Grandes transformações sociais, concomitantemente ao crescimento da atividade industrial e seu consequente impacto no meio ambiente, fizeram com que a preservação ecológica se tornasse parte importante das estratégias organizacionais. Conceitualmente, o desenvolvimento sustentável das organizações busca o equilíbrio entre as variáveis econômica, social e ecológica. Deste modo, com o intuito de verificar se as práticas de proteção ambiental das empresas são recompensadas pelo mercado, este estudo teve o objetivo de analisar, por meio da utilização de técnicas de análise fatorial e de ferramentas computacionais, a existência de correlação entre o desempenho financeiro e o desempenho ambiental de uma amostra de empresas posicionadas entre as maiores organizações, em valor de mercado, listadas na Bolsa de Valores de São Paulo - Bovespa. Por meio da filtragem de informações, a amostra e o número de variáveis foram reduzidos, a fim de se obter um banco de dados sem informações faltantes, permitindo a aplicação das técnicas estatísticas com maior grau de confiabilidade. Considerando os indicadores analisados nos cruzamentos de fatores rotacionados realizados na presente pesquisa, os resultados obtidos revelam a independência entre os dois grupos de variáveis, concluindo que o desempenho ambiental das empresas não impacta sobre o desempenho financeiro das mesmas. / Great social changes, along with the growth of industrial activity and its consequent impact on the environment, caused the ecological preservation became an important part of organizational strategies. Conceptually, sustainable development of organizations seeks a balance between economic, social and ecological variables related to business operations. Thus, in order to verify if the environmental protection practices of companies are rewarded by the market, this study aims to analyze, through the use of means of factorial analysis and computational tools, the existence of a correlation between the financial performance and environmental performance of a sample of companies placed among the largest organizations in market value, listed on the São Paulo Stock Exchange - Bovespa. Through filtering of information, the sample and the number of variables were reduced in order to obtain a database without missing information, allowing the application of statistical techniques with higher degree of reliability. Whereas the indicators analyzed in the crosses of rotated factors performed in this study, the results show the independence between the two groups of variables, concluding that the environmental performance of companies has no impact on the financial performance of the same.

Em experimentação agrícola, é freqüente a necessidade de análise conjunta de grupos de experimentos. Em muitos casos, o pesquisador deseja generalizar resultados para condições gerais de regiões e/ou em avaliar o desempenho de vários genótipos (tratamentos) em diversos ambientes (locais e/ou ano). Quando um conjunto de experimentos é planejado para vários locais é necessário considerar o delineamento individual em cada local e a combinação total dos genótipos com os locais (interação genótipo × ambiente). Logo, os dados observados podem ser organizados em uma tabela de dupla entrada. Existem várias metodologias de análise e interpretação para a interação genótipo × ambiente proveniente de um grupo de cultivares testados em vários ambientes. Entre essas metodologias destaca-se os modelos AMMI ("additive main effects and multiplicative interaction model"), como o próprio nome diz é um método uni-multivariado, que engloba uma análise de variância para os efeitos principais, que são os efeitos dos genótipos (G) e os ambientes (E) e para efeitos multiplicativos (interação genótipo × ambiente), utiliza-se a decomposição em valor singular (DVS). Essa técnica multivariada baseia-se no uso dos autovalores e autovetores provenientes da matriz de interação genótipo × ambiente. Araújo e Dias (2005) verificaram o problema de superestimação e subestimação de autovalores estimados da maneira convencional. Para superar esses problemas de estimação de autovalores, Muirhead (1987) apresenta três métodos para corrigir autovalores estimados a partir das matrizes de covariâncias amostral e alerta que nem sempre essas correções mantêm a ordem decrescente de valores, assim é sugerido o uso de regressão isotônica para ordenar esses dados, mas propriamente um algoritmo apresentado por Lin e Pearlman (1985). Os resultados indicaram que: A regressão isotônica juntamente com o algoritmo foi necessária e se mostrou muito importante em todos conjuntos de dados; Houve uma redução no número de componentes significativos para serem retidos nos modelos, fazendo com que os modelos AMMI selecionados sejam mais parcimoniosos quando se utiliza qualquer um dos métodos de correção; O método 2 apresentou as menores taxa de correção da soma de quadrados da interação genótipo × ambiente e o método 3 apresentou a maiores taxa de correção; Em relação a medida RMSPDPRESS, os menores valores foram obtidos quando se utilizou o método de correção 2. Já o método de correção 3 apresentou os maiores valores para RMSPDPRESS; O método 2 também se mostrou melhor quando o interesse era verificar o ganho em número de repetições, sendo que este benefício esteve sempre próximo de 3 repetições. Já o método 3 é o que apresenta um menor ganho em número de repetições, em torno de duas repetições. / In agricultural research is common to analyse groups of experiments. In many cases, the researcher intends to generalize results to general conditions of areas and/or evaluate the responses of several genotypes (treatments) in several environments (places and/or years). When a group of experiments is planned for several places it is necessary to consider the of design in each place and the combinations of the genotypes with the places (the interaction of genotype × environment). The observed data can be organized in an array. There are several methods of analysis and interpretation for the genotype × environment interaction from a group of genotype tested in several environments. These methods include AMMI models ("additive main effect and multiplicative interaction models"). As the name says it is a uni-multivariate method, that includes an analysis of variance for the main effects (the effects of the genotypes (G) and environments (E)) and assumes multiplicative effects for the genotype × environment interaction, using a singular value decomposition (DVS). This method estimates the eigenvalues and eigenvectors deriving from the matrix of genotype × environment interaction. Araújo and Dias (2005) found an overestimation and underestimation problem with the eigenvalues in the conventional way. To correct these problems Muirhead (1987) presents three methods to correct the eigenvalues from covariance the matrix and noted that these do not always maintain the order of values. The author suggested the use of isotonic regression to correct the eigenvalues, using an algorithm presented by Lin and Pearlman (1985). The results indicated that: The isotonic regression with the algorithm is necessary and it showed very important in all groups of data; There was a reduction in the number of significant components to be kept in the models and the order that the AMMI model selected is more parsimonious when any of the correction methods is used; The method 2 has the smallest rate of correction to the sum of squares of the genotype × environment interaction and method 3 has the largest correction rate; The measure RMSPDPRESS was smallest when method of correction 2 was used. The method of correction 3 has the largest values for RMSPDPRESS; Method 2 was also better when the interest was to verify the gain in number of replicates, and this benefit was always close to 3 replicates. The method 3 gives the smaller gain in the number of replicates, of around two replicates.

