O desenvolvimento das capacidades dinâmicas habilita a empresa à inovar de forma mais eficiente, e por conseguinte, melhorar seu desempenho. Esta tese apresenta um framework para mensuração do grau de desenvolvimento das capacidades dinâmicas da empresa. Através de técnicas de text mining uma bag of words específica para as capacidades dinâmicas é proposta, bem como, baseado na literatura é proposto um conjunto de rotinas para avaliar a operacionalização e desenvolvimento das capacidades dinâmicas. Para avaliação das capacidades dinâmicas, foram aplicadas técnicas de text mining utilizando como fonte de dados os relatórios anuais de catorze empresas aéreas. Através da aplicação piloto foi possível realizar um diagnóstico das empresas aéreas e do setor. O trabalho aborda uma lacuna da literatura das capacidades dinâmicas, ao propor um método quantitativo para sua mensuração, assim como, a proposição de uma bag of words específica para as capacidades dinâmicas. Em termos práticos, a proposição pode contribuir para a tomada de decisões estratégicas embasada em dados, possibilitando assim inovar com mais eficiência e melhorar desempenho da firma. / The development of dynamic capabilities enables the company to innovate more efficiently and therefore improves its performance. This thesis presents a framework for measuring the dynamic capabilities development. Text mining techniques were used to propose a specific bag of words for dynamic capabilities. Furthermore, based on the literature, a group of routines is proposed to evaluate the operationalization and development of dynamic capabilities. In order to evaluate the dynamic capabilities, text mining techniques were applied using the annual reports of fourteen airlines as the data source. Through this pilot application it was possible to carry out a diagnosis of the airlines and the sector as well. The thesis approaches a dynamic capabilities literature gap by proposing a quantitative method for its measurement, as well as, the proposition of a specific bag of words for dynamic capabilities. The proposition can contribute to strategic decision making based on data, allowing firms to innovate more efficiently and improve performance.

Técnicas de visualização de informaçoes têm sido usadas para a representação de ontologias visando permitir a compreensão de conceitos e propriedades em domínios específicos. A visualização de ontologias deve ser baseada em representaccões gráficas efetivas e téquinas de interação que auxiliem tarefas de usuários relacionadas a diferentes entidades e aspectos. Ontologias podem ser complexas devido tanto à grande quantidade de níveis da hierarquia de classes como também aos diferentes atributos. Neste trabalho, propo˜e-se uma abordagem baseada no uso de múltiplas e coordenadas visualizações para explorar ambos os níceis intensional e extensional de uma ontologia. Para tanto, são empregadas estruturas visuais baseadas em árvores que capturam a característica hierárquiva de partes da ontologia enquanto preservam as diferentes categorias de classes. Além desta contribuição, propõe-se um inovador emprego do conceito "Degree of Interest" de modo a reduzir a complexidade da representação da ontologia ao mesmo tempo que procura direcionar a atenção do usuádio para os principais conceitos de uma determinada tarefa. Através da análise automáfica dos diferentes aspectos da ontologia, o principal conceito é colocado em foco, distinguindo-o, assim, da informação desnecessária e facilitando a análise e o entendimento de dados correlatos. De modo a sincronizar as visualizações propostas, que se adaptam facilmente às tarefas de usuários, e implementar esta nova proposta de c´calculo baseado em "Degree of Interest", foi desenvolvida uma ferramenta de visualização de ontologias interativa chamada OntoViewer, cujo desenvolvimento seguiu um ciclo interativo baseado na coleta de requisitos e avaliações junto a usuários em potencial. Por fim, uma última contribuição deste trabalho é a proposta de um conjunto de "guidelines"visando auxiliar no projeto e na avaliação de téncimas de visualização para os níceis intensional e extensional de ontologias. / Visualization techniques have been used for the representation of ontologies to allow the comprehension of concepts and properties in specific domains. Techniques for visualizing ontologies should be based on effective graphical representations and interaction techniques that support users tasks related to different entities and aspects. Ontologies can be very large and complex due to many levels of classes’ hierarchy as well as diverse attributes. In this work we propose a multiple, coordinated views approach for exploring the intensional and extensional levels of an ontology. We use linked tree structures that capture the hierarchical feature of parts of the ontology while preserving the different categories of classes. We also present a novel use of the Degree of Interest notion in order to reduce the complexity of the representation itself while drawing the user attention to the main concepts for a given task. Through an automatic analysis of ontology aspects, we place the main concept in focus, distinguishing it from the unnecessary information and facilitating the analysis and understanding of correlated data. In order to synchronize the proposed views, which can be easily adapted to different user tasks, and implement this new Degree of Interest calculation, we developed an interactive ontology visualization tool called OntoViewer. OntoViewer was developed following an iterative cycle of refining designs and getting user feedback, and the final version was again evaluated by ten experts. As another contribution, we devised a set of guidelines to help the design and evaluation of visualization techniques for both the intensional and extensional levels of ontologies.

