1,128 research outputs found
Learning Social Affordance Grammar from Videos: Transferring Human Interactions to Human-Robot Interactions
In this paper, we present a general framework for learning social affordance
grammar as a spatiotemporal AND-OR graph (ST-AOG) from RGB-D videos of human
interactions, and transfer the grammar to humanoids to enable a real-time
motion inference for human-robot interaction (HRI). Based on Gibbs sampling,
our weakly supervised grammar learning can automatically construct a
hierarchical representation of an interaction with long-term joint sub-tasks of
both agents and short term atomic actions of individual agents. Based on a new
RGB-D video dataset with rich instances of human interactions, our experiments
of Baxter simulation, human evaluation, and real Baxter test demonstrate that
the model learned from limited training data successfully generates human-like
behaviors in unseen scenarios and outperforms both baselines.Comment: The 2017 IEEE International Conference on Robotics and Automation
(ICRA
CDEdit: A Highly Applicable Redactable Blockchain with Controllable Editing Privilege and Diversified Editing Types
Redactable blockchains allow modifiers or voting committees with modification
privileges to edit the data on the chain. Trapdoor holders in chameleon-based
hash redactable blockchains can quickly compute hash collisions for arbitrary
data, and without breaking the link of the hash-chain. However, chameleon-based
hash redactable blockchain schemes have difficulty solving the problem of
multi-level editing requests and competing for modification privileges. In this
paper, we propose CDEdit, a highly applicable redactable blockchain with
controllable editing privilege and diversified editing types. The proposed
scheme increases the cost of invalid or malicious requests by paying the
deposit on each edit request. At the same time, the editing privilege is
subdivided into request, modification, and verification privileges, and the
modification privilege token is distributed efficiently to prevent the abuse of
the modification privilege and collusion attacks. We use chameleon hashes with
ephemeral trapdoor (CHET) and ciphertext policy attribute-based encryption
(CP-ABE) to implement two editing types of transaction-level and block-level,
and present a practical instantiation and security analysis. Finally, the
implementation and evaluation show that our scheme only costs low-performance
overhead and is suitable for multi-level editing requests and modification
privilege competition scenarios.Comment: 11 pages, 6 figure
Testing Serial Independence of Object-Valued Time Series
We propose a novel method for testing serial independence of object-valued
time series in metric spaces, which is more general than Euclidean or Hilbert
spaces. The proposed method is fully nonparametric, free of tuning parameters,
and can capture all nonlinear pairwise dependence. The key concept used in this
paper is the distance covariance in metric spaces, which is extended to auto
distance covariance for object-valued time series. Furthermore, we propose a
generalized spectral density function to account for pairwise dependence at all
lags and construct a Cramer-von Mises type test statistic. New theoretical
arguments are developed to establish the asymptotic behavior of the test
statistic. A wild bootstrap is also introduced to obtain the critical values of
the non-pivotal limiting null distribution. Extensive numerical simulations and
two real data applications are conducted to illustrate the effectiveness and
versatility of our proposed method
Decoupled, Linear, and Energy Stable Finite Element Method for the Cahn-Hilliard-Navier-Stokes-Darcy Phase Field Model
In this paper, we consider the numerical approximation for a phase field model of the coupled two-phase free flow and two-phase porous media flow. This model consists of Cahn—Hilliard—Navier—Stokes equations in the free flow region and Cahn—Hilliard—Darcy equations in the porous media region that are coupled by seven interface conditions. The coupled system is decoupled based on the interface conditions and the solution values on the interface from the previous time step. A fully discretized scheme with finite elements for the spatial discretization is developed to solve the decoupled system. In order to deal with the difficulties arising from the interface conditions, the decoupled scheme needs to be constructed appropriately for the interface terms, and a modified discrete energy is introduced with an interface component. Furthermore, the scheme is linearized and energy stable. Hence, at each time step one need only solve a linear elliptic system for each of the two decoupled equations. Stability of the model and the proposed method is rigorously proved. Numerical experiments are presented to illustrate the features of the proposed numerical method and verify the theoretical conclusions. © 2018 Society for Industrial and Applied Mathematics
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FAM222A encodes a protein which accumulates in plaques in Alzheimer's disease.
Alzheimer's disease (AD) is characterized by amyloid plaques and progressive cerebral atrophy. Here, we report FAM222A as a putative brain atrophy susceptibility gene. Our cross-phenotype association analysis of imaging genetics indicates a potential link between FAM222A and AD-related regional brain atrophy. The protein encoded by FAM222A is predominantly expressed in the CNS and is increased in brains of patients with AD and in an AD mouse model. It accumulates within amyloid deposits, physically interacts with amyloid-β (Aβ) via its N-terminal Aβ binding domain, and facilitates Aβ aggregation. Intracerebroventricular infusion or forced expression of this protein exacerbates neuroinflammation and cognitive dysfunction in an AD mouse model whereas ablation of this protein suppresses the formation of amyloid deposits, neuroinflammation and cognitive deficits in the AD mouse model. Our data support the pathological relevance of protein encoded by FAM222A in AD
LEMMA: Learning Language-Conditioned Multi-Robot Manipulation
Complex manipulation tasks often require robots with complementary
capabilities to collaborate. We introduce a benchmark for LanguagE-Conditioned
Multi-robot MAnipulation (LEMMA) focused on task allocation and long-horizon
object manipulation based on human language instructions in a tabletop setting.
LEMMA features 8 types of procedurally generated tasks with varying degree of
complexity, some of which require the robots to use tools and pass tools to
each other. For each task, we provide 800 expert demonstrations and human
instructions for training and evaluations. LEMMA poses greater challenges
compared to existing benchmarks, as it requires the system to identify each
manipulator's limitations and assign sub-tasks accordingly while also handling
strong temporal dependencies in each task. To address these challenges, we
propose a modular hierarchical planning approach as a baseline. Our results
highlight the potential of LEMMA for developing future language-conditioned
multi-robot systems.Comment: 8 pages, 3 figure
Asymptotic analysis of V-BLAST MIMO for coherent optical wireless communications in Gamma-Gamma turbulence
This paper investigates the asymptotic BER performance of coherent optical wireless communication systems in Gamma-Gamma turbulence when applying the V-BLAST MIMO scheme. A new method is proposed to quantify the performance of the system and mathematical solutions for asymptotic BER performance are derived. Counterintuitive results are shown since the diversity gain of the V-BLAST MIMO system is equal to the number of the receivers. As a consequence, it is shown that when applying the V-BLAST MIMO scheme, the symbol rate per transmission can be equal to the number of transmitters with some cost to diversity gain. This means that we can simultaneously exploit the spatial multiplexing and diversity properties of the MIMO system to achieve a higher data rate than existing schemes in a channel that displays severe turbulence and moderate attenuation
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