37 resultados para IoT platforms
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Dissertação de mestrado integrado em Engenharia de Telecomunicações e Informática
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DNA microarrays are one of the most used technologies for gene expression measurement. However, there are several distinct microarray platforms, from different manufacturers, each with its own measurement protocol, resulting in data that can hardly be compared or directly integrated. Data integration from multiple sources aims to improve the assertiveness of statistical tests, reducing the data dimensionality problem. The integration of heterogeneous DNA microarray platforms comprehends a set of tasks that range from the re-annotation of the features used on gene expression, to data normalization and batch effect elimination. In this work, a complete methodology for gene expression data integration and application is proposed, which comprehends a transcript-based re-annotation process and several methods for batch effect attenuation. The integrated data will be used to select the best feature set and learning algorithm for a brain tumor classification case study. The integration will consider data from heterogeneous Agilent and Affymetrix platforms, collected from public gene expression databases, such as The Cancer Genome Atlas and Gene Expression Omnibus.
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Doctoral Program in Computer Science
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We are living in the era of Big Data. A time which is characterized by the continuous creation of vast amounts of data, originated from different sources, and with different formats. First, with the rise of the social networks and, more recently, with the advent of the Internet of Things (IoT), in which everyone and (eventually) everything is linked to the Internet, data with enormous potential for organizations is being continuously generated. In order to be more competitive, organizations want to access and explore all the richness that is present in those data. Indeed, Big Data is only as valuable as the insights organizations gather from it to make better decisions, which is the main goal of Business Intelligence. In this paper we describe an experiment in which data obtained from a NoSQL data source (database technology explicitly developed to deal with the specificities of Big Data) is used to feed a Business Intelligence solution.
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The Childhood protection is a subject with high value for the society, but, the Child Abuse cases are difficult to identify. The process from suspicious to accusation is very difficult to achieve. It must configure very strong evidences. Typically, Health Care services deal with these cases from the beginning where there are evidences based on the diagnosis, but they aren’t enough to promote the accusation. Besides that, this subject it’s highly sensitive because there are legal aspects to deal with such as: the patient privacy, paternity issues, medical confidentiality, among others. We propose a Child Abuses critical knowledge monitor system model that addresses this problem. This decision support system is implemented with a multiple scientific domains: to capture of tokens from clinical documents from multiple sources; a topic model approach to identify the topics of the documents; knowledge management through the use of ontologies to support the critical knowledge sensibility concepts and relations such as: symptoms, behaviors, among other evidences in order to match with the topics inferred from the clinical documents and then alert and log when clinical evidences are present. Based on these alerts clinical personnel could analyze the situation and take the appropriate procedures.
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The Internet of Things (IoT) is a concept that can foster the emergence of innovative applications. In order to minimize parents’s concerns about their children’s safety, this paper presents the design of a smart Internet of Things system for identifying dangerous situations. The system will be based on real time collection and analysis of physiological signals monitored by non-invasive and non-intrusive sensors, Frequency IDentification (RFID) tags and a Global Positioning System (GPS) to determine when a child is in danger. The assumption of a state of danger is made taking into account the validation of a certain number of biometric reactions to some specific situations and according to a self-learning algorithm developed for this architecture. The results of the analysis of data collected and the location of the child will be able in real time to child’s care holders in a web application.
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Today it is easy to find a lot of tools to define data migration schemas among different types of information systems. Data migration processes use to be implemented on a very diverse range of applications, ranging from conventional operational systems to data warehousing platforms. The implementation of a data migration process often involves a serious planning, considering the development of conceptual migration schemas at early stages. Such schemas help architects and engineers to plan and discuss the most adequate way to migrate data between two different systems. In this paper we present and discuss a way for enriching data migration conceptual schemas in BPMN using a domain-specific language, demonstrating how to convert such enriched schemas to a first correspondent physical representation (a skeleton) in a conventional ETL implementation tool like Kettle.
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Today recovering urban waste requires effective management services, which usually imply sophisticated monitoring and analysis mechanisms. This is essential for the smooth running of the entire recycling process as well as for planning and control urban waste recovering. In this paper we present a business intelligence system especially designed and im- plemented to support regular decision-making tasks on urban waste management processes. The system provides a set of domain-oriented analytical tools for studying and characterizing poten- tial scenarios of collection processes of urban waste, as well as for supporting waste manage- ment in urban areas, allowing for the organization and optimization of collection services. In or- der to clarify the way the system was developed and the how it operates, particularly in process visualization and data analysis, we also present the organization model of the system, the ser- vices it disposes, and the interface platforms for exploring data.
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Modeling Extract-Transform-Load (ETL) processes of a Data Warehousing System has always been a challenge. The heterogeneity of the sources, the quality of the data obtained and the conciliation process are some of the issues that must be addressed in the design phase of this critical component. Commercial ETL tools often provide proprietary diagrammatic components and modeling languages that are not standard, thus not providing the ideal separation between a modeling platform and an execution platform. This separation in conjunction with the use of standard notations and languages is critical in a system that tends to evolve through time and which cannot be undermined by a normally expensive tool that becomes an unsatisfactory component. In this paper we demonstrate the application of Relational Algebra as a modeling language of an ETL system as an effort to standardize operations and provide a basis for uncommon ETL execution platforms.
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The MAP-i Doctoral Programme in Informatics, of the Universities of Minho, Aveiro and Porto
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The MAP-i Doctoral Program of the Universities of Minho, Aveiro and Porto
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Tese de Doutoramento em Tecnologias e Sistemas de Informação.
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Dissertação de mestrado em Engenharia de Telecomunicações e Informática
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In the context of the scientific research into radio, recent years have encouraged many theories about the meaning of a post-radio (Oliveira & Portela, 2011), thus enlisting several parameters regarding the inclusion of contemporary radio in the digital and online environments. This digital migration has led to the development of mobile applications for radio, broadening the communicative potential of audiences (Aguado, Feijoo & Martínez, 2013), as well as promoting convergence of interactive content among listeners-users. Aware of this opportunity, the main broadcasters in Spain and Portugal have broadened their radiophonic scope to the mobile platform, especially geared towards smartphones through the development of mobile applications, commonly known as apps (Cerezo, 2010). As a symbol of a culture in permanent changing, smartphones not only provide greater easiness in terms of access and interaction, but also afford larger opportunities for disseminating content among audiences, a phenomenon that some studies have labelled as user distributed content (Villi, 2012). This article presents an exploratory analysis of the current policies of the main Spanish and Portuguese radio broadcasters regarding mobile applications, evaluating the different levels of interaction and participation in these platforms. This observation led to the conclusion, among other findings, that the mobile platform represents a supplementary channel for traditional FM radio, rather than a new medium with its own language and expression.
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Dissertação de mestrado integrado em Engenharia de Telecomunicações e Informática