abstract: Under the framework of intelligent management of power grids by leveraging advanced information, communication and control technologies, a primary objective of this study is to develop novel data mining and data processing schemes for several critical applications that can enhance the reliability of power systems. Specifically, this study is broadly organized into the following two parts: I) spatio-temporal wind power analysis for wind generation forecast and integration, and II) data mining and information fusion of synchrophasor measurements toward secure power grids. Part I is centered around wind power generation forecast and integration. First, a spatio-temporal analysis approach for short-term wind farm generation forecasting is proposed. Specifically, using extensive measurement data from an actual wind farm, the probability distribution and the level crossing rate of wind farm generation are characterized using tools from graphical learning and time-series analysis. Built on these spatial and temporal characterizations, finite state Markov chain models are developed, and a point forecast of wind farm generation is derived using the Markov chains. Then, multi-timescale scheduling and dispatch with stochastic wind generation and opportunistic demand response is investigated. Part II focuses on incorporating the emerging synchrophasor technology into the security assessment and the post-disturbance fault diagnosis of power systems. First, a data-mining framework is developed for on-line dynamic security assessment by using adaptive ensemble decision tree learning of real-time synchrophasor measurements. Under this framework, novel on-line dynamic security assessment schemes are devised, aiming to handle various factors (including variations of operating conditions, forced system topology change, and loss of critical synchrophasor measurements) that can have significant impact on the performance of conventional data-mining based on-line DSA schemes. Then, in the context of post-disturbance analysis, fault detection and localization of line outage is investigated using a dependency graph approach. It is shown that a dependency graph for voltage phase angles can be built according to the interconnection structure of power system, and line outage events can be detected and localized through networked data fusion of the synchrophasor measurements collected from multiple locations of power grids. Along a more practical avenue, a decentralized networked data fusion scheme is proposed for efficient fault detection and localization. / Dissertation/Thesis / Ph.D. Electrical Engineering 2013

