Big data analytics for proactive and predictive maintenance in electric car battery packs

The idea behind the project is to develop a methodology for analyzing and developing techniques for the diagnosis and the prediction of the state of charge and health of lithium-ion batteries for automotive applications. For lithium-ion batteries, residual functionality is measured in terms of state of health; however, this value cannot be directly associated with a measurable value, so it must be estimated. The development of the algorithms is based on the identification of the causes of battery degradation, in order to model and predict the trend. Therefore, models have been developed that are able to predict the electrical, thermal and aging behavior. In addition to the model, it was necessary to develop algorithms capable of monitoring the state of the battery, online and offline. This was possible with the use of algorithms based on Kalman filters, which allow the estimation of the system status in real time. Through machine learning algorithms, which allow offline analysis of battery deterioration using a statistical approach, it is possible to analyze information from the entire fleet of vehicles. Both systems work in synergy in order to achieve the best performance. Validation was performed with laboratory tests on different batteries and under different conditions. The development of the model allowed to reduce the time of the experimental tests. Some specific phenomena were tested in the laboratory, and the other cases were artificially generated.

Wireless Network Analytics for Next Generation Spectrum Awareness

The importance of networks, in their broad sense, is rapidly and massively growing in modern-day society thanks to unprecedented communication capabilities offered by technology. In this context, the radio spectrum will be a primary resource to be preserved and not wasted. Therefore, the need for intelligent and automatic systems for in-depth spectrum analysis and monitoring will pave the way for a new set of opportunities and potential challenges. This thesis proposes a novel framework for automatic spectrum patrolling and the extraction of wireless network analytics. It aims to enhance the physical layer security of next generation wireless networks through the extraction and the analysis of dedicated analytical features. The framework consists of a spectrum sensing phase, carried out by a patrol composed of numerous radio-frequency (RF) sensing devices, followed by the extraction of a set of wireless network analytics. The methodology developed is blind, allowing spectrum sensing and analytics extraction of a network whose key features (i.e., number of nodes, physical layer signals, medium access protocol (MAC) and routing protocols) are unknown. Because of the wireless medium, over-the-air signals captured by the sensors are mixed; therefore, blind source separation (BSS) and measurement association are used to estimate the number of sources and separate the traffic patterns. After the separation, we put together a set of methodologies for extracting useful features of the wireless network, i.e., its logical topology, the application-level traffic patterns generated by the nodes, and their position. The whole framework is validated on an ad-hoc wireless network accounting for MAC protocol, packet collisions, nodes mobility, the spatial density of sensors, and channel impairments, such as path-loss, shadowing, and noise. The numerical results obtained by extensive and exhaustive simulations show that the proposed framework is consistent and can achieve the required performance.

Analytics and optimization for emergency healthcare processes

This thesis deals with the analysis and management of emergency healthcare processes through the use of advanced analytics and optimization approaches. Emergency processes are among the most complex within healthcare. This is due to their non-elective nature and their high variability. This thesis is divided into two topics. The first one concerns the core of emergency healthcare processes, the emergency department (ED). In the second chapter, we describe the ED that is the case study. This is a real case study with data derived from a large ED located in northern Italy. In the next two chapters, we introduce two tools for supporting ED activities. The first one is a new type of analytics model. Its aim is to overcome the traditional methods of analyzing the activities provided in the ED by means of an algorithm that analyses the ED pathway (organized as event log) as a whole. The second tool is a decision-support system, which integrates a deep neural network for the prediction of patient pathways, and an online simulator to evaluate the evolution of the ED over time. Its purpose is to provide a set of solutions to prevent and solve the problem of the ED overcrowding. The second part of the thesis focuses on the COVID-19 pandemic emergency. In the fifth chapter, we describe a tool that was used by the Bologna local health authority in the first part of the pandemic. Its purpose is to analyze the clinical pathway of a patient and from this automatically assign them a state. Physicians used the state for routing the patients to the correct clinical pathways. The last chapter is dedicated to the description of a MIP model, which was used for the organization of the COVID-19 vaccination campaign in the city of Bologna, Italy.

Work environments implementation for genomic reporting and analytics

A global italian pharmaceutical company has to provide two work environments that favor different needs. The environments will allow to develop solutions in a controlled, secure and at the same time in an independent manner on a state-of-the-art enterprise cloud platform. The need of developing two different environments is dictated by the needs of the working units. Indeed, the first environment is designed to facilitate the creation of application related to genomics, therefore, designed more for data-scientists. This environment is capable of consuming, producing, retrieving and incorporating data, furthermore, will support the most used programming languages for genomic applications (e.g., Python, R). The proposal was to obtain a pool of ready-togo Virtual Machines with different architectures to provide best performance based on the job that needs to be carried out. The second environment has more of a traditional trait, to obtain, via ETL (Extract-Transform-Load) process, a global datamodel, resembling a classical relational structure. It will provide major BI operations (e.g., analytics, performance measure, reports, etc.) that can be leveraged both for application analysis or for internal usage. Since, both architectures will maintain large amounts of data regarding not only pharmaceutical informations but also internal company informations, it would be possible to digest the data by reporting/ analytics tools and also apply data-mining, machine learning technologies to exploit intrinsic informations. The thesis work will introduce, proposals, implementations, descriptions of used technologies/platforms and future works of the above discussed environments.

