High-resolution venography of the brain using magnetic resonance imaging

The purpose of this study was to evaluate a non-flow related magnetic resonance imaging method to visualize small veins independent of arteries in the human brain. A long TE, high-resolution 3D gradient echo MR acquisition was used to highlight venous information. The method is based on the paramagnetic property of deoxyhemoglobin and the resulting phase difference between veins and brain parenchyma at long echo times. The MR magnitude images were masked with a phase mask filter to enhance small structure visibility.. Venous information down to sub-pixel vessel diameters of several hundred microns is visible. Venous data are displayed in an angiographic manner using a minimum intensity projection algorithm. Both superficial veins and deep white matter veins are visible. The method has been successfully applied in volunteers. Preliminary results in patients with cerebral arteriovenous malformations indicate its potential in clinical applications. The proposed method is easy to implement and does not require administration of a contrast agent or application of specially designed rf pulses to highlight the veins. Rather it exploits the intrinsic magnetic properties (BOLD-effect) and the prolonged T ^_2* of venous blood. The method may be of diagnostic potential in the assessment of arteriovenous malformations or other vascular venous lesions. © 1998 Elsevier Science B.V. All rights reserved.     

In situ ray tracing and computational steering for interactive blood flow simulation

Recent algorithm and hardware developments have significantly improved our capability to interactively visualise time-varying flow fields. However, when visualising very large dynamically varying datasets interactively there are still limitations in the scalability and efficiency of these methods. Here we present a rendering pipeline which employs an efficient in situ ray tracing technique to visualise flow fields as they are simulated. The ray casting approach is particularly well suited for the visualisation of large and sparse time-varying datasets, where it is capable of rendering fluid flow fields at high image resolutions and at interactive frame rates on a single multi-core processor using OpenMP. The parallel implementation of our in situ visualisation method relies on MPI, requires no specialised hardware support, and employs the same underlying spatial decomposition as the fluid simulator. The visualisation pipeline allows the user to operate on a commodity computer and explore the simulation output interactively. Our simulation environment incorporates numerous features that can be utilised in a wide variety of research contexts.     

Semantic fusion of laser and vision in pedestrian detection

Fusion of laser and vision in object detection has been accomplished by two main approaches: (1) independent integration of sensor-driven features or sensor-driven classifiers, or (2) a region of interest (ROI) is found by laser segmentation and an image classifier is used to name the projected ROI. Here, we propose a novel fusion approach based on semantic information, and embodied on many levels. Sensor fusion is based on spatial relationship of parts-based classifiers, being performed via a Markov logic network. The proposed system deals with partial segments, it is able to recover depth information even if the laser fails, and the integration is modeled through contextual information—characteristics not found on previous approaches. Experiments in pedestrian detection demonstrate the effectiveness of our method over data sets gathered in urban scenarios.     

Experimental evaluation of pheromone models in ACOPlan

In this paper the system ACOPlan for planning with non uniform action cost is introduced and analyzed. ACOPlan is a planner based on the ant colony optimization framework, in which a colony of planning ants searches for near optimal solution plans with respect to an overall plan cost metric. This approach is motivated by the strong similarity between the process used by artificial ants to build solutions and the methods used by state?Cbased planners to search solution plans. Planning ants perform a stochastic and heuristic based search by interacting through a pheromone model. The proposed heuristic and pheromone models are presented and compared through systematic experiments on benchmark planning domains. Experiments are also provided to compare the quality of ACOPlan solution plans with respect to state of the art satisficing planners. The analysis of the results confirm the good performance of the Action?CAction pheromone model and points out the promising performance of the novel Fuzzy?CLevel?CAction pheromone model. The analysis also suggests general principles for designing performant pheromone models for planning and further extensions of ACOPlan to other optimization models.     

Robust model selection with flexible trimming

The forward search provides data-driven flexible trimming of a C_p statistic for the choice of regression models that reveals the effect of outliers on model selection. An informed robust model choice follows. Even in small samples, the statistic has a null distribution indistinguishable from an F distribution. Limits on acceptable values of the C_p statistic follow. Two examples of widely differing size are discussed. A powerful graphical tool is the generalized candlestick plot, which summarizes the information on all forward searches and on the choice of models. A comparison is made with the use of M-estimation in robust model choice.     

Exploring sociality and engagement in play through game-control distribution

This study explores how distributing the controls of a video game among multiple players affects the sociality and engagement experienced in game play. A video game was developed in which the distribution of game controls among the players could be varied, thereby affecting the abilities of the individual players to control the game. An experiment was set up in which eight groups of three players were asked to play the video game while the distribution of the game controls was increased in three steps. After each playing session, the players’ experiences of sociality and engagement were assessed using questionnaires. The results showed that distributing game control among the players increased the level of experienced sociality and reduced the level of experienced control. The game in which the controls were partly distributed led to the highest levels of experienced engagement, because the game allowed social play while still giving the players a sense of autonomy. The implications for interaction design are discussed.     

Sensitivity analysis of the rice model WARM in Europe: Exploring the effects of different locations,climates and methods of analysis on model sensitivity to crop parameters

Sensitivity analysis studies how the variation in model outputs can be due to different sources of variation. This issue is addressed, in this study, as an application of sensitivity analysis techniques to a crop model in the Mediterranean region. In particular, an application of Morris and Sobol' sensitivity analysis methods to the rice model WARM is presented. The output considered is aboveground biomass at maturity, simulated at five rice districts of different countries (France, Greece, Italy, Portugal, and Spain) for years characterized by low, intermediate, and high continentality. The total effect index of Sobol' (that accounts for the total contribution to the output variation due a given parameter) and two Morris indices (mean μ and standard deviation σ of the ratios output changes/parameter variations) were used as sensitivity metrics. Radiation use efficiency (RUE), optimum temperature (T_opt), and leaf area index at emergence (LAI_ini) ranked in most of the combinations site × year as first, second and third most relevant parameters. Exceptions were observed, depending on the sensitivity method (e.g. LAI_ini resulted not relevant by the Morris method), or site-continentality pattern (e.g. with intermediate continentality in Spain, LAI_ini and T_opt were second and third ranked; with low continentality in Portugal, RUE was outranked by T_opt). Low σ values associated with the most relevant parameters indicated limited parameter interactions. The importance of sensitivity analyses by exploring site × climate combinations is discussed as pre-requisite to evaluate either novel crop-modelling approaches or the application of known modelling solutions to conditions not explored previously. The need of developing tools for sensitivity analysis within the modelling environment is also emphasized.     

Piavca: a framework for heterogeneous interactions with virtual characters

This paper presents a virtual character animation system for real- time multimodal interaction in an immersive virtual reality setting. Human to human interaction is highly multimodal, involving features such as verbal language, tone of voice, facial expression, gestures and gaze. This multimodality means that, in order to simulate social interaction, our characters must be able to handle many different types of interaction and many different types of animation, simultaneously. Our system is based on a model of animation that represents different types of animations as instantiations of an abstract function representation. This makes it easy to combine different types of animation. It also encourages the creation of behavior out of basic building blocks, making it easy to create and configure new behaviors for novel situations. The model has been implemented in Piavca, an open source character animation system.