Spiking Neural Networks for Early Prediction in Human Robot Collaboration

This paper introduces the Turn-Taking Spiking Neural Network (TTSNet), which is a cognitive model to perform early turn-taking prediction about human or agent's intentions. The TTSNet framework relies on implicit and explicit multimodal communication cues (physical, neurological and physiological) to be able to predict when the turn-taking event will occur in a robust and unambiguous fashion. To test the theories proposed, the TTSNet framework was implemented on an assistant robotic nurse, which predicts surgeon's turn-taking intentions and delivers surgical instruments accordingly. Experiments were conducted to evaluate TTSNet's performance in early turn-taking prediction. It was found to reach a F1 score of 0.683 given 10% of completed action, and a F1 score of 0.852 at 50% and 0.894 at 100% of the completed action. This performance outperformed multiple state-of-the-art algorithms, and surpassed human performance when limited partial observation is given (< 40%). Such early turn-taking prediction capability would allow robots to perform collaborative actions proactively, in order to facilitate collaboration and increase team efficiency.Comment: Under review for journa

Early Prediction for Physical Human Robot Collaboration in the Operating Room

To enable a natural and fluent human robot collaboration flow, it is critical for a robot to comprehend their human peers' on-going actions, predict their behaviors in the near future, and plan its actions correspondingly. Specifically, the capability of making early predictions is important, so that the robot can foresee the precise timing of a turn-taking event and start motion planning and execution early enough to smooth the turn-taking transition. Such proactive behavior would reduce human's waiting time, increase efficiency and enhance naturalness in collaborative task. To that end, this paper presents the design and implementation of an early turn-taking prediction algorithm, catered for physical human robot collaboration scenarios. Specifically, a Robotic Scrub Nurse (RSN) system which can comprehend surgeon's multimodal communication cues and perform turn-taking prediction is presented. The developed algorithm was tested on a collected data set of simulated surgical procedures in a surgeon-nurse tandem. The proposed turn-taking prediction algorithm is found to be significantly superior to its algorithmic counterparts, and is more accurate than human baseline when little partial input is given (less than 30% of full action). After observing more information, the algorithm can achieve comparable performances as humans with a F1 score of 0.90

Object Tracking in Hyperspectral Videos with Convolutional Features and Kernelized Correlation Filter

Target tracking in hyperspectral videos is a new research topic. In this paper, a novel method based on convolutional network and Kernelized Correlation Filter (KCF) framework is presented for tracking objects of interest in hyperspectral videos. We extract a set of normalized three-dimensional cubes from the target region as fixed convolution filters which contain spectral information surrounding a target. The feature maps generated by convolutional operations are combined to form a three-dimensional representation of an object, thereby providing effective encoding of local spectral-spatial information. We show that a simple two-layer convolutional networks is sufficient to learn robust representations without the need of offline training with a large dataset. In the tracking step, KCF is adopted to distinguish targets from neighboring environment. Experimental results demonstrate that the proposed method performs well on sample hyperspectral videos, and outperforms several state-of-the-art methods tested on grayscale and color videos in the same scene.Comment: Accepted by ICSM 201

Coherent control via interplay between driving field and two-body interaction in a double well

We investigate interplay between external field and interatomic interaction and its applications to coherent control of quantum tunneling for two repulsive bosons confined in a high-frequency driven double well. A full solution of the system is generated analytically as a coherent non-Floquet state by using the Floquet states as a set of complete bases. It is demonstrated that the photon resonance of interaction leads to translation of the Floquet level-crossing points, and the non-resonant interaction causes avoided crossing of partial levels. In the non-Floquet states, the bosons beyond the crossing points slowly vary their populations, and the resonant (non-resonant) interactions enhance (decrease) the tunneling rate of the paired particles. Three different kinds of the coherent destructions of tunneling (CDT) at the crossing, avoided-crossing and uncrossing points, and the corresponding stationary-like states, are illustrated. The analytical results are numerically confirmed and perfect agreements are found. Based on the results, an useful scheme of quantum tunneling switch between stationary-like states is presented.Comment: 7 pages, 5 figure

Communication Modalities for Supervised Teleoperation in Highly Dexterous Tasks - Does one size fit all?

