914 resultados para Dynamic data analysis
Resumo:
Introduction and background: Survival following critical illness is associated with a significant burden of physical, emotional and psychosocial morbidity. Recovery can be protracted and incomplete, with important and sustained effects upon everyday life, including family life, social participation and return to work. In stark contrast with other critically ill patient groups (eg, those following cardiothoracic surgery), there are comparatively few interventional studies of rehabilitation among the general intensive care unit patient population. This paper outlines the protocol for a sub study of the RECOVER study: a randomised controlled trial evaluating a complex intervention of enhanced ward-based rehabilitation for patients following discharge from intensive care. Methods and analysis: The RELINQUISH study is a nested longitudinal, qualitative study of family support and perceived healthcare needs among RECOVER participants at key stages of the recovery process and at up to 1 year following hospital discharge. Its central premise is that recovery is a dynamic process wherein patients’ needs evolve over time. RELINQUISH is novel in that we will incorporate two parallel strategies into our data analysis: (1) a pragmatic health services-oriented approach, using an a priori analytical construct, the ‘Timing it Right’ framework and (2) a constructivist grounded theory approach which allows the emergence of new themes and theoretical understandings from the data. We will subsequently use Qualitative Health Needs Assessment methodology to inform the development of timely and responsive healthcare interventions throughout the recovery process. Ethics and dissemination: The protocol has been approved by the Lothian Research Ethics Committee (protocol number HSRU011). The study has been added to the UK Clinical Research Network Database (study ID. 9986). The authors will disseminate the findings in peer reviewed publications and to relevant critical care stakeholder groups.
Resumo:
Datacenters have emerged as the dominant form of computing infrastructure over the last two decades. The tremendous increase in the requirements of data analysis has led to a proportional increase in power consumption and datacenters are now one of the fastest growing electricity consumers in the United States. Another rising concern is the loss of throughput due to network congestion. Scheduling models that do not explicitly account for data placement may lead to a transfer of large amounts of data over the network causing unacceptable delays. In this dissertation, we study different scheduling models that are inspired by the dual objectives of minimizing energy costs and network congestion in a datacenter. As datacenters are equipped to handle peak workloads, the average server utilization in most datacenters is very low. As a result, one can achieve huge energy savings by selectively shutting down machines when demand is low. In this dissertation, we introduce the network-aware machine activation problem to find a schedule that simultaneously minimizes the number of machines necessary and the congestion incurred in the network. Our model significantly generalizes well-studied combinatorial optimization problems such as hard-capacitated hypergraph covering and is thus strongly NP-hard. As a result, we focus on finding good approximation algorithms. Data-parallel computation frameworks such as MapReduce have popularized the design of applications that require a large amount of communication between different machines. Efficient scheduling of these communication demands is essential to guarantee efficient execution of the different applications. In the second part of the thesis, we study the approximability of the co-flow scheduling problem that has been recently introduced to capture these application-level demands. Finally, we also study the question, "In what order should one process jobs?'' Often, precedence constraints specify a partial order over the set of jobs and the objective is to find suitable schedules that satisfy the partial order. However, in the presence of hard deadline constraints, it may be impossible to find a schedule that satisfies all precedence constraints. In this thesis we formalize different variants of job scheduling with soft precedence constraints and conduct the first systematic study of these problems.
