This paper describes a methodology based on human judgments of memory awareness states for assessing the simulation fidelity of a virtual environment (VE) in relation to its real scene counterpart. To demonstrate the distinction between task performance-based approaches and additional human evaluation of cognitive awareness states, a photorealistic VE was created. Resulting scenes displayed on a headmounted display (HMD) with or without head tracking and desktop monitor were then compared to the real-world task situation they represented, investigating spatial memory after exposure. Participants described how they completed their spatial recollections by selecting one of four choices of awareness states after retrieval in an initial test and a retention test a week after exposure to the environment. These reflected the level of visual mental imagery involved during retrieval, the familiarity of the recollection and also included guesses, even if informed. Experimental results revealed variations in the distribution of participants' awareness states across conditions while, in certain cases, task performance failed to reveal any. Experimental conditions that incorporated head tracking were not associated with visually induced recollections. Generally, simulation of task performance does not necessarily lead to simulation of the awareness states involved when completing a memory task. The general premise of this research focuses on how tasks are achieved, rather than only on what is achieved. The extent to which judgments of human memory recall, memory awareness states, and presence in the physical and VE are similar provides a fidelity metric of the simulation in question.

In a virtual environment (VE), efficient techniques are often needed to economize on rendering computation without compromising the information transmitted. The reported experiments devise a functional fidelity metric by exploiting research on memory schemata. According to the proposed measure, similar information would be transmitted across synthetic and real-world scenes depicting a specific schema. This would ultimately indicate which areas in a VE could be rendered in lower quality without affecting information uptake. We examine whether computationally more expensive scenes of greater visual fidelity affect memory performance after exposure to immersive VEs, or whether they are merely more aesthetically pleasing than their diminished visual quality counterparts. Results indicate that memory schemata function in VEs similar to real-world environments. "Highlevel" visual cognition related to late visual processing is unaffected by ubiquitous graphics manipulations such as polygon count and depth of shadow rendering; "normal" cognition operates as long as the scenes look acceptably realistic. However, when the overall realism of the scene is greatly reduced, such as in wireframe, then visual cognition becomes abnormal. Effects that distinguish schema-consistent from schema-inconsistent objects change because the whole scene now looks incongruent. We have shown that this effect is not due to a failure of basic recognition.

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We describe the design and implementation of Cells, a novel multi-tenanted virtual infrastructure service. Cells has the unique property of being self-hosting: it operates its own management system within one of the tenant virtual infrastructures that it manages and therefore benefits from the same security, flexibility and scalability as other tenant services. Cells is also differentiated by its declarative interface for infrastructure configuration, and its fine-grained control of network and storage connections within and between tenant infrastructures.

Interactive visual exploration techniques (IVET) such as those advocated by Shneiderman and extreme scale visual analytics have successfully increased our understanding of a variety of domains that produce huge amounts of complex data. In spite of their complexity, IT infrastructures have not benefited from the application of IVET techniques. Loom is inspired in IVET techniques and builds on them to tame increasing complexity in IT infrastructure management systems guaranteeing interactive response times and integrating key elements for IT management: Relationships between managed entities coming from different IT management subsystems, alerts and actions (or reconfigurations) of the IT setup. The Loom system builds on two main pillars: 1) a multiplex graph spanning data from different ITIMs; and 2) a novel visualisation arrangement: the Loom "Thread" visualisation model. We have tested this in a number of real-world applications, showing that Loom can handle million of entities without losing information, with minimum context switching, and offering better performance than other relational/graph-based systems. This ensures interactive response times (few seconds as 90th percentile). The value of the "Thread" visualisation model is shown in a qualitative analysis of users' experiences with Loom.