As dificuldades de aprendizagem sobre estatística e suas aplicações simplesmente em razão da matemática envolvida, principalmente, pelos alunos dos cursos de humanas, fazem dela um desafio para o professor que a ministra e também para o aluno que aprende. Assim, esta tese busca mostrar o quanto à elaboração e o desenvolvimento de uma ferramenta de avaliação tipo teste em um ambiente virtual pode contribuir como apoio ao ensino presencial do estudo de ferramentas estatísticas multivariadas para os alunos de graduação em Administração da FEARP/USP, matriculados na disciplina Estatística Aplicada à Administração II. Este trabalho faz parte do projeto virtual denominado LaViE, que é um ambiente virtual de ensino-aprendizagem de estatística, e que está fundamentado em três dimensões: Pedagogia Virtual, Tecnologia da Comunicação e Processo de Validação. Para a criação dessa ferramenta de avaliação tipo teste online foi necessário, primeiramente, a elaboração de um protocolo para desenvolvimento e implementação desse sistema no LaViE. A metodologia, então, foi baseada em três etapas: 1) elaboração do protocolo fundamentado na pesquisa exploratória de pedagogia virtual com base na teoria sobre processo de ensino-aprendizagem para o desenvolvimento de um conjunto de regras e passos que balizasse a criação de questões testes on-line com níveis diferentes de ?adaptação? pelo aluno para cada módulo apresentado na disciplina em questão. Neste caso, foram criados três níveis de adaptação: básico (I), intermediário (II) e avançado (III); 2) implementação dessa ferramenta de avaliação no LaViE (teste seu conhecimento), com o desenvolvimento das questões baseadas nos assuntos sobre análise estatística multivariada e; 3) avaliação quantitativa da opinião dos alunos (usuários) quanto à usabilidade do sistema ?teste seu conhecimento? desenvolvido. Esses dados foram coletados quando essa disciplina foi ministrada, porém em dois períodos diferentes; no segundo semestre de 2005 como projeto-piloto, e no segundo semestre de 2006. Dessa forma, pôde ser feita uma análise comparativa da opinião dos alunos sobre o sistema em dois momentos diferentes. Para esse levantamento foram utilizados dois questionários aplicados diretamente aos alunos em sala de aula momentos antes da avaliação presencial da disciplina e um outro logo após essa avaliação presencial. Essas três etapas finalizadas deram condição de existência de uma ferramenta que faz parte de uma das três dimensões citadas do LaViE ? Processo de Validação. / The mathematical knowledge involved in the process of learning statistics and its applications, brings about difficulties to the Humanities department students, thus making it a challenge not only to those who teach it but also to the ones who learn it. Therefore, this work aims at showing the contribution the elaboration and development of a tool such as an online evaluation test can give, as a support to the presencial teaching of the study of multivariate statistical resources, to the FEARP/USP Business Management undergraduate students, registered in Applied Statistics to Business Management II. This study is part of a virtual project named LaViE which is a virtual environment of teaching-learning of Statistics based on three dimensions: Virtual Pedagogy, Communication Technology and Validation Process. For the development and implementation of the online evaluation test in the LaViE project, a protocol was elaborated. The methodology involved is based on three phases: 1) protocol production built on the virtual pedagogy exploratory research founded on the theory concerning the teaching-learning process in order to develop a set of rules and measures which support the creation of online test problems presenting different levels of adaptation for each module of the mentioned discipline. Thus, three levels of adaptation were created: basic (I), intermediate (II), and advanced (III); 2) implementation of such evaluation tool in the LaViE project (test your knowledge) by developing questions based on topics about multivariate statistical analysis; 3) quantitative evaluation of the users? opinion as to the usability of the ?test your knowledge? system. Data were collected in two distinct occasions: second semester of 2005, as a pilot project, and second semester of 2006, what enabled a comparative analysis of the system by the users at two different moments. This survey was conducted by means of two questionnaires completed in class by the students, being the first before the presencial discipline evaluation, and the second immediately after it. At the completion of the three phases previously mentioned, the Validation Process was obtained.