Online communities of practice (CoPs) provide social spaces for people to connect, learn, and engage with one another around shared interests and passions. CoPs are innovatively employed within industry and education for their inherent knowledge management characteristics and as a means of improving professional practice. Measuring the success of a CoP is a challenge researchers are examining through various strategies. Recent literature supports measuring community effectiveness through the perceptions of its members; however, evaluating a community by means of member perception introduces complicating factors from outside the community. In order to gain insight into the importance of external factors, this quantitative study examined the influence of factors in the professional lives of educators on their perceptions of their CoP experience. Through an empirical examination of CoPs employed to connect educators and advance their professional learning, canonical correlation analysis was used to examine correlations between factors believed to be influential on the experiences of community members.

Orientador: Douglas Domingues Bueno / Resumo: A busca por uma melhor compreensão das regiões do cérebro e suas funções nas ações humanas tem sido uma tarefa árdua, porém muito útil, principalmente para aplicações da engenharia de interface cérebro-máquina (ICM), bem como para o auxílio a diagnósticos médicos a partir de sinais obtidos dos pacientes em avaliação. No contexto do presente trabalho, destacam-se os trabalhos de interface cérebro-máquina (ICM) pela abrangência no envolvimento de técnicas, métodos e ferramentas comumente estudadas nos cursos de engenharia. Em particular, análises envolvendo técnicas de processamento de sinais de eletroencefalograma (EEG) têm se mostrado de significativa importância para o desenvolvimento dessa área. Uma abordagem amplamente utilizada nesse contexto é a ICM usando Potenciais Visuais Evocados de Estados Estacionários (SSVEP, do inglês Steady-State Visual Evoked Potentials), que, de forma geral, são sinais caracterizados pela resposta evocada do cérebro a estímulos visuais modulados em uma frequência específica. Assim, este trabalho tem o objetivo de propor uma generalização do coeficiente de correlação, conceito-base da análise de correlação canônica (CCA), técnica que tem se mostrado robusta e eficiente no reconhecimento de padrões, especialmente no caso dos SSVEP, e detalhar seu comportamento em função dos parâmetros relevantes para se estabelecer melhores práticas de uso em aplicações de ICM, incluindo fatores fisiológicos, técnicos e operacionais. / Abstract: The search for a better understanding of the brain's anatomy and its functions on human actions has been a harsh yet very useful task, especially for brain-computer interface engineering applications, as well as for medical diagnosis using signals from patients. In the context of this work, brain-computer interface (BCI) applications are highlighted due to their compreehensiveness related to techniques, methods and tools commonly studied in engineering. In particular, analyses involving eletroencephalogram (EEG) signals processing have proven to be of great significance for developing this field of study. A widely used approach is Steady State Visual Evoked Potentials (SSVEP) based BCI, which, in general, are signals characterized by the brain’s evoked response to visual stimuli modulated at a certain frequency. This work aims thus to propose a generalization of the correlation coefficient, which entails Canonical Correlation Analysis (CCA), a technique that has presented robustness and efficiency for pattern recognition, especially in SSVEP-based BCIs, and describe its behavior under relevant varying parameters to stablish better use practices in BCI applications, comprising physiological, technical and operational factors. / Mestre

