Dense packings of nonoverlapping bodies in three-dimensional Euclidean space R3 are useful models of the structure of a variety of many-particle systems that arise in the physical and biological sciences. Here we inve...
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Dense packings of nonoverlapping bodies in three-dimensional Euclidean space R3 are useful models of the structure of a variety of many-particle systems that arise in the physical and biological sciences. Here we investigate the packing behavior of congruent ring tori in R3, which are multiply connected nonconvex bodies of genus 1, as well as horn and spindle tori. Specifically, we analytically construct a family of dense periodic packings of unlinked tori guided by the organizing principles originally devised for simply connected solid bodies [Torquato and Jiao, Phys. Rev. E 86, 011102 (2012)]. We find that the horn tori as well as certain spindle and ring tori can achieve a packing density not only higher than that of spheres (i.e., π/18=0.7404...) but also higher than the densest known ellipsoid packings (i.e., 0.7707...). In addition, we study dense packings of clusters of pair-linked ring tori (i.e., Hopf links), which can possess much higher densities than corresponding packings consisting of unlinked tori.
Studies with ensemble systems have gained attention recently and, most of them, propose new methods for the design (generation) of different components in these systems. In parallel, new contributions of meta-learning...
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Studies with ensemble systems have gained attention recently and, most of them, propose new methods for the design (generation) of different components in these systems. In parallel, new contributions of meta-learning have been presented as an efficient alternative to automatic recommendation of algorithms. In this paper, we apply meta-learning in the process of recommendation of important parameters of ensemble systems, which are: architecture and individual classifiers. The main goal is to provide an efficient way to design ensemble systems. In order to validate the proposed approach, an empirical investigation is conducted, recommending three possible types of ensemble architectures (Bagging, Boosting and Multi-Boosting) and five possible types of learning algorithms to compose the ensemble systems (individual classifiers or components). An initial analysis of the results confirms that meta-learning can be a promising tool to be used in the automatic choice of important parameters in ensemble systems.
In this paper, we present the application of the ZEM/ZEV guidance algorithm to the planar restricted three-body problem (PR3BP). The ZEM/ZEV guidance law as a feedback guidance strategy is presented and applied to the...
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ISBN:
(纸本)9780877036111
In this paper, we present the application of the ZEM/ZEV guidance algorithm to the planar restricted three-body problem (PR3BP). The ZEM/ZEV guidance law as a feedback guidance strategy is presented and applied to the PR3BP. The fuel optimal solution to the PR3BP for a transfer from GTO to L1 in the Earth-Moon system is presented as a point for comparison, showing the near optimality of the closed-loop guidance approach. Challenges of the approach and strategies for implementation in spacecraft mission design are discussed.
We survey the early history of the discovery of quark gluon plasma and the early history of the Universe, beginning with the present day and reaching deep into QGP and almost beyond. We introduce cosmological Universe...
We survey the early history of the discovery of quark gluon plasma and the early history of the Universe, beginning with the present day and reaching deep into QGP and almost beyond. We introduce cosmological Universe dynamics and connect the different Universe epochs with one another. We describe some of the many remaining open questions that emerge.
We present a novel idea for modeling maneuvering targets using GARCH process noise. GARCH processes seem to capture well the desired properties of evading aerial target maneuvers and, hence, overcome the shortcomings ...
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ISBN:
(纸本)9781627481144
We present a novel idea for modeling maneuvering targets using GARCH process noise. GARCH processes seem to capture well the desired properties of evading aerial target maneuvers and, hence, overcome the shortcomings of classical modeling methods. We derive two recursive state estimation algorithms for systems following the new model. The first method is based on a heuristic utilization of the KF mechanization with an ad-hoc technique for process noise estimation. The second algorithm consists of a direct utilization of the EKF approach. Being only an initial attempt, both filters succeed, to some extent, to estimate the target acceleration using position-only measurements.
The radiative transfer equation (RTE) arises in a variety of applications. The equation is challenging to solve numerically for a couple of reasons: high dimensionality, integro-differential form, highly forward-peake...
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Finite time Lyapunov exponents are used to determine expanding, contracting, and hyperbolic regions in computational simulations of laminar steady-state fluid flows within realistic three dimensional pore structures e...
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Finite time Lyapunov exponents are used to determine expanding, contracting, and hyperbolic regions in computational simulations of laminar steady-state fluid flows within realistic three dimensional pore structures embedded within an impermeable matrix. These regions correspond approximately to pores where flow converges (contraction) or diverges (expansion), and to throats between pores where the flow mixes (hyperbolic). The regions are sparse and disjoint from one another, occupying only a small percentage of the pore space. Nonetheless, nearly every percolating fluid particle trajectory passes through several hyperbolic regions indicating that the effects of in-pore mixing are distributed throughout an entire pore structure. Furthermore, the observed range of fluid dynamics evidences two scales of heterogeneity within each of these flow fields. There is a larger scale that affects dispersion of fluid particle trajectories across the connected network of pores and a relatively small scale of nonuniform distributions of velocities within an individual pore.
If a network of neurons is repeatedly driven by the same fluctuating signal, will it give the same response each time? If so, the network is said to be reliable. Reliability is of interest in computational neuroscienc...
If a network of neurons is repeatedly driven by the same fluctuating signal, will it give the same response each time? If so, the network is said to be reliable. Reliability is of interest in computational neuroscience because the degree to which a network is reliable constrains its ability to encode information in precise temporal patterns of spikes. This note outlines how the question of reliability may be fruitfully formulated and studied within the framework of random dynamical systems theory. A specific network architecture, that of a single-layer network, is examined. For the type of single-neuron dynamics and coupling considered here, single-layer networks are found to be very reliable. A qualitative explanation is proposed for this phenomenon.
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