932 resultados para data reduction by factor analysis


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The uncertainty of any analytical determination depends on analysis and sampling. Uncertainty arising from sampling is usually not controlled and methods for its evaluation are still little known. Pierre Gy’s sampling theory is currently the most complete theory about samplingwhich also takes the design of the sampling equipment into account. Guides dealing with the practical issues of sampling also exist, published by international organizations such as EURACHEM, IUPAC (International Union of Pure and Applied Chemistry) and ISO (International Organization for Standardization). In this work Gy’s sampling theory was applied to several cases, including the analysis of chromite concentration estimated on SEM (Scanning Electron Microscope) images and estimation of the total uncertainty of a drug dissolution procedure. The results clearly show that Gy’s sampling theory can be utilized in both of the above-mentioned cases and that the uncertainties achieved are reliable. Variographic experiments introduced in Gy’s sampling theory are beneficially applied in analyzing the uncertainty of auto-correlated data sets such as industrial process data and environmental discharges. The periodic behaviour of these kinds of processes can be observed by variographic analysis as well as with fast Fourier transformation and auto-correlation functions. With variographic analysis, the uncertainties are estimated as a function of the sampling interval. This is advantageous when environmental data or process data are analyzed as it can be easily estimated how the sampling interval is affecting the overall uncertainty. If the sampling frequency is too high, unnecessary resources will be used. On the other hand, if a frequency is too low, the uncertainty of the determination may be unacceptably high. Variographic methods can also be utilized to estimate the uncertainty of spectral data produced by modern instruments. Since spectral data are multivariate, methods such as Principal Component Analysis (PCA) are needed when the data are analyzed. Optimization of a sampling plan increases the reliability of the analytical process which might at the end have beneficial effects on the economics of chemical analysis,

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One hundred fifteen cachaça samples derived from distillation in copper stills (73) or in stainless steels (42) were analyzed for thirty five itens by chromatography and inductively coupled plasma optical emission spectrometry. The analytical data were treated through Factor Analysis (FA), Partial Least Square Discriminant Analysis (PLS-DA) and Quadratic Discriminant Analysis (QDA). The FA explained 66.0% of the database variance. PLS-DA showed that it is possible to distinguish between the two groups of cachaças with 52.8% of the database variance. QDA was used to build up a classification model using acetaldehyde, ethyl carbamate, isobutyl alcohol, benzaldehyde, acetic acid and formaldehyde as chemical descriptors. The model presented 91.7% of accuracy on predicting the apparatus in which unknown samples were distilled.

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Identification of order of an Autoregressive Moving Average Model (ARMA) by the usual graphical method is subjective. Hence, there is a need of developing a technique to identify the order without employing the graphical investigation of series autocorrelations. To avoid subjectivity, this thesis focuses on determining the order of the Autoregressive Moving Average Model using Reversible Jump Markov Chain Monte Carlo (RJMCMC). The RJMCMC selects the model from a set of the models suggested by better fitting, standard deviation errors and the frequency of accepted data. Together with deep analysis of the classical Box-Jenkins modeling methodology the integration with MCMC algorithms has been focused through parameter estimation and model fitting of ARMA models. This helps to verify how well the MCMC algorithms can treat the ARMA models, by comparing the results with graphical method. It has been seen that the MCMC produced better results than the classical time series approach.

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The calyxes of Hibiscus sabdariffa are used in traditional medicine around the world. However, quality assurance protocols and chemical variability have not been previously analyzed. In the present study, chemical characterization of a set of samples of H. sabdariffa calyxes commercialized in Colombia was accomplished with the aim to explore the chemical variability among them. Chemometrics-based analyses on the data obtained from the HPLC-UV-DAD-derived profiles were then performed. Thus, the pre-processed single-wavelength data were subjected to principal component analysis (PCA). The PCA-derived results evidenced different groups which were well-correlated to the corresponding total phenolic and total anthocyanin contents. Multi-wavelength chromatographic (HPLC-UV-DAD surfaces) data were additionally examined via parallel factor analysis (PARAFAC) as data reduction method and the obtained loadings were subsequently submitted to PCA and orthogonal partial least squares discriminant analysis (OPLS-DA). Results were thus consistent with those from single-wavelength data. PCA loadings were employed to determine those chemical components responsible for the data variance and OPLS-DA model, constructed from PARAFAC loadings, and indicated differentiation according total anthocyanin contents among samples. The present chemometric analysis therefore demonstrated to be an excellent tool for differentiation of H. sabdariffacalyxes according to their chemical composition.