Game Analytics är ett område som vuxit fram under senare år. Spelutvecklare har möjligheten att analysera hur deras kunder använder deras produkter ned till minsta knapptryckning. Detta kan resultera i stora mängder data och utmaning ligger i att lyckas göra något vettigt av sitt data. Utmaningarna med speldata beskrivs ofta med liknande egenskaper som används för att beskriva Big Data: volume, velocity och variability. Detta borde betyda att det finns potential för ett givande samarbete. Studiens syfte är att analysera och utvärdera vilka möjligheter Big Data ger att utveckla området Game Analytics. För att uppfylla syftet genomförs en litteraturstudie och semi-strukturerade intervjuer med individer aktiva inom spelbranschen. Resultatet visar att källorna är överens om att det finns värdefull information bland det data som kan lagras, framförallt i de monetära, generella och centrala (core) till spelet värdena. Med mer avancerad analys kan flera andra intressanta mönster grävas fram men ändå är det övervägande att hålla sig till de enklare variablerna och inte bry sig om att gräva djupare. Det är inte för att datahanteringen skulle bli för omständlig och svår utan för att analysen är en osäker investering. Även om någon tar sig an alla utmaningar speldata ställer fram finns det en osäkerhet på informationens tillit och användbarheten hos svaren. Framtidsvisionerna inom Game Analytics är blygsamma och inom den närmsta framtiden är det nästan bara effektiviseringar och en utbredning som förutspås vilket inte direkt ställer några nya krav på datahanteringen. / Game Analytics is a research field that appeared recently. Game developers have the ability to analyze how customers use their products down to every button pressed. This can result in large amounts of data and the challenge is to make sense of it all. The challenges with game data is often described with the same characteristics used to define Big Data: volume, velocity and variability. This should mean that there is potential for a fruitful collaboration. The purpose of this study is to analyze and evaluate what possibilities Big Data has to develop the Game Analytics field. To fulfill this purpose a literature review and semi-structured interviews with people active in the gaming industry were conducted. The results show that the sources agree that valuable information can be found within the data you can store, especially in the monetary, general and core values to the specific game. With more advanced analysis you may find other interesting patterns as well but nonetheless the predominant way seems to be sticking to the simple variables and staying away from digging deeper. It is not because data handling or storing would be tedious or too difficult but simply because the analysis would be too risky of an investment. Even if you have someone ready to take on all the challenges game data sets up, there is not enough trust in the answers or how useful they might be. Visions of the future within the field are very modest and the nearest future seems to hold mostly efficiency improvements and a widening of the field, making it reach more people. This does not really post any new demands or requirements on the data handling.

En la actualidad, las empresas manejan una gran cantidad de información, el cual era inimaginable años atrás, la capacidad de recolectarla es muy impresionante. En consecuencia, para varias empresas esta información se ha convertido en un tema difícil de manejar. Diariamente, las empresas sea del sector, tipo o tamaño que sea, toman decisiones, las cuales la mayoría son decisiones estratégicas que pueden afectar el correcto funcionamiento de la empresa. Es aquí, donde ingresa una de las herramientas más mencionadas en el área de TI: Business Intelligence, este término se refiere al uso de datos en una empresa para facilitar la toma de decisiones, explotar su información, y mejor aún, plantear o predecir escenarios a futuro. El presente trabajo permitirá al área de Marketing de la empresa Iasacorp International, obtener información sobre el comportamiento y hábitos de compra de los clientes, mediante técnicas de minería de datos como Árbol de Decisión y técnicas de análisis predictivo, la cual ayudará a la toma de decisiones para establecer estrategias de venta de las líneas (bisutería, complementos de vestir, accesorios de cabello, etc.) que maneja la empresa y de las próximas compras. De acuerdo a lo planteado anterior mente, la implementación de este tipo de sistemas de información ofrece a la empresa ventajas competitivas, permite a la gerencia analizar y entender mejor la información y por consecuencia tomar mejores decisiones de negocio. At present, companies handle a lot of information, which was unimaginable years ago, the ability to collect it is very impressive. Consequently, for many companies this information has become a difficult issue to handle. Due to the large volume of information we have, instead of being useful you can fall in a failed attempt to give proper use. Every day, companies in any sector, type or size, make decisions, most of which are strategic decisions that may affect the proper functioning of the company. It´s here, where we talk about the most mentioned tools in the area of IT: Business Intelligence, this term refers to the use of data in an enterprise to facilitate decision-making, exploit their information, and better yet, raise or predict scenarios future. This work will allow the area Iasacorp Marketing Company International, information on the behavior and buying habits of customers, through predictive analysis techniques, which will help the decision to establish sales strategies lines (jewelry, clothing, hair accessories, etc.) that manages the company and nearby shopping. According to the points made above, the implementation of such information systems offers companies competitive advantages, allows management to better analyze and understand information and consequently make better business decisions.