The increasing number of polluted watersheds and water bodies with total maximum daily loads (TMDLs) has resulted in increased research to find methods that effectively and universally identify fecal pollution sources. A fundamental requirement to identify such methods is understanding the microbial and chemical processes that influence fate and transport of fecal indicators from various sources to receiving streams. Using the Watauga River watershed in northeast Tennessee as a model to better understand these processes, multivariate statistical analyses were conducted on data collected from four creeks that have or are expected to have pathogen TMDLs. The application of canonical correlation and discriminant analyses revealed spatial and temporal variability in the microbial and chemical parameters influencing water quality, suggesting that these creeks differ in terms of the nature and extent of fecal pollution. The identification of creeks within a watershed that have similar sources of fecal pollution using this data analysis approach could change prioritization of best management practices selection and placement. Furthermore, this suggests that TMDL development may require multiyear and multisite data using a targeted sampling approach instead of a 30-d geometric mean in large, complex watersheds. This technique may facilitate the choice between watershed TMDLs and single segment or stream TMDLs.

It is not easy to state clearly to the public for quality of groundwater bodies, even if there are a large number of effective water quality data, it is still hard to combine and induct,and it often occurs in different units have each put forward to explain on the test results.Multivariate statistical analysis method can simplify high complex data into a representative function of the small number of factors, clearly explained to a group of inter-relationship of the original variables, or to be clustered and identified according to the similarity between the data to understand the reason behind the formation of certain phenomena, so this study utilize it to explore the groundwater characteristics. In this study, monitoring data come from the Kaohsiung city 48 groundwater monitoring wells of the EPA National Water Quality Monitoring Information website database, apply SPSS12.0 package software to execute multivariate statistical analysis, including factor analysis ,cluster analysis and discriminant analysis, and thus induction, sorting and classification of water quality characteristics, evaluating the causes of pollution and local area characteristics. The results of factor analysis to obtain the groundwater quality of the Kaohsiung region 4 representative factors: the factor of salinization, organic pollution factor, the factor of ore melting and acid-base factor. Four principal component factors instead of the 17 analysis projects of the regional groundwater quality in Kaohsiung city, the variance amounted to 78.3%. Use of cluster analysis of the 48 monitoring wells in the region is divided into four groups, according to the different nature of the monitoring data and the nature of similarity and group, to investigate the correlation between the monitoring well water quality within each cluster and the main factor, and by monitoring wells position to distinguish between the average underground water quality of inland area than the coastal area, we can get the results of seawater intrusion and salinization phenomena in coastal area, and monitoring wells located in the Cijin district are polluted by the pH factor. Kaohsiung regional groundwater quality is generally in the case of hard water to very hard water. In order to understand the difference of the multivariate statistical analysis method and the general groundwater pollution index analysis, draw Piper water quality diamond cluster analysis diagram to compare the similarities and differences,the results show that the multivariate statistical analysis can supply a systematic analysis of variable data and the overall variations of the water quality, and objective clustering, while the general composite index analytcial method such as Piper, by the characteristic position to get the type of pollution, but difficult to explain the overall pollution characteristics. At last, in this study, the hope to recommend the pollution control assessment and prevention strategies of Kaohsiung city underground water.

Made available in DSpace on 2014-06-11T19:30:31Z (GMT). No. of bitstreams: 0 Previous issue date: 2007-02-26Bitstream added on 2014-06-13T21:01:19Z : No. of bitstreams: 1 franco_c_dr_prud.pdf: 7388592 bytes, checksum: 3b1b05541970e72cb28df9a6b857ffe8 (MD5) / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Universidade Estadual de Maringa - Uem / Nas últimas décadas, a capacidade de gerar e coletar dados aumentou rapidamente, gerando a necessidade do desenvolvimento de novas técnicas e ferramentas capazes de processar e analisar esses dados descobrindo informações novas e úteis. Surgindo um proeminente campo de pesquisa para a extração de conhecimento de dados Descoberta de Conhecimento em Banco de Dados. Pela aplicação da metodologia da descoberta de conhecimento indireto aos atributos dos fragmentos cerâmicos coletados ao nível do solo no Sítio Arqueológico Piracanjuba Piraju SP, este trabalho pretende prover aos peritos em arqueologia uma visão sistêmica capaz de auxiliá-los no conhecimento das populações pretéritas que ali habitaram. / In the last decades, the capacities to produce and collect data has grown fast and the development of news techniques and tools capable to processes and analyze this datas discovering new and useful information as necessary. Therefore, a huge research area has beginning for the extraction of data understanding Knowledge Discovery in Database. The indirect knowledge discovery applied to ceramic fragment collected at soil level in Piracanjuba's Piraju, SP aims give to archaeology experts a whole vision able to be useful knowledge of the past people living there.