Resumo:
This dissertation research points out major challenging problems with current Knowledge Organization (KO) systems, such as subject gateways or web directories: (1) the current systems use traditional knowledge organization systems based on controlled vocabulary which is not very well suited to web resources, and (2) information is organized by professionals not by users, which means it does not reflect intuitively and instantaneously expressed users’ current needs. In order to explore users’ needs, I examined social tags which are user-generated uncontrolled vocabulary. As investment in professionally-developed subject gateways and web directories diminishes (support for both BUBL and Intute, examined in this study, is being discontinued), understanding characteristics of social tagging becomes even more critical. Several researchers have discussed social tagging behavior and its usefulness for classification or retrieval; however, further research is needed to qualitatively and quantitatively investigate social tagging in order to verify its quality and benefit. This research particularly examined the indexing consistency of social tagging in comparison to professional indexing to examine the quality and efficacy of tagging. The data analysis was divided into three phases: analysis of indexing consistency, analysis of tagging effectiveness, and analysis of tag attributes. Most indexing consistency studies have been conducted with a small number of professional indexers, and they tended to exclude users. Furthermore, the studies mainly have focused on physical library collections. This dissertation research bridged these gaps by (1) extending the scope of resources to various web documents indexed by users and (2) employing the Information Retrieval (IR) Vector Space Model (VSM) - based indexing consistency method since it is suitable for dealing with a large number of indexers. As a second phase, an analysis of tagging effectiveness with tagging exhaustivity and tag specificity was conducted to ameliorate the drawbacks of consistency analysis based on only the quantitative measures of vocabulary matching. Finally, to investigate tagging pattern and behaviors, a content analysis on tag attributes was conducted based on the FRBR model. The findings revealed that there was greater consistency over all subjects among taggers compared to that for two groups of professionals. The analysis of tagging exhaustivity and tag specificity in relation to tagging effectiveness was conducted to ameliorate difficulties associated with limitations in the analysis of indexing consistency based on only the quantitative measures of vocabulary matching. Examination of exhaustivity and specificity of social tags provided insights into particular characteristics of tagging behavior and its variation across subjects. To further investigate the quality of tags, a Latent Semantic Analysis (LSA) was conducted to determine to what extent tags are conceptually related to professionals’ keywords and it was found that tags of higher specificity tended to have a higher semantic relatedness to professionals’ keywords. This leads to the conclusion that the term’s power as a differentiator is related to its semantic relatedness to documents. The findings on tag attributes identified the important bibliographic attributes of tags beyond describing subjects or topics of a document. The findings also showed that tags have essential attributes matching those defined in FRBR. Furthermore, in terms of specific subject areas, the findings originally identified that taggers exhibited different tagging behaviors representing distinctive features and tendencies on web documents characterizing digital heterogeneous media resources. These results have led to the conclusion that there should be an increased awareness of diverse user needs by subject in order to improve metadata in practical applications. This dissertation research is the first necessary step to utilize social tagging in digital information organization by verifying the quality and efficacy of social tagging. This dissertation research combined both quantitative (statistics) and qualitative (content analysis using FRBR) approaches to vocabulary analysis of tags which provided a more complete examination of the quality of tags. Through the detailed analysis of tag properties undertaken in this dissertation, we have a clearer understanding of the extent to which social tagging can be used to replace (and in some cases to improve upon) professional indexing.
Resumo:
Résumé : La gestion des ressources humaines dans les écoles situées au sein de communautés autochtones est marquée par différents enjeux d’ordres social, culturel, ethnoculturel, économique et administratif qui impactent les pratiques de leurs directions. Ceux-ci touchent à tous les aspects de la gestion des écoles et peuvent être révélateurs d’un malaise dans l’encadrement des actrices et des acteurs à travers des structures administratives, juridiques, éducatives ou de gouvernance qui comportent des défis relationnels et interactionnels majeurs. Ce type de malaise peut moduler les actions des actrices et des acteurs des établissements et peut entrainer des impacts dans leurs relations, notamment au niveau de leurs relations de confiance, essentielles à la qualité de leurs actions communes. L’approfondissement de cette problématique porte essentiellement sur les conditions associées à la construction de la confiance qui sont de différents ordres, c’est-à-dire contextuel, institutionnel, organisationnel, relationnel ou individuel. Utilisant une approche qualitative, cette recherche repose sur vingt-trois entrevues semi-dirigées avec des directions d’établissement provenant de dix-sept communautés et de trois nations autochtones différentes. L’analyse est menée à partir d’une approche exploratoire constructiviste et interprétativiste. Les conclusions permettent de dégager que la construction de relations de confiance entre des actrices et des acteurs sont tributaires de conditions dans lesquelles s’inscrivent des dynamiques interactionnelles particulières. Influencées par le contexte autochtone singulier, ces conditions sont préalables aux actrices et aux acteurs ou associées à leurs comportements, attitudes, actions ou pratiques. Il apparait que ces dynamiques s’inscrivent dans une configuration des équipes-écoles se caractérisant par six catégories-types d’individus qui se déclinent selon leur origine et leur appartenance ou leur identité ethnique, à savoir les voyageurs autochtones et allochtones, les étrangers autochtones et allochtones et les natifs autochtones et allochtones. La meilleure compréhension de cette organisation conduit à une conception large de la configuration des dynamiques interactionnelles entre des individus et des groupes et entre des communautés d’individus. Ces individus s’affilient spécifiquement selon des identités ou des appartenances individuelles ou de groupe qui peuvent être de différents ordres soit particulièrement, mais non exclusivement, ethnique, linguistique, familial ou se rapportant à des croyances particulières.
