Dream characteristics in a Brazilian sample: an online survey focusing on lucid dreaming

During sleep, humans experience the offline images and sensations that we call dreams, which are typically emotional and lacking in rational judgment of their bizarreness. However, during lucid dreaming (LD), subjects know that they are dreaming, and may control oneiric content. Dreaming and LD features have been studied in North Americans, Europeans and Asians, but not among Brazilians, the largest population in Latin America. Here we investigated dreams and LD characteristics in a Brazilian sample (n=3,427; median age=25 years) through an online survey. The subjects reported recalling dreams at least once a week (76%), and that dreams typically depicted actions (93%), known people (92%), sounds/voices (78%), and colored images (76%). The oneiric content was associated with plans for the upcoming days (37%), memories of the previous day (13%), or unrelated to the dreamer (30%). Nightmares usually depicted anxiety/fear (65%), being stalked (48%), or other unpleasant sensations(47%). These data corroborate Freudian notion of day residue in dreams, and suggest that dreams and nightmares are simulations of life situations that are related to our psychobiological integrity. Regarding LD, we observed that 77% of the subjects experienced LD at least once in life (44% up to 10 episodes ever), and for 48% LD subjectively lasted less than 1 min. LD frequency correlated weakly with dream recall frequency (r =0.20,p< 0.01), and LD control was rare (29%). LD occurrence was facilitated when subjects did not need to wake up early (38%), a situation that increases rapid eye movement sleep (REMS) duration, or when subjects were under stress (30%), which increases REMS transitions into waking. These results indicate that LD is relatively ubiquitous but rare, unstable, difficult to control, and facilitated by increases in REMS duration and transitions to wake state. Together with LD incidence in USA, Europe and Asia, our data from Latin America strengthen the notion that LD is a general phenomenon of the human species.

New ethnicities online: reflexive racialisation and the internet

In this article we analyse the emergence of Internet activity addressing the experiences of young people in two British communities: South Asian and Chinese.We focus on two web sites: www.barficulture.com and www.britishbornchinese.org.uk, drawing on interviews with site editors, content analysis of the discussion forums, and E-mail exchanges with site users. Our analysis of these two web sites shows how collective identities still matter, being redefined rather than erased by online interaction. We understand the site content through the notion of reflexive racialisation. We use this term to modify the stress given to individualisation in accounts of reflexive modernisation. In addition we question the allocation of racialised meaning from above implied by the concept of racialisation. Internet discussion forums can act as witnesses to social inequalities and through sharing experiences of racism and marginalisation, an oppositional social perspective may develop. The online exchanges have had offline consequences: social gatherings, charitable donations and campaigns against adverse media representations. These web sites have begun to change the terms of engagement between these ethnic groups and the wider society,and they have considerable potential to develop new forms of social action.

Dynamic Programming Approaches for Estimating and Applying Large-scale Discrete Choice Models

People go through their life making all kinds of decisions, and some of these decisions affect their demand for transportation, for example, their choices of where to live and where to work, how and when to travel and which route to take. Transport related choices are typically time dependent and characterized by large number of alternatives that can be spatially correlated. This thesis deals with models that can be used to analyze and predict discrete choices in large-scale networks. The proposed models and methods are highly relevant for, but not limited to, transport applications. We model decisions as sequences of choices within the dynamic discrete choice framework, also known as parametric Markov decision processes. Such models are known to be difficult to estimate and to apply to make predictions because dynamic programming problems need to be solved in order to compute choice probabilities. In this thesis we show that it is possible to explore the network structure and the flexibility of dynamic programming so that the dynamic discrete choice modeling approach is not only useful to model time dependent choices, but also makes it easier to model large-scale static choices. The thesis consists of seven articles containing a number of models and methods for estimating, applying and testing large-scale discrete choice models. In the following we group the contributions under three themes: route choice modeling, large-scale multivariate extreme value (MEV) model estimation and nonlinear optimization algorithms. Five articles are related to route choice modeling. We propose different dynamic discrete choice models that allow paths to be correlated based on the MEV and mixed logit models. The resulting route choice models become expensive to estimate and we deal with this challenge by proposing innovative methods that allow to reduce the estimation cost. For example, we propose a decomposition method that not only opens up for possibility of mixing, but also speeds up the estimation for simple logit models, which has implications also for traffic simulation. Moreover, we compare the utility maximization and regret minimization decision rules, and we propose a misspecification test for logit-based route choice models. The second theme is related to the estimation of static discrete choice models with large choice sets. We establish that a class of MEV models can be reformulated as dynamic discrete choice models on the networks of correlation structures. These dynamic models can then be estimated quickly using dynamic programming techniques and an efficient nonlinear optimization algorithm. Finally, the third theme focuses on structured quasi-Newton techniques for estimating discrete choice models by maximum likelihood. We examine and adapt switching methods that can be easily integrated into usual optimization algorithms (line search and trust region) to accelerate the estimation process. The proposed dynamic discrete choice models and estimation methods can be used in various discrete choice applications. In the area of big data analytics, models that can deal with large choice sets and sequential choices are important. Our research can therefore be of interest in various demand analysis applications (predictive analytics) or can be integrated with optimization models (prescriptive analytics). Furthermore, our studies indicate the potential of dynamic programming techniques in this context, even for static models, which opens up a variety of future research directions.