Resumo: Nas últimas décadas, a capacidade de gerar e coletar dados aumentou rapidamente, gerando a necessidade do desenvolvimento de novas técnicas e ferramentas capazes de processar e analisar esses dados descobrindo informações novas e úteis. Surgindo um proeminente campo de pesquisa para a extração de conhecimento de dados Descoberta de Conhecimento em Banco de Dados. Pela aplicação da metodologia da descoberta de conhecimento indireto aos atributos dos fragmentos cerâmicos coletados ao nível do solo no Sítio Arqueológico Piracanjuba Piraju SP, este trabalho pretende prover aos peritos em arqueologia uma visão sistêmica capaz de auxiliá-los no conhecimento das populações pretéritas que ali habitaram. / Abstract: In the last decades, the capacities to produce and collect data has grown fast and the development of news techniques and tools capable to processes and analyze this datas discovering new and useful information as necessary. Therefore, a huge research area has beginning for the extraction of data understanding Knowledge Discovery in Database. The indirect knowledge discovery applied to ceramic fragment collected at soil level in Piracanjuba's Piraju, SP aims give to archaeology experts a whole vision able to be useful knowledge of the past people living there. / Orientador: Nilton Nobuhiro Imai / Coorientador: Neide Faccio Barrocá / Coorientador: Vilma Tachibana / Banca: Milton Hirokazu Shimabukuro / Banca: Mário Hissamitsu Tarumoto / Banca: José Luiz de Morais / Banca: Emília Mariko Kashimoto / Doutor

Made available in DSpace on 2014-06-11T19:26:11Z (GMT). No. of bitstreams: 0 Previous issue date: 2003Bitstream added on 2014-06-13T18:54:15Z : No. of bitstreams: 1 moreira_mr_me_rcla.pdf: 4230931 bytes, checksum: d03e922a64150ccc7e14429414e1555c (MD5) / As imagens de satélite, por serem um registro de alvos com diferentes comportamentos espectrais e diferentes arranjos espaciais, respondem com variações tonais de cinza e variações texturais. Esta variação textural é analisada normalmente através de interpretação visual, que é uma sistematização de várias técnicas, as quais convergem para um único objetivo, a compartimentação da imagem. Em geral, a textura apresenta-se como sendo uma arma valiosa na interpretação de formas de relevo, drenagem e de padrões da cobertura vegetal e de uso da terra. Acredita-se que, a partir da utilização das técnicas de processamento digital de imagens e técnicas estatísticas multivariadas, como subsidiária na redução do caráter subjetivo da análise textural e da correspondência entre zonas homólogas, será possível favorecer a discriminação de elementos imageados, e encontrar um modelo que possibilite explicar mais satisfatoriamente a compartimentação e a relação de equivalência entre zonas que constituem texturas semelhantes. Desta forma, o objetivo geral do trabalho, é avaliar diversas metodologias, com intuito de realizar uma compartimentação fisiográfica, explorando o aspecto textural da imagem além da similaridade existentes entre as áreas após compartimentada. A área de estudo abrange os municípios de Itanhaém e Peruíbe localizados no litoral sul do Estado de São Paulo. A partir dos resultados obtidos, verificou-se que o método convencional de fotointerpretação juntamente com a aplicação da análise estatística multivariada, mostrou-se viável de ser aplicado apresentando resultados satisfatórios e inovadores. Já no processamento de alguns algoritmos de textura a redução de informações foi bastante grande, devido à redução dos valores de níveis de cinza e à homogeneização dos alvos; mostrando que o resultados não foram positivos... / Satellite images record surface features based on their different spectral behaviors and spatial arrangements. As such, these features are discernable from different shades of gray and textural variations seen in the images. These textural variations represent a systematic utilization of various techniques, which converge for a single objective: compartmentalization of the image. In general, texture is used as an important tool in the interpretation of relief forms, drainage patterns and vegetative cover and land-use patterns. Through the application of digital processing techniques and multivariable statistical analyses, it is possible to reduce the subjective character of textural analysis and correspondence between homologous zones, hence enhance the discrimination of different elements in an image. These methods can help find a model that allows for a better explanation of the compartmentalization and equivalence between zones that consist of similar textures. In this form, the general objective of the study is to evaluate diverse methodologies with the objective of determining the physiographic compartmentalization, exploiting the textural aspect of the image in addition to the existing similarities between areas following compartmentalization. The study area is within the municipalities of Itanhaém e Peruíbe, located along the south coastal region of São Paulo State. Based on the results obtained, it is confirmed that the conventional method of photo-interpretation, together with the application of multivariate statistical analysis, shows that it is a viable combination, yielding both satisfactory and innovative results. Already, in the processing of some textural algorithms, the reduction of information was significant, owing to the reduction of the values in the shades of gray and to the homogenization of targets, showing that the results were not positive...(Complete abstract click electronic access below)