In medicine, data are produced from different sources and continuously stored in data depositories. Examples of these growing databases are quality registries. In Sweden, there are many cancer registries where data on cancer patients are gathered and recorded and are used mainly for reporting survival analyses to high level health authorities. In this thesis, a breast cancer quality registry operating in South-East of Sweden is used as the data source for newer analytical techniques, i.e. data mining as a part of knowledge discovery in databases (KDD) methodology. Analyses are done to sift through these data in order to find interesting information and hidden knowledge. KDD consists of multiple steps, starting with gathering data from different sources and preparing them in data pre-processing stages prior to data mining. Data were cleaned from outliers and noise and missing values were handled. Then a proper subset of the data was chosen by canonical correlation analysis (CCA) in a dimensionality reduction step. This technique was chosen because there were multiple outcomes, and variables had complex relationship to one another. After data were prepared, they were analyzed with a data mining method. Decision tree induction as a simple and efficient method was used to mine the data. To show the benefits of proper data pre-processing, results from data mining with pre-processing of the data were compared with results from data mining without data pre-processing. The comparison showed that data pre-processing results in a more compact model with a better performance in predicting the recurrence of cancer. An important part of knowledge discovery in medicine is to increase the involvement of medical experts in the process. This starts with enquiry about current problems in their field, which leads to finding areas where computer support can be helpful. The experts can suggest potentially important variables and should then approve and validate new patterns or knowledge as predictive or descriptive models. If it can be shown that the performance of a model is comparable to domain experts, it is more probable that the model will be used to support physicians in their daily decision-making. In this thesis, we validated the model by comparing predictions done by data mining and those made by domain experts without finding any significant difference between them. Breast cancer patients who are treated with mastectomy are recommended to receive radiotherapy. This treatment is called postmastectomy radiotherapy (PMRT) and there is a guideline for prescribing it. A history of this treatment is stored in breast cancer registries. We analyzed these datasets using rules from a clinical guideline and identified cases that had not been treated according to the PMRT guideline. Data mining revealed some patterns of non-compliance with the PMRT guideline. Further analysis with data mining revealed some reasons for guideline non-compliance. These patterns were then compared with reasons acquired from manual inspection of patient records. The comparisons showed that patterns resulting from data mining were limited to the stored variables in the registry. A prerequisite for better results is availability of comprehensive datasets. Medicine can take advantage of KDD methodology in different ways. The main advantage is being able to reuse information and explore hidden knowledge that can be obtained using advanced analysis techniques. The results depend on good collaboration between medical informaticians and domain experts and the availability of high quality data.

Smart cards are widely used in different areas of modern life including identification, banking, and transportation cards. Some types of cards are able to store data and process information as well. A number of them can run cryptographic algorithms to enhance the security of their transactions and it is usually believed that the information and values stored in them are completely safe. However, this is generally not the case due to the threat of the side channel. Side channel analysis is the process of obtaining additional information from the internal activity of a physical device beyond that allowed by its specifications. There exist different techniques to attempt to obtain information from a cryptosystem using other ways than the normally permitted. This thesis presents a series of experiments intended to study the side channel from a particular type of smart card, known as Java Cards. This investigation uses the well known technique, Correlation Analysis, and a new type of side channel attack called fast correlation in the frequency domain to study the side channel of Java Cards. This research presents a giant magnetoresistor (GMR) probe and for the first time, this type of sensor is used to investigate the side channel. A novel setup designed for studying the side channel of smart cards is described and two metrics used to evaluate the analysis results are presented. After testing the GMR probe and methodology on electronic devices executing the Advanced Encryption Standard (AES), such as 8 bit microcontrollers and 128 bit AES implementations on FPGAs, these techniques were applied to analyse two different models of Java Cards working in the contactless mode. The results show that successful attacks on a software implementation of AES running on both models of Java Cards are possible.

