Development of new intelligent autonomous robotic assistant for hospitals

Continuous technological development in modern societies has increased the quality of life and average life-span of people. This imposes an extra burden on the current healthcare infrastructure, which also creates the opportunity for developing new, autonomous, assistive robots to help alleviate this extra workload. The research question explored the extent to which a prototypical robotic platform can be created and how it may be implemented in a hospital environment with the aim to assist the hospital staff with daily tasks, such as guiding patients and visitors, following patients to ensure safety, and making deliveries to and from rooms and workstations. In terms of major contributions, this thesis outlines five domains of the development of an actual robotic assistant prototype. Firstly, a comprehensive schematic design is presented in which mechanical, electrical, motor control and kinematics solutions have been examined in detail. Next, a new method has been proposed for assessing the intrinsic properties of different flooring-types using machine learning to classify mechanical vibrations. Thirdly, the technical challenge of enabling the robot to simultaneously map and localise itself in a dynamic environment has been addressed, whereby leg detection is introduced to ensure that, whilst mapping, the robot is able to distinguish between people and the background. The fourth contribution is geometric collision prediction into stabilised dynamic navigation methods, thus optimising the navigation ability to update real-time path planning in a dynamic environment. Lastly, the problem of detecting gaze at long distances has been addressed by means of a new eye-tracking hardware solution which combines infra-red eye tracking and depth sensing. The research serves both to provide a template for the development of comprehensive mobile assistive-robot solutions, and to address some of the inherent challenges currently present in introducing autonomous assistive robots in hospital environments.Open Acces

How do Clusters/Pipelines and Core/Periphery Structures Work Together in Knowledge Processes?

This paper contributes to the empirical identification of geographical and structural properties of innovative networks, focusing on the particular case of Global Navigation Satellite Systems (GNSS) at the European level. We show that knowledge bases of organizations and knowledge phases of the innovation process are the critical factors in determining the nature of the interplay between structural and geographical features of knowledge networks. Developing a database of R&D collaborative projects of the 5th and 6th European Framework Programs, we propose a methodology based on social network analysis. Its originality consists in starting from a bimodal network, in order to deduce two affiliation matrixes that allow us to study both the properties of the organization network and the properties of the project network. The results are discussed in the light of the mutual influence of the cognitive, structural and geographical dimensions on knowledge production and diffusion, and in the light of the knowledge drivers that give rise to the coexistence of a relational core-periphery structure with a geographical cluster and pipeline structure.Economic Geography, Knowledge networks, Social network analysis, EU Framework Programs, GNSS

Getting Into Networks and Clusters: Evidence on the GNSS composite knowledge process in (and from) Midi-Pyrénées

This paper aims to contribute to the empirical identification of clusters by proposing methodological issues based on network analysis. We start with the detection of a composite knowledge process rather than a territorial one stricto sensu. Such a consideration allows us to avoid the overestimation of the role played by geographical proximity between agents, and grasp its ambivalence in knowledge relations. Networks and clusters correspond to the complex aggregation process of bi or n-lateral relations in which agents can play heterogeneous structural roles. Their empirical reconstitution requires thus to gather located relational data, whereas their structural properties analysis requires to compute a set of indexes developed in the field of the social network analysis. Our theoretical considerations are tested in the technological field of GNSS (Global Satellite Navigation Systems). We propose a sample of knowledge relations based on collaborative R&D projects and discuss how this sample is shaped and why we can assume its representativeness. The network we obtain allows us to show how the composite knowledge process gives rise to a structure with a peculiar combination of local and distant relations. Descriptive statistics and structural properties show the influence or the centrality of certain agents in the aggregate structure, and permit to discuss the complementarities between their heterogeneous knowledge profiles. Quantitative results are completed and confirmed by an interpretative discussion based on a run of semi-structured interviews. Concluding remarks provide theoretical feedbacks.Knowledge, Networks, Economic Geography, Cluster, GNSS

The cellular epitranscriptome

Several chemical modifications in cellular RNAs have been identified to date. The most common internal modification of eukaryotic RNAs is known as m6A. This modification is able to configure the outcome of gene expression by adjusting RNA decay, translation efficiency, RNA structure and alternative splicing. Although thousands of m6A sites were found in RNAs of several plant species, nearly nothing is known about the impact of m6A on plant acclimation. Here, we showed that mRNAs encoding writers, erasers and readers - proteins capable of installing, removing and recognizing/interpreting RNA modifications, respectively, - are responsive to cold, heat and high light conditions in Arabidopsis thaliana. Quantification of m6A by mass spectrometric analysis showed that m6A-modified poly(A)-enriched mRNAs are more abundant under cold acclimation. Under this condition, knockdown lines for components of the major m6A writer complex showed a decrease in photosynthetic performance, especially in the fip37-4 mutant. Immunological analysis of photosynthetic proteins and blue native gels has shown that under cold specific proteins and supercomplexes are downregulated in fip37-4. Interestingly, fip37-4 has a further role in thylakoid organization under cold as revealed by chloroplast ultrastructure analysis. In addition, ROS formation was increased while the expression of cold acclimation-related genes was reduced in fip37-4 at low temperatures. Plant development regarding leaf area, weight, chlorophyll/anthocyanin content and root development was impaired under control, but a much stronger deficiency especially in photosynthesis was clear under cold acclimation. Altogether, these results indicate that FIP37-based RNA methylations play crucial roles in plastid functions under cold and several other aspects of plant development