As dificuldades de aprendizagem sobre estatística e suas aplicações simplesmente em razão da matemática envolvida, principalmente, pelos alunos dos cursos de humanas, fazem dela um desafio para o professor que a ministra e também para o aluno que aprende. Assim, esta tese busca mostrar o quanto à elaboração e o desenvolvimento de uma ferramenta de avaliação tipo teste em um ambiente virtual pode contribuir como apoio ao ensino presencial do estudo de ferramentas estatísticas multivariadas para os alunos de graduação em Administração da FEARP/USP, matriculados na disciplina Estatística Aplicada à Administração II. Este trabalho faz parte do projeto virtual denominado LaViE, que é um ambiente virtual de ensino-aprendizagem de estatística, e que está fundamentado em três dimensões: Pedagogia Virtual, Tecnologia da Comunicação e Processo de Validação. Para a criação dessa ferramenta de avaliação tipo teste online foi necessário, primeiramente, a elaboração de um protocolo para desenvolvimento e implementação desse sistema no LaViE. A metodologia, então, foi baseada em três etapas: 1) elaboração do protocolo fundamentado na pesquisa exploratória de pedagogia virtual com base na teoria sobre processo de ensino-aprendizagem para o desenvolvimento de um conjunto de regras e passos que balizasse a criação de questões testes on-line com níveis diferentes de ?adaptação? pelo aluno para cada módulo apresentado na disciplina em questão. Neste caso, foram criados três níveis de adaptação: básico (I), intermediário (II) e avançado (III); 2) implementação dessa ferramenta de avaliação no LaViE (teste seu conhecimento), com o desenvolvimento das questões baseadas nos assuntos sobre análise estatística multivariada e; 3) avaliação quantitativa da opinião dos alunos (usuários) quanto à usabilidade do sistema ?teste seu conhecimento? desenvolvido. Esses dados foram coletados quando essa disciplina foi ministrada, porém em dois períodos diferentes; no segundo semestre de 2005 como projeto-piloto, e no segundo semestre de 2006. Dessa forma, pôde ser feita uma análise comparativa da opinião dos alunos sobre o sistema em dois momentos diferentes. Para esse levantamento foram utilizados dois questionários aplicados diretamente aos alunos em sala de aula momentos antes da avaliação presencial da disciplina e um outro logo após essa avaliação presencial. Essas três etapas finalizadas deram condição de existência de uma ferramenta que faz parte de uma das três dimensões citadas do LaViE ? Processo de Validação. / The mathematical knowledge involved in the process of learning statistics and its applications, brings about difficulties to the Humanities department students, thus making it a challenge not only to those who teach it but also to the ones who learn it. Therefore, this work aims at showing the contribution the elaboration and development of a tool such as an online evaluation test can give, as a support to the presencial teaching of the study of multivariate statistical resources, to the FEARP/USP Business Management undergraduate students, registered in Applied Statistics to Business Management II. This study is part of a virtual project named LaViE which is a virtual environment of teaching-learning of Statistics based on three dimensions: Virtual Pedagogy, Communication Technology and Validation Process. For the development and implementation of the online evaluation test in the LaViE project, a protocol was elaborated. The methodology involved is based on three phases: 1) protocol production built on the virtual pedagogy exploratory research founded on the theory concerning the teaching-learning process in order to develop a set of rules and measures which support the creation of online test problems presenting different levels of adaptation for each module of the mentioned discipline. Thus, three levels of adaptation were created: basic (I), intermediate (II), and advanced (III); 2) implementation of such evaluation tool in the LaViE project (test your knowledge) by developing questions based on topics about multivariate statistical analysis; 3) quantitative evaluation of the users? opinion as to the usability of the ?test your knowledge? system. Data were collected in two distinct occasions: second semester of 2005, as a pilot project, and second semester of 2006, what enabled a comparative analysis of the system by the users at two different moments. This survey was conducted by means of two questionnaires completed in class by the students, being the first before the presencial discipline evaluation, and the second immediately after it. At the completion of the three phases previously mentioned, the Validation Process was obtained.

