986 resultados para Virtual Promotional Tools


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Mestrado em Engenharia Informática - Área de Especialização em Sistemas Gráficos e Multimédia

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Dissertation presented to obtain a Ph.D. degree in Engineering and Technology Sciences, Biotechnology at the Instituto de Tecnologia Química e Biológica, Universidade Nova de Lisboa

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Relatório de Estágio apresentado para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Novos Media e Práticas Web.

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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Biomédica

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O Geocaching é um jogo, criado pela Groundspeak, que consiste em esconder e encontrar objetos geolocalizados conhecidos como geocaches. A busca das geocaches é na realidade uma aventura que promove a vivência de novas experiências, o convívio entre utilizadores, a descoberta de novos espaços na natureza, a realização de jogos em tempo e cenário real, entre outros. Existem geocaches espalhadas por todo o mundo e milhares de utilizadores estão já registados no jogo. Além de passatempo, o Geocaching consegue ser uma ferramenta de marketing digital, quer para a própria Groundspeak, mas também para diferentes empresas/instituições por todo o mundo normalmente associadas à localização das geocaches. A Groundspeak é, naturalmente, a mais beneficiada uma vez que, praticamente sem investir em publicidade, conseguiu que o jogo tenha cada vez mais adeptos. A sua divulgação é essencialmente feita pelos próprios utilizadores, quer através da comunicação direta com um não utilizador, quer através de redes sociais, de eventos organizados, mas também através de outras empresas que desenvolveram aplicações com funcionalidades extra que permitem ao utilizador uma melhor experiência. O objetivo desta dissertação foi o de demonstrar como é que o Geocaching pode ser usado como uma ferramenta de Marketing Digital. Inicialmente, foi analisada a questão do Marketing Digital e das suas ferramentas, focando o Geocaching e a sua dimensão no mundo, explicando os diferentes tipos de caches e de que forma as mesmas podem ser utilizadas como ferramentas de marketing. Como elemento de validação, foi concebida, desenvolvida e validada uma wherigo (um tipo de geocache), que consiste num jogo virtual onde o progresso do jogador depende das tarefas realizadas e da sua movimentação geolocalizada. A wherigo criada no âmbito do projeto é um meio de marketing digital, de divulgação do Castelo de Santa Maria da Feira, realizada de uma forma interativa e divertida, através de questionários, desafios e fantasia. O jogo incita a percorrer os jardins que rodeiam o Castelo bem como o interior do mesmo e permite ainda o acesso dos jogadores ao Castelo com desconto de geocacher na aquisição do ingresso. Os objetivos propostos inicialmente foram completamente cumpridos, sendo que o jogo já se encontra disponível para ser jogado por geocachers e foi por eles avaliado muito positivamente.

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This paper intends to present the legal background that support dissemination and access to documents from European institutions, namely the Parliament, the Council and the European Commission. Currently, this legal framework is accomplished with a set of Internet tools that are analyzed regarding official documents types and options searches available. Some statistical data on access to European information published in annual reports from the institutions are also evaluated. The relationship between shadow and light in transparency to access administrative documents and marketing issues of a political communication are underlined. Neo-institutional approach, reputational concept in public organizations and systemic perspective are used as theoretical background.

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Relatório de Estágio apresentada para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Ciências da Informação e da Documentação

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Demand response is assumed as an essential resource to fully achieve the smart grids operating benefits, namely in the context of competitive markets and of the increasing use of renewable-based energy sources. Some advantages of Demand Response (DR) programs and of smart grids can only be achieved through the implementation of Real Time Pricing (RTP). The integration of the expected increasing amounts of distributed energy resources, as well as new players, requires new approaches for the changing operation of power systems. The methodology proposed in this paper aims the minimization of the operation costs in a distribution network operated by a virtual power player that manages the available energy resources focusing on hour ahead re-scheduling. When facing lower wind power generation than expected from day ahead forecast, demand response is used in order to minimize the impacts of such wind availability change. In this way, consumers actively participate in regulation up and spinning reserve ancillary services through demand response programs. Real time pricing is also applied. The proposed model is especially useful when actual and day ahead wind forecast differ significantly. Its application is illustrated in this paper implementing the characteristics of a real resources conditions scenario in a 33 bus distribution network with 32 consumers and 66 distributed generators.

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This paper proposes a wind speed forecasting model that contributes to the development and implementation of adequate methodologies for Energy Resource Man-agement in a distribution power network, with intensive use of wind based power generation. The proposed fore-casting methodology aims to support the operation in the scope of the intraday resources scheduling model, name-ly with a time horizon of 10 minutes. A case study using a real database from the meteoro-logical station installed in the GECAD renewable energy lab was used. A new wind speed forecasting model has been implemented and it estimated accuracy was evalu-ated and compared with a previous developed forecast-ing model. Using as input attributes the information of the wind speed concerning the previous 3 hours enables to obtain results with high accuracy for the wind short-term forecasting.

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The integration of growing amounts of distributed generation in power systems, namely at distribution networks level, has been fostered by energy policies in several countries around the world, including in Europe. This intensive integration of distributed, non-dispatchable, and natural sources based generation (including wind power) has caused several changes in the operation and planning of power systems and of electricity markets. Sometimes the available non-dispatchable generation is higher than the demand. This generation must be used; otherwise it is wasted if not stored or used to supply additional demand. New policies and market rules, as well as new players, are needed in order to competitively integrate all the resources. The methodology proposed in this paper aims at the maximization of the social welfare in a distribution network operated by a virtual power player that aggregates and manages the available energy resources. When facing a situation of excessive non-dispatchable generation, including wind power, real time pricing is applied in order to induce the increase of consumption so that wind curtailment is minimized. This method is especially useful when actual and day-ahead resources forecast differ significantly. The distribution network characteristics and concerns are addressed by including the network constraints in the optimization model. The proposed methodology has been implemented in GAMS optimization tool and its application is illustrated in this paper using a real 937-bus distribution network with 20.310 consumers and 548 distributed generators, some of them non-dispatchable and with must take contracts. The implemented scenario corresponds to a real day in Portuguese power system.

