Multi-Layer Cyber-Physical Security and Resilience for Smart Grid

The smart grid is a large-scale complex system that integrates communication technologies with the physical layer operation of the energy systems. Security and resilience mechanisms by design are important to provide guarantee operations for the system. This chapter provides a layered perspective of the smart grid security and discusses game and decision theory as a tool to model the interactions among system components and the interaction between attackers and the system. We discuss game-theoretic applications and challenges in the design of cross-layer robust and resilient controller, secure network routing protocol at the data communication and networking layers, and the challenges of the information security at the management layer of the grid. The chapter will discuss the future directions of using game-theoretic tools in addressing multi-layer security issues in the smart grid.Comment: 16 page

Autonomous Robust Skill Generation Using Reinforcement Learning with Plant Variation

This paper discusses an autonomous space robot for a truss structure assembly using some reinforcement learning. It is difficult for a space robot to complete contact tasks within a real environment, for example, a peg-in-hole task, because of error between the real environment and the controller model. In order to solve problems, we propose an autonomous space robot able to obtain proficient and robust skills by overcoming error to complete a task. The proposed approach develops skills by reinforcement learning that considers plant variation, that is, modeling error. Numerical simulations and experiments show the proposed method is useful in real environments

Gross-Neveu Models, Nonlinear Dirac Equations, Surfaces and Strings

Recent studies of the thermodynamic phase diagrams of the Gross-Neveu model (GN2), and its chiral cousin, the NJL2 model, have shown that there are phases with inhomogeneous crystalline condensates. These (static) condensates can be found analytically because the relevant Hartree-Fock and gap equations can be reduced to the nonlinear Schr\"odinger equation, whose deformations are governed by the mKdV and AKNS integrable hierarchies, respectively. Recently, Thies et al have shown that time-dependent Hartree-Fock solutions describing baryon scattering in the massless GN2 model satisfy the Sinh-Gordon equation, and can be mapped directly to classical string solutions in AdS3. Here we propose a geometric perspective for this result, based on the generalized Weierstrass spinor representation for the embedding of 2d surfaces into 3d spaces, which explains why these well-known integrable systems underlie these various Gross-Neveu gap equations, and why there should be a connection to classical string theory solutions. This geometric viewpoint may be useful for higher dimensional models, where the relevant integrable hierarchies include the Davey-Stewartson and Novikov-Veselov systems.Comment: 27 pages, 1 figur

Eye movements and brain oscillations to symbolic safety signs with different comprehensibility

Background: The aim of this study was to investigate eye movements and brain oscillations to symbolic safety signs with different comprehensibility. Methods: Forty-two young adults participated in this study, and ten traffic symbols consisting of easy-to-comprehend and hard-to-comprehend signs were used as stimuli. During the sign comprehension test, real-time eye movements and spontaneous brain activity [electroencephalogram (EEG) data] were simultaneously recorded. Results: The comprehensibility level of symbolic traffic signs significantly affects eye movements and EEG spectral power. The harder to comprehend the sign is, the slower the blink rate, the larger the pupil diameter, and the longer the time to first fixation. Noticeable differences on EEG spectral power between easy-to-comprehend and hard-to-comprehend signs are observed in the prefrontal and visual cortex of the human brain. Conclusions: Sign comprehensibility has significant effects on real-time nonintrusive eye movements and brain oscillations. These findings demonstrate the potential to integrate physiological measures from eye movements and brain oscillations with existing evaluation methods in assessing the comprehensibility of symbolic safety signs.open

EEG windowed statistical wavelet scoring for evaluation and discrimination of muscular artifacts