A three-dimensional representation method for noisy point clouds based on growing self-organizing maps accelerated on GPUs

The research described in this thesis was motivated by the need of a robust model capable of representing 3D data obtained with 3D sensors, which are inherently noisy. In addition, time constraints have to be considered as these sensors are capable of providing a 3D data stream in real time. This thesis proposed the use of Self-Organizing Maps (SOMs) as a 3D representation model. In particular, we proposed the use of the Growing Neural Gas (GNG) network, which has been successfully used for clustering, pattern recognition and topology representation of multi-dimensional data. Until now, Self-Organizing Maps have been primarily computed offline and their application in 3D data has mainly focused on free noise models, without considering time constraints. It is proposed a hardware implementation leveraging the computing power of modern GPUs, which takes advantage of a new paradigm coined as General-Purpose Computing on Graphics Processing Units (GPGPU). The proposed methods were applied to different problem and applications in the area of computer vision such as the recognition and localization of objects, visual surveillance or 3D reconstruction.

Water-enema multidetector computed tomography for planning surgery

International audience

A perspectiva do utilizador do Facebook relativamente à escolha de alojamento turístico

Atualmente assistimos a um aumento exponencial do uso dos social media como meio para planear as viagens lazer, bem como procurar por informações relativas a hotéis, restaurantes e outras empresas na indústria de turismo e viagens. Os social media criaram um novo canal de distribuição, tendo este influenciado e alterado a forma como os viajantes determinam o local onde vão ficar alojados. É importante que as empresas hoteleiras compreendam o comportamento dos consumidores face aos social media e, assim, determinar qual a forma de comunicação e que informações deverão disponibilizar nos seus sites. A título de exemplo, os hotéis conseguem interagir com os clientes através das redes sociais, como o Facebook, Instagram ou Youtube, partilhar diversos tipos de conteúdos informativos e prestar assistência a questões. O presente estudo tem como objetivo compreender o uso das redes sociais, apresentando-se um maior foco na rede social Facebook, na promoção de um estabelecimento hoteleiro e, com isto, determinar se a promoção dos serviços hoteleiros através deste meio, apresenta influência na tomada de decisão de escolha de alojamento turístico. Por outro lado, pretendese analisar o impacto das avaliações/recomendações realizadas pelos consumidores presentes no Facebook. Adotou-se uma metodologia quantitativa, através de um questionário online. Para analisar as hipóteses de estudo recorreu-se a diversos testes estatísticos. Os principais resultados demonstraram que são diversos os meios online e offline em que os consumidores se baseiam para fazer a sua decisão de escolha de alojamento, sendo um destes o Facebook, que apresenta uma grande representatividade. O word-of-mouth, contabilizado através das opiniões dos antigos clientes presentes em sites de avaliações e em redes sociais revela-se uma componente determinante no processo de recolha de informação sobre determinado alojamento e consequentemente influenciador na escolha de alojamento. Por último, verificou-se que o Facebook apresenta ter um papel decisivo no processo de decisão de escolha de alojamento turístico.