Resumo:
This work has as its main purpose to investigate the contribution of supply chain management in order to obtain competitive advantage by companies from the textile industry and from Ceará footwear industry, focusing its analysis mainly in the interorganizational relations (dyadic). For this, the theoretical referential contemplates different explanatory streams of the competitive advantage, detaching the relational perception of the resources theory, as well as, the main presuppositions of the supply chain management which culminates with the development of an analysis sample that runs the empirical study; the one which considers an expanded purpose of the supply chain which includes the government and the abetment institutions as institutional environment representatives. Besides supply chain management consideration as a competitive advantage source, the work also tried to identify other possible competitive advantage sources for the companies of the investigated sectors. It represents a study of multiple interpretive cases, having four cases as a total; meaning two cases in each one of the sectors, which used as a primary data collecting instrument a semi-structured interview schedule. Different methods were used for the data analysis, the content analysis and the constant comparison methods, the analytical procedure originated from the grounded theory research strategy, which were applied the Atlas/ti software recourse. Considering the theoretical referential and the used analysis sample, four basic categories of the work were defined, including its respective proprieties and dimensions: (1) characteristics concerning to the relationship with the supplier; (2) the company relations with the government; (3) the company relations with the abetment institutions and; (4) obtaining sources of competitive advantage. In general, the applied research in the footwear sector revealed that in the relationships of the researched companies related to its suppliers, there is a predominance of the partnership system and the main presuppositions of the supply chain management are applied which contributes for the acquisition of the relational competitive advantage; while in the textile sector, only some of these presuppositions are applied, with little contribution for the relational competitive advantage. The main resource which was accessed by the companies in both sectors through its relationships with the government and the abetment institutions are the tax incentives which, for the footwear companies, contribute for the acquisition of the temporary competitive advantage in relation to the contestants who do not own productive installations in the Northeast region, it also conducts to a competitive parity situation in relation to the contestants who own productive installations in the Northeast region and to the external market contestants; while for the companies of the textile sector, the tax incentives run the companies to a competitive parity situation in relation to its contestants. Furthermore, the investigated companies from the two sectors possess acquisition sources of the competitive advantage which collimate with different explanatory streams (industrial analysis, resources theory, Austrian school and the dynamic capabilities theory), although there is a predominance of the product innovation as a competitive advantage source in both sectors, due to the bond of these with the fashion tendencies
Resumo:
This study investigates the development of relationships in same global virtual team working on different projects. The purpose is to explore how do interpersonal relationships develop in terms of characteristics of virtuality and if there is any influence of project lifespan on the development of these relationships. Since relationships are dynamic in nature and are influenced by multiple levels of variables including individual, group and organizational level, therefore characteristics of virtuality have been considered from all these aspects so as to study their influence on development of relationships. In this study, relationships have been studied at two different levels. At first, dyadic relationships between two members of a GVT have been analyzed and thereafter, focus has been on the development of relationships among the team, based on these dyads. Characteristics having influence on development of relationships include trust, physical distance, time zone difference, cultural and language differences, level of formalization in the organization and means of communication used by team members. Level of formalization and means of communication are two characteristics which emerged after empirical study and are found to have direct influence on development of relationships. Remaining characteristics have been identified through literature review. In order to conduct the study, qualitative methodology has been applied. Empirical data has been collected based on a single case study while using semi-structured interviews as data gathering technique. Data analysis has been performed by applying thematic analysis along with the utilization of company documents such as work sheets, minutes of meetings and recordings of conferences. Findings of the study indicate that development of relationships, both at dyadic level and team level, is influenced by different events taking place among different members of GVT. These events have either positive or negative influence on the characteristics of virtuality, which leads to development of the relationships. It has been found that, trust, among all factors plays a greater role in development of these relations. Contrary to the belief that most conflicts arise among members of different cultures, they are equally likely to happen among the members from same culture in GVT environment. Study suggests that relationship development is not a smooth process but it fluctuates based on different events in teams. For further research, teams within large firms shall be studied along these lines. This study is an early attempt towards bringing different characteristics of virtuality together which previously, have been studied individually. It is therefore plausible to conduct similar studies so as to generalize the findings of this study which has provided a starting point.