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Electricity markets are complex environments comprising several negotiation mechanisms. MASCEM (Multi- Agent System for Competitive Electricity Markets) is a simulator developed to allow deep studies of the interactions between the players that take part in the electricity market negotiations. ALBidS (Adaptive Learning Strategic Bidding System) is a multiagent system created to provide decision support to market negotiating players. Fully integrated with MASCEM it considers several different methodologies based on very distinct approaches. The Six Thinking Hats is a powerful technique used to look at decisions from different perspectives. This paper aims to complement ALBidS strategies usage by MASCEM players, providing, through the Six Thinking Hats group decision technique, a means to combine them and take advantages from their different perspectives. The combination of the different proposals resulting from ALBidS’ strategies is performed through the application of a Genetic Algorithm, resulting in an evolutionary learning approach.

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Power systems have been through deep changes in recent years, namely due to the operation of competitive electricity markets in the scope the increasingly intensive use of renewable energy sources and distributed generation. This requires new business models able to cope with the new opportunities that have emerged. Virtual Power Players (VPPs) are a new type of player that allows aggregating a diversity of players (Distributed Generation (DG), Storage Agents (SA), Electrical Vehicles (V2G) and consumers) to facilitate their participation in the electricity markets and to provide a set of new services promoting generation and consumption efficiency, while improving players’ benefits. A major task of VPPs is the remuneration of generation and services (maintenance, market operation costs and energy reserves), as well as charging energy consumption. This paper proposes a model to implement fair and strategic remuneration and tariff methodologies, able to allow efficient VPP operation and VPP goals accomplishment in the scope of electricity markets.

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This paper presents a decision support tool methodology to help virtual power players (VPPs) in the Smart Grid (SGs) context to solve the day-ahead energy resource scheduling considering the intensive use of Distributed Generation (DG) and Vehicle-To-Grid (V2G). The main focus is the application of a new hybrid method combing a particle swarm approach and a deterministic technique based on mixedinteger linear programming (MILP) to solve the day-ahead scheduling minimizing total operation costs from the aggregator point of view. A realistic mathematical formulation, considering the electric network constraints and V2G charging and discharging efficiencies is presented. Full AC power flow calculation is included in the hybrid method to allow taking into account the network constraints. A case study with a 33-bus distribution network and 1800 V2G resources is used to illustrate the performance of the proposed method.

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Artificial Intelligence has been applied to dynamic games for many years. The ultimate goal is creating responses in virtual entities that display human-like reasoning in the definition of their behaviors. However, virtual entities that can be mistaken for real persons are yet very far from being fully achieved. This paper presents an adaptive learning based methodology for the definition of players’ profiles, with the purpose of supporting decisions of virtual entities. The proposed methodology is based on reinforcement learning algorithms, which are responsible for choosing, along the time, with the gathering of experience, the most appropriate from a set of different learning approaches. These learning approaches have very distinct natures, from mathematical to artificial intelligence and data analysis methodologies, so that the methodology is prepared for very distinct situations. This way it is equipped with a variety of tools that individually can be useful for each encountered situation. The proposed methodology is tested firstly on two simpler computer versus human player games: the rock-paper-scissors game, and a penalty-shootout simulation. Finally, the methodology is applied to the definition of action profiles of electricity market players; players that compete in a dynamic game-wise environment, in which the main goal is the achievement of the highest possible profits in the market.

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A forma como aprendemos depende do contexto tecnológico e sociocultural que nos rodeia, actualmente a inclusão de tecnologia recente na sala de aula não é mais considerada opcional, mas sim uma necessidade pois a forma como o aluno aprende está em constante evolução. Tendo em atenção esta necessidade, foi desenvolvido no decorrer desta tese um simulador em realidade virtual que utiliza comandos/interfaces hápticos. O objectivo deste simulador é ensinar conceitos de física de forma interactiva. Os dispositivos hápticos permitem adicionar o sentido táctil ou de toque à interacção entre homem e máquina, permitindo assim aceder a novas sensações relativas ao seu uso nomeadamente com objectivos de aprendizagem. O simulador desenvolvido designado por “Forces of Physics” aborda três tipos de forças da física: forças de atrito, forças gravitacionais e forças aerodinâmicas. Cada tipo de força corresponde a um módulo do simulador contendo uma simulação individual em que são explicados conceitos específicos dessa força num ambiente visual estimulante e com uma interacção mais realista devido à inclusão do dispositivo háptico Novint Falcon. O simulador foi apresentado a vários utilizadores bem como á comunidade científica através de apresentações em conferências. A avaliação foi realizada com recurso a um questionário com dez perguntas, cinco de sobre aprendizagem e cinco sobre a utilização, tendo sido preenchido por 14 utilizadores. O simulador obteve uma boa recepção por parte dos utilizadores, tendo vários utilizadores expressado as suas opiniões sobre estado actual do simulador, do futuro do mesmo e da respectiva validade para uso na sala de aula.