Energy Cooperation in Energy Harvesting Communication Systems

In energy harvesting communications, users transmit messages using energy harvested from nature. In such systems, transmission policies of the users need to be carefully designed according to the energy arrival profiles. When the energy management policies are optimized, the resulting performance of the system depends only on the energy arrival profiles. In this dissertation, we introduce and analyze the notion of energy cooperation in energy harvesting communications where users can share a portion of their harvested energy with the other users via wireless energy transfer. This energy cooperation enables us to control and optimize the energy arrivals at users to the extent possible. In the classical setting of cooperation, users help each other in the transmission of their data by exploiting the broadcast nature of wireless communications and the resulting overheard information. In contrast to the usual notion of cooperation, which is at the signal level, energy cooperation we introduce here is at the battery energy level. In a multi-user setting, energy may be abundant in one user in which case the loss incurred by transferring it to another user may be less than the gain it yields for the other user. It is this cooperation that we explore in this dissertation for several multi-user scenarios, where energy can be transferred from one user to another through a separate wireless energy transfer unit. We first consider the offline optimal energy management problem for several basic multi-user network structures with energy harvesting transmitters and one-way wireless energy transfer. In energy harvesting transmitters, energy arrivals in time impose energy causality constraints on the transmission policies of the users. In the presence of wireless energy transfer, energy causality constraints take a new form: energy can flow in time from the past to the future for each user, and from one user to the other at each time. This requires a careful joint management of energy flow in two separate dimensions, and different management policies are required depending on how users share the common wireless medium and interact over it. In this context, we analyze several basic multi-user energy harvesting network structures with wireless energy transfer. To capture the main trade-offs and insights that arise due to wireless energy transfer, we focus our attention on simple two- and three-user communication systems, such as the relay channel, multiple access channel and the two-way channel. Next, we focus on the delay minimization problem for networks. We consider a general network topology of energy harvesting and energy cooperating nodes. Each node harvests energy from nature and all nodes may share a portion of their harvested energies with neighboring nodes through energy cooperation. We consider the joint data routing and capacity assignment problem for this setting under fixed data and energy routing topologies. We determine the joint routing of energy and data in a general multi-user scenario with data and energy transfer. Next, we consider the cooperative energy harvesting diamond channel, where the source and two relays harvest energy from nature and the physical layer is modeled as a concatenation of a broadcast and a multiple access channel. Since the broadcast channel is degraded, one of the relays has the message of the other relay. Therefore, the multiple access channel is an extended multiple access channel with common data. We determine the optimum power and rate allocation policies of the users in order to maximize the end-to-end throughput of this system. Finally, we consider the two-user cooperative multiple access channel with energy harvesting users. The users cooperate at the physical layer (data cooperation) by establishing common messages through overheard signals and then cooperatively sending them. For this channel model, we investigate the effect of intermittent data arrivals to the users. We find the optimal offline transmit power and rate allocation policy that maximize the departure region. When the users can further cooperate at the battery level (energy cooperation), we find the jointly optimal offline transmit power and rate allocation policy together with the energy transfer policy that maximize the departure region.