Resumo:
This research explores the business model (BM) evolution process of entrepreneurial companies and investigates the relationship between BM evolution and firm performance. Recently, it has been increasingly recognised that the innovative design (and re-design) of BMs is crucial to the performance of entrepreneurial firms, as BM can be associated with superior value creation and competitive advantage. However, there has been limited theoretical and empirical evidence in relation to the micro-mechanisms behind the BM evolution process and the entrepreneurial outcomes of BM evolution. This research seeks to fill this gap by opening up the ‘black box’ of the BM evolution process, exploring the micro-patterns that facilitate the continuous shaping, changing, and renewing of BMs and examining how BM evolutions create and capture value in a dynamic manner. Drawing together the BM and strategic entrepreneurship literature, this research seeks to understand: (1) how and why companies introduce BM innovations and imitations; (2) how BM innovations and imitations interplay as patterns in the BM evolution process; and (3) how BM evolution patterns affect firm performances. This research adopts a longitudinal multiple case study design that focuses on the emerging phenomenon of BM evolution. Twelve entrepreneurial firms in the Chinese Online Group Buying (OGB) industry were selected for their continuous and intensive developments of BMs and their varying success rates in this highly competitive market. Two rounds of data collection were carried out between 2013 and 2014, which generates 31 interviews with founders/co-founders and in total 5,034 pages of data. Following a three-stage research framework, the data analysis begins by mapping the BM evolution process of the twelve companies and classifying the changes in the BMs into innovations and imitations. The second stage focuses down to the BM level, which addresses the BM evolution as a dynamic process by exploring how BM innovations and imitations unfold and interplay over time. The final stage focuses on the firm level, providing theoretical explanations as to the effects of BM evolution patterns on firm performance. This research provides new insights into the nature of BM evolution by elaborating on the missing link between BM dynamics and firm performance. The findings identify four patterns of BM evolution that have different effects on a firm’s short- and long-term performance. This research contributes to the BM literature by presenting what the BM evolution process actually looks like. Moreover, it takes a step towards the process theory of the interplay between BM innovations and imitations, which addresses the role of companies’ actions, and more importantly, reactions to the competitors. Insights are also given into how entrepreneurial companies achieve and sustain value creation and capture by successfully combining the BM evolution patterns. Finally, the findings on BM evolution contributes to the strategic entrepreneurship literature by increasing the understanding of how companies compete in a more dynamic and complex environment. It reveals that, the achievement of superior firm performance is more than a simple question of whether to innovate or imitate, but rather an integration of innovation and imitation strategies over time. This study concludes with a discussion of the findings and their implications for theory and practice.
