On the Three-dimensional Lattice Model

Using the restricted star-triangle relation, it is shown that the $N$-state spin integrable model on a three-dimensional lattice with spins interacting round each elementary cube of the lattice proposed by Mangazeev, Sergeev and Stroganov is a particular case of the Bazhanov-Baxter model.Comment: 8 pages, latex, 4 figure

Effect and Compensation of Timing Jitter in Through-Wall Human Indication via Impulse Through-Wall Radar

Impulse through-wall radar (TWR) is considered as one of preferred choices for through-wall human indication due to its good penetration and high range resolution. Large bandwidth available for impulse TWR results in high range resolution, but also brings an atypical adversity issue not substantial in narrowband radars — high timing jitter effect, caused by the non-ideal sampling clock at the receiver. The fact that impulse TWR employs very narrow pulses makes little jitter inaccuracy large enough to destroy the signal correlation property and then degrade clutter suppression performance. In this paper, we focus on the timing jitter impact on clutter suppression in through-wall human indication via impulse TWR. We setup a simple timing jitter model and propose a criterion namely average range profile (ARP) contrast is to evaluate the jitter level. To combat timing jitter, we also develop an effective compensation method based on local ARP contrast maximization. The proposed method can be implemented pulse by pulse followed by exponential average background subtraction algorithm to mitigate clutters. Through-wall experiments demonstrate that the proposed method can dramatically improve through-wall human indication performance

Electron-hydrogen scattering in Faddeev-Merkuriev integral equation approach

Electron-hydrogen scattering is studied in the Faddeev-Merkuriev integral equation approach. The equations are solved by using the Coulomb-Sturmian separable expansion technique. We present $S$- and $P$-wave scattering and reactions cross sections up to the $H(n=4)$ threshold.Comment: 2 eps figure

Measurement of the c-axis optical reflectance of AFe2_2As2_2 (A=Ba, Sr) single crystals: Evidence of different mechanisms for the formation of two energy gaps

We present the c-axis optical reflectance measurement on single crystals of BaFe$_2$As$_2$ and SrFe$_2$As$_2$, the parent compounds of FeAs based superconductors. Different from the ab-plane optical response where two distinct energy gaps were observed in the SDW state, only the smaller energy gap could be seen clearly for \textbf{E}$\parallel$c-axis. The very pronounced energy gap structure seen at a higher energy scale for \textbf{E}$\parallel$ab-plane is almost invisible. We propose a novel picture for the band structure evolution across the SDW transition and suggest different driving mechanisms for the formation of the two energy gaps.Comment: 4 page

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

Evidence for the band broadening across the ferromagnetic transition in Cr1/3_{1/3}NbSe2_2

The electronic structure of Cr$_{1/3}$NbSe$_2$ is studied via optical spectroscopy. We observe two low-energy interband transitions in the paramagnetic phase, which split into four peaks as the compound enters the ferromagnetic state. The band structure calculation indicates the four peaks are interband transitions to the spin up Cr e$_g$ states. We show that the peak splitting below the Curie temperature is \emph{not} due to the exchange splitting of spin up and down bands, but directly reflects a band broadening effect in Cr-derived states upon the spontaneous ferromagnetic ordering.Comment: 6 pages, 5 figures, to be published in Phys. Rev.

A portable MBE system for in situ X-Ray investigations at synchrotron beamlines

A portable synchrotron MBE system is designed and applied for in situ investigations. The growth chamber is equipped with all the standard MBE components such as effusion cells with shutters, main shutter, cooling shroud, manipulator, RHEED setup and pressure gauges. The characteristic feature of the system is the beryllium windows which are used for in situ x-ray measurements. An UHV sample transfer case allows in-vacuo transfer of samples prepared elsewhere. We describe the system design and demonstrate it's performance by investigating the annealing process of buried InGaAs self organized quantum dots

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