Contributions to 3D Data Registration and Representation

Nowadays, new computers generation provides a high performance that enables to build computationally expensive computer vision applications applied to mobile robotics. Building a map of the environment is a common task of a robot and is an essential part to allow the robots to move through these environments. Traditionally, mobile robots used a combination of several sensors from different technologies. Lasers, sonars and contact sensors have been typically used in any mobile robotic architecture, however color cameras are an important sensor due to we want the robots to use the same information that humans to sense and move through the different environments. Color cameras are cheap and flexible but a lot of work need to be done to give robots enough visual understanding of the scenes. Computer vision algorithms are computational complex problems but nowadays robots have access to different and powerful architectures that can be used for mobile robotics purposes. The advent of low-cost RGB-D sensors like Microsoft Kinect which provide 3D colored point clouds at high frame rates made the computer vision even more relevant in the mobile robotics field. The combination of visual and 3D data allows the systems to use both computer vision and 3D processing and therefore to be aware of more details of the surrounding environment. The research described in this thesis was motivated by the need of scene mapping. Being aware of the surrounding environment is a key feature in many mobile robotics applications from simple robotic navigation to complex surveillance applications. In addition, the acquisition of a 3D model of the scenes is useful in many areas as video games scene modeling where well-known places are reconstructed and added to game systems or advertising where once you get the 3D model of one room the system can add furniture pieces using augmented reality techniques. In this thesis we perform an experimental study of the state-of-the-art registration methods to find which one fits better to our scene mapping purposes. Different methods are tested and analyzed on different scene distributions of visual and geometry appearance. In addition, this thesis proposes two methods for 3d data compression and representation of 3D maps. Our 3D representation proposal is based on the use of Growing Neural Gas (GNG) method. This Self-Organizing Maps (SOMs) has been successfully used for clustering, pattern recognition and topology representation of various kind of data. Until now, Self-Organizing Maps have been primarily computed offline and their application in 3D data has mainly focused on free noise models without considering time constraints. Self-organising neural models have the ability to provide a good representation of the input space. In particular, the Growing Neural Gas (GNG) is a suitable model because of its flexibility, rapid adaptation and excellent quality of representation. However, this type of learning is time consuming, specially for high-dimensional input data. Since real applications often work under time constraints, it is necessary to adapt the learning process in order to complete it in a predefined time. This thesis proposes a hardware implementation leveraging the computing power of modern GPUs which takes advantage of a new paradigm coined as General-Purpose Computing on Graphics Processing Units (GPGPU). Our proposed geometrical 3D compression method seeks to reduce the 3D information using plane detection as basic structure to compress the data. This is due to our target environments are man-made and therefore there are a lot of points that belong to a plane surface. Our proposed method is able to get good compression results in those man-made scenarios. The detected and compressed planes can be also used in other applications as surface reconstruction or plane-based registration algorithms. Finally, we have also demonstrated the goodness of the GPU technologies getting a high performance implementation of a CAD/CAM common technique called Virtual Digitizing.

Cybersex in portuguese chatrooms: A study of sexual behaviors related to online sex

The present article is about a particular form of sexual activity on the Internet: cybersex in chatrooms-in Portuguese by Portuguese people. This study aims to identify the reasons for engaging in cybersex on chats and the behavioral domains that characterize this activity. To carry out the study, we developed a self-report questionnaire that we made available on a website. The sample was collected online (n = 400) through the Portuguese Internet Relay Chat. Factor analyses revealed seven domain structures: (a) social skills, (b) preference for cybersex, (c) filter for a later date, (d) sex by phone, (e) fantasies, (f) using masks, and (g) impact on real relationships. We found a huge variety of sexual attitudes and behaviors connected to cybersex in chatrooms and the existence of two major trends: (a) people that use these chats as a starting place for offline relationships (online anonymity prevents the fear of rejection and social sanctions in real life), and (b) people who want and prefer online sex without any interest in further real contacts.

Augmented Dissent: The Affordances of ICTs for Citizen Protest (A Case Study of the Ukraine Euromaidan Protests of 2013-2014).

This dissertation research project uses the Euromaidan protests in Ukraine to inform and shape a theory of augmented dissent to help explain the complex ways in which protest participants guided by the political, social, and cultural contexts engage in dissent augmented by ICTs in a reality where both the physical and the digital are used in concert. The purpose of this research is to conceptualize the use and perception of ICTs in protest activity using the communicative affordances framework. Through a mixed-method research approach involving interviews with protest participants, as well as qualitative and thematic analysis of online content from social media pages of several key Euromaidan protest communities, the research project examines the role ICTs played in the information and media landscape during the Euromaidan protest. The findings of the online content analysis were used to inform the questions for the 59 semi-structured, open-ended interviews with Euromaidan protest participants in Ukraine and abroad. The research findings provide in-depth insights about how ICTs were used and perceived by protest participants, and their role as vehicles for information and civic media content. The study employs the theoretical framework of social media affordances to interpret the data gathered during the interviews and content analysis to better understand how digital media augmented citizens’ protest activity through affording them new possibilities for dissent, and how they made meaning of said protest activity as augmented by ICTs. The findings contribute towards shaping a theory of digitally augmented dissent that conceptualizes the complex relationship between citizens and ICTs during protest activity as an affordance-driven one, where online and offline tools and activity merge into a unified dissent space and extend or augment the possibilities for action in interesting, and sometimes unexpected ways. Such a conceptual model could inform broader theories about civic participation and digital activism in the post-Soviet world and beyond, as ICTs become an inseparable part of civic life.