Journalism and Big Data : the Nónio case

As Clive Humby discribed in 2006, “Big Data is the new oil”, which is why in 2014 more than 91% of Fortune 1000 companies were investing in Big Data projects, based on the promise of higher returns. The goal of this study is to see if that is also happening with Portuguese media corporations by examining Big Data’s impact on content production and the business model of newspapers and news channels. Big Data is a term that simultaneously describes large pools of data as well as the computer techniques used to analyse those data sets. This investigation focuses on the NÓNIO project, a Big Data initiative developed by five of the largest media companies in Portugal: Cofina, Global Media, Grupo Renascença Multimédia, Impresa and Media Capital. This dissertation follows a qualitative approach. In order to gather insights on how the NÓNIO is shaping newsrooms, interviews are conducted with the people in charge of the project at each of the five media companies. Findings suggest that Big Data is having a small impact in content production, but a big one in the business model, as it is radically changing how media companies conduct advertising and how they attract and retain subscriptions.Tal como Clive Humby descreveu, em 2006, “Big Data é o novo petróleo”. A comprovar a declaração, observou-se, em 2014, que mais de 91% das empresas da Fortune 1000 estavam a investir em projectos de Big Data. Esta investigação procura perceber se o mesmo se passa com as empresas de media portuguesas, analisando o impacto de Big Data na produção de conteúdo e no modelo de negócio dos jornais e canais de televisão noticiosos. A designação Big Data é utilizada para descrever simultaneamente grandes conjuntos de dados bem como as técnicas algorítmicas usadas para os analisar. O objeto de estudo desta investigação é o NÓNIO, um projecto de Big Data desenvolvido em conjunto por cinco dos maiores grupos de media portugueses: Cofina, Global Media, Grupo Renascença Multimédia, Impresa e Media Capital. A dissertação segue uma metodologia qualitativa. Para compreender as implicações do NÓNIO nas redacções, são feitas entrevistas aos responsáveis pelo projecto em cada uma das organizações. As conclusões revelam que a tecnologia Big Data está a ter um impacto reduzido na produção de conteúdo, mas um grande impacto no modelo de negócio das empresas de media, com as principais alterações a verificarem-se no modo como é feita a publicidade e na capacidade de retenção e atracção de subscriçõe

Learning at the Ends: From Hand to Tool Affordances in Humanoid Robots

One of the open challenges in designing robots that operate successfully in the unpredictable human environment is how to make them able to predict what actions they can perform on objects, and what their effects will be, i.e., the ability to perceive object affordances. Since modeling all the possible world interactions is unfeasible, learning from experience is required, posing the challenge of collecting a large amount of experiences (i.e., training data). Typically, a manipulative robot operates on external objects by using its own hands (or similar end-effectors), but in some cases the use of tools may be desirable, nevertheless, it is reasonable to assume that while a robot can collect many sensorimotor experiences using its own hands, this cannot happen for all possible human-made tools. Therefore, in this paper we investigate the developmental transition from hand to tool affordances: what sensorimotor skills that a robot has acquired with its bare hands can be employed for tool use? By employing a visual and motor imagination mechanism to represent different hand postures compactly, we propose a probabilistic model to learn hand affordances, and we show how this model can generalize to estimate the affordances of previously unseen tools, ultimately supporting planning, decision-making and tool selection tasks in humanoid robots. We present experimental results with the iCub humanoid robot, and we publicly release the collected sensorimotor data in the form of a hand posture affordances dataset.Comment: dataset available at htts://vislab.isr.tecnico.ulisboa.pt/, IEEE International Conference on Development and Learning and on Epigenetic Robotics (ICDL-EpiRob 2017

CASE ID DETECTION IN UNLABEL LED EVENT LOGS FOR PROCESS MINING

In the realm of data science, event logs serve as valuable sources of information, capturing sequences of events or activities in various processes. However, when dealing with unlabelled event logs, the absence of a designated Case ID column poses a critical challenge, hindering the understanding of relationships and dependencies among events within a case or process. Motivated by the increasing adoption of data-driven decision-making and the need for efficient data analysis techniques, this master’s project presents the "Case ID Column Identification Library" project. This library aims to streamline data preprocessing and enhance the efficiency of subsequent data analysis tasks by automatically identifying the Case ID column in unlabelled event logs. The project’s objective is to develop a versatile and user-friendly library that incorporates multiple methods, including a Convolutional Neural Network (CNN) and a parameterizable heuristic approach, to accurately identify the Case ID column. By offering flexibility to users, they can choose individual methods or a combination of methods based on their specific requirements, along with adjusting heuristic-based formula coefficients and settings for fine-tuning the identification process. This report presents a comprehensive exploration of related work, methodology, data understanding, methods for Case ID column identification, software library development, and experimental results. The results demonstrate the effectiveness of the proposed methods and their implications for decision support systems

