Daniela M. Romano

An Analysis of Usage of Different Types of Visualisation Media within a Collaborative Planning Workshop Environment

Within the planning process, there is a recent trend to engage with stakeholders. Traditionally, visualisation media such as plans, sections, and physical models have been used to aid communication of planning proposals, yet technological advances now allow for virtual interactive, three-dimensional visualisations of proposals to be created. It is unclear whether these new technologies will usurp or augment the more traditional media. In an experimental setting, a set of participants in a collaborative planning workshop were introduced to a range of different visualisation media for a riverside flood-defence proposal and asked to discuss the proposal. Video recordings were made of the workshop and a questionnaire was completed by each participant. A method for capturing the time usage of each media type is presented. This shows that plans and interactive eye-level walkthroughs were the most used media types, but that user-based assessment of media might not match observed usage. These results lead to a discussion about visualisation media that should be created and further research to support the participatory planning process.

Agent-based Large Scale Simulation of Pedestrians With Adaptive Realistic Navigation Vector Fields

A large scale pedestrian simulation method, implemented with an agent based modelling paradigm, is presented within this paper. It allows rapid prototyping and real-time modifications, suitable for quick generation and testing of the viability of pedestrian movement in urban environments. The techniques described for pedestrian simulation make use of parallel processing through graphics card hardware allowing simulation scales to far exceed those of serial frameworks for agent based modelling. The simulation has been evaluated through benchmarking of the performances manipulating population size, navigation grid, and averaged simulation steps. The results demonstrate that this is a robust and scalable method for implementing pedestrian navigation behaviour. Furthermore an algorithm for generating smooth and realistic pedestrian navigation paths that works well in both small and large spaces is presented. An adaptive smoothing function has been utilised to optimise the path used by pedestrian agents to navigate around in a complex dynamic environment. Optimised and un-optimised vectors maps obtained by applying or not such function are compared, and the results show that the optimized path generates a more realistic flow.

A Serious Game for Traffic Accident Investigators.

In Dubai, traffic accidents kill one person every 37 hours and injure one person every 3 hours. Novice traffic accident investigators in the Dubai police force are expected to ‘learn by doing’ in this intense environment. Currently, they use no alternative to the real world in order to practice. This paper argues for the use of an alternative learning environment, where the novice investigator can feel safe in exploring different investigative routes without fear for the consequences. The paper describes a game‐based learning environment that has been built using a game engine. The effectiveness of this environment in improving the performance of traffic accident investigators is also presented. Fifty‐six policemen took part in an experiment involving a virtual traffic accident scenario. They were divided into two groups: novices (0 to 2 years experience) and experienced personnel (with more than 2 years experience). The experiment revealed significant performance improvements in both groups, with the improvement reported in novices significantly higher than the one reported in experienced personnel. Both groups showed significant differences in navigational patterns (e.g. distances travelled and time utilization) between the two training sessions.

Template-Driven Agent-Based Modeling and Simulation with CUDA

Publisher Summary This chapter describes a number of key techniques that are used to implement a flexible agent-based modeling (ABM) framework entirely on the GPU in CUDA. Performance rates, which is better than high-performance computing (HPC) clusters, can easily be achieved. Agent-based modeling is a technique for computational simulation of complex interacting systems through the specification of the behavior of a number of autonomous individuals acting simultaneously. The focus on individuals is considerably more computationally demanding than top–down system-level simulation, but provides a natural and flexible environment for studying systems demonstrating emergent behavior. Massive population sizes can be simulated, far exceeding those that can be computed (in reasonable time constraints) within traditional ABM toolkits. The use of data parallel methods ensures that the techniques used within this chapter are applicable to emerging multicore and data parallel architectures that will continue to increase their level of parallelism to improve performance. The concept of a flexible architecture is built around the use of a neutral modeling language (XML) for agents. The technique of template-driven dynamic code generation specifically using XML template processing is also general enough to be effective in other domains seeking to solve the issue of portability and abstraction of modeling logic from simulation code.