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Direct leaching is an alternative to conventional roast-leach-electrowin (RLE) zinc production method. The basic reaction of direct leach method is the oxidation of sphalerite concentrate in acidic liquid by ferric iron. The reaction mechanism and kinetics, mass transfer and current modifications of zinc concentrate direct leaching process are considered. Particular attention is paid to the oxidation-reduction cycle of iron and its role in direct leaching of zinc concentrate, since it can be one of the limiting factors of the leaching process under certain conditions. The oxidation-reduction cycle of iron was experimentally studied with goal of gaining new knowledge for developing the direct leaching of zinc concentrate. In order to obtain this aim, ferrous iron oxidation experiments were carried out. Affect of such parameters as temperature, pressure, sulfuric acid concentration, ferrous iron and copper concentrations was studied. Based on the experimental results, mathematical model of the ferrous iron oxidation rate was developed. According to results obtained during the study, the reaction rate orders for ferrous iron concentration, oxygen concentration and copper concentration are 0.777, 0.652 and 0.0951 respectively. Values predicted by model were in good concordance with the experimental results. The reliability of estimated parameters was evaluated by MCMC analysis which showed good parameters reliability.

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Broadcasting systems are networks where the transmission is received by several terminals. Generally broadcast receivers are passive devices in the network, meaning that they do not interact with the transmitter. Providing a certain Quality of Service (QoS) for the receivers in heterogeneous reception environment with no feedback is not an easy task. Forward error control coding can be used for protection against transmission errors to enhance the QoS for broadcast services. For good performance in terrestrial wireless networks, diversity should be utilized. The diversity is utilized by application of interleaving together with the forward error correction codes. In this dissertation the design and analysis of forward error control and control signalling for providing QoS in wireless broadcasting systems are studied. Control signaling is used in broadcasting networks to give the receiver necessary information on how to connect to the network itself and how to receive the services that are being transmitted. Usually control signalling is considered to be transmitted through a dedicated path in the systems. Therefore, the relationship of the signaling and service data paths should be considered early in the design phase. Modeling and simulations are used in the case studies of this dissertation to study this relationship. This dissertation begins with a survey on the broadcasting environment and mechanisms for providing QoS therein. Then case studies present analysis and design of such mechanisms in real systems. The mechanisms for providing QoS considering signaling and service data paths and their relationship at the DVB-H link layer are analyzed as the first case study. In particular the performance of different service data decoding mechanisms and optimal signaling transmission parameter selection are presented. The second case study investigates the design of signaling and service data paths for the more modern DVB-T2 physical layer. Furthermore, by comparing the performances of the signaling and service data paths by simulations, configuration guidelines for the DVB-T2 physical layer signaling are given. The presented guidelines can prove useful when configuring DVB-T2 transmission networks. Finally, recommendations for the design of data and signalling paths are given based on findings from the case studies. The requirements for the signaling design should be derived from the requirements for the main services. Generally, these requirements for signaling should be more demanding as the signaling is the enabler for service reception.