Controle preditivo neural aplicado à processos petroquímicos

A pesquisa tem como objetivo desenvolver uma estrutura de controle preditivo neural, com o intuito de controlar um processo de pH, caracterizado por ser um sistema SISO (Single Input - Single Output). O controle de pH é um processo de grande importância na indústria petroquímica, onde se deseja manter constante o nível de acidez de um produto ou neutralizar o afluente de uma planta de tratamento de fluidos. O processo de controle de pH exige robustez do sistema de controle, pois este processo pode ter ganho estático e dinâmica nãolineares. O controlador preditivo neural envolve duas outras teorias para o seu desenvolvimento, a primeira referente ao controle preditivo e a outra a redes neurais artificiais (RNA s). Este controlador pode ser dividido em dois blocos, um responsável pela identificação e outro pelo o cálculo do sinal de controle. Para realizar a identificação neural é utilizada uma RNA com arquitetura feedforward multicamadas com aprendizagem baseada na metodologia da Propagação Retroativa do Erro (Error Back Propagation). A partir de dados de entrada e saída da planta é iniciado o treinamento offline da rede. Dessa forma, os pesos sinápticos são ajustados e a rede está apta para representar o sistema com a máxima precisão possível. O modelo neural gerado é usado para predizer as saídas futuras do sistema, com isso o otimizador calcula uma série de ações de controle, através da minimização de uma função objetivo quadrática, fazendo com que a saída do processo siga um sinal de referência desejado. Foram desenvolvidos dois aplicativos, ambos na plataforma Builder C++, o primeiro realiza a identificação, via redes neurais e o segundo é responsável pelo controle do processo. As ferramentas aqui implementadas e aplicadas são genéricas, ambas permitem a aplicação da estrutura de controle a qualquer novo processo

Physics-Based Modeling of Power System Components for the Evaluation of Low-Frequency Radiated Electromagnetic Fields

The low-frequency electromagnetic compatibility (EMC) is an increasingly important aspect in the design of practical systems to ensure the functional safety and reliability of complex products. The opportunities for using numerical techniques to predict and analyze system’s EMC are therefore of considerable interest in many industries. As the first phase of study, a proper model, including all the details of the component, was required. Therefore, the advances in EMC modeling were studied with classifying analytical and numerical models. The selected model was finite element (FE) modeling, coupled with the distributed network method, to generate the model of the converter’s components and obtain the frequency behavioral model of the converter. The method has the ability to reveal the behavior of parasitic elements and higher resonances, which have critical impacts in studying EMI problems. For the EMC and signature studies of the machine drives, the equivalent source modeling was studied. Considering the details of the multi-machine environment, including actual models, some innovation in equivalent source modeling was performed to decrease the simulation time dramatically. Several models were designed in this study and the voltage current cube model and wire model have the best result. The GA-based PSO method is used as the optimization process. Superposition and suppression of the fields in coupling the components were also studied and verified. The simulation time of the equivalent model is 80-100 times lower than the detailed model. All tests were verified experimentally. As the application of EMC and signature study, the fault diagnosis and condition monitoring of an induction motor drive was developed using radiated fields. In addition to experimental tests, the 3DFE analysis was coupled with circuit-based software to implement the incipient fault cases. The identification was implemented using ANN for seventy various faulty cases. The simulation results were verified experimentally. Finally, the identification of the types of power components were implemented. The results show that it is possible to identify the type of components, as well as the faulty components, by comparing the amplitudes of their stray field harmonics. The identification using the stray fields is nondestructive and can be used for the setups that cannot go offline and be dismantled

Analyse quantitative de la carrière criminelle des internautes effectuant du leurre d’enfants

