Pose-based SLAM with probabilistic scan matching algorithm using a mechanical scanned imaging sonar

This paper proposes a pose-based algorithm to solve the full SLAM problem for an autonomous underwater vehicle (AUV), navigating in an unknown and possibly unstructured environment. The technique incorporate probabilistic scan matching with range scans gathered from a mechanical scanning imaging sonar (MSIS) and the robot dead-reckoning displacements estimated from a Doppler velocity log (DVL) and a motion reference unit (MRU). The proposed method utilizes two extended Kalman filters (EKF). The first, estimates the local path travelled by the robot while grabbing the scan as well as its uncertainty and provides position estimates for correcting the distortions that the vehicle motion produces in the acoustic images. The second is an augment state EKF that estimates and keeps the registered scans poses. The raw data from the sensors are processed and fused in-line. No priory structural information or initial pose are considered. The algorithm has been tested on an AUV guided along a 600 m path within a marina environment, showing the viability of the proposed approach

Formal Education, Mismatch and Wages After Transition: Assessing the Impact of Unobserved Heterogeneity using Matching Estimators

This paper studies the incidence and consequences of the mismatch between formal education and the educational requirements of jobs in Estonia during the years 1997-2003. We fi nd large wage penalties associated with the phenomenon of educational mismatch. Moreover, the incidence and wage penalty of mismatches increase with age. This suggests that structural educational mismatches can occur after fast transition periods. Our results are robust for various methodologies, and more importantly regarding departures from the exogeneity assumptions inherent in the matching estimators used in our analysis

Feature-based matching of underwater images

This work investigates performance of recent feature-based matching techniques when applied to registration of underwater images. Matching methods are tested versus different contrast enhancing pre-processing of images. As a result of the performed experiments for various dominating in images underwater artifacts and present deformation, the outperforming preprocessing, detection and description methods are proposed

LSB Matching Steganalysis Based on Patterns of Pixel Differences and Random Embedding

Peer-reviewed

Development of Color Difference Equations Matching to Human Vision System

Research on color difference evaluation has been active in recent thirty years. Several color difference formulas were developed for industrial applications. The aims of this thesis are to develop the color density which is denoted by comb g and to propose the color density based chromaticity difference formulas. Color density is derived from the discrimination ellipse parameters and color positions in the xy , xyY and CIELAB color spaces, and the color based chromaticity difference formulas are compared with the line element formulas and CIE 2000 color difference formulas. As a result of the thesis, color density represents the perceived color difference accurately, and it could be used to characterize a color by the attribute of perceived color difference from this color.

A validated method using RP-HPLC for quantification of reserpine in the Brazilian tree Rauvolfia sellowii Müll. Arg. (Apocynaceae)

This study describes a simple, fast and reproducible method using RP-HPLC-UV, in a gradient system, for quantification of reserpine in Rauvolfia sellowii stem bark. The analysis were carried out on a C18 column; mobile phase was water and acetonitrile, and separations were carried out in 10 min, flow rate of 1.0 mL min-1, 25 ºC and 268 nm. The validation data showed that the method was specific, accurate, precise and robust. Results were linear over a range of 0.625-40.0 μg mL-1, and the mean recovery was 95.1%. The amount of reserpine found in the dried stem bark was 0.01% (m/m).

Regeneration of five commercially-valuable tree species after experimental logging in an Amazonian forest

This study investigated the regeneration variation of five commercially valuable tree species in relation to different intensities of felling in fourteen 4-ha plots in an area under experimental forest management. This experiment was carried out in a typical Amazonian tropical forest sample on "terra-firme," in Manaus (AM). Plots were logged 7 and 8 years (1987 and 1988), or 3 years (1993) before the study. All trees with height greater than 2 m, and diameter at breast height (DBH) smaller than 10 cm were measured. Only Aniba hostmanniana, Ocotea aciphylla, Licaria pachycarpa, Eschweilera coriacea and Goupia glabra were sufficiently common for individual analyses. These species have high timber values in the local market. Eight years after logging, the species responded differently to logging intensities. The numbers of individuals of Goupia glabra and Aniba hostmanniana were positively related to the intensity of logging, while Ocotea aciphylla, Licaria pachycarpa, and Eschweilera coriacea showed no statistically significant response. In the most recently (1993) logged areas, Goupia glabra and Aniba hostmanniana had higher numbers of individuals than the control plots.