Recuperação e identificação de momentos em imagens

In our modern society almost anyone is able to capture moments and record events due to the ease accessibility to smartphones. This leads to the question, if we record so much of our life how can we easily retrieve specific moments? The answer to this question would open the door for a big leap in human life quality. The possibilities are endless, from trivial problems like finding a photo of a birthday cake to being capable of analyzing the progress of mental illnesses in patients or even tracking people with infectious diseases. With so much data being created everyday, the answer to this question becomes more complex. There is no stream lined approach to solve the problem of moment localization in a large dataset of images and investigations into this problem have only started a few years ago. ImageCLEF is one competition where researchers participate and try to achieve new and better results in the task of moment retrieval. This complex problem, along with the interest in participating in the ImageCLEF Lifelog Moment Retrieval Task posed a good challenge for the development of this dissertation. The proposed solution consists in developing a system capable of retriving images automatically according to specified moments described in a corpus of text without any sort of user interaction and using only state-of-the-art image and text processing methods. The developed retrieval system achieves this objective by extracting and categorizing relevant information from text while being able to compute a similarity score with the extracted labels from the image processing stage. In this way, the system is capable of telling if images are related to the specified moment in text and therefore able to retrieve the pictures accordingly. In the ImageCLEF Life Moment Retrieval 2020 subtask the proposed automatic retrieval system achieved a score of 0.03 in the F1-measure@10 evaluation methodology. Even though this scores are not competitve when compared to other teams systems scores, the built system presents a good baseline for future work.Na sociedade moderna, praticamente qualquer pessoa consegue capturar momentos e registar eventos devido à facilidade de acesso a smartphones. Isso leva à questão, se registamos tanto da nossa vida, como podemos facilmente recuperar momentos específicos? A resposta a esta questão abriria a porta para um grande salto na qualidade da vida humana. As possibilidades são infinitas, desde problemas triviais como encontrar a foto de um bolo de aniversário até ser capaz de analisar o progresso de doenças mentais em pacientes ou mesmo rastrear pessoas com doenças infecciosas. Com tantos dados a serem criados todos os dias, a resposta a esta pergunta torna-se mais complexa. Não existe uma abordagem linear para resolver o problema da localização de momentos num grande conjunto de imagens e investigações sobre este problema começaram há apenas poucos anos. O ImageCLEF é uma competição onde investigadores participam e tentam alcançar novos e melhores resultados na tarefa de recuperação de momentos a cada ano. Este problema complexo, em conjunto com o interesse em participar na tarefa ImageCLEF Lifelog Moment Retrieval, apresentam-se como um bom desafio para o desenvolvimento desta dissertação. A solução proposta consiste num sistema capaz de recuperar automaticamente imagens de momentos descritos em formato de texto, sem qualquer tipo de interação de um utilizador, utilizando apenas métodos estado da arte de processamento de imagem e texto. O sistema de recuperação desenvolvido alcança este objetivo através da extração e categorização de informação relevante de texto enquanto calcula um valor de similaridade com os rótulos extraídos durante a fase de processamento de imagem. Dessa forma, o sistema consegue dizer se as imagens estão relacionadas ao momento especificado no texto e, portanto, é capaz de recuperar as imagens de acordo. Na subtarefa ImageCLEF Life Moment Retrieval 2020, o sistema de recuperação automática de imagens proposto alcançou uma pontuação de 0.03 na metodologia de avaliação F1-measure@10. Mesmo que estas pontuações não sejam competitivas quando comparadas às pontuações de outros sistemas de outras equipas, o sistema construído apresenta-se como uma boa base para trabalhos futuros.Mestrado em Engenharia Eletrónica e Telecomunicaçõe

CHORUS Deliverable 2.2: Second report - identification of multi-disciplinary key issues for gap analysis toward EU multimedia search engines roadmap