Objectifs: L’objectif principal de ce mémoire consiste à comprendre les caractéristiques des carrières criminelles d’individus connus de la police pour avoir perpétré une infraction de leurre d’enfants sur Internet. Aussi, par une analyse typologique à l’aide des antécédents criminels, il sera possible d’établir une typologie d’individus ayant leurré des enfants sur Internet. Également, il sera question de vérifier s’il y a un lien entre les caractéristiques des antécédents criminels de ces individus sur la perpétration de l’agression sexuelle hors ligne. Méthodologie: Provenant de données officielles de la communauté policière du Québec, l’échantillon comprend les parcours de criminels ayant perpétré une infraction de leurre d’enfants sur Internet. Des analyses descriptives en lien avec les différents paramètres de la carrière criminelle seront effectuées. Ensuite, des tests de moyenne et une analyse de régression Cox permettront de vérifier la présence ou non d’un lien statistique entre les caractéristiques des antécédents criminels des individus connus de la police pour leurre d’enfants sur Internet et le passage à l’acte physique. Résultats: Les analyses ont montré que la majorité des sujets n’avaient aucun antécédent judiciaire. Pour la plupart, le leurre d’enfants est le crime le plus grave perpétré au cours de leur carrière criminelle. Trois catégories d’individus ont été décelées : les amateurs, les spécialistes et les généralistes. Ce sont les individus polymorphes ayant une carrière criminelle plus grave et plus longue qui sont portés à agresser sexuellement avant le leurre. Cependant, ce sont des individus spécialisés ayant une importante proportion de délits sexuels dans leurs antécédents criminels qui ont plus de chance d’agresser sexuellement suite à l’exploitation sexuelle sur Internet.

An investigation of two real time machine learning techniques that could enhance the adaptability of game AI agents

Developers strive to create innovative Artificial Intelligence (AI) behaviour in their games as a key selling point. Machine Learning is an area of AI that looks at how applications and agents can be programmed to learn their own behaviour without the need to manually design and implement each aspect of it. Machine learning methods have been utilised infrequently within games and are usually trained to learn offline before the game is released to the players. In order to investigate new ways AI could be applied innovatively to games it is wise to explore how machine learning methods could be utilised in real-time as the game is played, so as to allow AI agents to learn directly from the player or their environment. Two machine learning methods were implemented into a simple 2D Fighter test game to allow the agents to fully showcase their learned behaviour as the game is played. The methods chosen were: Q-Learning and an NGram based system. It was found that N-Grams and QLearning could significantly benefit game developers as they facilitate fast, realistic learning at run-time.

Analyse quantitative de la carrière criminelle des internautes effectuant du leurre d’enfants

Objectifs: L’objectif principal de ce mémoire consiste à comprendre les caractéristiques des carrières criminelles d’individus connus de la police pour avoir perpétré une infraction de leurre d’enfants sur Internet. Aussi, par une analyse typologique à l’aide des antécédents criminels, il sera possible d’établir une typologie d’individus ayant leurré des enfants sur Internet. Également, il sera question de vérifier s’il y a un lien entre les caractéristiques des antécédents criminels de ces individus sur la perpétration de l’agression sexuelle hors ligne. Méthodologie: Provenant de données officielles de la communauté policière du Québec, l’échantillon comprend les parcours de criminels ayant perpétré une infraction de leurre d’enfants sur Internet. Des analyses descriptives en lien avec les différents paramètres de la carrière criminelle seront effectuées. Ensuite, des tests de moyenne et une analyse de régression Cox permettront de vérifier la présence ou non d’un lien statistique entre les caractéristiques des antécédents criminels des individus connus de la police pour leurre d’enfants sur Internet et le passage à l’acte physique. Résultats: Les analyses ont montré que la majorité des sujets n’avaient aucun antécédent judiciaire. Pour la plupart, le leurre d’enfants est le crime le plus grave perpétré au cours de leur carrière criminelle. Trois catégories d’individus ont été décelées : les amateurs, les spécialistes et les généralistes. Ce sont les individus polymorphes ayant une carrière criminelle plus grave et plus longue qui sont portés à agresser sexuellement avant le leurre. Cependant, ce sont des individus spécialisés ayant une importante proportion de délits sexuels dans leurs antécédents criminels qui ont plus de chance d’agresser sexuellement suite à l’exploitation sexuelle sur Internet.