A system for learning statistical motion patterns

Analysis of motion patterns is an effective approach for anomaly detection and behavior prediction. Current approaches for the analysis of motion patterns depend on known scenes, where objects move in predefined ways. It is highly desirable to automatically construct object motion patterns which reflect the knowledge of the scene. In this paper, we present a system for automatically learning motion patterns for anomaly detection and behavior prediction based on a proposed algorithm for robustly tracking multiple objects. In the tracking algorithm, foreground pixels are clustered using a fast accurate fuzzy k-means algorithm. Growing and prediction of the cluster centroids of foreground pixels ensure that each cluster centroid is associated with a moving object in the scene. In the algorithm for learning motion patterns, trajectories are clustered hierarchically using spatial and temporal information and then each motion pattern is represented with a chain of Gaussian distributions. Based on the learned statistical motion patterns, statistical methods are used to detect anomalies and predict behaviors. Our system is tested using image sequences acquired, respectively, from a crowded real traffic scene and a model traffic scene. Experimental results show the robustness of the tracking algorithm, the efficiency of the algorithm for learning motion patterns, and the encouraging performance of algorithms for anomaly detection and behavior prediction

A system for learning statistical motion patterns

Analysis of motion patterns is an effective approach for anomaly detection and behavior prediction. Current approaches for the analysis of motion patterns depend on known scenes, where objects move in predefined ways. It is highly desirable to automatically construct object motion patterns which reflect the knowledge of the scene. In this paper, we present a system for automatically learning motion patterns for anomaly detection and behavior prediction based on a proposed algorithm for robustly tracking multiple objects. In the tracking algorithm, foreground pixels are clustered using a fast accurate fuzzy k-means algorithm. Growing and prediction of the cluster centroids of foreground pixels ensure that each cluster centroid is associated with a moving object in the scene. In the algorithm for learning motion patterns, trajectories are clustered hierarchically using spatial and temporal information and then each motion pattern is represented with a chain of Gaussian distributions. Based on the learned statistical motion patterns, statistical methods are used to detect anomalies and predict behaviors. Our system is tested using image sequences acquired, respectively, from a crowded real traffic scene and a model traffic scene. Experimental results show the robustness of the tracking algorithm, the efficiency of the algorithm for learning motion patterns, and the encouraging performance of algorithms for anomaly detection and behavior prediction

Calibration of YSZ Sensors for the Measurement of Oxygen Concentration in Liquid Pb-Bi Eutectic

Although liquid lead-bismuth eutectic (LBE) is a good candidate for coolant in the subcritical transmutation blanket, it is known to be corrosive to stainless steel, the material of the carrying tubes and containers. Such longterm corrosion problem can be prevented by producing and maintaining a protective oxide layer on the exposed surface of stainless steel. For this purpose, it is required to accurately control the concentration of oxygen dissolved in LBE. Currently, YSZ (Yttria Stabilized Zirconia) oxygen sensors, based on an existing automotive oxygen sensor, with molten bismuth saturated with oxygen as the reference, have been selected for oxygen-concentration measurement. The oxygen concentration difference across the solid electrolyte and the resultant oxygen ion conduction inside the electrolyte establishes an electromagnetic force that is used to measure the ppb level concentration of oxygen dissolved in liquid LBE. A set of calibration curves of voltage vs. temperature ranging from 300 0C to 500 0C under various oxygen concentrations in liquid LBE for the YSZ oxygen sensor has been obtained and is presented in this paper. Although the current calibration strategy using the direct injection of hydrogen and oxygen is still inadequate to determine the oxygen concentration in the system, we have found a good candidate for our purpose, which is varying hydrogen to water steam ratio in the system

On the magnetic stability at the surface in strongly correlated electron systems

The stability of ferromagnetism at the surface at finite temperatures is investigated within the strongly correlated Hubbard model on a semi-infinite lattice. Due to the reduced surface coordination number the effective Coulomb correlation is enhanced at the surface compared to the bulk. Therefore, within the well-known Stoner-picture of band ferromagnetism one would expect the magnetic stability at the surface to be enhanced as well. However, by taking electron correlations into account well beyond the Hartree-Fock (Stoner) level we find the opposite behavior: As a function of temperature the magnetization of the surface layer decreases faster than in the bulk. By varying the hopping integral within the surface layer this behavior becomes even more pronounced. A reduced hopping integral at the surface tends to destabilize surface ferromagnetism whereas the magnetic stability gets enhanced by an increased hopping integral. This behavior represents a pure correlation effect and can be understood in terms of general arguments which are based on exact results in the limit of strong Coulomb interaction.Comment: 6 pages, RevTeX, 4 eps figures, accepted (Phys. Rev. B), for related work and info see http://orion.physik.hu-berlin.d