After addressing the state-of-the-art during the first year of Chorus and establishing the existing landscape in multimedia search engines, we have identified and analyzed gaps within European research effort during our second year. In this period we focused on three directions, notably technological issues, user-centred issues and use-cases and socio- economic and legal aspects. These were assessed by two central studies: firstly, a concerted vision of functional breakdown of generic multimedia search engine, and secondly, a representative use-cases descriptions with the related discussion on requirement for technological challenges. Both studies have been carried out in cooperation and consultation with the community at large through EC concertation meetings (multimedia search engines cluster), several meetings with our Think-Tank, presentations in international conferences, and surveys addressed to EU projects coordinators as well as National initiatives coordinators. Based on the obtained feedback we identified two types of gaps, namely core technological gaps that involve research challenges, and “enablers”, which are not necessarily technical research challenges, but have impact on innovation progress. New socio-economic trends are presented as well as emerging legal challenges

Ontology based data warehousing for mining of heterogeneous and multidimensional data sources

Heterogeneous and multidimensional big-data sources are virtually prevalent in all business environments. System and data analysts are unable to fast-track and access big-data sources. A robust and versatile data warehousing system is developed, integrating domain ontologies from multidimensional data sources. For example, petroleum digital ecosystems and digital oil field solutions, derived from big-data petroleum (information) systems, are in increasing demand in multibillion dollar resource businesses worldwide. This work is recognized by Industrial Electronic Society of IEEE and appeared in more than 50 international conference proceedings and journals

Analysis of peer-to-peer electricity trading models in a microgrid

La tesi propone uno indagine nel campo degli scambi di energia peer-to-peer a livello locale. nella prima parte viene fornito uno stato dell'arte della tecnologia, con una revisione bibliografica dei vari progetti svolti e delle tecnologie utilizzate. Successivamente viene presentato il caso di studio considerato nel progetto, l'implementazione e applicazione di due specifici algoritmi di trading e la discussione di risultati ottenuti e prospettive future

Urban food strategies in Central and Eastern Europe: what's specific and what's at stake?

Integrating a larger set of instruments into Rural Development Programmes implied an increasing focus on monitoring and evaluation. Against the highly diversified experience with regard to implementation of policy instruments the Common Monitoring and Evaluation Framework has been set up by the EU Commission as a strategic and streamlined method of evaluating programmes’ impacts. Its indicator-based approach mainly reflects the concept of a linear, measure-based intervention logic that falls short of the true nature of RDP operation and impact capacity on rural changes. Besides the different phases of the policy process, i.e. policy design, delivery and evaluation, the regional context with its specific set of challenges and opportunities seems critical to the understanding and improvement of programme performance. In particular the role of local actors can hardly be grasped by quantitative indicators alone, but has to be addressed by assessing processes of social innovation. This shift in the evaluation focus underpins the need to take account of regional implementation specificities and processes of social innovation as decisive elements for programme performance.

Advanced Analytics Success Factors - A Case Study

Companies are increasingly taking into use advanced analytics solutions. Advanced analytics solutions are computer programs that analyze data, make predictions on the future, and give optimization-based recommendations on courses of action for achieving pre-determined business goals. Analytics solutions employ sophisticated statistical and mathematical models, and are often offered by third parties. Companies use analytics solutions to improve the efficiency of their operations. This thesis studies whether the distinction between analytics and advanced analytics made in literature is well-founded. The second aim of this study is to find out, what contributes to an analytics initiative’s success. The study begins with a literature review synthesizing the findings of previous analytics research. The resulting synthesis identifies four distinct stages in an analytics project. They are acquiring data, transforming it into insights, communicating the insights, making business decisions, and finally implementing the decisions. Factors that contribute to each stage’s success are identified. The hypotheses that were developed in the theoretical part of the thesis are subsequently tested empirically using the single case study method and semi-structured interviews. The case study confirms the findings of earlier research. Analytics can be viewed as a process with clearly identifiable stages. Specific measures can be taken to improve the success of each stage. The results obtained suggest that an analytics initiative should always be preceded by a thorough goal definition stage. This is a finding that earlier research has not emphasized sufficiently. The study offers business executives a clear roadmap for managing analytics initiatives. It formulates clear action points and allocates parties the responsibility for executing them. The study also highlights some ordinary pitfalls preventing companies from fully benefitting from the results of analytics initiatives. Finally, the study points out new interesting research opportunities in the intersection of information systems science and cognitive science. A key difficulty in using analytics effectively is that the reasoning behind the insights created by the solutions are often complex. Cognitive science could provide us tools for making the insights easier to digest. Lastly, the study highlights that process decoupling will eventually be applied to analytics initiatives. Future studies should research how the stages of an analytics initiative can be separated from each other, and outsourced to parties performing them the most effectively

