31 resultados para Context-Aware and Adaptable Architectures
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Trabalho apresentado no âmbito do Mestrado em Engenharia Informática, como requisito parcial para obtenção do grau de Mestre em Engenharia Informática
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Dissertação para obtenção do Grau de Mestre em Engenharia Informática
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This Work Project aims to discuss the Context Costs and Comparative Advantages of the Telecommunications sector both in Portugal and China. The work was built mostly on primary research by interviews with relevant people (business persons, University Professors and Agencies directors), and by economic data publicly available. A list of context costs and comparative advantages was drawn for each country and possible resolutions suggestions were made in the end. The context costs depend heavily on the economic situation of the countries and it should be taken into account when assessing the degree of magnitude of each cost of context. The competitive advantages of each country were drawn in comparison with one another. Some key results stand out: firstly, Portugal’s costs of context depend mainly on governmental decisions, uncertainties and instability and China’s cost of context depend primarily on cultural norms, mainly the Guanxi; second, the telecommunications sector shares most of its context costs and advantages with other sectors; third, China as an economic power could use the telecommunications sector as a way to further develop and boost its economy.
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This dissertation presents a solution for environment sensing using sensor fusion techniques and a context/environment classification of the surroundings in a service robot, so it could change his behavior according to the different rea-soning outputs. As an example, if a robot knows he is outdoors, in a field environment, there can be a sandy ground, in which it should slow down. Contrariwise in indoor environments, that situation is statistically unlikely to happen (sandy ground). This simple assumption denotes the importance of context-aware in automated guided vehicles.
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In the current global and competitive business context, it is essential that enterprises adapt their knowledge resources in order to smoothly interact and collaborate with others. However, due to the existent multiculturalism of people and enterprises, there are different representation views of business processes or products, even inside a same domain. Consequently, one of the main problems found in the interoperability between enterprise systems and applications is related to semantics. The integration and sharing of enterprises knowledge to build a common lexicon, plays an important role to the semantic adaptability of the information systems. The author proposes a framework to support the development of systems to manage dynamic semantic adaptability resolution. It allows different organisations to participate in a common knowledge base building, letting at the same time maintain their own views of the domain, without compromising the integration between them. Thus, systems are able to be aware of new knowledge, and have the capacity to learn from it and to manage its semantic interoperability in a dynamic and adaptable way. The author endorses the vision that in the near future, the semantic adaptability skills of the enterprise systems will be the booster to enterprises collaboration and the appearance of new business opportunities.
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MSCC Dissertation in Computer Engineering
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Based on the report for “Project IV” unit of the PhD programme on Technology Assessment (Doctoral Conference) at Universidade Nova de Lisboa (December 2011). This thesis research has the supervision of António Moniz (FCT-UNL and ITAS-KIT) and Michael Decker (Karlsruhe Institute of Technology-ITAS). Other members of the thesis committee are Carlos Alberto da Silva (University of Évora), José Maria de Albuquerque (Institute of Welding and Quality), Lotte Steuten (University of Twente), Mário Forjaz Secca (FCT-UNL) and Nelson Chibeles Martins (FCT-UNL).
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Dissertação para obtenção do Grau de Doutor em Informática
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Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores
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Dissertação para obtenção do Grau de Mestre em Engenharia Informática
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics
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Nowadays, reducing energy consumption is one of the highest priorities and biggest challenges faced worldwide and in particular in the industrial sector. Given the increasing trend of consumption and the current economical crisis, identifying cost reductions on the most energy-intensive sectors has become one of the main concerns among companies and researchers. Particularly in industrial environments, energy consumption is affected by several factors, namely production factors(e.g. equipments), human (e.g. operators experience), environmental (e.g. temperature), among others, which influence the way of how energy is used across the plant. Therefore, several approaches for identifying consumption causes have been suggested and discussed. However, the existing methods only provide guidelines for energy consumption and have shown difficulties in explaining certain energy consumption patterns due to the lack of structure to incorporate context influence, hence are not able to track down the causes of consumption to a process level, where optimization measures can actually take place. This dissertation proposes a new approach to tackle this issue, by on-line estimation of context-based energy consumption models, which are able to map operating context to consumption patterns. Context identification is performed by regression tree algorithms. Energy consumption estimation is achieved by means of a multi-model architecture using multiple RLS algorithms, locally estimated for each operating context. Lastly, the proposed approach is applied to a real cement plant grinding circuit. Experimental results prove the viability of the overall system, regarding both automatic context identification and energy consumption estimation.
