Classification of multipartite entanglement containing infinitely many kinds of states

We give a further investigation of the range criterion and Low-to-High Rank Generating Mode (LHRGM) introduced in \cite{Chen}, which can be used for the classification of $2\times{M}\times{N}$ states under reversible local filtering operations. By using of these techniques, we entirely classify the family of $2\times4\times4$ states, which actually contains infinitely many kinds of states. The classifications of true entanglement of $2\times(M+3)\times(2M+3)$ and $2\times(M+4)\times(2M+4)$ systems are briefly listed respectively.Comment: 11 pages, revte

Theoretical foundations for 1-D shock filtering

While shock filters are popular morphological image enhancement methods, no well-posedness theory is available for their corresponding partial differential equations (PDEs). By analysing the dynamical system of ordinary differential equations that results from a space discretisation of a PDE for 1-D shock filtering, we derive an analytical solution and prove well-posedness. We show that the results carry over to the fully discrete case when an explicit time discretisation is applied. Finally we establish an equivalence result between discrete shock filtering and local mode filtering

Revised progressive morphological method for ground point classification of airborne LiDAR data

Airborne Light Detection and Ranging (LiDAR) has been very effectively used in collecting terrain information over different scales of area. Inevitably, filtering the non-ground returns is the major step of digital terrain model (DTM) generation and this step poses the greatest challenge especially for tropical forest environment which consists of steep undulating terrain and mostly covered by a relatively thick canopy density. The aim of this research is to assess the performance of the Progressive Morphological (PM) algorithm after the implementation of local slope value in the ground filtering process. The improvement on the PM filtering method was done by employing local slope values obtained either using initial filtering of airborne LiDAR data or ground survey data. The filtering process has been performed with recursive mode and it stops after the results of the filtering does not show any improvement and the DTM error larger than the previous iteration. The revised PM filtering method has decreasing pattern of DTM error with increasing filtering iterations with minimum ±0.520 m of RMSE value. The results also suggest that spatially distributed slope value applied in PM filtering algorithm either from LiDAR ground points or ground survey data is capable in preserving discontinuities of terrain and correctly remove non-terrain points especially in steep area

Evaluation of Single-Chip, Real-Time Tomographic Data Processing on FPGA - SoC Devices

A novel approach to tomographic data processing has been developed and evaluated using the Jagiellonian PET (J-PET) scanner as an example. We propose a system in which there is no need for powerful, local to the scanner processing facility, capable to reconstruct images on the fly. Instead we introduce a Field Programmable Gate Array (FPGA) System-on-Chip (SoC) platform connected directly to data streams coming from the scanner, which can perform event building, filtering, coincidence search and Region-Of-Response (ROR) reconstruction by the programmable logic and visualization by the integrated processors. The platform significantly reduces data volume converting raw data to a list-mode representation, while generating visualization on the fly.Comment: IEEE Transactions on Medical Imaging, 17 May 201

Polarization filtering for automatic picking of seismic data and improved converted phase detection

Data-adaptive polarization filtering is used to improve the detection of converted seismic phases. Both direct waves and mode-converted PS and SP arrivals may be more easily picked on the filtered records. An autopicking routine is applied that cuts the polarization filtered traces according to the modelled traveltime of each phase through an initial structure. Use of forward-modelled, source–receiver times reduces the likelihood of an automatic pick being incorrectly made on spurious spikes in the polarization filtered trace. It is therefore a realistic way of automatically picking multiphase data sets or, more generally, linearly polarized phases where low signal-to-noise ratios may be encountered. The method is suitable for any three-component seismic data and is here applied to local earthquakes recorded in North Island, New Zealand. Intermediate energy is observed between the direct P and S arrivals due to phase conversion at the interface between the Indo-Australian and subducting Pacific plates. The amplitudes of these converted arrivals are often too low for them to be identified above the P-wave coda but polarization filtering of the records enables the yield of converted phase picks to be greatly increased

Full wave field signal processing techniques for NDT of composites : a case study

Non-destructive testing of composites using full wave field analysis of guided waves is illustrated for a CFRP aircraft panel with production defects. The full wave field is measured using 3D scanning laser Doppler vibrometry for broadband chirp excitation through one piezoelectric actuator. First, the A0 mode is extracted through mode filtering in the frequency-wavenumber domain. Next, the measured chirp response is converted to a narrowband burst response. At last, the local wavenumber map is constructed and evaluated. A debonding defect between stiffener and base plate is detected and confirmed by the ultrasonic C-scan time-of-flight map