68 resultados para applied game
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ABSTRACT: BACKGROUND: The main objective of our study was to assess the impact of a board game on smoking status and smoking-related variables in current smokers. To accomplish this objective, we conducted a randomized controlled trial comparing the game group with a psychoeducation group and a waiting-list control group. METHODS: The following measures were performed at participant inclusion, as well as after a 2-week and a 3-month follow-up period: "Attitudes Towards Smoking Scale" (ATS-18), "Smoking Self-Efficacy Questionnaire" (SEQ-12), "Attitudes Towards Nicotine Replacement Therapy" scale (ANRT-12), number of cigarettes smoked per day, stages of change, quit attempts, and smoking status. Furthermore, participants were assessed for concurrent psychiatric disorders and for the severity of nicotine dependence with the Fagerström Test for Nicotine Dependence (FTND). RESULTS: A time × group effect was observed for subscales of the ANRT-12, ATS-18 and SEQ-12, as well as for the number of cigarettes smoked per day. At three months follow-up, compared to the participants allocated to the waiting list group, those on Pick-Klop group were less likely to remain smoker.Outcomes at 3 months were not predicted by gender, age, FTND, stage of change, or psychiatric disorders at inclusion. CONCLUSIONS: The board game seems to be a good option for smokers. The game led to improvements in variables known to predict quitting in smokers. Furthermore, it increased smoking-cessation rates at 3-months follow-up. The game is also an interesting alternative for smokers in the precontemplation stage.
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Game theory is a branch of applied mathematics used to analyze situation where two or more agents are interacting. Originally it was developed as a model for conflicts and collaborations between rational and intelligent individuals. Now it finds applications in social sciences, eco- nomics, biology (particularly evolutionary biology and ecology), engineering, political science, international relations, computer science, and philosophy. Networks are an abstract representation of interactions, dependencies or relationships. Net- works are extensively used in all the fields mentioned above and in many more. Many useful informations about a system can be discovered by analyzing the current state of a network representation of such system. In this work we will apply some of the methods of game theory to populations of agents that are interconnected. A population is in fact represented by a network of players where one can only interact with another if there is a connection between them. In the first part of this work we will show that the structure of the underlying network has a strong influence on the strategies that the players will decide to adopt to maximize their utility. We will then introduce a supplementary degree of freedom by allowing the structure of the population to be modified along the simulations. This modification allows the players to modify the structure of their environment to optimize the utility that they can obtain.
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Basé sur les psychothérapies cognitives des psychoses, Michael's Game est un jeu de cartes qui propose à des patients de s'entraîner au raisonnement par hypothèses. Après une présentation théorique du jeu (cadre, déroulement, bénéfices attendus pour les patients...) les auteurs illustrent avec des réactions d'un groupe de patients.
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Compte rendu de l'exposition « Game Story. Une histoire du jeu vidéo » qui s'est tenue au Grand Palais à Paris du 10 novembre 2011 au 9 janvier 2012, envisagée à partir du champ de l'histoire et de la théorie du cinéma en termes de discours historique sur un « nouveau média » ainsi que dans une optique intermédiale.