ISOMORFISMO INSTITUCIONAL EM IESS PÚBLICAS CATARINENSES: UMA ANÁLISE COMPARATIVA DE PRÁTICAS EM EDUCAÇÃO AMBIENTAL

As pressões da sociedade em relação à questão ambiental levaram um conjunto bastante grande de organizações a desenvolverem políticas ligadas à educação ambiental. As universidades, organizações inovadoras sustentáveis por excelência, começam a adotar práticas ligadas ao tema. O presente artigo tentar explicar, a luz do isomorfismo institucional se existe similaridade entre as estruturas e formas ligadas a práticas de ensino em educação ambiental entre as duas principais universidades públicas catarinenses. Desenvolveu-se uma pesquisa qualitativa, com fins exploratórios, por estudo de caso e levantamento documental nos sites das universidades, identificando cursos e as disciplinas ligadas à educação ambiental, além de entrevistas com professores ligados a algumas destas disciplinas. Ao final conclui-se que o isomorfismo encontrado caracteriza-se na oferta de algumas disciplinas ligadas à educação ambiental, na sua inserção em novos currículos e novos cursos, sendo tipificados como cognitivo e normativo

Assessment of Literacy to Biotechnological Solutions for Environmental Sustainability in Portugal

In today’s world, the importance of preserving the environment has become increasingly evident. As a result, more sustainable solutions and techniques are being developed to combat environmental destruction. Higher education institutions are now including environmental themes in their technological courses to promote sustainable behavior and indirectly enhance environmental literacy among the population. This study aims to evaluate the level of literacy to biotechnological solutions for environmental sustainability in four areas, namely Air Pollution, Aquatic Pollution, Global Warming, and Energy Resources. A questionnaire was developed and distributed to a sample consisting of 471 individuals of both genders, age range between 15 and 78 years old, to collect data characterizing the sample and assess their literacy in environmental issues. The questionnaire was distributed in Portugal, and the participants were asked to indicate their level of agreement with several statements related to the aforementioned environmental themes. The findings suggest that literacy regarding biotechnological solutions for environmental sustainability is influenced by age group and academic qualifications. The age group above 65 years old is the one with the lowest levels of literacy, exhibiting frequencies of response I don’t know exceeding 50% in 10 out of the 22 issues present in the questionnaire. The findings also suggest that the levels of literacy are higher in the thematic areas of Global Warming and Aquatic Pollution and lower in the thematic areas of Air Pollution and Energy Resources, with lower levels of literacy in the issues that have not been widely disseminated by the media. Additionally, a model based on Artificial Neural Networks was presented to predict literacy to biotechnological solutions for environmental sustainability. The proposed model performs well, achieving accuracy rates of 90.8% for the training set and 86.6% for the test set

A importância das medidas de acalmia de tráfego na redução da sinistralidade rodoviária

O sistema rodoviário desempenha actualmente um papel importante na mobilidade da sociedade, mas também apresenta consequências negativas em termos sociais e económicos resultantes dos acidentes/sinistralidade rodoviária, de tal forma que urge reduzir estas mesmas consequências nefastas para a sociedade. As medidas de acalmia de tráfego fazem parte de um leque de medidas para a redução da sinistralidade rodoviária. A implementação de medidas de acalmia de tráfego no sistema rodoviário tem como objectivos a diminuição da velocidade e do volume de tráfego, permitindo deste modo reduzir o número de acidentes, bem como a gravidade dos mesmos. Ao longo deste estudo são abordadas as diferentes possibilidades de implementação de medidas de acalmia de tráfego, bem como os seus impactos, vantagens e desvantagens, na redução da sinistralidade rodoviária em meio urbano. O trabalho apresenta ainda, para um conjunto de casos reais correspondentes a locais identificados como sensíveis em termos de sinistralidade, na cidade da Covilhã, propostas de intervenção com recurso a técnicas de acalmia de tráfego.Nowadays the road system plays an important part in the mobility of society, but it also presents negative social and economical consequences resulting from road accidents, in a way that it urges to diminish these consequences. The traffic calming measures are a part of a range of measures to decrease road accidents. The implementation of these measures is intended to reduce the speed and traffic volume, and therefore the number of accidents, as well as their gravity. Along this study different possibilities of traffic calming measures are addressed, as well as their advantages and disadvantages and their impact in decreasing road accidents in urban context. This work also presents, for a set of real places located in Covilhã and considered sensitive in terms of road accidents, intervention proposals using traffic calming techniques