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This paper examines the job quality in Europe. It is based on the results of the Fourth European Foundation Survey on working conditions covering different dimensions including work organisation, job content, autonomy at work, aspects of worker dignity, working time and work-life balance, working conditions and safety in the workplace. The results point to the existence of great diversity in the job quality across Europe and the north-south divide. The job quality differences are related to the variety of social and institutional contexts. The countries of Southern Europe, with their social and institutional contexts falling within the scope of the Mediterranean model, generally present indicators below the European average contrasting Nordic countries having the best job quality indicators.
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Due to global warming and shrinking fossil fuel resources, politics as well as society urge for a reduction of green house gas (GHG) emissions. This leads to a re-orientation towards a renewable energy sector. In this context, innovation and new technologies are key success factors. Moreover, the renewable energy sector has entered a consolidation stage, where corporate investors and mergers and acquisitions (M&A) gain in importance. Although both M&A and innovation in the renewable energy sector are important corporate strategies, the link between those two aspects has not been examined before. The present thesis examines the research question how M&A influence the acquirer’s post-merger innovative performance in the renewable energy sector. Based on a framework of relevant literature, three hypotheses are defined. First, the relation between non-technology oriented M&A and post-merger innovative performance is discussed. Second, the impact of absolute acquired knowledge on postmerger innovativeness is examined. Third, the target-acquirer relatedness is discussed. A panel data set of 117 firms collected over a period of six years has been analyzed via a random effects negative binomial regression model and a time lag of one year. The results support a non-significant, negative impact of non-technology M&A on postmerger innovative performance. The applied model did not support a positive and significant impact of absolute acquired knowledge on post-merger innovative performance. Lastly, the results suggest a reverse relation than postulated by Hypothesis 3. Targets from the same industry significantly and negatively influence the acquirers’ innovativeness.
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This work presents research conducted to understand the role of indicators in decisions of technology innovation. A gap was detected in the literature of innovation and technology assessment about the use and influence of indicators in this type of decision. It was important to address this gap because indicators are often frequent elements of innovation and technology assessment studies. The research was designed to determine the extent of the use and influence of indicators in decisions of technology innovation, to characterize the role of indicators in these decisions, and to understand how indicators are used in these decisions. The latter involved the test of four possible explanatory factors: the type and phase of decision, and the context and process of construction of evidence. Furthermore, it focused on three Portuguese innovation groups: public researchers, business R&D&I leaders and policymakers. The research used a combination of methods to collect quantitative and qualitative information, such as surveys, case studies and social network analysis. This research concluded that the use of indicators is different from their influence in decisions of technology innovation. In fact, there is a high use of indicators in these decisions, but lower and differentiated differences in their influence in each innovation group. This suggests that political-behavioural methods are also involved in the decisions to different degrees. The main social influences in the decisions came mostly from hierarchies, knowledge-based contacts and users. Furthermore, the research established that indicators played mostly symbolic roles in decisions of policymakers and business R&D&I leaders, although their role with researchers was more differentiated. Indicators were also described as helpful instruments to conduct a reasonable interpretation of data and to balance options in innovation and technology assessments studies, in particular when contextualised, described in detail and with discussion upon the options made. Results suggest that there are four main explanatory factors for the role of indicators in these decisions: First, the type of decision appears to be a factor to consider when explaining the role of indicators. In fact, each type of decision had different influences on the way indicators are used, and each type of decision used different types of indicators. Results for policy-making were particularly different from decisions of acquisition and development of products/technology. Second, the phase of the decision can help to understand the role indicators play in these decisions. Results distinguished between two phases detected in all decisions – before and after the decision – as well as two other phases that can be used to complement the decision process and where indicators can be involved. Third, the context of decision is an important factor to consider when explaining the way indicators are taken into consideration in policy decisions. In fact, the role of indicators can be influenced by the particular context of the decision maker, in which all types of evidence can be selected or downplayed. More importantly, the use of persuasive analytical evidence appears to be related with the dispute existent in the policy context. Fourth and last, the process of construction of evidence is a factor to consider when explaining the way indicators are involved in these decisions. In fact, indicators and other evidence were brought to the decision processes according to their availability and capacity to support the different arguments and interests of the actors and stakeholders. In one case, an indicator lost much persuasion strength with the controversies that it went through during the decision process. Therefore, it can be argued that the use of indicators is high but not very influential; their role is mostly symbolic to policymakers and business decisions, but varies among researchers. The role of indicators in these decisions depends on the type and phase of the decision and the context and process of construction of evidence. The latter two are related to the particular context of each decision maker, the existence of elements of dispute and controversies that influence the way indicators are introduced in the decision-making process.