60,350 research outputs found
Transport-Based Neural Style Transfer for Smoke Simulations
Artistically controlling fluids has always been a challenging task.
Optimization techniques rely on approximating simulation states towards target
velocity or density field configurations, which are often handcrafted by
artists to indirectly control smoke dynamics. Patch synthesis techniques
transfer image textures or simulation features to a target flow field. However,
these are either limited to adding structural patterns or augmenting coarse
flows with turbulent structures, and hence cannot capture the full spectrum of
different styles and semantically complex structures. In this paper, we propose
the first Transport-based Neural Style Transfer (TNST) algorithm for volumetric
smoke data. Our method is able to transfer features from natural images to
smoke simulations, enabling general content-aware manipulations ranging from
simple patterns to intricate motifs. The proposed algorithm is physically
inspired, since it computes the density transport from a source input smoke to
a desired target configuration. Our transport-based approach allows direct
control over the divergence of the stylization velocity field by optimizing
incompressible and irrotational potentials that transport smoke towards
stylization. Temporal consistency is ensured by transporting and aligning
subsequent stylized velocities, and 3D reconstructions are computed by
seamlessly merging stylizations from different camera viewpoints.Comment: ACM Transaction on Graphics (SIGGRAPH ASIA 2019), additional
materials: http://www.byungsoo.me/project/neural-flow-styl
Neuromorphic analogue VLSI
Neuromorphic systems emulate the organization and function of nervous systems. They are usually composed of analogue electronic circuits that are fabricated in the complementary metal-oxide-semiconductor (CMOS) medium using very large-scale integration (VLSI) technology. However, these neuromorphic systems are not another kind of digital computer in which abstract neural networks are simulated symbolically in terms of their mathematical behavior. Instead, they directly embody, in the physics of their CMOS circuits, analogues of the physical processes that underlie the computations of neural systems. The significance of neuromorphic systems is that they offer a method of exploring neural computation in a medium whose physical behavior is analogous to that of biological nervous systems and that operates in real time irrespective of size. The implications of this approach are both scientific and practical. The study of neuromorphic systems provides a bridge between levels of understanding. For example, it provides a link between the physical processes of neurons and their computational significance. In addition, the synthesis of neuromorphic systems transposes our knowledge of neuroscience into practical devices that can interact directly with the real world in the same way that biological nervous systems do
Internet's Critical Path Horizon
Internet is known to display a highly heterogeneous structure and complex
fluctuations in its traffic dynamics. Congestion seems to be an inevitable
result of user's behavior coupled to the network dynamics and it effects should
be minimized by choosing appropriate routing strategies. But what are the
requirements of routing depth in order to optimize the traffic flow? In this
paper we analyse the behavior of Internet traffic with a topologically
realistic spatial structure as described in a previous study (S-H. Yook et al.
,Proc. Natl Acad. Sci. USA, {\bf 99} (2002) 13382). The model involves
self-regulation of packet generation and different levels of routing depth. It
is shown that it reproduces the relevant key, statistical features of
Internet's traffic. Moreover, we also report the existence of a critical path
horizon defining a transition from low-efficient traffic to highly efficient
flow. This transition is actually a direct consequence of the web's small world
architecture exploited by the routing algorithm. Once routing tables reach the
network diameter, the traffic experiences a sudden transition from a
low-efficient to a highly-efficient behavior. It is conjectured that routing
policies might have spontaneously reached such a compromise in a distributed
manner. Internet would thus be operating close to such critical path horizon.Comment: 8 pages, 8 figures. To appear in European Journal of Physics B (2004
Reasoning About Liquids via Closed-Loop Simulation
Simulators are powerful tools for reasoning about a robot's interactions with
its environment. However, when simulations diverge from reality, that reasoning
becomes less useful. In this paper, we show how to close the loop between
liquid simulation and real-time perception. We use observations of liquids to
correct errors when tracking the liquid's state in a simulator. Our results
show that closed-loop simulation is an effective way to prevent large
divergence between the simulated and real liquid states. As a direct
consequence of this, our method can enable reasoning about liquids that would
otherwise be infeasible due to large divergences, such as reasoning about
occluded liquid.Comment: Robotics: Science & Systems (RSS), July 12-16, 2017. Cambridge, MA,
US
To boldly go:an occam-Ļ mission to engineer emergence
Future systems will be too complex to design and implement explicitly. Instead, we will have to learn to engineer complex behaviours indirectly: through the discovery and application of local rules of behaviour, applied to simple process components, from which desired behaviours predictably emerge through dynamic interactions between massive numbers of instances. This paper describes a process-oriented architecture for fine-grained concurrent systems that enables experiments with such indirect engineering. Examples are presented showing the differing complex behaviours that can arise from minor (non-linear) adjustments to low-level parameters, the difficulties in suppressing the emergence of unwanted (bad) behaviour, the unexpected relationships between apparently unrelated physical phenomena (shown up by their separate emergence from the same primordial process swamp) and the ability to explore and engineer completely new physics (such as force fields) by their emergence from low-level process interactions whose mechanisms can only be imagined, but not built, at the current time
Brownian motion near an elastic cell membrane: A theoretical study
Elastic confinements are an important component of many biological systems
and dictate the transport properties of suspended particles under flow. In this
chapter, we review the Brownian motion of a particle moving in the vicinity of
a living cell whose membrane is endowed with a resistance towards shear and
bending. The analytical calculations proceed through the computation of the
frequency-dependent mobility functions and the application of the
fluctuation-dissipation theorem. Elastic interfaces endow the system with
memory effects that lead to a long-lived anomalous subdiffusive regime of
nearby particles. In the steady limit, the diffusional behavior approaches that
near a no-slip hard wall. The analytical predictions are validated and
supplemented with boundary-integral simulations.Comment: 16 pages, 7 figures and 161 references. Contributed chapter to the
flowing matter boo
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