Corpos e subjetividades : análise dos processos de embodiment dos ursos no Espírito Santo

Este trabalho vem analisar processos de subjetivação de sujeitos homossexuais que se assumem como ursos. Trazemos o debate de corpos para explicitarmos seus agenciamentos, tanto na produção imagética do que socialmente seriam aqueles sujeitos, dos locais de onde falam, dos grupos que apresentam afinidades, quanto nos processos em que constroem a si mesmos. Os processos de subjetivação não pressupõem um sujeito autônomo, pois sofrem interferências de organizações de forças e saberes que operam na sociedade (FOUCAULT, 2003). Diante disso, recorremos à analíticas de poder propostas por Michel Foucault (1995), Judith Butler (2010) e Laclau e Mouffe (1987), tanto para nos afastarmos de noções de corpos passivos, universais e objetivos, recorrentes em enfoques em hegemonia na Administração, quanto para analisarmos sua construção somente em relação à construção de um sujeito, ou seja, em processos sociais, históricos e políticos de embodiments. Foi realizada uma pesquisa qualitativa, cujos dados foram coletados por meio de entrevistas individuais semiestruturadas com 19 participantes capixabas. Os dados foram analisados sob a ótica pós-estruturalista do discurso tendo em vista as abordagens laclauniana e foucaultiana. O trabalho conclui que o discurso ursino sobredetermina práticas dispersas no campo de homoafetividades ao articular um esquema corpóreo “masculino”. Este esquema se assume como uma das práticas hegemônicas LGBT e, consequentemente, é o primeiro a ser acionado nas subjetivações dos participantes. Porém, este processo não se concretiza de forma plena, nem elimina particularidades e contingências que parodiam as demandas comportamentais emergentes das construções identitárias.

A satisfação profissional dos enfermeiros especialistas em enfermagem de reabilitação

Em termos profissionais, a satisfação no trabalho é sem dúvida um tema bastante debatido e atual. Neste sentido, este estudo teve como objetivo analisar a satisfação profissional dos enfermeiros especialistas em enfermagem de reabilitação e também averiguar se o local de trabalho ou o exercício de cuidados de especialidade influenciam a satisfação profissional deste grupo de enfermeiros. A satisfação profissional foi avaliada através da aplicação da “Escala de Avaliação da Satisfação no Trabalho dos Enfermeiros”, construída e validada por Frederico & Loureiro (2009) a 306 profissionais de Enfermagem, especialistas em enfermagem de reabilitação. O Alpha de Cronbach foi de 0,85, refletindo um bom nível de consistência interna. Foram analisadas seis dimensões da satisfação: satisfação com as chefias; satisfação com benefícios e recompensas; satisfação com a natureza do trabalho; satisfação com a comunicação; satisfação com a equipa e satisfação com os requisitos do trabalho. Foi realizado um estudo transversal analítico. Na análise estatística dos dados, recorreu-se à análise fatorial, ao coeficiente de correlação de Spearman, a testes paramétricos t-student para amostras independentes e One-Way ANOVA. Os resultados mostram que os enfermeiros especialistas em enfermagem de reabilitação encontram-se ligeiramente insatisfeitos. Os fatores de insatisfação estão relacionados com benefícios e recompensas, requisitos do trabalho e com a comunicação. A natureza do trabalho e o relacionamento com a equipa são fatores com os quais obtêm maior satisfação. Em relação às chefias existe uma aproximação à satisfação. Relativamente à avaliação do grau de satisfação profissional global, concluiu-se que os enfermeiros que exercem funções nos Cuidados de Saúde Primários encontram-se mais insatisfeitos profissionalmente, do que os que exercem a sua atividade profissional ao nível hospitalar. Os enfermeiros que exercem cuidados gerais apresentam-se mais insatisfeitos do que os que exercem cuidados de especialidade. Também a idade e a remuneração pelo cargo desempenhado são fatores determinantes. Os enfermeiros mais jovens são os que se apresentam mais insatisfeitos. Os enfermeiros que não são remunerados pelo cargo desempenhado demonstram maior insatisfação profissional.

