Information security has been an area of research and teaching within various computing disciplines in higher education almost since the beginnings of modern computers. The need for security in computing curricula has steadily grown over this period. Recently, with an emerging global crisis, because of the limitations of security within the nascent information technology infrastructure, the field of "cybersecurity" is emerging with international interest and support. Recent evolution of cybersecurity shows that it has begun to take shape as a true academic perspective, as opposed to simply being a training domain for certain specialized jobs. This report starts from the premise that cybersecurity is a "meta-discipline." That is, cybersecurity is used as an aggregate label for a wide variety of similar disciplines, much in the same way that the terms "engineering" and "computing" are commonly used. Thus, cybersecurity should be formally interpreted as a meta-discipline with a variety of disciplinary variants, also characterized through a generic competency model. The intention is that this simple organizational concept will improve the clarity with which the field matures, resulting in improved standards and goals for many different types of cybersecurity programs.
The prevalence of self-reported ADRs to first-line antiretroviral regimens was high and patients using DTG/TDF/3TC had a smaller number of ADRs. In addition to HAART regimen, sociodemographic, clinical, and quality of life characteristics were associated with ADRs.
This work focuses on issues typically encountered in organizations whose core business largely depends on ICT: continuous monitoring, continuous auditing, controlling and assessment of transactions risk. Organizations have been making efforts to implement methods and systems which enable them to increase reliability of their business and, simultaneously, to be in accordance with their organizational objectives and compliant with external regulations. Thus, this work presents and validates an innovative solution to implement Continuous Assurance services in information systems applicable to any organizational transaction, regardless of its type, dimension, business area or even its information system support technology. This last objective is pursued having as support an ontological model at an abstraction level that guarantees that independence. This research culminated with the development of a prototype and consequent results analysis, using data collected from the near-real implementation, allowing us to ensure the feasibility and the effective use of the proposal.
Abstract. Collaborative Filtering can be used in the context of e-learning to recommend learning objects to students and teachers involved with the teaching and learning process. Even though such technique presents a great potential for e-learning, studies related to this application in this field are still limited, mostly because the inexistence of available datasets for testing and evaluating. The present work evaluates two pre-processsing methods through clustering for future use of collaborative filtering algorithms. For that we use a large data set collected from the MERLOT repository. The initial results point out that clustering learning objects before the use of collaborative filtering techniques can improve the recommender performance.Resumo. No contexto de e-learning a filtragem colaborativa pode servir para a recomendação de objetos de aprendizagem aos estudantes e professores envolvidos no processo de ensino-aprendizagem. Ainda que tal técnica apresente grande potencial no contexto educacional, os estudos existentes sobre sua utilização nesse domínio são bastante limitados, sobretudo pelas barreiras encontradas na disponibilização de conjuntos de dados para teste e avaliação. O presente trabalho avalia dois métodos de pré-processamento por meio de clusterização para a posterior utilização por um algoritmo de filtragem colaborativa utilizando uma base de dados de ratings de objetos de aprendizagem coletada do tradicional repositório MERLOT. Os resultados iniciais encontrados apontam que o agrupamento de objetos de aprendizagem melhora o desempenho do algoritmo de filtragem colaborativa.
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