Resumo:
Focalizando as dimensões humana e comportamental da gestão do conhecimento, a presente investigação visa uma análise do(s) impacto(s) (facilitador ou inibidor) dos pressupostos da gestão de recursos humanos no grau de aplicação da gestão do conhecimento em organizações industriais. Em particular, explora a(s) dinâmica(s) de influência entre a sofisticação dos pressupostos da formação profissional, da avaliação de desempenho e da gestão de recompensas na aplicação da gestão do conhecimento. Tendo em vista a medição dos constructos centrais do presente estudo, de acordo com a revisão de literatura efectuada, desenvolveram-se acções conducentes à adaptação de um questionário de gestão do conhecimento (GC), à construção, validação e desenvolvimento de três novos questionários (PPFP, PPAD e PPSR) que visaram aceder à percepção dos agentes organizacionais acerca dos pressupostos da gestão de recursos humanos vigentes ou culturalmente característicos do seu contexto laboral. O presente estudo envolveu múltiplas análises aos dados de 1364 questionários individuais auto-administrados e recolhidos em 55 empresas de quatro sub-sectores da cerâmica em Portugal. Para o estudo da relação linear entre um conjunto de variáveis preditoras e uma variável critério optou-se por realizar equações de regressão múltipla hierárquica, considerando-se dois blocos de variáveis. Num primeiro modelo foram introduzidas, apenas, as duas dimensões relativas à formação profissional medidas pelo instrumento PPFP e num segundo modelo aduziram-se as variáveis de avaliação de desempenho e de sistema de recompensas, especificamente, o primeiro factor retido na análise psicométrica dos instrumentos PPAD e PPSR.
Resumo:
Mestrado em Ciências Empresariais
Resumo:
Tall buildings are wind-sensitive structures and could experience high wind-induced effects. Aerodynamic boundary layer wind tunnel testing has been the most commonly used method for estimating wind effects on tall buildings. Design wind effects on tall buildings are estimated through analytical processing of the data obtained from aerodynamic wind tunnel tests. Even though it is widely agreed that the data obtained from wind tunnel testing is fairly reliable the post-test analytical procedures are still argued to have remarkable uncertainties. This research work attempted to assess the uncertainties occurring at different stages of the post-test analytical procedures in detail and suggest improved techniques for reducing the uncertainties. Results of the study showed that traditionally used simplifying approximations, particularly in the frequency domain approach, could cause significant uncertainties in estimating aerodynamic wind-induced responses. Based on identified shortcomings, a more accurate dual aerodynamic data analysis framework which works in the frequency and time domains was developed. The comprehensive analysis framework allows estimating modal, resultant and peak values of various wind-induced responses of a tall building more accurately. Estimating design wind effects on tall buildings also requires synthesizing the wind tunnel data with local climatological data of the study site. A novel copula based approach was developed for accurately synthesizing aerodynamic and climatological data up on investigating the causes of significant uncertainties in currently used synthesizing techniques. Improvement of the new approach over the existing techniques was also illustrated with a case study on a 50 story building. At last, a practical dynamic optimization approach was suggested for tuning structural properties of tall buildings towards attaining optimum performance against wind loads with less number of design iterations.
Resumo:
Social capital, or social cohesion or group connectedness, can influence both HIV risk behavior and substance use. Because recent immigrants undergo a change in environment, one of the consequences can be a change in social capital. There may be an association among changes in social capital, and HIV risk behavior and substance use post immigration. The dissertation focused on the interface of these three variables among recent Latino immigrants (RLIs) in South Florida. The first manuscript is a systematic review of social capital and HIV risk behavior, and served as a partial background for the second and third manuscripts. Twelve papers with a measure of social capital as an independent variable and HIV risk as the dependent variable were included in the analysis. Eleven studies measured social capital at the individual level, and one study measured social capital at the group level. HIV risk was influenced by social capital, but the type of influence was dependent on the type of social capital and on the study population. Cognitive social capital, or levels of collective action, was protective against HIV in