This study tries to explain the connection between communication modalities and levels of supervision in teleoperation during a dexterous task, like surgery. This concept is applied to two surgical related tasks: incision and peg transfer. It was found that as the complexity of the task escalates, the combination linking human supervision with a more expressive modality shows better performance than other combinations of modalities and control. More specifically, in the peg transfer task, the combination of speech modality and action level supervision achieves shorter task completion time (77.1 +- 3.4 s) with fewer mistakes (0.20 +- 0.17 pegs dropped).Comment: Previously published online at 2nd Workshop on the Role of Human Sensormotor Control in Surgical Robotics at 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Hamburg, German

Ψ(2S)\Psi(2S) Decay to J/Ψ(1S)J/\Psi(1S) + 2π\pi or J/Ψ(1S)J/\Psi(1S) +σ\sigma + 2π\pi

The BES Collaboration has measured $\Psi(2S)$ decay to $J/\Psi \pi^+\pi^-$. Using the mixed hybrid theory for the $\Psi(2S)$ we estimate the decay to $J/\Psi(1S)$ + $\sigma$. Using the known $\sigma \rightarrow 2\pi$ coupling constant, we estimate the $\Psi(2S)$ to $J/\Psi(1S)$ + $2\pi$ decay rate and angular distribution. This is an extension of our previous research on $\Psi(2S)$ Decay to $J/\Psi(1S)$ +$\sigma$ + 2$\pi^o$, without the production of 2$\pi^o$, and with an estimate of the $\sigma \rightarrow \pi^+ + \pi^-$ transition.Comment: 11 pages, 7 figures. arXiv admin note: substantial text overlap with arXiv:1509.0836

Cubic vertex-transitive non-Cayley graphs of order 12p

A graph is said to be {\em vertex-transitive non-Cayley} if its full automorphism group acts transitively on its vertices and contains no subgroups acting regularly on its vertices. In this paper, a complete classification of cubic vertex-transitive non-Cayley graphs of order $12p$, where $p$ is a prime, is given. As a result, there are $11$ sporadic and one infinite family of such graphs, of which the sporadic ones occur when $p=5$, $7$ or $17$, and the infinite family exists if and only if $p\equiv1\ (\mod 4)$, and in this family there is a unique graph for a given order.Comment: This paper has been accepted for publication in SCIENCE CHINA Mathematic

Nonzero Mean Squared Momentum of Quarks in the Non-Perturbative QCD Vacuum

The non-local vacuum condensates of QCD describe the distributions of quarks and gluons in the non-perturbative QCD vacuum. Physically, this means that vacuum quarks and gluons have nonzero mean-squared momentum, called virtuality. In this paper we study the quark virtuality which is given by the ratio of the local quark-gluon mixed vacuum condensate to the quark local vacuum condensate. The two vacuum condensates are obtained by solving Dyson-Schwinger Equations of a fully dressed quark propagator with an effective gluon propagator. Using our calculated condensates, we obtain the virtuality of quarks in the QCD vacuum state. Our numerical predictions differ from the other theoretical model calculations such as QCD sum rules, Lattice QCD and instanton models.Comment: 8 pages, no figures, 4 tables Our previous version had an error, and the results in this new version are quite different

Quark Virtuality Distribution in Non-perturbative QCD Vacuum

We introduce the quark virtuality distribution [$\lambda^{2}_{q}(x)$] as an extenson of the quark virtuality by using nonlocal rather than local quark vacuum condensates. Our results show that the quark virtuality distribution decreases gradually from a finite value to zero as $x$ increases. This clearly indicates that quarks are confined inside hadrons, whereas, as $x$ approaches zero quarks have a finite virtuality, which shows asymptotic freedom of quarks in QCD. The present predictions are important not only for studying the properties of QCD vacuum states, and non-perturbative QCD problems, but also for study of the cosmological constant problem, which we have shown should be treated using nonlocal quark vacuum condensate in the Ghost theory of QCD.Comment: 5 pages, 1 figur

Reconstructing light curves from HXMT imaging observations

The Hard X-ray Modulation Telescope (HXMT) is a Chinese space telescope mission. It is scheduled for launch in 2015. The telescope will perform an all-sky survey in hard X-ray band (1 - 250 keV), a series of deep imaging observations of small sky regions as well as pointed observations. In this work we present a conceptual method to reconstruct light curves from HXMT imaging observation directly, in order to monitor time-varying objects such as GRB, AXP and SGR in hard X-ray band with HXMT imaging observations.Comment: In proceedings of Statistical Challenges of 21st Century Cosmology, an International Astronomy Union Symposia. 1 figur