Visualização personalizada sensível ao contexto e às emoções

Mestrado em Engenharia Informática

Recommendation and planning through mobile devices in tourism context

In this paper we present a mobile recommendation and planning system, named PSiS Mobile. It is designed to provide effective support during a tourist visit through context-aware information and recommendations about points of interest, exploiting tourist preferences and context. Designing a tool like this brings several challenges that must be addressed. We discuss how these challenges have been overcame, present the overall system architecture, since this mobile application extends the PSiS project website, and the mobile application architecture.

Context-aware emotion-based model for group decision making

Involving groups in important management processes such as decision making has several advantages. By discussing and combining ideas, counter ideas, critical opinions, identified constraints, and alternatives, a group of individuals can test potentially better solutions, sometimes in the form of new products, services, and plans. In the past few decades, operations research, AI, and computer science have had tremendous success creating software systems that can achieve optimal solutions, even for complex problems. The only drawback is that people don’t always agree with these solutions. Sometimes this dissatisfaction is due to an incorrect parameterization of the problem. Nevertheless, the reasons people don’t like a solution might not be quantifiable, because those reasons are often based on aspects such as emotion, mood, and personality. At the same time, monolithic individual decisionsupport systems centered on optimizing solutions are being replaced by collaborative systems and group decision-support systems (GDSSs) that focus more on establishing connections between people in organizations. These systems follow a kind of social paradigm. Combining both optimization- and socialcentered approaches is a topic of current research. However, even if such a hybrid approach can be developed, it will still miss an essential point: the emotional nature of group participants in decision-making tasks. We’ve developed a context-aware emotion based model to design intelligent agents for group decision-making processes. To evaluate this model, we’ve incorporated it in an agent-based simulator called ABS4GD (Agent-Based Simulation for Group Decision), which we developed. This multiagent simulator considers emotion- and argument based factors while supporting group decision-making processes. Experiments show that agents endowed with emotional awareness achieve agreements more quickly than those without such awareness. Hence, participant agents that integrate emotional factors in their judgments can be more successful because, in exchanging arguments with other agents, they consider the emotional nature of group decision making.

An emotional and context-aware model for adapting RSS news to users and groups

The exhibition of information does not always attend to the preferences and characteristics of the users, nor the context that involves the user. With the aim of overcoming this gap, we propose an emotional context-aware model for adapting information contents to users and groups. The proposed model is based on OCC and Big Five models to handle emotion and personality respectively. The idea is to adapt the representation of the information in order to maximize the positive emotional valences and minimize the negatives. To evaluate the proposed model it was developed a prototype for adapting RSS news to users and group of users.

Safety high accuracy Context-Aware Matrix (CAM) making based on X.509 proxy certificate

Human Computer Interaction (HCl) is to interaction between computers and each person. And context-aware (CA) is very important one of HCI composition. In particular, if there are sequential or continuous tasks between users and devices, among users, and among devices etc, it is important to decide the next action using right CA. And to take perfect decision we have to get together all CA into a structure. We define that structure is Context-Aware Matrix (CAM) in this article. However to make exact decision is too hard for some problems like low accuracy, overhead and bad context by attacker etc. Many researcher has been studying to solve these problems. Moreover, still it has weak point HCI using in safety. In this Article, we propose CAM making include best selecting Server in each area. As a result, moving users could be taken the best way.

Optimization, high availability and redundancy in information communications and technology using networks and systems virtualization architectures

Mestrado em Engenharia Informática

Building adaptable, QoS-aware dependable embedded systems

Most of today’s embedded systems are required to work in dynamic environments, where the characteristics of the computational load cannot always be predicted in advance. Furthermore, resource needs are usually data dependent and vary over time. Resource constrained devices may need to cooperate with neighbour nodes in order to fulfil those requirements and handle stringent non-functional constraints. This paper describes a framework that facilitates the distribution of resource intensive services across a community of nodes, forming temporary coalitions for a cooperative QoSaware execution. The increasing need to tailor provided service to each application’s specific needs determines the dynamic selection of peers to form such a coalition. The system is able to react to load variations, degrading its performance in a controlled fashion if needed. Isolation between different services is achieved by guaranteeing a minimal service quality to accepted services and by an efficient overload control that considers the challenges and opportunities of dynamic distributed embedded systems.

CANDi: context-aware node discovery for short-range cooperation

Multi-standard mobile devices are allowing users to enjoy higher data rates with ubiquitous connectivity. However, the benefits gained from multiple interfaces come at an expense—that being higher energy consumption in an era where mobile devices need to be energy compliant. One promising solution is the usage of short-range cooperative communication as an overlay for infrastructure-based networks taking advantage of its context information. However, the node discovery mechanism, which is pivotal to the bearer establishment process, still represents a major burden in terms of the total energy budget. In this paper, we propose a technology agnostic approach towards enhancing the MAC energy ratings by presenting a context-aware node discovery (CANDi) algorithm, which provides a priori knowledge towards the node discovery mechanism by allowing it to search nodes in the near vicinity at the ‘right time and at the right place’. We describe the different beacons required for establishing the cooperation, as well as the context information required, including battery level, modes, location and so on. CANDi uses the long-range network (WiMAX and WiFi) to distribute the context information about cooperative clusters (Ultra-wideband-based) in the vicinity. The searching nodes can use this context in locating the cooperative clusters/nodes, which facilitates the establishing of short-range connections. Analytical and simulation results are obtained, and the energy saving gains are further demonstrated in the laboratory using a customised testbed. CANDi saves up to 50% energy during the node discovery process, while the demonstrative testbed shows up to 75% savings in the total energy budget, thus validating the algorithm, as well as providing viable evidence to support the usage of short-range cooperative communications for energy savings.

