The Data of Things: Strategies, Patterns and Practice of Cloud-based Participatory Sensing

The broad capabilities of current mobile devices have paved the way for Mobile Crowd Sensing (MCS) applications. The success of this emerging paradigm strongly depends on the quality of received data which, in turn, is contingent to mass user participation; the broader the participation, the more useful these systems become. However, there is an ongoing trend that tries to integrate MCS applications with emerging computing paradigms such as cloud computing. The intuition is that such a transition can significantly improve the overall efficiency while at the same time it offers stronger security and privacy-preserving mechanisms for the end-user. In this position paper, we dwell on the underpinnings of incorporating cloud computing techniques to facilitate the vast amount of data collected in MCS applications. That is, we present a list of core system, security and privacy requirements that must be met if such a transition is to be successful. To this end, we first address several competing challenges not previously considered in the literature such as the scarce energy resources of battery-powered mobile devices as well as their limited computational resources that they often prevent the use of computationally heavy cryptographic operations and thus offering limited security services to the end-user. Finally, we present a use case scenario as a comprehensive example. Based on our findings, we posit open issues and challenges, and discuss possible ways to address them, so that security and privacy do not hinder the migration of MCS systems to the cloud.

Ecodesign e usabilidade no redesign de produtos de usos quotidiano

A crescente saturação dos mercados com produtos similares aos já existentes ou cuja adaptação ao utilizador se revelou ineficiente, torna pertinente a elaboração de projectos que se traduzam em produtos que, efectivamente, tragam vantagem competitiva e, consequentemente, contribuam para o desenvolvimento e bem estar tanto da sociedade como do ecossistema. Como tal, a actividade do design deve assumir uma posição estratégica por forma a conseguir conceber soluções que preservem tanto quanto possível, os recursos naturais ao mesmo tempo que melhoram os contextos físicos e sociais dos seus utilizadores. Assim, com este trabalho pretende-se elaborar uma estratégia para conseguir um processo de desenvolvimento de produto optimizado que englobe, de igual forma, as preocupações ambientais e o utilizador. Portanto, numa primeira fase são revistos os princípios de ecodesign, segue-se o estudo das áreas vocacionadas para o utilizador, que dizem respeito a ergonomia e, consequentemente, a usabilidade. E por fim é formulada uma metodologia projectual adaptada dos estudos revistos, que pretende dar resposta a este sistema de projecto optimizado. A metodologia é depois validada, com a sua implementação num projecto real, de redesign de um aspirador de uso quotidiano. Esta metodologia foi dividida em duas fases principais de pesquisa: (i) o reconhecimento das necessidades reais dos utilizadores, bem como problemas associados ao produto, por meio de pesquisas e testes de usabilidade (N=120), e (ii) a quantificação do impacto ambiental do produto (através do método do eco-indicador 99). Os dados globais permitem definir os requisitos do produto e delinear os critérios a serem incorporados no redesign do produto e também as medidas para melhorar a usabilidade que foram consistentes com as soluções de concepção ecológica.

Investigation on the development of bidding strategies for a wind farm owner

In this paper, the development of bidding strategies is investigated for a wind farm owner. The optimization model is characterized by making the analysis of scenarios. The proposed approach allows evaluating alternative production strategies in order to submit bids to the electricity market with the goal of maximizing profits. The problem is formulated as a linear programming problem. An application to a case study is presented

Comparative study of power converter topologies and control strategies for the harmonic performance of variable-speed wind turbine generator systems

Power converters play a vital role in the integration of wind power into the electrical grid. Variable-speed wind turbine generator systems have a considerable interest of application for grid connection at constant frequency. In this paper, comprehensive simulation studies are carried out with three power converter topologies: matrix, two-level and multilevel. A fractional-order control strategy is studied for the variable-speed operation of wind turbine generator systems. The studies are in order to compare power converter topologies and control strategies. The studies reveal that the multilevel converter and the proposed fractional-order control strategy enable an improvement in the power quality, in comparison with the other power converters using a classical integer-order control strategy. (C) 2010 Elsevier Ltd. All rights reserved.

Learning business strategies for competitive electronic marketplaces

This paper presents a Multi-Agent Market simulator designed for developing new agent market strategies based on a complete understanding of buyer and seller behaviors, preference models and pricing algorithms, considering user risk preferences and game theory for scenario analysis. This tool studies negotiations based on different market mechanisms and, time and behavior dependent strategies. The results of the negotiations between agents are analyzed by data mining algorithms in order to extract rules that give agents feedback to improve their strategies. The system also includes agents that are capable of improving their performance with their own experience, by adapting to the market conditions, and capable of considering other agent reactions.

Virtual power producers market strategies

This paper presents MASCEM - a multi-agent based electricity market simulator. MASCEM uses game theory, machine learning techniques, scenario analysis and optimisation techniques to model market agents and to provide them with decision-support. This paper mainly focus on the MASCEM ability to provide the means to model and simulate Virtual Power Producers (VPP). VPPs are represented as a coalition of agents, with specific characteristics and goals. The paper detail some of the most important aspects considered in VPP formation and in the aggregation of new producers and includes a case study.