Computational Design and Optimization of Non-Circular Gears

We study a general form of gears known as non‐circular gears that can transfer periodic motion with variable speed through their irregular shapes and eccentric rotation centers. To design functional non‐circular gears is nontrivial, since the gear pair must have compatible shape to keep in contact during motion, so the driver gear can push the follower to rotate via a bounded torque that the motor can exert. To address the challenge, we model the geometry, kinematics, and dynamics of non‐circular gears, formulate the design problem as a shape optimization, and identify necessary independent variables in the optimization search. Taking a pair of 2D shapes as inputs, our method optimizes them into gears by locating the rotation center on each shape, minimally modifying each shape to form the gear's boundary, and constructing appropriate teeth for gear meshing. Our optimized gears not only resemble the inputs but can also drive the motion with relatively small torque. We demonstrate our method's usability by generating a rich variety of non‐circular gears from various inputs and 3D printing several of the

Electrolyte gate dependent high-frequency measurement of graphene field-effect transistor for sensing applications

We performed radiofrequency (RF) reflectometry measurements at 2.4 GHz on electrolyte-gated graphene field-effect transistors (GFETs) utilizing a tunable stub-matching circuit for impedance matching. We demonstrate that the gate voltage dependent RF resistivity of graphene can be deduced even in the presence of the electrolyte which is in direct contact with the graphene layer. The RF resistivity is found to be consistent with its DC counterpart in the full gate voltage range. Furthermore, in order to access the potential of high-frequency sensing for applications, we demonstrate time-dependent gating in solution with nanosecond time resolution.Comment: 14 pages, 4 figure

L-functions of Symmetric Products of the Kloosterman Sheaf over Z

The classical $n$-variable Kloosterman sums over the finite field ${\bf F}_p$ give rise to a lisse $\bar {\bf Q}_l$-sheaf ${\rm Kl}_{n+1}$ on ${\bf G}_{m, {\bf F}_p}={\bf P}^1_{{\bf F}_p}-\{0,\infty\}$, which we call the Kloosterman sheaf. Let $L_p({\bf G}_{m,{\bf F}_p}, {\rm Sym}^k{\rm Kl}_{n+1}, s)$ be the $L$-function of the $k$-fold symmetric product of ${\rm Kl}_{n+1}$. We construct an explicit virtual scheme $X$ of finite type over ${\rm Spec} {\bf Z}$ such that the $p$-Euler factor of the zeta function of $X$ coincides with $L_p({\bf G}_{m,{\bf F}_p}, {\rm Sym}^k{\rm Kl}_{n+1}, s)$. We also prove similar results for $\otimes^k {\rm Kl}_{n+1}$ and $\bigwedge^k {\rm Kl}_{n+1}$.Comment: 16 page

Spin-Wave and Electromagnon Dispersions in Multiferroic MnWO4 as Observed by Neutron Spectroscopy: Isotropic Heisenberg Exchange versus Anisotropic Dzyaloshinskii-Moriya Interaction

High resolution inelastic neutron scattering reveals that the elementary magnetic excitations in multiferroic MnWO4 consist of low energy dispersive electromagnons in addition to the well-known spin-wave excitations. The latter can well be modeled by a Heisenberg Hamiltonian with magnetic exchange coupling extending to the 12th nearest neighbor. They exhibit a spin-wave gap of 0.61(1) meV. Two electromagnon branches appear at lower energies of 0.07(1) meV and 0.45(1) meV at the zone center. They reflect the dynamic magnetoelectric coupling and persist in both, the collinear magnetic and paraelectric AF1 phase, and the spin spiral ferroelectric AF2 phase. These excitations are associated with the Dzyaloshinskii-Moriya exchange interaction, which is significant due to the rather large spin-orbit coupling.Comment: 8 pages, 6 figures, accepted for publication in Physical Review

States interpolating between number and coherent states and their interaction with atomic systems

Using the eigenvalue definition of binomial states we construct new intermediate number-coherent states which reduce to number and coherent states in two different limits. We reveal the connection of these intermediate states with photon-added coherent states and investigate their non-classical properties and quasi-probability distributions in detail. It is of interest to note that these new states, which interpolate between coherent states and number states, neither of which exhibit squeezing, are nevertheless squeezed states. A scheme to produce these states is proposed. We also study the interaction of these states with atomic systems in the framework of the two-photon Jaynes-Cummings model, and describe the response of the atomic system as it varies between the pure Rabi oscillation and the collapse-revival mode and investigate field observables such as photon number distribution, entropy and the Q-function.Comment: 26 pages, 29 EPS figures, Latex, Accepted for publication in J.Phys.