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The coverage and volume of geo-referenced datasets are extensive and incessantly¦growing. The systematic capture of geo-referenced information generates large volumes¦of spatio-temporal data to be analyzed. Clustering and visualization play a key¦role in the exploratory data analysis and the extraction of knowledge embedded in¦these data. However, new challenges in visualization and clustering are posed when¦dealing with the special characteristics of this data. For instance, its complex structures,¦large quantity of samples, variables involved in a temporal context, high dimensionality¦and large variability in cluster shapes.¦The central aim of my thesis is to propose new algorithms and methodologies for¦clustering and visualization, in order to assist the knowledge extraction from spatiotemporal¦geo-referenced data, thus improving making decision processes.¦I present two original algorithms, one for clustering: the Fuzzy Growing Hierarchical¦Self-Organizing Networks (FGHSON), and the second for exploratory visual data analysis:¦the Tree-structured Self-organizing Maps Component Planes. In addition, I present¦methodologies that combined with FGHSON and the Tree-structured SOM Component¦Planes allow the integration of space and time seamlessly and simultaneously in¦order to extract knowledge embedded in a temporal context.¦The originality of the FGHSON lies in its capability to reflect the underlying structure¦of a dataset in a hierarchical fuzzy way. A hierarchical fuzzy representation of¦clusters is crucial when data include complex structures with large variability of cluster¦shapes, variances, densities and number of clusters. The most important characteristics¦of the FGHSON include: (1) It does not require an a-priori setup of the number¦of clusters. (2) The algorithm executes several self-organizing processes in parallel.¦Hence, when dealing with large datasets the processes can be distributed reducing the¦computational cost. (3) Only three parameters are necessary to set up the algorithm.¦In the case of the Tree-structured SOM Component Planes, the novelty of this algorithm¦lies in its ability to create a structure that allows the visual exploratory data analysis¦of large high-dimensional datasets. This algorithm creates a hierarchical structure¦of Self-Organizing Map Component Planes, arranging similar variables' projections in¦the same branches of the tree. Hence, similarities on variables' behavior can be easily¦detected (e.g. local correlations, maximal and minimal values and outliers).¦Both FGHSON and the Tree-structured SOM Component Planes were applied in¦several agroecological problems proving to be very efficient in the exploratory analysis¦and clustering of spatio-temporal datasets.¦In this thesis I also tested three soft competitive learning algorithms. Two of them¦well-known non supervised soft competitive algorithms, namely the Self-Organizing¦Maps (SOMs) and the Growing Hierarchical Self-Organizing Maps (GHSOMs); and the¦third was our original contribution, the FGHSON. Although the algorithms presented¦here have been used in several areas, to my knowledge there is not any work applying¦and comparing the performance of those techniques when dealing with spatiotemporal¦geospatial data, as it is presented in this thesis.¦I propose original methodologies to explore spatio-temporal geo-referenced datasets¦through time. Our approach uses time windows to capture temporal similarities and¦variations by using the FGHSON clustering algorithm. The developed methodologies¦are used in two case studies. In the first, the objective was to find similar agroecozones¦through time and in the second one it was to find similar environmental patterns¦shifted in time.¦Several results presented in this thesis have led to new contributions to agroecological¦knowledge, for instance, in sugar cane, and blackberry production.¦Finally, in the framework of this thesis we developed several software tools: (1)¦a Matlab toolbox that implements the FGHSON algorithm, and (2) a program called¦BIS (Bio-inspired Identification of Similar agroecozones) an interactive graphical user¦interface tool which integrates the FGHSON algorithm with Google Earth in order to¦show zones with similar agroecological characteristics.
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Games are powerful and engaging. On average, one billion people spend at least 1 hour a day playing computer and videogames. This is even more true with the younger generations. Our students have become the < digital natives >, the < gamers >, the < virtual generation >. Research shows that those who are most at risk for failure in the traditional classroom setting, also spend more time than their counterparts, using video games. They might strive, given a different learning environment. Educators have the responsibility to align their teaching style to these younger generation learning styles. However, many academics resist the use of computer-assisted learning that has been "created elsewhere". This can be extrapolated to game-based teaching: even if educational games were more widely authored, their adoption would still be limited to the educators who feel a match between the authored games and their own beliefs and practices. Consequently, game-based teaching would be much more widespread if teachers could develop their own games, or at least customize them. Yet, the development and customization of teaching games are complex and costly. This research uses a design science methodology, leveraging gamification techniques, active and cooperative learning theories, as well as immersive sandbox 3D virtual worlds, to develop a method which allows management instructors to transform any off-the-shelf case study into an engaging collaborative gamified experience. This method is applied to marketing case studies, and uses the sandbox virtual world of Second Life. -- Les jeux sont puissants et motivants, En moyenne, un milliard de personnes passent au moins 1 heure par jour jouer à des jeux vidéo sur ordinateur. Ceci se vérifie encore plus avec les jeunes générations, Nos étudiants sont nés à l'ère du numérique, certains les appellent des < gamers >, d'autres la < génération virtuelle >. Les études montrent que les élèves qui se trouvent en échec scolaire dans les salles de classes traditionnelles, passent aussi plus de temps que leurs homologues à jouer à des jeux vidéo. lls pourraient potentiellement briller, si on leur proposait un autre environnement d'apprentissage. Les enseignants ont la responsabilité d'adapter leur style d'enseignement aux styles d'apprentissage de ces jeunes générations. Toutefois, de nombreux professeurs résistent lorsqu'il s'agit d'utiliser des contenus d'apprentissage assisté par ordinateur, développés par d'autres. Ceci peut être extrapolé à l'enseignement par les jeux : même si un plus grand nombre de jeux éducatifs était créé, leur adoption se limiterait tout de même aux éducateurs qui perçoivent une bonne adéquation entre ces jeux et leurs propres convictions et pratiques. Par conséquent, I'enseignement par les jeux serait bien plus répandu si les enseignants pouvaient développer leurs propres jeux, ou au moins les customiser. Mais le développement de jeux pédagogiques est complexe et coûteux. Cette recherche utilise une méthodologie Design Science pour développer, en s'appuyant sur des techniques de ludification, sur les théories de pédagogie active et d'apprentissage coopératif, ainsi que sur les mondes virtuels immersifs < bac à sable > en 3D, une méthode qui permet aux enseignants et formateurs de management, de transformer n'importe quelle étude de cas, provenant par exemple d'une centrale de cas, en une expérience ludique, collaborative et motivante. Cette méthode est appliquée aux études de cas Marketing dans le monde virtuel de Second Life.