both men and women. The role of structural social capital, or levels of civic engagement/group participation, on HIV risk was dependent on the type of structural social capital and varied by gender. Microfinance programs and functional group participation were protective for women, while dysfunctional group participation and peer-level support may have increased HIV risk among men. The second manuscript was an original study assessing changes in social capital and HIV risk behavior pre to post immigration among RLIs in South Florida (n=527). HIV risk behavior was assessed through the frequency of vaginal-penile condom use, and the number of sexual partners. It was a longitudinal study using secondary data analysis to assess changes in social capital and HIV risk behavior pre immigration to two years post immigration, and to determine if there was a relationship between the two variables. There was an 8% decrease in total social capital (p ˂ .05). Reporting of ‘Never use’ of condoms in the past 90 days increased in all subcategories (p ˂ .05). Single men had a decrease in number of sexual partners (p ˂ .05). Lower social capital measured on the dimension of ‘friend and other’ was marginally associated with fewer sexual partners. The third manuscript was another original study looking at the association between social capital and substance use among RLIs in South Florida (n=527). Substance use with measured by frequency of hazardous alcoholic drinking, and illicit drug use. It was a longitudinal study of social capital and substance-use from pre to two years post immigration. Post-immigration, social capital, hazardous drinking and illicit drug use decreased (p˂.001). After adjusting for time, compared to males, females were less likely to engage in hazardous drinking (OR=.31, p˂.001), and less likely to engage in illicit drug use (OR=.67, p=.01). Documentation status was a moderator between social capital and illicit drug use. ‘Business’ and ‘Agency’ social capital were associated with changes in illicit drug use for documented immigrants. After adjusting for gender and marital status, on average, documented immigrants with a one-unit increase in ‘business’ social capital were 1.2 times more likely to engage in illicit drug use (p˂.01), and documented immigrants with one-unit increase in ‘agency’ social capital were 38% less likely to engage in illicit drug use (p˂.01). ‘Friend and other’ social capital was associated with a decrease in illicit drug use among undocumented immigrants. After adjusting for gender and marital status, on average, undocumented immigrants with a one-unit increase in ‘friend and other’ social capital were 45% less likely to engage in hazardous drinking and 44% less likely to use illicit drugs (p˂.01, p˂.05). Studying these three domains is relevant because HIV continues to be a public health issue, particularly in Miami-Dade County, which is ranked among other U.S. regions with high rates of HIV/AIDS prevalence. Substance use is associated with HIV risk behavior; in most studies, increased substance use is associated with increased chances of HIV risk behavior. Immigration, which is the hypothesized catalyst for the change in social capital, has an impact on the dynamic of a society. Greater immigration can be burdensome on the host country’s societal resources; however immigrants are also potentially a source of additional skilled labor for the workforce. Therefore, successful adaption of immigrants can have a positive influence on receiving communities. With Florida being a major receiver of immigrants to the U.S, this dissertation attempts to address an important public health issue for South Florida and the U.S. at large.
Resumo:
An overview is given of a user interaction monitoring and analysis framework called BaranC. Monitoring and analysing human-digital interaction is an essential part of developing a user model as the basis for investigating user experience. The primary human-digital interaction, such as on a laptop or smartphone, is best understood and modelled in the wider context of the user and their environment. The BaranC framework provides monitoring and analysis capabilities that not only records all user interaction with a digital device (e.g. smartphone), but also collects all available context data (such as from sensors in the digital device itself, a fitness band or a smart appliances). The data collected by BaranC is recorded as a User Digital Imprint (UDI) which is, in effect, the user model and provides the basis for data analysis. BaranC provides functionality that is useful for user experience studies, user interface design evaluation, and providing user assistance services. An important concern for personal data is privacy, and the framework gives the user full control over the monitoring, storing and sharing of their data.
