Three-dimensional planar model estimation using multi-constraint knowledge based on k-means and RANSAC

Plane model extraction from three-dimensional point clouds is a necessary step in many different applications such as planar object reconstruction, indoor mapping and indoor localization. Different RANdom SAmple Consensus (RANSAC)-based methods have been proposed for this purpose in recent years. In this study, we propose a novel method-based on RANSAC called Multiplane Model Estimation, which can estimate multiple plane models simultaneously from a noisy point cloud using the knowledge extracted from a scene (or an object) in order to reconstruct it accurately. This method comprises two steps: first, it clusters the data into planar faces that preserve some constraints defined by knowledge related to the object (e.g., the angles between faces); and second, the models of the planes are estimated based on these data using a novel multi-constraint RANSAC. We performed experiments in the clustering and RANSAC stages, which showed that the proposed method performed better than state-of-the-art methods.

Contribution to Real-Time Estimation of Crop Phenological States in a Dynamical Framework Based on NDVI Time Series: Data Fusion With SAR and Temperature

In this study, a methodology based in a dynamical framework is proposed to incorporate additional sources of information to normalized difference vegetation index (NDVI) time series of agricultural observations for a phenological state estimation application. The proposed implementation is based on the particle filter (PF) scheme that is able to integrate multiple sources of data. Moreover, the dynamics-led design is able to conduct real-time (online) estimations, i.e., without requiring to wait until the end of the campaign. The evaluation of the algorithm is performed by estimating the phenological states over a set of rice fields in Seville (SW, Spain). A Landsat-5/7 NDVI series of images is complemented with two distinct sources of information: SAR images from the TerraSAR-X satellite and air temperature information from a ground-based station. An improvement in the overall estimation accuracy is obtained, especially when the time series of NDVI data is incomplete. Evaluations on the sensitivity to different development intervals and on the mitigation of discontinuities of the time series are also addressed in this work, demonstrating the benefits of this data fusion approach based on the dynamic systems.

Radiolarian-based bransfer function for the estimation of sea surface temperatures in the Southern Ocean (Atlantic Sector)

A new radiolarian-based transfer function for sea surface temperature (SST) estimations has been developed from 23 taxa and taxa groups in 53 surface sediment samples recovered between 35° and 72°S in the Atlantic sector of the Southern Ocean. For the selection of taxa and taxa groups ecological information from water column studies was considered. The transfer function allows the estimation of austral summer SST (December-March) ranging between -1 and 18°C with a standard error of estimate of 1.2°C. SST estimates from selected late Pleistocene squences were sucessfully compared with independend paleotemperature estimates derived from a diatom transfer function. This shows that radiolarians provide an excellent tool for paleotemperature reconstructions in Pleistocene sediments of the Southern Ocean.

Estimation of an origin-destination trip table based on observed link volumes and turning movements. Executive summary. Final report.

Federal Highway Administration, Washington, D.C.

Estimation of an origin-destination trip table based on observed link volumes and turning movements. Volume 1: technical report. Final report.

Federal Highway Administration, Washington, D.C.

Estimation of an origin-destination trip table based on observed link volumes and turning movments. Volume 2: user's manual. Final report.

Federal Highway Administration, Washington, D.C.

Estimation of an origin-destination trip table based on observed link volumes and turning movements. Volume 3: program manual. Final report.

Federal Highway Administration, Washington, D.C.

Genetic assignment methods for the direct, real-time estimation of migration rate: a simulation-based exploration of accuracy and power

Genetic assignment methods use genotype likelihoods to draw inference about where individuals were or were not born, potentially allowing direct, real-time estimates of dispersal. We used simulated data sets to test the power and accuracy of Monte Carlo resampling methods in generating statistical thresholds for identifying F-0 immigrants in populations with ongoing gene flow, and hence for providing direct, real-time estimates of migration rates. The identification of accurate critical values required that resampling methods preserved the linkage disequilibrium deriving from recent generations of immigrants and reflected the sampling variance present in the data set being analysed. A novel Monte Carlo resampling method taking into account these aspects was proposed and its efficiency was evaluated. Power and error were relatively insensitive to the frequency assumed for missing alleles. Power to identify F-0 immigrants was improved by using large sample size (up to about 50 individuals) and by sampling all populations from which migrants may have originated. A combination of plotting genotype likelihoods and calculating mean genotype likelihood ratios (D-LR) appeared to be an effective way to predict whether F-0 immigrants could be identified for a particular pair of populations using a given set of markers.

Pattern-based phylogenetic distance estimation and tree reconstruction

We have developed an alignment-free method that calculates phylogenetic distances using a maximum-likelihood approach for a model of sequence change on patterns that are discovered in unaligned sequences. To evaluate the phylogenetic accuracy of our method, and to conduct a comprehensive comparison of existing alignment-free methods (freely available as Python package decaf+py at http://www.bioinformatics.org.au), we have created a data set of reference trees covering a wide range of phylogenetic distances. Amino acid sequences were evolved along the trees and input to the tested methods; from their calculated distances we infered trees whose topologies we compared to the reference trees. We find our pattern-based method statistically superior to all other tested alignment-free methods. We also demonstrate the general advantage of alignment-free methods over an approach based on automated alignments when sequences violate the assumption of collinearity. Similarly, we compare methods on empirical data from an existing alignment benchmark set that we used to derive reference distances and trees. Our pattern-based approach yields distances that show a linear relationship to reference distances over a substantially longer range than other alignment-free methods. The pattern-based approach outperforms alignment-free methods and its phylogenetic accuracy is statistically indistinguishable from alignment-based distances.

Motion analysis of right ventricular wall based on an electromechanical biventricular model

Based on our previously developed electrical heart model, an electromechanical biventricular model, which couples the electrical property and mechanical property of the heart, was constructed and the right ventricular wall motion and deformation was simulated using this model. The model was developed on the basis of composite material theory and finite element method. The excitation propagation was simulated by electrical heart model, and the resultant active forces were used to study the ventricular wall motion during systole. The simulation results show that: (1) The right ventricular free wall moves towards the septum, and at the same time, the base and middle of free wall move towards the apex, which reduce the volume of right ventricle; (2) The minimum principle strain (E3) is largest at the apex, then at the middle of free wall, and its direction is in the approximate direction of epicardial muscle fibers. These results are in good accordance with solutions obtained from MR tagging images. It suggests that such electromechanical biventricular model can be used to assess the mechanical function of two ventricles.

Heart rate variability characterization using a time-frequency based instantaneous frequency estimation technique

In this paper, a new method for characterizing the newborn heart rate variability (HRV) is proposed. The central of the method is the newly proposed technique for instantaneous frequency (IF) estimation specifically designed for nonstationary multicomponen signals such as HRV. The new method attempts to characterize the newborn HRV using features extracted from the time–frequency (TF) domain of the signal. These features comprise the IF, the instantaneous bandwidth (IB) and instantaneous energy (IE) of the different TF components of the HRV. Applied to the HRV of both normal and seizure suffering newborns, this method clearly reveals the locations of the spectral peaks and their time-varying nature. The total energy of HRV components, ET and ratio of energy concentrated in the low-frequency (LF) to that in high frequency (HF) components have been shown to be significant features in identifying the HRV of newborn with seizures.