A framework for the design of business intelligence dashboard tools

Vast amounts of data are collected on a daily basis, making it difficult for humans to derive at valuable information to make effective decisions. In recent years, the field of Business Intelligence (BI) and Information Visualisation (IV) have become a key driver of an organisation’s success. BI tools supporting decision making need to be accessible to a larger audience on different levels of the organisation. The problem is that non-expert users, or novice users, of BI tools do not have the technical knowledge to conduct data analysis and often rely on expert users to assist. For this reason, BI vendors are shifting their focus to self-service BI, a relatively new term where novice users can analyse data without the traditional human mediator. Despite the proliferation of self-service BI tools, limited research is available on their usability and design considerations to assist novice users with decision making and BI analysis. The contribution of this study is a conceptual framework for designing, evaluating or selecting BI tools that support non-expert users to create dashboards (the BI Framework). A dashboard is a particular IV technique that enables users to view critical information at a glance. The main research problem addressed by this study is that non-expert users often have to utilise a number of software tools to conduct data analysis and to develop visualisations, such as BI dashboards. The research problem was further investigated by following a two-step approach. The first approach was to investigate existing problems by using an in-depth literature review in the fields of BI and IV. The second approach was to conduct a field study (Field Study 1) using a development environment consisting of a number of software components of which SAP Xcelsius was the main BI tool used to create a dashboard. The aim of the field study was to compare the identified problems and requirements with those found in literature. The results of the problem analysis revealed a number of problems in terms of BI software. One of the major problems is that BI tools do not adequately guide users through a logical process to conduct data analysis. In addition, the process becomes increasingly difficult when several BI tools are involved that need to be integrated. The results showed positive aspects when the data was mapped to a visualisation, which increased the users’ understanding of data they were analysing. The results were verified in a focus group discussion and were used to establish an initial set of problems and requirements, which were then synthesised with the problems and requirements identified from literature. Once the major problems were verified, a framework was established to guide the design of BI dashboard tools for novice users. The framework includes a set of design guidelines and usability evaluation criteria for BI tools. An extant systems analysis was conducted using BI tools to compare the advantages and disadvantages. The results revealed that a number of tools could be used by non-experts, however, their usability hinders users. All the participants used in all field studies and evaluations were Computer Science (CS) and Information Systems (IS) students. Participants were specially sourced from a higher education institution such as the Nelson Mandela Metropolitan University (NMMU). A second field study (Field Study 2) was conducted with participants using another traditional BI tool identified from the extant systems analysis, PowerPivot. The objective of this field study was to verify the design guidelines and related features that served as a BI Scorecard that can be used to select BI tools. Another BI tool, Tableau, was used for the final evaluation. The final evaluation was conducted with a large participant sample consisting of IS students in their second and third year of study. The results for the two groups revealed a significant difference between participants’ education levels and the usability ratings of Tableau. Additionally, the results indicated a significant relationship between the participants’ experience level and the usability ratings of Tableau. The usability ratings of Tableau were mostly positive and the results revealed that participants found the tool easy to use, flexible and efficient. The proposed BI Framework can be used to assist organisations when evaluating BI tools for adoption. Furthermore, designers of BI tools can use the framework to improve the usability of these tools, reduce the workload for users when creating dashboards, and increase the effectiveness and efficiency of decision support