Automatic features detection in a fluvial environment through machine learning techniques based on uavs multispectral data

The present work aims to demonstrate how machine learning (ML) techniques can be used for automatic feature detection and extraction in fluvial environments. The use of photogrammetry and machine learning algorithms has improved the understanding of both environmental and an-thropic issues. The developed methodology was applied considering the acquisition of multiple photogrammetric images thanks to unmanned aerial vehicles (UAV) carrying multispectral cam-eras. These surveys were carried out in the Salbertrand area, along the Dora Riparia River, situated in Piedmont (Italy). The authors developed an algorithm able to identify and detect the water table contour concerning the landed areas: the automatic classification in ML found a valid identification of different patterns (water, gravel bars, vegetation, and ground classes) in specific hydraulic and geomatics conditions. Indeed, the RE+NIR data gave us a sharp rise in terms of accuracy by about 11% and 13.5% of F1-score average values in the testing point clouds compared to RGB data. The obtained results about the automatic classification led us to define a new procedure with precise validity conditions

Rock mass characterization by UAV and close-range photogrammetry: A multiscale approach applied along the vallone dell’elva road (Italy)

Geostructural rock mass surveys and the collection of data related to discontinues provide the basis for the characterization of rock masses and the study of their stability conditions. This paper describes a multiscale approach that was carried out using both non-contact techniques and traditional support techniques to survey certain geometrical features of discontinuities, such as their orientation, spacing, and useful persistence. This information is useful in identifying the possible kinematics and stability conditions. These techniques are extremely useful in the case study of the Elva valley road (Northern Italy), in which instability phenomena are spread across 9 km in an overhanging rocky mass. A multiscale approach was applied, obtaining digital surface models (DSMs) at three different scales: large-scale DSM of the entire road, a medium-scale DSM to assess portions of the slope, and a small-scale DSM to assess single discontinuities. The georeferenced point cloud and consequent DSMs of the slopes were obtained using an unmanned aerial vehicle (UAV) and terrestrial photogrammetric technique, allowing topographic and rapid traditional geostructural surveys. This technique allowed us to take measurements along the entire road, obtaining geometrical data for the discontinuities that are statistically representative of the rock mass and useful in defining the possible kinematic mechanisms and volumes of potentially detachable blocks. The main purpose of this study was to analyse how the geostructural features of a rock mass can affect the stability slope conditions at different scales in order to identify road sectors susceptible to different potential failure mechanisms using only kinematic analysis

ToppCluster: a multiple gene list feature analyzer for comparative enrichment clustering and network-based dissection of biological systems

ToppCluster is a web server application that leverages a powerful enrichment analysis and underlying data environment for comparative analyses of multiple gene lists. It generates heatmaps or connectivity networks that reveal functional features shared or specific to multiple gene lists. ToppCluster uses hypergeometric tests to obtain list-specific feature enrichment P-values for currently 17 categories of annotations of human-ortholog genes, and provides user-selectable cutoffs and multiple testing correction methods to control false discovery. Each nameable gene list represents a column input to a resulting matrix whose rows are overrepresented features, and individual cells per-list P-values and corresponding genes per feature. ToppCluster provides users with choices of tabular outputs, hierarchical clustering and heatmap generation, or the ability to interactively select features from the functional enrichment matrix to be transformed into XGMML or GEXF network format documents for use in Cytoscape or Gephi applications, respectively. Here, as example, we demonstrate the ability of ToppCluster to enable identification of list-specific phenotypic and regulatory element features (both cis-elements and 3′UTR microRNA binding sites) among tissue-specific gene lists. ToppCluster’s functionalities enable the identification of specialized biological functions and regulatory networks and systems biology-based dissection of biological states. ToppCluster can be accessed freely at http://toppcluster.cchmc.org

A High Statistics Measurement of the Lambdac+ Lifetime

A high statistics measurement of the Lambdac+ lifetime from the Fermilab fixed-target FOCUS photoproduction experiment is presented. We describe the analysis technique with particular attention to the determination of the systematic uncertainty. The measured value of 204.6 +/- 3.4 (stat.) +/- 2.5 (syst.) fs from 8034 +/- 122 Lambdac -> pKpi decays represents a significant improvement over the present world average.Comment: Submitted to Physical Review Letter

A Measurement of the Ds+ Lifetime

A high statistics measurement of the Ds+ lifetime from the Fermilab fixed-target FOCUS photoproduction experiment is presented. We describe the analysis of the two decay modes, Ds+ -> phi(1020)pi+ and Ds+ -> \bar{K}*(892)0K+, used for the measurement. The measured lifetime is 507.4 +/- 5.5 (stat.) +/- 5.1 (syst.) fs using 8961 +/- 105 Ds+ -> phi(1020)pi+ and 4680 +/- 90 Ds+ -> \bar{K}*(892)0K+ decays. This is a significant improvement over the present world average.Comment: 5 pages, 3 figures, 2 tables, submitted to PR