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Melt-rock reaction in the upper mantle is recorded in a variety of ultramafic rocks and is an important process in modifying melt composition on its way from the source region towards the surface. This experimental study evaluates the compositional variability of tholeiitic basalts upon reaction with depleted peridotite at uppermost-mantle conditions. Infiltration-reaction processes are simulated by employing a three-layered set-up: primitive basaltic powder ('melt layer') is overlain by a 'peridotite layer' and a layer of vitreous carbon spheres ('melt trap'). Melt from the melt layer is forced to move through the peridotite layer into the melt trap. Experiments were conducted at 0.65 and 0.8 GPa in the temperature range 1,170-1,290 degrees C. In this P-T range, representing conditions encountered in the transition zone (thermal boundary layer) between the asthenosphere and the lithosphere underneath oceanic spreading centres, the melt is subjected to fractionation, and the peridotite is partially melting (T (s) similar to 1,260 degrees C). The effect of reaction between melt and peridotite on the melt composition was investigated across each experimental charge. Quenched melts in the peridotite layers display larger compositional variations than melt layer glasses. A difference between glasses in the melt and peridotite layer becomes more important at decreasing temperature through a combination of enrichment in incompatible elements in the melt layer and less efficient diffusive equilibration in the melt phase. At 1,290A degrees C, preferential dissolution of pyroxenes enriches the melt in silica and dilutes it in incompatible elements. Moreover, liquids become increasingly enriched in Cr(2)O(3) at higher temperatures due to the dissolution of spinel. Silica contents of liquids decrease at 1,260 degrees C, whereas incompatible elements start to concentrate in the melt due to increasing levels of crystallization. At the lowest temperatures investigated, increasing alkali contents cause silica to increase as a consequence of reactive fractionation. Pervasive percolation of tholeiitic basalt through an upper-mantle thermal boundary layer can thus impose a high-Si 'low-pressure' signature on MORB. This could explain opx + plag enrichment in shallow plagioclase peridotites and prolonged formation of olivine gabbros.
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This paper presents a new non parametric atlas registration framework, derived from the optical flow model and the active contour theory, applied to automatic subthalamic nucleus (STN) targeting in deep brain stimulation (DBS) surgery. In a previous work, we demonstrated that the STN position can be predicted based on the position of surrounding visible structures, namely the lateral and third ventricles. A STN targeting process can thus be obtained by registering these structures of interest between a brain atlas and the patient image. Here we aim to improve the results of the state of the art targeting methods and at the same time to reduce the computational time. Our simultaneous segmentation and registration model shows mean STN localization errors statistically similar to the most performing registration algorithms tested so far and to the targeting expert's variability. Moreover, the computational time of our registration method is much lower, which is a worthwhile improvement from a clinical point of view.
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Using a new dynamical network model of society in which pairwise interactions are weighted according to mutual satisfaction, we show that cooperation is the norm in the hawks-doves game when individuals are allowed to break ties with undesirable neighbors and to make new acquaintances in their extended neighborhood. Moreover, cooperation is robust with respect to rather strong strategy perturbations. We also discuss the empirical structure of the emerging networks, and the reasons that allow cooperators to thrive in the population. Given the metaphorical importance of this game for social interaction, this is an encouraging positive result as standard theory for large mixing populations prescribes that a certain fraction of defectors must always exist at equilibrium.