Personalised Advertising Supported by Agents

This paper reports the development of a B2B platform for the personalization of the publicity transmitted during the program intervals. The platform as a whole must ensure that the intervals are filled with ads compatible with the profile, context and expressed interests of the viewers. The platform acts as an electronic marketplace for advertising agencies (content producer companies) and multimedia content providers (content distribution companies). The companies, once registered at the platform, are represented by agents who negotiate automatically the price of the interval timeslots according to the specified price range and adaptation behaviour. The candidate ads for a given viewer interval are selected through a matching mechanism between ad, viewer and the current context (program being watched) profiles. The overall architecture of the platform consists of a multiagent system organized into three layers consisting of: (i) interface agents that interact with companies; (ii) enterprise agents that model the companies, and (iii) delegate agents that negotiate a specific ad or interval. The negotiation follows a variant of the Iterated Contract Net Interaction Protocol (ICNIP) and is based on the price/s offered by the advertising agencies to occupy the viewer’s interval.

Management Driven Hybrid Multicast Framework for Content Aware Networks

The need for better adaptation of networks to transported flows has led to research on new approaches such as content aware networks and network aware applications. In parallel, recent developments of multimedia and content oriented services and applications such as IPTV, video streaming, video on demand, and Internet TV reinforced interest in multicast technologies. IP multicast has not been widely deployed due to interdomain and QoS support problems; therefore, alternative solutions have been investigated. This article proposes a management driven hybrid multicast solution that is multi-domain and media oriented, and combines overlay multicast, IP multicast, and P2P. The architecture is developed in a content aware network and network aware application environment, based on light network virtualization. The multicast trees can be seen as parallel virtual content aware networks, spanning a single or multiple IP domains, customized to the type of content to be transported while fulfilling the quality of service requirements of the service provider.

An uncertainty and sensitivity analysis applied to the prioritisation of pharmaceuticals as surface water contaminants from wastewater treatment plant direct emissions

In this study, the concentration probability distributions of 82 pharmaceutical compounds detected in the effluents of 179 European wastewater treatment plants were computed and inserted into a multimedia fate model. The comparative ecotoxicological impact of the direct emission of these compounds from wastewater treatment plants on freshwater ecosystems, based on a potentially affected fraction (PAF) of species approach, was assessed to rank compounds based on priority. As many pharmaceuticals are acids or bases, the multimedia fate model accounts for regressions to estimate pH-dependent fate parameters. An uncertainty analysis was performed by means of Monte Carlo analysis, which included the uncertainty of fate and ecotoxicity model input variables, as well as the spatial variability of landscape characteristics on the European continental scale. Several pharmaceutical compounds were identified as being of greatest concern, including 7 analgesics/anti-inflammatories, 3 β-blockers, 3 psychiatric drugs, and 1 each of 6 other therapeutic classes. The fate and impact modelling relied extensively on estimated data, given that most of these compounds have little or no experimental fate or ecotoxicity data available, as well as a limited reported occurrence in effluents. The contribution of estimated model input variables to the variance of freshwater ecotoxicity impact, as well as the lack of experimental abiotic degradation data for most compounds, helped in establishing priorities for further testing. Generally, the effluent concentration and the ecotoxicity effect factor were the model input variables with the most significant effect on the uncertainty of output results.

Visitas imersivas em contexto turístico

Engenharia Informática, Área de Especialização em Sistemas Gráficos e Multimédia

Análise de Desempenho e Recomendação para Soluções IVR

Mestrado em Engenharia Informática, Área de Especialização em Tecnologias do Conhecimento e da Decisão

Ambientes Tridimensionais Sonoros

O estado emocional de um individuo tem um papel importante na realização de determinada tarefa, ou conjunto de tarefas, na medida em que pode influenciar o bom desempenho na realização destas. O ser humano pode sentir diversas emoções e, conjugadas, resultam em inúmeros estados emocionais. A música pode influenciar o nosso estado emocional, mesmo de uma forma inconsciente. Por isso ouvimos música enquanto realizamos várias tarefas. O foco desta dissertação consistiu na criação de uma ferramenta multimédia – EMOCUBE (emotion cube – caixa de emoções) que, através da música, contribuísse para o sucesso da realização de determinada tarefa/situação. A cada situação é atribuído um estado emocional, que influenciará a seleção das músicas sugeridas ao ouvinte. Os resultados da avaliação efetuada sobre a aplicação foram, de uma forma geral, positivos e salientaram a originalidade da ideia deste projeto. Com o desenvolvimento desta aplicação, abriram-se portas para novos projetos e possíveis parcerias com ferramentas e aplicações já existentes no mercado.