EEG recordings are usually corrupted by spurious extra-cerebral artifacts, which should be rejected or cleaned up by the practitioner. Since manual screening of human EEGs is inherently error prone and might induce experimental bias, automatic artifact detection is an issue of importance. Automatic artifact detection is the best guarantee for objective and clean results. We present a new approach, based on the time–frequency shape of muscular artifacts, to achieve reliable and automatic scoring. The impact of muscular activity on the signal can be evaluated using this methodology by placing emphasis on the analysis of EEG activity. The method is used to discriminate evoked potentials from several types of recorded muscular artifacts—with a sensitivity of 98.8% and a specificity of 92.2%. Automatic cleaning ofEEGdata are then successfully realized using this method, combined with independent component analysis. The outcome of the automatic cleaning is then compared with the Slepian multitaper spectrum based technique introduced by Delorme et al (2007 Neuroimage 34 1443–9)

A Twisted Kink Crystal in the Chiral Gross-Neveu model

We present the detailed properties of a self-consistent crystalline chiral condensate in the massless chiral Gross-Neveu model. We show that a suitable ansatz for the Gorkov resolvent reduces the functional gap equation, for the inhomogeneous condensate, to a nonlinear Schr\"odinger equation, which is exactly soluble. The general crystalline solution includes as special cases all previously known real and complex condensate solutions to the gap equation. Furthermore, the associated Bogoliubov-de Gennes equation is also soluble with this inhomogeneous chiral condensate, and the exact spectral properties are derived. We find an all-orders expansion of the Ginzburg-Landau effective Lagrangian and show how the gap equation is solved order-by-order.Comment: 28 pages, 13 figs; v2: new appendix on Eilenberger eq and refs; version in PR

Incomplete information about the partner affects the development of collaborative strategies in joint action.

Physical interaction with a partner plays an essential role in our life experience and is the basis of many daily activities. When two physically coupled humans have different and partly conflicting goals, they face the challenge of negotiating some type of collaboration. This requires that both participants understand their partner's state and current actions. But, how would the collaboration be affected if information about their partner were unreliable or incomplete? We designed an experiment in which two players (a dyad) are mechanically connected through a virtual spring, but cannot see each other. They were instructed to perform reaching movements with the same start and end position, but through different via-points. In different groups of dyads we varied the amount of information provided to each player about his/her partner: haptic only (the interaction force perceived through the virtual spring), visuo-haptic (the interaction force is also displayed on the screen), and partner visible (in addition to interaction force, partner position is continuously displayed on the screen). We found that incomplete information about the partner affects not only the speed at which collaboration is achieved (less information, slower learning), but also the actual collaboration strategy. In particular, incomplete or unreliable information leads to an interaction strategy characterized by alternating leader-follower roles. Conversely, more reliable information leads to more synchronous behaviors, in which no specific roles can be identified. Simulations based on a combination of game theory and Bayesian estimation suggested that synchronous behaviors correspond to optimal interaction (Nash equilibrium). Roles emerge as sub-optimal forms of interaction, which minimize the need to account for the partner. These findings suggest that collaborative strategies in joint action are shaped by the trade-off between the task requirements and the uncertainty of the information available about the partner

Thermodynamics as a theory of decision-making with information processing costs

Perfectly rational decision-makers maximize expected utility, but crucially ignore the resource costs incurred when determining optimal actions. Here we propose an information-theoretic formalization of bounded rational decision-making where decision-makers trade off expected utility and information processing costs. Such bounded rational decision-makers can be thought of as thermodynamic machines that undergo physical state changes when they compute. Their behavior is governed by a free energy functional that trades off changes in internal energy-as a proxy for utility-and entropic changes representing computational costs induced by changing states. As a result, the bounded rational decision-making problem can be rephrased in terms of well-known concepts from statistical physics. In the limit when computational costs are ignored, the maximum expected utility principle is recovered. We discuss the relation to satisficing decision-making procedures as well as links to existing theoretical frameworks and human decision-making experiments that describe deviations from expected utility theory. Since most of the mathematical machinery can be borrowed from statistical physics, the main contribution is to axiomatically derive and interpret the thermodynamic free energy as a model of bounded rational decision-making.Comment: 26 pages, 5 figures, (under revision since February 2012