>Magister Scientiae - MSc / Groundwater is one of the most valuable natural resources on earth and it forms an important part of the total water resources of South Africa. For this reason, this resource should be monitored and controlled on a regular basis. The study was conducted in Newcastle, in the KwaZulu-Natal province of South Africa. The aim of this study was to assess groundwater quality geochemically and determine its suitability for domestic and irrigation purposes. For the purpose of this study 31 samples were collected from 31 boreholes in and around the town of Newcastle. The samples were analysed for Magnesium (Mg2+), Calcium (Ca2+), Sodium (Na+), Potassium (K+), Chloride (Cl-), Sulfate (SO42-), Bicarbonate (HCO3-), Nitrate (NO3-), Fluoride (F-) (pH, TDS and Ec. The SAQWG (DWAF, 1996) and the WHO (2011) water standards were used as the basis of evaluating the suitability of groundwater for drinking purposes. For irrigation, Electrical Conductivity (EC), Sodium Percent (Na %), Sodium Adsorption Ratio (SAR), Residual Sodium Carbonate (RSC), Kelly’s Ratio (KR), Magnesium Ratio (MR) and Permeability Index (PI) were used to evaluate suitability. Classical hydro-chemical methods together with multivariate statistical methods were used to further understand the composition controlling processes. Lastly, the spatial distribution of the results was presented using ArcGIS. The results showed that the groundwater is alkaline in nature and that most of the samples are within the permissible range of both SAWQG (DWAF, 1996) and WHO (2011). Few samples showed concentration of Na+, Cl-, SO42- , F- and TDS above the guideline value as per WHO (2011) standards. The order of abundance of major ions in the groundwater, based on their mean values is as follows: Na+>Ca2+>Mg2+>K+ and HCO3->SO42- >Cl->NO3-. Classical hydro-chemical methods revealed four hydro-chemical facies in the study area, which are Ca-Mg-HCO3, Na-HCO3, Ca-Na-SO4-HCO3 and Na-Cl. The major ion chemistry analysis revealed that the main composition controlling processes in the study area is rock-water interaction. It further revealed that the ionic concentration is due to silicate weathering, carbonate weathering, cation exchange, gypsum dissolution and halite dissolution. Factor analysis indicated three factors, which explained 79.71 % of the total variance in the water quality data. The first factor which accounted for the highest variance in the data was the Alkalinity factor, followed by the Hardness factor and the Anthropogenic factor which accounted for the least variance. The cluster analysis revealed five clusters and discriminant analysis showed that Na+, TH, HCO3- and SO42- discriminate these clusters by 96.8%. In conclusion, the study revealed that the groundwater in most of the boreholes in the study area is generally suitable for drinking and irrigation. This is with exception to boreholes 13 and 31 which showed concentrations higher than the permitted level by WHO (2011) standards of TDS, Na+, Cl-, SO42- and F-. Similarly, 45.16% the groundwater samples showed that the groundwater has high sodium hazard potential which makes water from these boreholes unsuitable for irrigation purposes without proper treatment. accounted for the least variance. The cluster analysis revealed five clusters and discriminant analysis showed that Na+, TH, HCO3- and SO42- discriminate these clusters by 96.8%. accounted for the least variance. The cluster analysis revealed five clusters and discriminant analysis showed that Na+, TH, HCO3- and SO42- discriminate these clusters by 96.8%.In conclusion, the study revealed that the groundwater in most of the boreholes in the study area is generally suitable for drinking and irrigation. This is with exception to boreholes 13 and 31 which showed concentrations higher than the permitted level by WHO (2011) standards of TDS, Na+, Cl-, SO42- and F-. Similarly, 45.16% the groundwater samples showed that the groundwater has high sodium hazard potential which makes water from these boreholes unsuitable for irrigation purposes without proper treatment.