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Although social capital and health have been extensively studied during the last decade, there are still open issues in current empirical research. These concern for instance the measurement of the concept in different contexts, as well as the association between different types of social capital and different dimensions of health. The present thesis addressed these questions. The general aim was to promote the understanding of social capital and health by investigating the oldest old and the two major language groups in Finland, Swedish- and Finnish-speakers. Another aim was to contribute to the discussion on methodological issues in social capital and health research. The present thesis investigated two empirical data sets, Umeå 85+ and Health 2000. The Umeå 85+ study was a cross-sectional study of 163 individuals aged 85, 90, and 95 or older, living in the municipality of Umeå, Sweden, in the year of 2000. The Health 2000 survey was a national study of 8,028 persons aged 30 or above carried out in Finland in 2000-2001. Different indicators of structural (e.g. social contacts) and cognitive (e.g. trust) social capital, as well as health indicators were used as variables in the analyses. The Umeå 85+ data set was analyzed with factor analysis, as well as univariate and multivariate analysis of variance. The Health 2000 data was analyzed with logistic regression techniques. The results showed that the Swedish-speakers in the Finnish data set Health 2000 had consistently higher prevalence of social capital compared to the Finnish-speakers even after controlling for central sociodemographic variables. The results further showed that even if the language group differences in health were small, the Swedishspeakers experienced in general better self-reported health compared with the Finnish-speakers. Common sociodemographic variables could not explain these observed differences in health. The results imply that social capital is often, but not always, associated with health. This was clearly seen in the Umeå 85+ data set where only one health indicator (depressive symptoms) was associated with structural social capital among the oldest old. The results based on the analysis of the Health 2000 survey demonstrated that the cognitive component of social capital was associated with self-rated health and psychological health rather than with participation in social activities and social contacts. In addition, social capital statistically reduced the health advantage especially for Swedish-speaking men, indicating that high prevalence of social capital may promote health. Finally, the present thesis also discussed the issue of methodological challenges faced with when analyzing social capital and health. It was suggested that certain components of social capital such as bonding and bridging social capital may be more relevant than structural and cognitive components when investigating social capital among the two language groups in Finland. The results concerning the oldest old indicated that the structural aspects of social capital probably reflect current living conditions, whereas cognitive social capital reflects attitudes and traits often acquired decades earlier. This is interpreted as an indication of the fact that structural and cognitive social capital are closely related yet empirically two distinctive concepts. Taken together, some components of social capital may be more relevant to study than others depending on which population group and age group is under study. The results also implied that the choice of cut-off point of dichotomization of selfrated health has an impact on the estimated effects of the explanatory variables. When the whole age interval, 35-64 years, was analyzed with logistic regression techniques the choice of cut-off point did not matter for the estimated effects of marital status and educational level. The results changed, however, when the age interval was divided into three shorter intervals. If self-rated health is explored using wide age intervals that do not account for age-dependent covariates there is a risk of drawing misleading conclusions. In conclusion, the results presented in the thesis suggest that the uneven distribution of social capital observed between the two language groups in Finland are of importance when trying to further understand health inequalities that exist between Swedish- and Finnish-speakers in Finland. Although social capital seemed to be relevant to the understanding of health among the oldest old, the meaning of social capital is probably different compared to a less vulnerable age group. This should be noticed in future empirical research. In the present thesis, it was shown that the relationship between social capital and health is complex and multidimensional. Different aspects of social capital seem to be important for different aspects of health. This reduces the possibility to generalize the results and to recommend general policy implementations in this area. An increased methodological awareness regarding social capital as well as health are called for in order to further understand the cfomplex association between them. However, based on the present data and findings social capital is associated with health. To understand individual health one must also consider social aspects of the individuals’ environment such as social capital.

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The objective of this master’s thesis was to study how customer relationships should be assessed and categorized in order to support customer relationship management (CRM) in the context of business-to-business (B2B) and professional services. This sophisticated and complex market is utilizing possibilities of CRM only rarely and even then the focus is often on technology. The theoretical part considered first CRM from the value chain point of view and then discussed the cyclical nature of relationships. The case study focused on B2B professional service firm. The data was collected from company databases and included the sample of 90 customers. The research was conducted in three phases first studying the age, then the service type of relationships and finally executing the cluster analysis. The data was analysed by statistical analysis program SAS Enterprise Guide. The results indicate that there are great differences between developments of customer relationships. While some relationships are dynamically growing and changing, most of customers are remaining constant. This implies expectations and requirements of customers are similarly divergent and relationships should be managed accordingly.

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This study focuses on observing how Finnish companies execute their new product launch processes. The main objective was to find out how entry timing moderates the relationship between launch tactics (namely product innovativeness, price and emotional advertising) and new product performance (namely sales volume and customer profitability). The empirical analysis was based on data collected in Lappeenranta University of Technology. The sample consisted of Finnish companies representing different industries and innovation activities. Altogether 272 usable responses were received representing a response rate of 37.67%. The measures were first assessed by using exploratory factor analysis (EFA) in PASW Statistics 18 and then further verified with confirmatory factor analysis (CFA) in LISREL 8.80. To test the hypotheses of the moderating effects of entry timing, hierarchical regression analysis was used in PASW Statistics 18. The results of the study revealed that the effect of product innovativeness on new product sales volume is dependent on entry timing. This implies that companies should carefully consider what would be the best time for entering the market when launching highly innovative new products. The results also depict a positive relationship between emotional advertising and new product sales volume. In addition, partial support was found for a positive relationship between pricing and new product customer profitability.