Search for CP Violation in the decays D+ -> K_S pi+ and D+ -> K_S K+

A high statistics sample of photo-produced charm from the FOCUS(E831) experiment at Fermilab has been used to search for direct CP violation in the decays D+->K_S pi+ and D+ -> K_S K+. We have measured the following asymmetry parameters relative to D+->K-pi+pi+: A_CP(K_S pi+) = (-1.6 +/- 1.5 +/- 0.9)%, A_CP(K_S K+) = (+6.9 +/- 6.0 +/- 1.5)% and A_CP(K_S K+) = (+7.1 +/- 6.1 +/- 1.2)% relative to D+->K_S pi+. The first errors quoted are statistical and the second are systematic. We also measure the relative branching ratios: \Gamma(D+->\bar{K0}pi+)/\Gamma(D+->K-pi+pi+) = (30.60 +/- 0.46 +/- 0.32)%, \Gamma(D+->\bar{K0}K+)/\Gamma(D+->K-pi+pi+) = (6.04 +/- 0.35 +/- 0.30)% and \Gamma(D+->\bar{K0}K+)/\Gamma(D+->\bar{K0}pi+) = (19.96 +/- 1.19 +/- 0.96)%.Comment: 4 pages, 3 figure

A Non-parametric Approach to the D+ to K*0bar mu+ nu Form Factors

Using a large sample of D+ -> K- pi+ mu+ nu decays collected by the FOCUS photoproduction experiment at Fermilab, we present the first measurements of the helicity basis form factors free from the assumption of spectroscopic pole dominance. We also present the first information on the form factor that controls the s-wave interference discussed in a previous paper by the FOCUS collaboration. We find reasonable agreement with the usual assumption of spectroscopic pole dominance and measured form factor ratios.Comment: 14 pages, 5 figures, and 2 tables. We updated the previous version by changing some words, removing one plot, and adding two tables. These changes are mostly stylisti

Search for Λc+→pK+π−\Lambda_c^+ \to p K^+ \pi^- and Ds+→K+K+π−D_s^+ \to K^+ K^+ \pi^- Using Genetic Programming Event Selection

We apply a genetic programming technique to search for the double Cabibbo suppressed decays $\Lambda_c^+ \to p K^+ \pi^-$ and $D_s^+ \to K^+ K^+ \pi^-$. We normalize these decays to their Cabibbo favored partners and find $\text{BR}($\Lambda_c^+ \to p K^+ \pi^-$)/\text{BR}($\Lambda_c^+ \to p K^- \pi^+$) = (0.05 \pm 0.26 \pm 0.02)$ and $\text{BR}($D_s^+ \to K^+ K^+ \pi^-$)/\text{BR}($D_s^+ \to K^+ K^- \pi^+$) = (0.52\pm 0.17\pm 0.11)$ where the first errors are statistical and the second are systematic. Expressed as 90% confidence levels (CL), we find $< 0.46$ and $< 0.78$ respectively. This is the first successful use of genetic programming in a high energy physics data analysis.Comment: 10 page

A measurement of branching ratios of D+D^+ and Ds+D^+_s hadronic decays to four-body final states containing a KSK_S

We have studied hadronic four-body decays of $D^+$ and $D^+_s$ mesons with a $K_S$ in the final state using data recorded during the 1996-1997 fixed-target run at Fermilab high energy photoproduction experiment FOCUS. We report a new branching ratio measurement of $\Gamma(D^+\to K_S K^-\pi^+\pi^+)/\Gamma(D^+\to K_S \pi^+\pi^+\pi^-)=0.0768\pm0.0041\pm0.0032$. We make the first observation of three new decay modes with branching ratios $\Gamma(D^+\to K_S K^+\pi^+\pi^-)/\Gamma(D^+\to K_S \pi^+\pi^+\pi^-)=0.0562\pm0.0039\pm0.0040$, \Gamma(D^+\to\K_S K^+ K^-\pi^+)/\Gamma(D^+\to K_S \pi^+\pi^+\pi^-)=0.0077\pm0.0015\pm0.0009, and $\Gamma(D^+_s\to K_S K^+\pi^+\pi^-)/\Gamma(D^+_s\to K_S K^-\pi^+\pi^+)=0.586\pm0.052\pm0.043$, where in each case the first error is statistical and the second error is systematic.Comment: 4 pages, 1 table, 2 figures, submitted to Physical Review Letter