Multi-agent electricity market simulation with dynamic strategies & virtual power producers

Distributed energy resources will provide a significant amount of the electricity generation and will be a normal profitable business. In the new decentralized grid, customers will be among the many decentralized players and may even help to co-produce the required energy services such as demand-side management and load shedding. So, they will gain the opportunity to be more active market players. The aggregation of DG plants gives place to a new concept: the Virtual Power Producer (VPP). VPPs can reinforce the importance of these generation technologies making them valuable in electricity markets. In this paper we propose the improvement of MASCEM, a multi-agent simulation tool to study negotiations in electricity spot markets based on different market mechanisms and behavior strategies, in order to take account of decentralized players such as VPP.

Optimal strategies for marine wildlife tourism in small islands

Tese de Doutoramento, Ciências Económicas e Empresariais (especialidade de Economia), 18 de Junho de 2015, Universidade dos Açores

Immune responses in Bathymodiolus azoricus upon Vibrio challenges : approaches to characterize mussel survival strategies and physiological adaptations in deep sea extreme environments

Tese de Doutoramento, Ciências do Mar, especialidade de Biologia Marinha, 18 de Dezembro de 2015, Universidade dos Açores.

Fractional model for malaria transmission under control strategies

We study a fractional model for malaria transmission under control strategies.Weconsider the integer order model proposed by Chiyaka et al. (2008) in [15] and modify it to become a fractional order model. We study numerically the model for variation of the values of the fractional derivative and of the parameter that models personal protection, b. From observation of the figures we conclude that as b is increased from 0 to 1 there is a corresponding decrease in the number of infectious humans and infectious mosquitoes, for all values of α. This means that this result is invariant for variation of fractional derivative, in the values tested. These results are in agreement with those obtained in Chiyaka et al.(2008) [15] for α = 1.0 and suggest that our fractional model is epidemiologically wellposed.

Besnoitia besnoiti and Toxoplasma gondii: two apicomplexan strategies to manipulate the host cell centrosome and Golgi apparatus

Besnoitia besnoiti and Toxoplasma gondii are two closely related parasites that interact with the host cell microtubule cytoskeleton during host cell invasion. Here we studied the relationship between the ability of these parasites to invade and to recruit the host cell centrosome and the Golgi apparatus. We observed that T. gondii recruits the host cell centrosome towards the parasitophorous vacuole (PV), whereas B. besnoiti does not. Notably, both parasites recruit the host Golgi apparatus to the PV but its organization is affected in different ways. We also investigated the impact of depleting and over-expressing the host centrosomal protein TBCCD1, involved in centrosome positioning and Golgi apparatus integrity, on the ability of these parasites to invade and replicate. Toxoplasma gondii replication rate decreases in cells over-expressing TBCCD1 but not in TBCCD1-depleted cells; while for B. besnoiti no differences were found. However, B. besnoiti promotes a reorganization of the Golgi ribbon previously fragmented by TBCCD1 depletion. These results suggest that successful establishment of PVs in the host cell requires modulation of the Golgi apparatus which probably involves modifications in microtubule cytoskeleton organization and dynamics. These differences in how T. gondii and B. besnoiti interact with their host cells may indicate different evolutionary paths.

Plano de marketing para a empresa: Salss - Importação e Comércio Lda

Trabalho de projeto apresentado à Escola Superior de Comunicação Social como parte dos requisitos para obtenção de grau de mestre em Publicidade e Marketing.

Chaînes opératoires and resource-exploitation strategies in chimpanzee (Pan troglodytes) nut cracking

Journal of Human Evolution, V. 55, pp. 148-163

A stochastic programming approach for the development of offering strategies for a wind power producer

A stochastic programming approach is proposed in this paper for the development of offering strategies for a wind power producer. The optimization model is characterized by making the analysis of several scenarios and treating simultaneously two kinds of uncertainty: wind power and electricity market prices. The approach developed allows evaluating alternative production and offers strategies to submit to the electricity market with the ultimate goal of maximizing profits. An innovative comparative study is provided, where the imbalances are treated differently. Also, an application to two new realistic case studies is presented. Finally, conclusions are duly drawn.

Race-to-halt energy saving strategies

Energy consumption is one of the major issues for modern embedded systems. Early, power saving approaches mainly focused on dynamic power dissipation, while neglecting the static (leakage) energy consumption. However, technology improvements resulted in a case where static power dissipation increasingly dominates. Addressing this issue, hardware vendors have equipped modern processors with several sleep states. We propose a set of leakage-aware energy management approaches that reduce the energy consumption of embedded real-time systems while respecting the real-time constraints. Our algorithms are based on the race-to-halt strategy that tends to run the system at top speed with an aim to create long idle intervals, which are used to deploy a sleep state. The effectiveness of our algorithms is illustrated with an extensive set of simulations that show an improvement of up to 8% reduction in energy consumption over existing work at high utilization. The complexity of our algorithms is smaller when compared to state-of-the-art algorithms. We also eliminate assumptions made in the related work that restrict the practical application of the respective algorithms. Moreover, a novel study about the relation between the use of sleep intervals and the number of pre-emptions is also presented utilizing a large set of simulation results, where our algorithms reduce the experienced number of pre-emptions in all cases. Our results show that sleep states in general can save up to 30% of the overall number of pre-emptions when compared to the sleep-agnostic earliest-deadline-first algorithm.