PSiS mobile

Os sistemas de recomendação têm vindo a ser cada vez mais utilizados nos últimos anos. Por isso, é imprescindível que estes sistemas se adaptem à evolução da sociedade incluindo cada vez mais novas funcionalidades, tais como a adaptação do sistema ao contexto da pessoa. Esta adaptação pode ser feita através de, por exemplo, dispositivos móveis, que têm vindo a apresentar uma taxa de crescimento de vendas muito grande. Dada a crescente integração dos sistemas de recomendação com os sistemas móveis, foi elaborado um estudo sobre o estado da arte dos sistemas de auxílio ao turista que utilizam dispositivos móveis, sendo apresentadas as suas vantagens e desvantagens. Estes sistemas móveis de auxílio a turistas foram divididos em dois grupos: os que apresentam apenas a informação sobre pontos de interesse e os sistemas que são capazes de efectuar recomendações, com base no perfil do turista. Um breve estudo sobre os sistemas operativos para dispositivos móveis é apresentado, sendo especialmente focado o sistema operativo Android que foi o escolhido para esta implementação. Como os dispositivos móveis, actualmente, ainda possuem várias limitações, estas foram descritas e apresentadas as boas práticas no desenvolvimento de aplicações para este tipo de sistemas. É também apresentado um estudo que visa descobrir qual é o método mais leve e mais rápido para trocar dados entre a parte servidora e a parte móvel. Com a parte introdutória apresentada, é exposto o projecto desenvolvido nesta tese, o PSiS Mobile. Este sistema é um módulo que faz parte do projecto PSiS e pretende trazer todas as vantagens dos sistemas móveis para o sistema base já implementado. O projecto PSiS foca-se no estabelecimento de planos de visita personalizados com indicação de percursos para turistas com tempo limitado. Apoiando a definição de planos de visitas de acordo com o perfil do turista (interesses, valores pessoais, desejos, restrições, deficiências, etc.) combinando os produtos de turismo mais adequados (locais de interesse, eventos, restaurantes, etc.) em itinerários eficientes. A utilização de dispositivos móveis para acompanhamento da visita permite uma rápida interacção entre o turista e o sistema. Assim, o PSiS poderá recolher informação contextual do utilizador para que o perfil do mesmo seja enriquecido. O sistema apresentado é composto por duas partes: a parte cliente e a parte servidora. Toda a informação, como por exemplo o perfil do turista, histórico de viagens e valores de similaridade entre utilizadores está presente na parte servidora. O processo de recomendação também é efectuado pela aplicação servidora, sendo esta a responsável pela atribuição de uma classificação aos pontos de interesse tendo em conta o perfil do utilizador em causa. A base de dados do PSiS possui toda a informação relativa aos pontos de interesse numa determinada cidade ou região e o portfólio completo do histórico de visitas de cada utilizador. A componente móvel é uma parte muito importante para o sistema, pois interage com o utilizador no terreno. Um dispositivo móvel como o PDA, não só permite a apresentação de informação relevante ao utilizador, como também permite a recolha automática de informação contextual (por exemplo, a localização). Toda esta informação contribui para a definição de um perfil completo e para uma melhor adaptação do sistema às necessidades do utilizador. De forma a nem sempre estar dependente do servidor, a aplicação móvel possui rotinas para a realização de recomendações básicas. Ou seja, a aplicação móvel não realiza a classificação dos pontos de interesse, mas apenas mostra os principais resultados já formados pela parte servidora. Por exemplo, se um utilizador gostar de comida Chinesa, um restaurante Chinês nas imediações irá ter uma boa classificação e, por isso, ser recomendado. A aplicação móvel mostra ao turista o percurso definido para o dia em que o mesmo se encontra, sendo feito o rastreio do trajecto que o mesmo efectua. Assim, o sistema consegue saber se o horário do planeamento está a ser cumprido ou não. Caso não esteja, é invocado um algoritmo de planeamento que irá tentar corrigir o atraso ou o adiantamento perante o horário inicial. Depois de visitar um ponto de interesse, é pedido ao utilizador para fornecer feedback sobre o mesmo. Se desejado também é possível mostrar os pontos de interesse existentes perto do turista (usando as coordenadas GPS obtidas pelo dispositivo móvel) organizados por categorias, raio de distância, etc. Apesar dos dispositivos móveis possuírem várias restrições, pretendeu-se proporcionar ao utilizador uma boa experiência, através de uma aplicação rápida, de fácil utilização e adaptável, incluindo funcionalidades de planeamento, realidade aumentada e integração com a rede social do sistema. Todos estes factores contribuem para a disponibilização de informação detalhada ao turista.