Smart cards are widely used in different areas of modern life including identification, banking, and transportation cards. Some types of cards are able to store data and process information as well. A number of them can run cryptographic algorithms to enhance the security of their transactions and it is usually believed that the information and values stored in them are completely safe. However, this is generally not the case due to the threat of the side channel. Side channel analysis is the process of obtaining additional information from the internal activity of a physical device beyond that allowed by its specifications. There exist different techniques to attempt to obtain information from a cryptosystem using other ways than the normally permitted. This thesis presents a series of experiments intended to study the side channel from a particular type of smart card, known as Java Cards. This investigation uses the well known technique, Correlation Analysis, and a new type of side channel attack called fast correlation in the frequency domain to study the side channel of Java Cards. This research presents a giant magnetoresistor (GMR) probe and for the first time, this type of sensor is used to investigate the side channel. A novel setup designed for studying the side channel of smart cards is described and two metrics used to evaluate the analysis results are presented. After testing the GMR probe and methodology on electronic devices executing the Advanced Encryption Standard (AES), such as 8 bit microcontrollers and 128 bit AES implementations on FPGAs, these techniques were applied to analyse two different models of Java Cards working in the contactless mode. The results show that successful attacks on a software implementation of AES running on both models of Java Cards are possible.

Submitted by Lucienne Costa (lucienneferreira@ufcg.edu.br) on 2018-08-30T17:25:22Z No. of bitstreams: 1 CAIO LIBÂNIO MELO JERÔNIMO – DISSERTAÇÃO (PPGCC) 2017.pdf: 4821943 bytes, checksum: 615dc29730ed480c902a5496dce5492f (MD5) / Made available in DSpace on 2018-08-30T17:25:22Z (GMT). No. of bitstreams: 1 CAIO LIBÂNIO MELO JERÔNIMO – DISSERTAÇÃO (PPGCC) 2017.pdf: 4821943 bytes, checksum: 615dc29730ed480c902a5496dce5492f (MD5) Previous issue date: 2017-07-07 / Capes / A demanda constante por melhorias na qualidade de vida dos habitantes das grandes cidades, somado à crescente urbanização desses centros, torna imprescindível a utilização de meios tecnológicos para um melhor entendimento da dinâmica dos centros urbanos e como seus habitantes interagem nesses ambientes. Nesse sentido, o aumento na utilização de dispositivos eletrônicos equipados com sistemas GPS e o constante anseio da humanidade por comunicação e, mais atualmente, por conexão à internet, vem criando novas oportunidades de estudo e também grandes desafios, especialmente no que tange a grande quantidade de dados gerados pelas redes sociais. Diversas pesquisas vêm utilizando esses dados para realizar estudos que buscam compreender traços do comportamento humano, especialmente no que diz respeito à mobilidade urbana e trajetórias. Porém, grande parte das pesquisas que utilizam dados georreferenciados se restringem às dimensões espaciais e temporais, desconsiderando outros aspectos que podem influenciar na mobilidade humana. Este trabalho propõe um método computacional capaz de extrair padrões de mobilidade oriundos de mensagens georreferenciadas de redes sociais e correlacioná-los com indicadores sociais, econômicos e demográficos fornecidos por órgãos governamentais, buscando assim, analisar quais possíveis fatores poderiam exercer alguma influência sobre a mobilidade dos moradores de uma grande cidade. Para validar o método proposto, foram utilizadas mensagens postadas no Twitter e um conjunto de indicadores sociais, ambos oriundos da cidade de Londres. Os resultados mostraram a existência de correlações entre padrões de mobilidade e indicadores sociais, especialmente os relacionados com condições de emprego e renda, como também com características étnico-religiosas dos indivíduos em estudo. / The constant need for improvements in life quality of inhabitants of big cities, together with the increasing urbanization of these centers, demands the use of technological means for a better understanding of the dynamics of urban centers and how their inhabitants interact in these environments. In this sense, the adoption of electronic devices equipped with GPS systems, the human need for communication and, more recently, for Internet connection, have brought new research opportunities and great challenges, especially due to the huge amount of data generated by social networks. Several studies have used this data to carry out research that seek to understand traces of human behavior, especially with respect to urban mobility and trajectories. However, much of the research that uses georeferenced data are restricted to spatial and temporal dimensions, disregarding other aspects that may influence human mobility. This work proposes a model capable of extracting mobility patterns from georeferenced messages of social networks and correlating them with social, economic and demographic indicators provided by government agencies, seeking to analyze which factors may impact in urban mobility. To evaluate the model, we used messages posted on Twitter and a set of social indicators, both related to the city of London. The results revealed the existence of correlations between mobility patterns and social indicators, especially those related to employment and income conditions, as well as ethnic and religious characteristics of the individuals under study.