Resumo:
Understanding the fluctuations in population abundance is a central question in fisheries. Sardine fisheries is of great importance to Portugal and is data-rich and of primary concern to fisheries managers. In Portugal, sub-stocks of Sardina pilchardus (sardine) are found in different regions: the Northwest (IXaCN), Southwest (IXaCS) and the South coast (IXaS-Algarve). Each of these sardine sub-stocks is affected differently by a unique set of climate and ocean conditions, mainly during larval development and recruitment, which will consequently affect sardine fisheries in the short term. Taking this hypothesis into consideration we examined the effects of hydrographic (river discharge), sea surface temperature, wind driven phenomena, upwelling, climatic (North Atlantic Oscillation) and fisheries variables (fishing effort) on S. pilchardus catch rates (landings per unit effort, LPUE, as a proxy for sardine biomass). A 20-year time series (1989-2009) was used, for the different subdivisions of the Portuguese coast (sardine sub-stocks). For the purpose of this analysis a multi-model approach was used, applying different time series models for data fitting (Dynamic Factor Analysis, Generalised Least Squares), forecasting (Autoregressive Integrated Moving Average), as well as Surplus Production stock assessment models. The different models were evaluated, compared and the most important variables explaining changes in LPUE were identified. The type of relationship between catch rates of sardine and environmental variables varied across regional scales due to region-specific recruitment responses. Seasonality plays an important role in sardine variability within the three study regions. In IXaCN autumn (season with minimum spawning activity, larvae and egg concentrations) SST, northerly wind and wind magnitude were negatively related with LPUE. In IXaCS none of the explanatory variables tested was clearly related with LPUE. In IXaS-Algarve (South Portugal) both spring (period when large abundances of larvae are found) northerly wind and wind magnitude were negatively related with LPUE, revealing that environmental effects match with the regional peak in spawning time. Overall, results suggest that management of small, short-lived pelagic species, such as sardine quotas/sustainable yields, should be adapted to a regional scale because of regional environmental variability.
Resumo:
Big data are reshaping the way we interact with technology, thus fostering new applications to increase the safety-assessment of foods. An extraordinary amount of information is analysed using machine learning approaches aimed at detecting the existence or predicting the likelihood of future risks. Food business operators have to share the results of these analyses when applying to place on the market regulated products, whereas agri-food safety agencies (including the European Food Safety Authority) are exploring new avenues to increase the accuracy of their evaluations by processing Big data. Such an informational endowment brings with it opportunities and risks correlated to the extraction of meaningful inferences from data. However, conflicting interests and tensions among the involved entities - the industry, food safety agencies, and consumers - hinder the finding of shared methods to steer the processing of Big data in a sound, transparent and trustworthy way. A recent reform in the EU sectoral legislation, the lack of trust and the presence of a considerable number of stakeholders highlight the need of ethical contributions aimed at steering the development and the deployment of Big data applications. Moreover, Artificial Intelligence guidelines and charters published by European Union institutions and Member States have to be discussed in light of applied contexts, including the one at stake. This thesis aims to contribute to these goals by discussing what principles should be put forward when processing Big data in the context of agri-food safety-risk assessment. The research focuses on two interviewed topics - data ownership and data governance - by evaluating how the regulatory framework addresses the challenges raised by Big data analysis in these domains. The outcome of the project is a tentative Roadmap aimed to identify the principles to be observed when processing Big data in this domain and their possible implementations.
Resumo:
The world of Computational Biology and Bioinformatics presently integrates many different expertise, including computer science and electronic engineering. A major aim in Data Science is the development and tuning of specific computational approaches to interpret the complexity of Biology. Molecular biologists and medical doctors heavily rely on an interdisciplinary expert capable of understanding the biological background to apply algorithms for finding optimal solutions to their problems. With this problem-solving orientation, I was involved in two basic research fields: Cancer Genomics and Enzyme Proteomics. For this reason, what I developed and implemented can be considered a general effort to help data analysis both in Cancer Genomics and in Enzyme Proteomics, focusing on enzymes which catalyse all the biochemical reactions in cells. Specifically, as to Cancer Genomics I contributed to the characterization of intratumoral immune microenvironment in gastrointestinal stromal tumours (GISTs) correlating immune cell population levels with tumour subtypes. I was involved in the setup of strategies for the evaluation and standardization of different approaches for fusion transcript detection in sarcomas that can be applied in routine diagnostic. This was part of a coordinated effort of the Sarcoma working group of "Alleanza Contro il Cancro". As to Enzyme Proteomics, I generated a derived database collecting all the human proteins and enzymes which are known to be associated to genetic disease. I curated the data search in freely available databases such as PDB, UniProt, Humsavar, Clinvar and I was responsible of searching, updating, and handling the information content, and computing statistics. I also developed a web server, BENZ, which allows researchers to annotate an enzyme sequence with the corresponding Enzyme Commission number, the important feature fully describing the catalysed reaction. More to this, I greatly contributed to the characterization of the enzyme-genetic disease association, for a better classification of the metabolic genetic diseases.