A Review on the Characterization of Signals and Systems by Power Law Distributions

Power laws, also known as Pareto-like laws or Zipf-like laws, are commonly used to explain a variety of real world distinct phenomena, often described merely by the produced signals. In this paper, we study twelve cases, namely worldwide technological accidents, the annual revenue of America׳s largest private companies, the number of inhabitants in America׳s largest cities, the magnitude of earthquakes with minimum moment magnitude equal to 4, the total burned area in forest fires occurred in Portugal, the net worth of the richer people in America, the frequency of occurrence of words in the novel Ulysses, by James Joyce, the total number of deaths in worldwide terrorist attacks, the number of linking root domains of the top internet domains, the number of linking root domains of the top internet pages, the total number of human victims of tornadoes occurred in the U.S., and the number of inhabitants in the 60 most populated countries. The results demonstrate the emergence of statistical characteristics, very close to a power law behavior. Furthermore, the parametric characterization reveals complex relationships present at higher level of description.

Personalized sightseeing tours support using mobile devices

In this paper, we present PSiS (Personalized Sightseeing Tours Recommendation System) Mobile. PSiS Mobile is our proposal to a mobile recommendation and planning support system, which is designed to provide effective support during the tourist visit with context-aware information and recommendations about places of interest (POI), exploiting tourist preferences and context.

SPARTS: simulator for power aware and real-time systems

Real-time systems demand guaranteed and predictable run-time behaviour in order to ensure that no task has missed its deadline. Over the years we are witnessing an ever increasing demand for functionality enhancements in the embedded real-time systems. Along with the functionalities, the design itself grows more complex. Posed constraints, such as energy consumption, time, and space bounds, also require attention and proper handling. Additionally, efficient scheduling algorithms, as proven through analyses and simulations, often impose requirements that have significant run-time cost, specially in the context of multi-core systems. In order to further investigate the behaviour of such systems to quantify and compare these overheads involved, we have developed the SPARTS, a simulator of a generic embedded real- time device. The tasks in the simulator are described by externally visible parameters (e.g. minimum inter-arrival, sporadicity, WCET, BCET, etc.), rather than the code of the tasks. While our current implementation is primarily focused on our immediate needs in the area of power-aware scheduling, it is designed to be extensible to accommodate different task properties, scheduling algorithms and/or hardware models for the application in wide variety of simulations. The source code of the SPARTS is available for download at [1].

Mobile application to provide personalized sightseeing tours

Tourist recommendation systems have been growing over the last years, mainly because of the use of mobile devices to get user context. This work discuss some of the most relevant systems on the field and presents PSiS Mobile, which is a mobile recommendation and planning application designed to support a tourist during his vacations. It provides recommendations about points of interest to visit based on tourist preferences and on user and sight context. Also, it suggests a visit planning which can be dynamically adapted based on current user and sight context. This tool works like a journey dairy since it records the tourist moves and tasks to help him remember how the trip was like. To conclude, some field experiences will be presented.

A survey of techniques and technologies for web-based real-time interactive rendering

When exploring a virtual environment, realism depends mainly on two factors: realistic images and real-time feedback (motions, behaviour etc.). In this context, photo realism and physical validity of computer generated images required by emerging applications, such as advanced e-commerce, still impose major challenges in the area of rendering research whereas the complexity of lighting phenomena further requires powerful and predictable computing if time constraints must be attained. In this technical report we address the state-of-the-art on rendering, trying to put the focus on approaches, techniques and technologies that might enable real-time interactive web-based clientserver rendering systems. The focus is on the end-systems and not the networking technologies used to interconnect client(s) and server(s).

Towards high-available and energy-efficient virtual computing environments in the cloud

Empowered by virtualisation technology, cloud infrastructures enable the construction of flexi- ble and elastic computing environments, providing an opportunity for energy and resource cost optimisation while enhancing system availability and achieving high performance. A crucial re- quirement for effective consolidation is the ability to efficiently utilise system resources for high- availability computing and energy-efficiency optimisation to reduce operational costs and carbon footprints in the environment. Additionally, failures in highly networked computing systems can negatively impact system performance substantially, prohibiting the system from achieving its initial objectives. In this paper, we propose algorithms to dynamically construct and readjust vir- tual clusters to enable the execution of users’ jobs. Allied with an energy optimising mechanism to detect and mitigate energy inefficiencies, our decision-making algorithms leverage virtuali- sation tools to provide proactive fault-tolerance and energy-efficiency to virtual clusters. We conducted simulations by injecting random synthetic jobs and jobs using the latest version of the Google cloud tracelogs. The results indicate that our strategy improves the work per Joule ratio by approximately 12.9% and the working efficiency by almost 15.9% compared with other state-of-the-art algorithms.