Submitted by Divisão de Documentação/BC Biblioteca Central (ddbc@ufam.edu.br) on 2017-10-18T13:19:42Z No. of bitstreams: 2 Dissertação - Euler V. Silva.pdf: 7157206 bytes, checksum: 4be0bca843596ef4c83ff1a1bcd9903f (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Approved for entry into archive by Divisão de Documentação/BC Biblioteca Central (ddbc@ufam.edu.br) on 2017-10-18T13:20:01Z (GMT) No. of bitstreams: 2 Dissertação - Euler V. Silva.pdf: 7157206 bytes, checksum: 4be0bca843596ef4c83ff1a1bcd9903f (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Made available in DSpace on 2017-10-18T13:20:01Z (GMT). No. of bitstreams: 2 Dissertação - Euler V. Silva.pdf: 7157206 bytes, checksum: 4be0bca843596ef4c83ff1a1bcd9903f (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2017-08-24 / FAPEAM - Fundação de Amparo à Pesquisa do Estado do Amazonas / In public high schools, it is increasingly difficult for the teacher to identify individual or collective difficulties in specific content of the Mathematics discipline. According to the report presented by the National Institute of Educational Studies and Research Anísio Teixeira (INEP), a body linked to the Ministry of Education (MEC), the level of learning of Brazilian students in Secondary Education has worsened in Mathematics and reached in 2015 Worse result since 2005, beginning of the historical series of the System of Evaluation of Basic Education (SAEB). Based on this information, the present work proposes and describes the contributions of the use of a mechanism to visualize student performance in assessments carried out in Moodle by the teacher. As proof of concept, the proposed mechanism was based on a prototype to dynamically present the result of the evaluations in graphs. The applied methodology was delineated by Case Study, and submitted to the validation of Mathematics teachers of the 1st Year of High School of a Federal Institute of Education (IFE) of the State of Amazonas. According to the teachers' opinion register, the results indicate that the approach is valid, since it allows the application of pedagogical interventions based on the information provided by the mechanism. / Nas escolas públicas de Ensino Médio é cada vez mais difícil para o professor identificar as dificuldades individuais ou coletivas em conteúdos específicos da disciplina de Matemática. De acordo com o relatório apresentado pelo Instituto Nacional de Estudos e Pesquisas Educacionais Anísio Teixeira (INEP), órgão vinculado ao Ministério da Educação (MEC), o nível de aprendizado dos estudantes brasileiros no Ensino Médio piorou em Matemática e chegou em 2015 ao pior resultado desde 2005, início da série histórica do Sistema de Avaliação da Educação Básica (SAEB). Com base nessas informações, o presente trabalho propõe e descreve quais são as contribuições do uso de um mecanismo para visualização do desempenho de estudantes em avaliações realizadas no Moodle pelo professor. Como prova de conceito, o mecanismo proposto foi baseado num protótipo para apresentar dinamicamente o resultado das avaliações em gráficos. A metodologia aplicada foi delineada por Estudo de Caso e submetido à validação de professores de Matemática do 1º Ano do Ensino Médio de um Instituto Federal de Educação (IFE) do Estado do Amazonas. De acordo com o registro da opinião dos professores, os resultados apontam que a abordagem é válida, pois permite aplicação de intervenções pedagógicas com base nas informações fornecidas pelo mecanismo.

Genom att analysera olika individers surfbeteende så kan man även optimera hemsidor efter sitt eget tycke. Detta gör man med hjälp av webbanalysverktyg som finns av alla dess slag. Betalversioner såväl som gratisversioner. Dessa i sin tur innehåller olika features som möjliggör, för dig som användare, olika tillvägagångssätt och metoder över hur du ska analysera en besökares beteende. Med denna uppsats har vi valt att undersöka vilka av de vanligaste features som finns som är de viktigaste ur en användares perspektiv. För att få svar på vår huvudfrågeställning, Vilka är de viktigaste features inom webbanalysverktyg för användare och varför? gjorde vi en kvantitativ enkätundersökning innehållandes kvalitativa element. De respondenter vi hade utgjorde dock en mindre grupp som inte kunde representera en större population, men detta kan ändå ligga till grund för vidare forskning med tanke på att våra kvalitativa element gav bra riktmärken. Under analysen framgick det att flera features var mer prioriterade än andra utifrån en användares perspektiv och vi identifierade ett flertal faktorer som stöttade detta.   Studien resulterade i en beskrivning över vilka som är de mest förekommande features, hur viktiga de är för användare samt vilka faktorer som antyder på detta.