Geocaching como ferramenta de Marketing Digital

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.

Media Brokerage: Agent-Based SLA Negotiation

Media content personalisation is a major challenge involving viewers as well as media content producer and distributor businesses. The goal is to provide viewers with media items aligned with their interests. Producers and distributors engage in item negotiations to establish the corresponding service level agreements (SLA). In order to address automated partner lookup and item SLA negotiation, this paper proposes the MultiMedia Brokerage (MMB) platform, which is a multiagent system that negotiates SLA regarding media items on behalf of media content producer and distributor businesses. The MMB platform is structured in four service layers: interface, agreement management, business modelling and market. In this context, there are: (i) brokerage SLA (bSLA), which are established between individual businesses and the platform regarding the provision of brokerage services; and (ii) item SLA (iSLA), which are established between producer and distributor businesses about the provision of media items. In particular, this paper describes the negotiation, establishment and enforcement of bSLA and iSLA, which occurs at the agreement and negotiation layers, respectively. The platform adopts a pay-per-use business model where the bSLA define the general conditions that apply to the related iSLA. To illustrate this process, we present a case study describing the negotiation of a bSLA instance and several related iSLA instances. The latter correspond to the negotiation of the Electronic Program Guide (EPG) for a specific end viewer.

Automatização de sistemas de inspeção COGNEX

Com um mercado automóvel cada vez mais competitivo e com os construtores automóveis à procura de atingir os zero defeitos nos seus produtos, a Bosch Car Multimédia Portugal S.A, fabricante de sistemas multimédia para o mercado automóvel, tem como objetivo a qualidade perfeita dos seus produtos. Tal perfeição exige processos de fabrico cada vez mais evoluídos e com melhores sistemas de auxílio à montagem. Nesse sentido, a incorporação de sistemas de visão artificial para verificação da montagem correta dos componentes em sistemas multimédia tem vindo a crescer largamente. Os sistemas de inspeção visual da Cognex tornaram-se o standard da Bosch para a verifi-cação da montagem de componentes por serem sistemas bastante completos, fáceis de con-figurar e com um suporte técnico bastante completo. Estes sistemas têm vindo a ser inte-grados em diversas máquinas (postos) de montagem e nunca foi desenvolvida uma ferra-menta normalizada para integração destes sistemas com as máquinas. A ideia principal deste projeto passou por desenvolver um sistema (uma aplicação informá-tica) que permita controlar os indicadores de qualidade destes sistemas de visão, garantir o seguimento dos produtos montados e, ao mesmo tempo, efetuar cópias de segurança de todo o sistema para utilização em caso de avaria ou de troca de equipamento. Tal sistema foi desenvolvido recorrendo à programação de uma Dynamic Link Library (DLL), através da linguagem VisualBasic.NET, que permite às aplicações dos equipamen-tos (máquinas) da Bosch Car Multimédia comunicarem de uma forma universal e transpa-rente com os sistemas de inspeção visual da marca Cognex. Os objetivos a que o autor se propôs no desenvolvimento deste sistema foram na sua maioria alcançados e o projeto encontra-se atualmente implementado e em execução nas linhas de produção da Bosch Car Multimédia.

Brokerage Platform for Media Content Recommendation

Near real time media content personalisation is nowadays a major challenge involving media content sources, distributors and viewers. This paper describes an approach to seamless recommendation, negotiation and transaction of personalised media content. It adopts an integrated view of the problem by proposing, on the business-to-business (B2B) side, a brokerage platform to negotiate the media items on behalf of the media content distributors and sources, providing viewers, on the business-to-consumer (B2C) side, with a personalised electronic programme guide (EPG) containing the set of recommended items after negotiation. In this setup, when a viewer connects, the distributor looks up and invites sources to negotiate the contents of the viewer personal EPG. The proposed multi-agent brokerage platform is structured in four layers, modelling the registration, service agreement, partner lookup, invitation as well as item recommendation, negotiation and transaction stages of the B2B processes. The recommendation service is a rule-based switch hybrid filter, including six collaborative and two content-based filters. The rule-based system selects, at runtime, the filter(s) to apply as well as the final set of recommendations to present. The filter selection is based on the data available, ranging from the history of items watched to the ratings and/or tags assigned to the items by the viewer. Additionally, this module implements (i) a novel item stereotype to represent newly arrived items, (ii) a standard user stereotype for new users, (iii) a novel passive user tag cloud stereotype for socially passive users, and (iv) a new content-based filter named the collinearity and proximity similarity (CPS). At the end of the paper, we present off-line results and a case study describing how the recommendation service works. The proposed system provides, to our knowledge, an excellent holistic solution to the problem of recommending multimedia contents.