Using device detection techniques in M-learning scenarios

Recent studies of mobile Web trends show the continued explosion of mobile-friend content. However, the wide number and heterogeneity of mobile devices poses several challenges for Web programmers, who want automatic delivery of context and adaptation of the content to mobile devices. Hence, the device detection phase assumes an important role in this process. In this chapter, the authors compare the most used approaches for mobile device detection. Based on this study, they present an architecture for detecting and delivering uniform m-Learning content to students in a Higher School. The authors focus mainly on the XML device capabilities repository and on the REST API Web Service for dealing with device data. In the former, the authors detail the respective capabilities schema and present a new caching approach. In the latter, they present an extension of the current API for dealing with it. Finally, the authors validate their approach by presenting the overall data and statistics collected through the Google Analytics service, in order to better understand the adherence to the mobile Web interface, its evolution over time, and the main weaknesses.

Laboratório de criação digital

O projeto aqui apresentado consiste no desenvolvimento de um plano estratégico de marketing digital para o projeto Laboratório de Criação Digital (LCDPorto). O LCDPorto tem sete anos de existência, sem nunca ter definido uma estratégia de comunicação. O principal objetivo passa por aprofundar os vários temas que integram Marketing Digital, e desenvolver um plano que permita ao LCDPorto ganhar mais notoriedade pelas atividades que desenvolve e, também, obter mais público para participar nas atividades. Áreas como email marketing, contente marketing, SEO, social media e outras, não são áreas que funcionam de forma independente, mas sim, parte de um plano estratégico. Neste relatório serão apresentados alguns dos passos deste plano, nomeadamente Análise de Concorrência Online, estratégia de SEO, com o objetivo de obter dados prévios essenciais ao desenvolvimento desta estratégia de Marketing Digital.

Growth hacking

Com o crescente aumento de utilizadores e da importância no quotidiano de uma grande parte da população mundial, a Internet disponibiliza hoje às empresas, um conjunto de oportunidades que devidamente aproveitadas, se poderão traduzir na captação de novos clientes e no aumento da notoriedade da marca. Tem-se assistido nos últimos anos a um crescimento considerável do investimento das empresas em Marketing Digital, fazendo uso das mais variadas ferramentas que potenciam e aumentam a sua presença online. Decorrente do aumento de competividade no meio digital, têm surgido diversos casos de startups que desenvolveram e aplicaram técnicas e acções de marketing digital inovadoras, que se traduziram num crescimento exponencial do seu número de clientes/utilizadores. Desta forma, o presente trabalho tem como principais objetivos identificar o conceito de Growth Hacking, principais tácticas e ferramentas utilizadas, e avaliar qual impacto que o mesmo poderá ter para o sucesso de uma organização no meio online. Recorrendo ao estudo de dois casos de sucesso é feita uma análise das estratégias adotadas pelas empresas Uber e Dropbox e apresentadas as principais caraterísticas que as diferenciam e que permitiram o seu sucesso no meio digital.

The development and implementation of math projects in a HEI: expectations, objectives, experiences and analysis

An overwhelming problem in Math Curriculums in Higher Education Institutions (HEI), we are daily facing in the last decade, is the substantial differences in Math background of our students. When you try to transmit, engage and teach subjects/contents that your “audience” is unable to respond to and/or even understand what we are trying to convey, it is somehow frustrating. In this sense, the Math projects and other didactic strategies, developed through Learning Management System Moodle, which include an array of activities that combine higher order thinking skills with math subjects and technology, for students of HE, appear as remedial but important, proactive and innovative measures in order to face and try to overcome these considerable problems. In this paper we will present some of these strategies, developed in some organic units of the Polytechnic Institute of Porto (IPP). But, how “fruitful” are the endless number of hours teachers spent in developing and implementing these platforms? Do students react to them as we would expect? Do they embrace this opportunity to overcome their difficulties? How do they use/interact individually with LMS platforms? Can this environment that provides the teacher with many interesting tools to improve the teaching – learning process, encourages students to reinforce their abilities and knowledge? In what way do they use each available material – videos, interactive tasks, texts, among others? What is the best way to assess student’s performance in these online learning environments? Learning Analytics tools provides us a huge amount of data, but how can we extract “good” and helpful information from them? These and many other questions still remain unanswered but we look forward to get some help in, at least, “get some drafts” for them because we feel that this “learning analysis”, that tackles the path from the objectives to the actual results, is perhaps the only way we have to move forward in the “best” learning and teaching direction.

Exploraty Multivariate Statistical Methods Applied to Pharmaceutical Industry CRM Data

Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação

Heterogeneous sensor database framework for the sensor observation service: integrating remote and in-situ sensor observations at the database backend

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Location-based Marketing: the academic framework

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Building clusters for CRM strategies by mining airlines customer data

Trabalho de Projeto apresentado como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação

Descoberta de conhecimento accionável sobre os comportamentos geradores de risco operacional de colaboradores de uma instituição bancária

Trabalho de Projeto apresentado como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação