114 research outputs found

    Visualization for biomedical ontologies alignment

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    Tese de mestrado, Bioinformática e Biologia Computacional (Bioinformática), Universidade de Lisboa, Faculdade de Ciências, 2016Desde o início do século, a investigação biomédica e a prática clínica levaram a uma acumulação de grandes quantidades de informação, por exemplo, os dados resultantes da sequenciação genómica ou os registos médicos. As ontologias fornecem um modelo estruturado com o intuito de representar o conhecimento e têm sido bem sucedidas no domínio biomédico na melhoria da interoperabilidade e partilha. O desenvolvimento desconectado das ontologias biomédicas levou à criação de modelos que apresentam domínios idênticos ou sobrepostos. As técnicas de emparelhamento de ontologias foram desenvolvidas afim de estabelecer ligações significativas entre as classes das ontologias, por outras palavras, para criar alinhamentos. Para alcançar um alinhamento ótimo é, não só importante melhorar as técnicas de emparelhamentos mas também criar as ferramentas necessárias para que possa existir intervenção humana, particularmente na visualização. Apesar da importância da intervenção de utilizadores e da visualização no emparelhamento de ontologias, poucos sistemas o suportam, sobretudo para grandes e complexas ontologias como as do domínio biomédico, concretamente no contexto da revisão de alinhamentos e interpretação de incoerências lógicas. O objetivo central desta tese consistiu na investigação dos principais paradigmas de visualização de ontologias, no contexto do alinhamento de ontologias biomédicas, e desenvolver abordagens de visualização e interação que vão de encontro a estes desafios. O trabalho desenvolvido levou, então, à criação de um novo módulo de visualização para um sistema de emparelhamento do state of the art que suporta a revisão de alinhamentos, e à construção de uma ferramenta online que visa ajudar o utilizador a compreender os conflitos encontrados nos alinhamentos, ambos baseados numa abordagem de visualização de subgrafos. Ambas as contribuições foram avaliadas em pequena escala, por testes a utilizadores que revelaram a relevância da visualização de subgrafos contra a visualização em árvore, mais comum no domínio biomédico.Since the begin of the century, biomedical research and clinical practice have resulted in the accumulation of very large amounts of information, e.g. data from genomic sequencing or medical records. Ontologies provide a structured model to represent knowledge and have been quite successful in the biomedical domain at improving interoperability and sharing. The disconnected development of biomedical ontologies has led to the creation of models that have overlapping or even equal domains. Ontology matching techniques were developed to establish meaningful connections between classes of the ontologies, in other words to create alignments. In order to achieve an optimal alignment, it is not only important to improve the matching techniques but also to create the necessary tools for human intervention, namely in visualization. Despite the importance of user intervention and visualization in ontology matching, few systems support these, especially for large and complex ontologies such as those in the biomedical domain, specifically in the context of the alignment revision and logical incoherence explanation. The central objective of this thesis was to investigate the main ontology visualization paradigms, in the context of biomedical ontology matching, and to develop visualization and interaction approaches addressing those challenges. The work developed lead to the creation of a new visualization module for a state of the art ontology matching system, that supports the alignment review, and to the construction of an online tool that aims to help the user understand the conflicts found in the alignments both based on a subgraph visualization approach. Both contributions were evaluated, in a small-scale, by user tests that revealed the relevance of subgraph visualization versus the more common tree visualization for the biomedical domain

    Reflexion and reflection: A social cognitive neuroscience approach to attributional inference

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    Traction awareness through haptic feedback for the teleoperation of UGVs*

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    Teleoperation of Unmanned Ground Vehicles (UGVs) is dependent on several factors as the human operator is physically detached from the UGV. This paper focuses on situations where a UGV designed for search and rescue loses traction, thus becoming unable to comply with the operator's commands. In such situations, the lack of Situation Awareness (SA) may lead to an incorrect and inefficient response to the current UGV state usually confusing and frustrating the human operator. The exclusive use of visual information to simultaneously perform the main task (e.g. search and rescue) and to be aware of possible impediments to UGV operation, such as loss of traction, becomes a very challenging task for a single human operator. We address the challenge of unburdening the visual channel by using other human senses to provide multimodal feedback in UGV teleoperation. To achieve this goal we present a teleoperation architecture comprising (1) a laser-based traction detector module, to discriminate between traction losses (stuck and sliding) and (2) a haptic interface to convey the detected traction state to the human operator through different types of tactile stimuli provided by three haptic devices (E-Vita, Traction Cylinder and Vibrotactile Glove). We also report the experimental results of a user study to evaluate to what extent this new feedback modality improves the user SA regarding the UGV traction state. Statistically significant results were found supporting the hypothesis that two of the haptic devices improved the comprehension of the traction state of the UGV when comparing to exclusively visual modality.info:eu-repo/semantics/acceptedVersio

    Comparison of MRI Spectroscopy software packages performance and application on HCV-infected patients’ real data

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    Treballs Finals de Grau d'Enginyeria Biomèdica. Facultat de Medicina i Ciències de la Salut. Universitat de Barcelona. Curs: 2022-2023. Tutor/Director: Sala Llonch, Roser, Laredo Gregorio, Carlos1H MRS is conceived as a pioneer methodology for brain metabolism inspection and health status appraisal. Post-processing interventions are required to obtain explicit metabolite quantification values from which to derive diagnosis. On the grounds of addressing and covering such operation, multiple software packages have been recently developed and launched leading to an amorphous assortment of spectroscopic image processing tools, with lack of standardization and regulation. The current study thereby intends to judge the coherence and consistency of compound estimation outputs in terms of result variability by intercorrelation and intracorrelation analyses between appointed programs, being LCModel, Osprey, TARQUIN, and spant toolbox. The examination is performed on a 83-subject SVS short-TE 3T SIEMENS PRESS spectroscopic acquisitions’ collection, including healthy controls and HCV-infected patients assisted with DAA treatment. The analytical core of the project assesses software performance through the creation of a Python script in order to automatically compute and display the results sought. The statistical tests providing enough information to draw substantial conclusions stem from extraction of coefficient of determination (R2 ), Pearson’s coefficient (r), and intraclass correlation coefficient (ICC) together with representation of boxplots, rainclouds, and scatter plots easing data visualization. A clinical implementation is also entailed on the same basis, whose purpose is to reveal actual DAA treatment effect on HCV-infected patients by means of metabolite concentration alteration and hypothetical restoration. Conclusions declare evident and alarming variability among MRS platforms compromising the rigor, sharpness and systematization demanded in this discipline since quantification results hold incoherences, although they do not seem to affect or oppose medical determinations jeopardizing patient’s health. However, it would be interesting to extend the analysis to a greater cohort of subjects to reinforce and get to more solid resolutions

    Data Profiling in Cloud Migration: Data Quality Measures while Migrating Data from a Data Warehouse to the Google Cloud Platform

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    Internship Report presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced AnalyticsIn today times, corporations have gained a vast interest in data. More and more, companies realized that the key to improving their efficiency and effectiveness and understanding their customers’ needs and preferences better was reachable by mining data. However, as the amount of data grow, so must the companies necessities for storage capacity and ensuring data quality for more accurate insights. As such, new data storage methods must be considered, evolving from old ones, still keeping data integrity. Migrating a company’s data from an old method like a Data Warehouse to a new one, Google Cloud Platform is an elaborate task. Even more so when data quality needs to be assured and sensible data, like Personal Identifiable Information, needs to be anonymized in a Cloud computing environment. To ensure these points, profiling data, before or after it migrated, has a significant value by design a profile for the data available in each data source (e.g., Databases, files, and others) based on statistics, metadata information, and pattern rules. Thus, ensuring data quality is within reasonable standards through statistics metrics, and all Personal Identifiable Information is identified and anonymized accordingly. This work will reflect the required process of how profiling Data Warehouse data can improve data quality to better migrate to the Cloud

    iFAct Recoding

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    Estágio realizado na Critical Software, S. ATese de mestrado integrado. Engenharia Informática e Computação. Faculdade de Engenharia. Universidade do Porto. 200

    Quality and representativity of the traffic accident data in urban areas: State of the Art

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    The reduction of the number of road accident fatalities by 50 %, by the year 2010, suggested by the EU, involves the active contribution of all the agents in charge of the road safety in Europe. Even though the accidents that happened in urban areas have a relative smaller severity, it is the place where, for the moment, in absolute terms, the major number of accidents take place in the EU countries, as well as generating serious consequences on the more vulnerable users (pedestrians, cyclists, children, the elderly…). The current action has as main objective the creation, validation, discussion and spreading, at European level, of the ‘best practices’ for the collection, processing and analysis of traffic accident (TA) data in urban areas. The foreseen final result fundamentally consists in the disposal of a European guide of advices or of “best practices” in order to implement / improve the traffic accident collection, analysis and monitoring systems in urban areas. For that, a compilation of the current “best practices” and on the exchange of experiences between municipalities from several EU countries will be counted on, added to the practical pilot experience that will be carried out as part of this project in several Spanish cities. With the spreading of this guide, the purpose is to contribute to the development of local tools in order to help giving answers and solutions, with more reliable and accurate knowledge, to the problematic of the accident rate in each municipality. The concrete actions that are developed in the project are the following ones: 1) Bibliographical revision and summary of the “state of the art” on the problem of underreporting, the quality, management and analysis / exploitation of TA data in urban area. 2) Development of an in-depth “case study” and application and evaluation of the best practices in some Spanish municipalities from different sizes. D1.1 [8] 3) Execution of a survey study with the objective of getting an approximation to the current situation and practice from a representative sample of European cities from different sizes. 4) Organization of a workshop where the results will be discussed, after the fulfilment of the previously exposed objectives. From all the information obtained from the previous stages, writing and spreading of the Guide of Best Practices throughout the EU. The document that is delivered hereafter is the Deliverable I: Quality and representativity of the traffic accident data in urban area: State of the art. In this stage, as it has been pointed out in the project statement, it is expected, through a bibliographical and documentary revision and summary, to get a general perspective of the state of the accident rate urban records in terms of data collection and information quality, as well as the rules in force in relation to the accident rate collection systems at the European level. The results obtained in this first stage mean a starting point on which the next stages of the SAU study will be developed
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