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Työn tavoitteena oli luoda työkalu kestomagneettikoneiden roottoreiden väsymisen analysointia varten. Työkalu toteutettiin siten, että siihen voidaan liittää oikeasta koneesta mitattu kuormitusdata, sekä tarvittavat materiaalitiedot. Kuormitusdata muunnetaan työkalussa jännityshistoriaksi käyttämällä elementtimenetelmän avulla laskettavaa skaalauskerrointa. Kestoiän laskemiseen analyysityökalu käyttää jännitykseen perustuvaa menetelmää sekä rainflowmenetelmää ja Palmgren-Minerin kumulatiivista vauriosääntöä. Lisäksi työkalu tekee tutkittavalle tapaukselle Smithin väsymislujuuspiirroksen. Edellä mainittujen menetelmien lisäksi työn teoriaosassa esiteltiin väsymisanalyysimenetelmistä myös paikalliseen venymään perustuva menetelmä sekä murtumismekaniikka. Nämä menetelmät jäivät monimutkaisuutensa vuoksi toteuttamatta työkalussa. Väsymisanalyysityökalulla laskettiin kestoiät kahdelle esimerkkitapaukselle. Kummassakin tapauksessa saatiin tulokseksi ääretön kestoikä, mutta aksiaalivuokoneen roottorin dynaaminen varmuus oli pieni. Vaikka tulokset vaikuttavat järkeviltä, ne olisi vielä hyvä verifioida esimerkiksi kaupallisen ohjelmiston avulla täyden varmuuden saamiseksi.

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The focus of this dissertation is the motivational influences on transfer in higher education and professional training contexts. To estimate these motivational influences, the dissertation includes seven individual studies that are structured in two parts. Part I, Dimensions, aims at identifying the dimensionality of motivation to transfer and its structural relations with training-related antecedents and outcomes. Part II, Boundary Conditions, aims at testing the predictive validity of motivation theories used in contemporary training research under different study conditions. Data in this dissertation was gathered from multi-item questionnaires, which were analyzed differently in Part I and Part II. Studies in Part I employed exploratory and confirmatory factor analysis, structural equation modeling, partial least squares (PLS) path modeling, and mediation analysis. Studies in Part II used artifact distribution meta-analysis, (nested) subgroup analysis, and weighted least squares (WLS) multiple regression. Results demonstrate that motivation to transfer can be conceptualized as a three-dimensional construct, including autonomous motivation to transfer, controlled motivation to transfer, and intention to transfer, given a theoretical framework informed by expectancy theory, self-determination theory, and the theory of planned behavior. Results also demonstrate that a range of boundary conditions moderates motivational influences on transfer. To test the predictive validity of expectancy theory, social cognitive theory, and the theory of goal orientations under different study settings, a total of 17 boundary conditions were meta-analyzed, including age; assessment criterion; assessment source; attendance policy; collaboration among trainees; computer support; instruction; instrument used to measure motivation; level of education; publication type; social training context; SS/SMC bias; study setting; survey modality; type of knowledge being trained; use of a control group; and work context. Together, the findings cumulated in this thesis support the basic premise that motivation is centrally important for transfer, but that motivational influences need to be understood from a more differentiated perspective than commonly found in the literature, in order to account for several dimensions and boundary conditions. The results of this dissertation across the seven individual studies are reflected in terms of their implications for theory development and their significance for training evaluation and the design of training environments. Limitations and directions to take in future research are discussed.