Google Analytics is the most widely used web traffic analytics program in the world with a wide array of functionality which serve several different purposes for its users. However the cost of training employees in the usage of Google Analytics can be expensive and time consuming due to the generality of the software. The purpose of this thesis is to explore an alternative solution to hav- ing employees learn the default Google Analytics interface and thus possibly re- ducing training expenses. A prototype written in the Java programming lan- guage is developed which implements the MVC and facade software patterns for the purpose of making the development process more efficient. It contains a feature for retrieving custom reports from Google Analytics using Google’s Core Reporting API in addition to two web pages are integrated into the proto- type using the Google Embed API. In the result the prototype is used along with the software estimation method COCOMO to make an estimation of the amount of effort required to develop a similar program. This is done by counting the prototype’s source lines of code manually, following the guidelines given by the COCOMO manual, and then implementing the result in the COCOMO estima- tion formula. The count of lines of code for the entire prototype is 567 and the count which considers reused code is 466. The value retrieved from the formula is 1.61±0.14 person months for the estimation of the entire program and 1.31± 0.16 for a program with reused code. The conclusion of the thesis is that the res- ult from the estimation has several weaknesses and further research is necessary in order to improve the accuracy of the result.

Social media analytics is a critical research area spawned by the increasing availability of rich and abundant online user-generated content. So far, social media analytics has had a profound impact on organizational decision making in many aspects, including product and service design, market segmentation, customer relationship management, and more. However, the cybersecurity sector is behind other sectors in benefiting from the business intelligence offered by social media analytics. Given the role of hacker communities in cybercrimes and the prevalence of hacker communities, there is an urgent need for developing hacker social media analytics capable of gathering cyber threat intelligence from hacker communities for exchanging hacking knowledge and tools. My dissertation addressed two broad research questions: (1) How do we help organizations gain cyber threat intelligence through social media analytics on hacker communities? And (2) how do we advance social media analytics research by developing innovative algorithms and models for hacker communities? Using cyber threat intelligence as a guiding principle, emphasis is placed on the two major components in hacker communities: threat actors and their cybercriminal assets. To these ends, the dissertation is arranged in two parts. The first part of the dissertation focuses on gathering cyber threat intelligence on threat actors. In the first essay, I identify and profile two types of key sellers in hacker communities: malware sellers and stolen data sellers, both of which are responsible for data breach incidents. In the second essay, I develop a method for recovering social interaction networks, which can be further used for detecting major hacker groups, and identifying their specialties and key members. The second part of the dissertation seeks to develop cyber threat intelligence on cybercriminal assets. In the third essay, a novel supervised topic model is proposed to further address the language complexities in hacker communities. In the fourth essay, I propose the development of an innovative emerging topic detection model. Models, frameworks, and design principles developed in this dissertation not only advance social media analytics research, but also broadly contribute to IS security application and design science research.

Despite advances in the application of analytics in business functions such as marketing and finance, and a significant degree of interest in the topic of Human Resource analytics, its usage is still nowhere near where it could be. This study’s primary aim was to measure the levels of usage of HR analytics among South African organisations, an exercise that has not been done before. This qualitative, exploratory study was conducted among 16 senior Human Resource practitioners from large organisations in South Africa. Being qualitative, a limitation of this study is that it is not representative and therefore the results cannot be generalised. Further opportunities therefore exist for quantitative, longitudinal research in this field to objectively ascertain the extent of usage of HR analytics. It was found that South African organisations’ usage of HR analytics is still in its infancy and that the concept and its implications are little understood. It also found that there is consensus regarding the importance for HR analytics in organisations and that the HR analytical skills challenge is the main hindrance to implementation. Importantly, the study demonstrated and that the overall outlook for HR analytics is positive. The research makes recommendations and proposes a model that should enable organisations, the HR profession and the academic world to implement HR analytics. / Dissertation (MBA)--University of Pretoria, 2013. / ccgibs2014 / Gordon Institute of Business Science (GIBS) / MBA / Unrestricted