The broader research area investigated during this programme was conceived from a goal to contribute towards solving the challenge of food security in the 21st century through the reduction of crop loss and minimisation of fungicide use. This is aimed to be achieved through the introduction of an empirical approach to agricultural disease monitoring. In line with this, the SYIELD project, initiated by a consortium involving University of Manchester and Syngenta, among others, proposed a novel biosensor design that can electrochemically detect viable airborne pathogens by exploiting the biology of plant-pathogen interaction. This approach offers improvement on the inefficient and largely experimental methods currently used. Within this context, this PhD focused on the adoption of multidisciplinary methods to address three key objectives that are central to the success of the SYIELD project: local spore ingress near canopies, the evaluation of a suitable model that can describe spore transport, and multivariate analysis of the potential monitoring network built from these biosensors. The local transport of spores was first investigated by carrying out a field trial experiment at Rothamsted Research UK in order to investigate spore ingress in OSR canopies, generate reliable data for testing the prototype biosensor, and evaluate a trajectory model. During the experiment, spores were air-sampled and quantified using established manual detection methods. Results showed that the manual methods, such as colourimetric detection are more sensitive than the proposed biosensor, suggesting the proxy measurement mechanism used by the biosensor may not be reliable in live deployments where spores are likely to be contaminated by impurities and other inhibitors of oxalic acid production. Spores quantified using the more reliable quantitative Polymerase Chain Reaction proved informative and provided novel of data of high experimental value. The dispersal of this data was found to fit a power decay law, a finding that is consistent with experiments in other crops. In the second area investigated, a 3D backward Lagrangian Stochastic model was parameterised and evaluated with the field trial data. The bLS model, parameterised with Monin-Obukhov Similarity Theory (MOST) variables showed good agreement with experimental data and compared favourably in terms of performance statistics with a recent application of an LS model in a maize canopy. Results obtained from the model were found to be more accurate above the canopy than below it. This was attributed to a higher error during initialisation of release velocities below the canopy. Overall, the bLS model performed well and demonstrated suitability for adoption in estimating above-canopy spore concentration profiles which can further be used for designing efficient deployment strategies. The final area of focus was the monitoring of a potential biosensor network. A novel framework based on Multivariate Statistical Process Control concepts was proposed and applied to data from a pollution-monitoring network. The main limitation of traditional MSPC in spatial data applications was identified as a lack of spatial awareness by the PCA model when considering correlation breakdowns caused by an incoming erroneous observation. This resulted in misclassification of healthy measurements as erroneous. The proposed Kriging-augmented MSPC approach was able to incorporate this capability and significantly reduce the number of false alarms.

This Master's thesis focuses on improving the understanding and monitoring of the Hot Isostatic Pressing (HIP) sintering process used by Seco Tools AB to manufacture cemented carbides for cutting tools. While essential for producing cutting tools with superior hardness and toughness the HIP sintering process introduces a complex relationship between the selected process parameters and the achieved materials properties. With the goal of establishing batch process monitoring capabilities, this master thesis employs Multivariate Statistical Process Control (MSPC) strategies through the creation of Batch Evolution Models (BEMs) and Batch Level Models (BLMs) to monitor, predict end-product quality, and analyze the batch production HIP sintering process.  The developed models effectively account for significant variation in the HIP sintering process and demonstrate potential in identifying deviant batches. Enhancements to the models' performance are achieved through the incorporation of preprocessing, phase-specific variable selection, and specialized model training. These proposed enhancements yield discernible improvements, as evidenced by enhanced model fit and other statistical metrics.  Challenges arise when the models are tested with real-time data due to progressive changes in some tracked process variables. Block-scaling is applied to restore the real-time monitoring capabilities, but also introduces additional complexity to the models. In addition, this master thesis highlights the need for continuous and regular maintenance of these models to ensure real-time monitoring and anomaly detection capabilities. The models demonstrate varied effectiveness in predicting final product quality. For instance, they exhibit some potential in predicting Magnetic Saturation (MS), but their ability to predict Magnetic Coercivity (HC) seems nonexistent. Despite attempts to improve the predictive abilities the models are still not able to confidently predict these metrics. The master’s thesis highlights variability in powder contents and access to data of known quality nonconformities as potential areas for improving the predictive models.