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This research establishes the primary components, predictors, and consequences of organizational commitment in the military context. Specifically, the research examines commitment to the military service among Finnish conscripts and whether initial affective commitment prior to service predicts later commitment, attitudes, behavior, and performance, and, furthermore, analyzes the changes in commitment and its possible outcomes. The data were collected from records as well as by surveys from 1,387 rank and file soldiers, immediately after they reported for duty, near the end of basic training, and near the end of 6 to 12 months of service. The data covered a wide array of predictor variables, including background items, attitudes toward conscription, mental and physical health, sociability, training quality, and leadership. Moreover, the archival data included such items as rank, criminal record, performance ratings, and the number of medical examines and exemptions. The measures were further refined based on the results of factor analysis and reliability tests. The results indicated that initial commitment significantly corresponded with expected adjustment, intentions to stay in the military, and acceptance of authority. Moreover, initial commitment moderately related to personal growth, perceived performance, and the number of effective service days at the end of service. During basic training, affective commitment was mostly influenced by challenging training, adjustment experiences, regimentation, and unit climate. At the end of service, committed soldiers demonstrated more personal growth and development in service, had higher-level expected performance, and less malingering during their service. Additionally, they had significantly more positive attitudes toward national defense. The results suggest that affective commitment requires adequate personal adjustment, experiences of personal growth and development, and satisfaction with unit dynamics and training. This research contributes to the theoretical discussion on organizational commitment and the will to defend the nation and advances developing models to support and manage conscript training, education, leadership, and personnel policy. This is achieved by determining the main factors and variables, including their relative strength, that affect commitment to the military service. These findings may also facilitate in designing programs aimed at reducing unwanted discharges and inadequate performance. In particular, these results provide tools for improving conscripts’ overall attachment to and identification with the military service.

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This study uses several measures derived from the error matrix for comparing two thematic maps generated with the same sample set. The reference map was generated with all the sample elements and the map set as the model was generated without the two points detected as influential by the analysis of local influence diagnostics. The data analyzed refer to the wheat productivity in an agricultural area of 13.55 ha considering a sampling grid of 50 x 50 m comprising 50 georeferenced sample elements. The comparison measures derived from the error matrix indicated that despite some similarity on the maps, they are different. The difference between the estimated production by the reference map and the actual production was of 350 kilograms. The same difference calculated with the mode map was of 50 kilograms, indicating that the study of influential points is of fundamental importance to obtain a more reliable estimative and use of measures obtained from the error matrix is a good option to make comparisons between thematic maps.

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ABSTRACT This study aimed to compare thematic maps of soybean yield for different sampling grids, using geostatistical methods (semivariance function and kriging). The analysis was performed with soybean yield data in t ha-1 in a commercial area with regular grids with distances between points of 25x25 m, 50x50 m, 75x75 m, 100x100 m, with 549, 188, 66 and 44 sampling points respectively; and data obtained by yield monitors. Optimized sampling schemes were also generated with the algorithm called Simulated Annealing, using maximization of the overall accuracy measure as a criterion for optimization. The results showed that sample size and sample density influenced the description of the spatial distribution of soybean yield. When the sample size was increased, there was an increased efficiency of thematic maps used to describe the spatial variability of soybean yield (higher values of accuracy indices and lower values for the sum of squared estimation error). In addition, more accurate maps were obtained, especially considering the optimized sample configurations with 188 and 549 sample points.

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The intent of this research was to develop a model that describes the extent to which customer behavioral intentions are influenced by service quality, customer satisfaction and customer perceived value in the business-to-business service context. Research on customer behavioral intentions is quite fragmented and no generalized model has been presented. Thus, there was need for empirical testing. This study builds on the services marketing theory and assesses the relationships between the identified constructs. The data for the empirical analysis was collected via a quantitative online survey and a total of 226 usable responses were obtained for further analysis. The model was tested in an employment agency service setting. The measures used in this survey were first assessed by using confirmatory factor analysis (CFA) after which the hypothesized relationships were further verified using structural equation modeling (SEM) in LISREL 8.80. The analysis identified that customer satisfaction played a pivotal role in the model as it was the only direct antecedent of customer behavioral intentions, however, customer perceived value showed a strong indirect impact on buying intentions via customer satisfaction. In contrast to what was hypothesized, service quality and customer perceived value did not have a direct positive effect on behavioral intentions. Also, a contradicting finding with current literature was that sacrifice was argued to have a direct but positive impact on customer perceived value. Based on the findings in this study, managers should carefully think of their service strategies that lead to their customers’ favorable behavioral intentions.