Virtual integration of temporal and conflicting information

This paper is presenting a way of integrating conflicting temporal information from multiple information providers considering a property-based resolution. The properties considered in this paper are the time and uncertainty because of conflicting information providers. The property based resolution requires a flexible query mechanism, where answers are considered as bounds, taking into account the tendency of things to occur and also the might happen ability of things. Finally some attention is paid to a database environment with non-static members

Acquisition of ownership illusion with self-disownership in neurological patients

The multisensory regions in frontoparietal cortices play a crucial role in the sense of body and self. Disrupting this sense may lead to a feeling of disembodiment, or more generally, a sense of disownership. Experimentally, this altered consciousness disappears during illusory own-body perceptions, increasing the intensity of perceived ownership for an external virtual limb. In many clinical conditions, particularly in individuals with a discontinuous or absent sense of bodily awareness, the brain may effortlessly create a convincing feeling of body ownership over a surrogate body or body part. The immediate visual input dominates the current bodily state and induces rapid plastic adaptation that reconfigures the dynamics of bodily representation, allowing the brain to acquire an alternative sense of body and self. Investigating strategies to deconstruct the lack of a normal sense of bodily ownership, especially after a neurological injury, may aid the selection of appropriate clinical treatment

An Integrated Approach for Characterizing Aerosol Climate Impacts and Environmental Interactions

Aerosols exert myriad influences on the earth's environment and climate, and on human health. The complexity of aerosol-related processes requires that information gathered to improve our understanding of climate change must originate from multiple sources, and that effective strategies for data integration need to be established. While a vast array of observed and modeled data are becoming available, the aerosol research community currently lacks the necessary tools and infrastructure to reap maximum scientific benefit from these data. Spatial and temporal sampling differences among a diverse set of sensors, nonuniform data qualities, aerosol mesoscale variabilities, and difficulties in separating cloud effects are some of the challenges that need to be addressed. Maximizing the long-term benefit from these data also requires maintaining consistently well-understood accuracies as measurement approaches evolve and improve. Achieving a comprehensive understanding of how aerosol physical, chemical, and radiative processes impact the earth system can be achieved only through a multidisciplinary, inter-agency, and international initiative capable of dealing with these issues. A systematic approach, capitalizing on modern measurement and modeling techniques, geospatial statistics methodologies, and high-performance information technologies, can provide the necessary machinery to support this objective. We outline a framework for integrating and interpreting observations and models, and establishing an accurate, consistent, and cohesive long-term record, following a strategy whereby information and tools of progressively greater sophistication are incorporated as problems of increasing complexity are tackled. This concept is named the Progressive Aerosol Retrieval and Assimilation Global Observing Network (PARAGON). To encompass the breadth of the effort required, we present a set of recommendations dealing with data interoperability; measurement and model integration; multisensor synergy; data summarization and mining; model evaluation; calibration and validation; augmentation of surface and in situ measurements; advances in passive and active remote sensing; and design of satellite missions. Without an initiative of this nature, the scientific and policy communities will continue to struggle with understanding the quantitative impact of complex aerosol processes on regional and global climate change and air quality

Cortical Dynamics of Navigation and Steering in Natural Scenes: Motion-Based Object Segmentation, Heading, and Obstacle Avoidance

Visually guided navigation through a cluttered natural scene is a challenging problem that animals and humans accomplish with ease. The ViSTARS neural model proposes how primates use motion information to segment objects and determine heading for purposes of goal approach and obstacle avoidance in response to video inputs from real and virtual environments. The model produces trajectories similar to those of human navigators. It does so by predicting how computationally complementary processes in cortical areas MT-/MSTv and MT+/MSTd compute object motion for tracking and self-motion for navigation, respectively. The model retina responds to transients in the input stream. Model V1 generates a local speed and direction estimate. This local motion estimate is ambiguous due to the neural aperture problem. Model MT+ interacts with MSTd via an attentive feedback loop to compute accurate heading estimates in MSTd that quantitatively simulate properties of human heading estimation data. Model MT interacts with MSTv via an attentive feedback loop to compute accurate estimates of speed, direction and position of moving objects. This object information is combined with heading information to produce steering decisions wherein goals behave like attractors and obstacles behave like repellers. These steering decisions lead to navigational trajectories that closely match human performance.National Science Foundation (SBE-0354378, BCS-0235398); Office of Naval Research (N00014-01-1-0624); National Geospatial Intelligence Agency (NMA201-01-1-2016

Autonomic Cloud Computing: Open Challenges and Architectural Elements

As Clouds are complex, large-scale, and heterogeneous distributed systems, management of their resources is a challenging task. They need automated and integrated intelligent strategies for provisioning of resources to offer services that are secure, reliable, and cost-efficient. Hence, effective management of services becomes fundamental in software platforms that constitute the fabric of computing Clouds. In this direction, this paper identifies open issues in autonomic resource provisioning and presents innovative management techniques for supporting SaaS applications hosted on Clouds. We present a conceptual architecture and early results evidencing the benefits of autonomic management of Clouds.Comment: 8 pages, 6 figures, conference keynote pape

Transitory Inhibition of the left anterior intraparietal sulcus impairs joint actions: a continuous Theta-Burst stimulation study

Although temporal coordination is a hallmark of motor interactions, joint action (JA) partners do not simply synchronize; they rather dynamically adapt to each other to achieve a joint goal. We created a novel paradigm to tease apart the processes underlying synchronization and JA and tested the causal contribution of the left anterior intraparietal sulcus (aIPS) in these behaviors. Participants had to synchronize their congruent or incongruent movements with a virtual partner in two conditions: (i) being instructed on what specific action to perform, independently from what action the partner performed (synchronization), and (ii) being instructed to adapt online to the partner's action (JA). Offline noninvasive inhibitory brain stimulation (continuous theta-burst stimulation) over the left aIPS selectively modulated interpersonal synchrony in JA by boosting synchrony during congruent interactions and impairing it during incongruent ones, while leaving performance in the synchronization condition unaffected. These results suggest that the left aIPS plays a causal role in supporting online adaptation to a partner's action goal, whereas it is not necessarily engaged in social situations where the goal of the partner is irrelevant. This indicates that, during JAs, the integration of one's own and the partner's action goal is supported by aIPS

Performance prediction tools for low impact building design

IT systems are emerging that may be used to support decisions relating to the design of a built enviroment that has low impact in terms of energy use and environmental emissions. This paper summarises this prospect in relation to four complementary application areas: digital cities, rational planning, virtual design and Internet energy services