An intelligent clustering scheme for distributed intrusion detection in vehicular cloud computing

In recent years, vehicular cloud computing (VCC) has emerged as a new technology which is being used in wide range of applications in the area of multimedia-based healthcare applications. In VCC, vehicles act as the intelligent machines which can be used to collect and transfer the healthcare data to the local, or global sites for storage, and computation purposes, as vehicles are having comparatively limited storage and computation power for handling the multimedia files. However, due to the dynamic changes in topology, and lack of centralized monitoring points, this information can be altered, or misused. These security breaches can result in disastrous consequences such as-loss of life or financial frauds. Therefore, to address these issues, a learning automata-assisted distributive intrusion detection system is designed based on clustering. Although there exist a number of applications where the proposed scheme can be applied but, we have taken multimedia-based healthcare application for illustration of the proposed scheme. In the proposed scheme, learning automata (LA) are assumed to be stationed on the vehicles which take clustering decisions intelligently and select one of the members of the group as a cluster-head. The cluster-heads then assist in efficient storage and dissemination of information through a cloud-based infrastructure. To secure the proposed scheme from malicious activities, standard cryptographic technique is used in which the auotmaton learns from the environment and takes adaptive decisions for identification of any malicious activity in the network. A reward and penalty is given by the stochastic environment where an automaton performs its actions so that it updates its action probability vector after getting the reinforcement signal from the environment. The proposed scheme was evaluated using extensive simulations on ns-2 with SUMO. The results obtained indicate that the proposed scheme yields an improvement of 10 % in detection rate of malicious nodes when compared with the existing schemes.

Mode-Controlled Data-Flow Modeling of Real-Time Memory Controllers

Accepted in 13th IEEE Symposium on Embedded Systems for Real-Time Multimedia (ESTIMedia 2015), Amsterdam, Netherlands.

Tuning metadata for better movie content-based recommendation systems

The increasing number of television channels, on-demand services and online content, is expected to contribute to a better quality of experience for a costumer of such a service. However, the lack of efficient methods for finding the right content, adapted to personal interests, may lead to a progressive loss of clients. In such a scenario, recommendation systems are seen as a tool that can fill this gap and contribute to the loyalty of users. Multimedia content, namely films and television programmes are usually described using a set of metadata elements that include the title, a genre, the date of production, and the list of directors and actors. This paper provides a deep study on how the use of different metadata elements can contribute to increase the quality of the recommendations suggested. The analysis is conducted using Netflix and Movielens datasets and aspects such as the granularity of the descriptions, the accuracy metric used and the sparsity of the data are taken into account. Comparisons with collaborative approaches are also presented.

A Multi–Agent Brokerage Platform for Media Content Recommendation

Near real time media content personalisation is nowadays a major challenge involving media content sources, distributors and viewers. This paper describes an approach to seamless recommendation, negotiation and transaction of personalised media content. It adopts an integrated view of the problem by proposing, on the business-to-business (B2B) side, a brokerage platform to negotiate the media items on behalf of the media content distributors and sources, providing viewers, on the business-to-consumer (B2C) side, with a personalised electronic programme guide (EPG) containing the set of recommended items after negotiation. In this setup, when a viewer connects, the distributor looks up and invites sources to negotiate the contents of the viewer personal EPG. The proposed multi-agent brokerage platform is structured in four layers, modelling the registration, service agreement, partner lookup, invitation as well as item recommendation, negotiation and transaction stages of the B2B processes. The recommendation service is a rule-based switch hybrid filter, including six collaborative and two content-based filters. The rule-based system selects, at runtime, the filter(s) to apply as well as the final set of recommendations to present. The filter selection is based on the data available, ranging from the history of items watched to the ratings and/or tags assigned to the items by the viewer. Additionally, this module implements (i) a novel item stereotype to represent newly arrived items, (ii) a standard user stereotype for new users, (iii) a novel passive user tag cloud stereotype for socially passive users, and (iv) a new content-based filter named the collinearity and proximity similarity (CPS). At the end of the paper, we present off-line results and a case study describing how the recommendation service works. The proposed system provides, to our knowledge, an excellent holistic solution to the problem of recommending multimedia contents.

Localização de jogos

Dissertação de Mestrado apresentada ao Instituto de Contabilidade e Administração do Porto para a obtenção do grau de Mestre em Tradução e Interpretação Especializadas, sob orientação do Doutor Manuel Moreira da Silva Esta versão não contém as críticas e sugestões dos elementos do júri