This dissertation called The Statistical Investigation of Time and Economical Development of the Extraordinary Incident Kind Selected deals with traffic accidents on roads within the Czech Republic. The goal of this work is to investigate a time and economical connection of traffic accidents. The theoretical part specifies basic terms which are related to road transport in the Czech Republic and which are mainly based on valid laws in the field of road transportation. There is also deeply analysed the term "traffic accident" which has to gain specific features in order to be classified as a traffic accident. Subsequently, there are also presented and discussed the most common causes of accidents. Impacts of economic damage to the state budget were described by a certified methodology for calculating losses from a traffic accident rate on roads. Within possibilities of a bigger kind of an extraordinary incident during which emergency could be announced, there is described a system of crisis management in transport and an operation of Crisis Management Department of the Ministry of Transport. In the last section of the theoretical part there are summarized the basic methods of descriptive and mathematical statistics which were used for processing of the practical part of the dissertation. In the practical part three hypotheses were being tested based on the collected data, which was drawn from statistical yearbooks of a traffic accident rate published on the website of the Police of the Czech Republic. The methodology provides basic methods of descriptive and mathematical statistics to whom the gained data has been subjected. To verify the hypothesis H2 the amounts of damage per a time unit have a distribution close to the normal distribution. It was used within the mathematical statistics of nonparametric testing of hypothesis. Through the non-parametric testing was allowed to prove normality of damage amount in traffic accidents in the period 2009 - 2013. For verification of the hypothesis H1 number of traffic accidents and the amount of damage are positively correlated and hypotheses H3 time development of traffic accidents per one time unit can be expressed by linear regression with negative correlation. Simple linear and correlation dependence was used in the context of mathematical statistics. The aim of the hypotheses H1 and H3 mentioned above was to find out a kind of regression, depending on given statistical features, to find suitable regression function and to determine tightness of correlation using an appropriate coefficient. A negative correlation coefficient was calculated for the hypothesis H1 so it was rejected. This result is possible to comment on the fact that, although there is less material damage, the number of incidents in particular time units does not reflect this fact. For the hypotheses H3 we can conclude that traffic accidents have been declining in a longer time interval and this leads to fulfilment of the goal of the national road safety strategy 2011 - 2020. For the short time period 2009 - 2013 it is not possible to come to the same conclusion and the hypotheses H3 has to be rejected. In the context of a deeper research of the impact of economic damage to our state, it would be good to work e.g. with the amount of money which insurance companies have to pay to persons involved in an accident. We could also work with the amount of costs which the state has to spend on activities of organs of emergency service for dealing with all consequences of any emergencies associated with an accident. Determination of the total amount of economic damage from a traffic accident rate and from a number of traffic accidents helps us to realize the seriousness of this issue. Just as other indicators of traffic safety, economic damage and a number of traffic accidents are important indicators of prevention and effectiveness of traffic-safety measures.

The aim of the study was to determine whether there is a relationship between organisational culture and occupational health. The General Health Questionnaire and the South African Culture Instruments were used for this purpose. Structural equation modelling (SEM) was used for this purpose. The study focused on clarifying the two concepts and their impact on the organisation. The effects of general health factors were determined in the organisation under investigation. The existing organisational culture was also investigated. In conclusion, the assumption that occupational health can have an impact on organisational health, or vice versa, was confirmed. / Industrial and Organisational Psychology / MCom (Industrial and Organisational Psychology)