI). In this sense, Orange County presented higher correlations with HI than the county of Los Angeles, in addition to a greater variance (11.36% vs. 9.89%). Finally, in Santa Barbara the results were very different, since both episodes of cold and heat did not show clear impacts in the elderly population, regarding both groups of diseases. The difference was that SO2 levels had the highest positive association with CD mortality (0.53), although this county had the lowest concentrations studied (mean 0.29 ppb). In sum, counties have different social structures, despite the similarity of the climate, making the results quite different between them. The perspectives of these studies intend to place these results for future climates, since several episodes of heat waves occurred after 2005.