Using computational modeling to investigate sperm navigation and behavior in the female reproductive tract

The processes by which individual sperm cells navigate the length and complexity of the female reproductive tract and then reach and fertilize the oocyte is fascinating. Numerous complex processes potentially influence the transport of spermatozoa within the tract, resulting in a regulated supply of spermatozoa to the oocytes at the site of fertilization. Despite significant differences between species, breeds, and individuals, these processes converge to ensure that a sufficient number of high quality spermatozoa reach the oocytes, resulting in successful fertilization without a significant risk of polyspermy. Different factors, such as the physical complexity of the oviductal environment, changing swimming patterns, capacitation, chemotactic and thermotactic attraction, attachment and detachment from the oviductal epithelium, interactions with local oviductal secretions, individual variations in spermatozoa and subpopulations, peristaltic contractions, and the movement of fluid have all been theorized to influence the transport of spermatozoa to the site of fertilization. However, the predominance of each factor is not fully understood. Computational modeling provides a useful method for combining knowledge about the individual processes in complex systems to help understand the relative significance of each factor. The process of constructing and validating an agent-based computational model of sperm movement and transport within the oviductal environment is described in this report. Spermatozoa are modeled as individual cells with a set of behavioral rules defining how they interact with their local environment and regulate their internal state. The inclusion or potential exclusion of each factor is discussed, along with problems identifying parameters and defining behavioral rules from available literature. Finally, the benefits and limitations of the model are described.

Exploring the use of a respiratory-computer interface for game interaction

Interaction techniques play a fundamental role in the success of video games. An example of this success is the Nintendo Wii console. Its novel interaction method based on motion-sensing technology has attracted gamers of different generations. In this paper, real-time processing of physiological signals is presented as an alternative approach for natural and intuitive communication with computer applications. Particularly, respiration measures are used as an innovative technique for game interaction. A respiratory-computer interface (RCI) has been designed and evaluated with the aid of an ad-hoc mini-game where the players participated in a race to blow up 3D virtual balloons. Twenty-four participants evaluated attributes of the interface such as: usability, learnability, satisfaction and immersion. The results show that the RCI can be very useful as a natural and involving game interface.

Game logic portability

Many game engines integrate the game logic with the graphics engine. In this paper we separate the two, thus making the logic portable between game engines. In our architecture the logic is represented as an ontology and a set of rules for a particular application domain. A mediator with an embedded rules-engine links the logic to a suitable game engine.We demonstrate our architecture in two ways. First, we show a traffic accident scenario running on two different game engines, with a separate mediator for each engine. The logic type is smart-terrain logic, with participants triggering events based on interaction and proximity tests. In the second demonstration (a simple first-person shooting game) we show the extensibility and performance of the architecture to control non-player characters quickly manoeuvring using proximity tests and waypoints.

Constructing Complex 3D Biological Environments from Medical Imaging Using High Performance Computing

Extracting information about the structure of biological tissue from static image data is a complex task requiring computationally intensive operations. Here, we present how multicore CPUs and GPUs have been utilized to extract information about the shape, size, and path followed by the mammalian oviduct, called the fallopian tube in humans, from histology images, to create a unique but realistic 3D virtual organ. Histology images were processed to identify the individual cross sections and determine the 3D path that the tube follows through the tissue. This information was then related back to the histology images, linking the 2D cross sections with their corresponding 3D position along the oviduct. A series of linear 2D spline cross sections, which were computationally generated for the length of the oviduct, were bound to the 3D path of the tube using a novel particle system technique that provides smooth resolution of self-intersections. This results in a unique 3D model of the oviduct, which is grounded in reality. The GPU is used for the processor intensive operations of image processing and particle physics based simulations, significantly reducing the time required to generate a complete model.

Computational modelling of maternal interactions with spermatozoa: potentials and prospects

Understanding the complex interactions between gametes, embryos and the maternal tract is required knowledge for combating infertility and developing new methods of contraception. Here we present some main aspects of spermatozoa interactions with the mammalian oviduct before fertilisation and discuss how computational modelling can be used as an invaluable aid to experimental investigation in this field. A complete predictive computational model of gamete and embryo interactions with the female reproductive tract is a long way off. However, the enormity of this task should not discourage us from working towards it. Computational modelling allows us to investigate aspects of maternal communication with gametes and embryos, which are financially, ethically or practically difficult to look at experimentally. In silico models of maternal communication with gametes and embryos can be used as tools to complement in vivo experiments, in the same way as in vitro and in situ models.

Bio-Affective Computer Interface for Game Interaction

Affective bio-feedback can be an important instrument to enhance the game experience. Several studies have provided evidence of the usefulness of physiological signals for affective gaming; however, due to the limited knowledge about the distinctive autonomic signatures for every emotion, the pattern matching models employed are limited in the number of emotions they are able to classify. This paper presents a bio-affective gaming interface BAGI that can be used to customize a game experience according to the players emotional response. Its architecture offers important characteristics for gaming that are important because they make possible the reusability of previous findings and the inclusion of new models to the system. In order to prove the effectiveness of BAGI, two different types of neural networks have been trained to recognize emotions. They were incorporated into the system to customize, in real-time, the computer wallpaper according to the emotion experienced by the user. Best results were obtained with a probabilistic neural network with accuracy results of 84.46% on the training data and 78.38% on the validation for new independent data sets.