We consider the problem of calibrating range measurements of a Light Detection and Ranging (lidar) sensor that is dealing with the sensor nonlinearity and heteroskedastic, range-dependent, measurement error. We solved the calibration problem without using additional hardware, but rather exploiting assumptions on the environment surrounding the sensor during the calibration procedure. More specifically we consider the assumption of calibrating the sensor by placing it in an environment so that its measurements lie in a 2D plane that is parallel to the ground. Then, its measurements come from fixed objects that develop orthogonally w.r.t. the ground, so that they may be considered as fixed points in an inertial reference frame. Moreover, we consider the intuition that moving the distance sensor within this environment implies that its measurements should be such that the relative distances and angles among the fixed points above remain the same. We thus exploit this intuition to cast the sensor calibration problem as making its measurements comply with this assumption that “fixed features shall have fixed relative distances and angles”. The resulting calibration procedure does thus not need to use additional (typically expensive) equipment, nor deploy special hardware. As for the proposed estimation strategies, from a mathematical perspective we consider models that lead to analytically solvable equations, so to enable deployment in embedded systems. Besides proposing the estimators we moreover analyze their statistical performance both in simulation and with field tests. We report the dependency of the MSE performance of the calibration procedure as a function of the sensor noise levels, and observe that in field tests the approach can lead to a tenfold improvement in the accuracy of the raw measurements.
Background: Severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) is still a severe threaft for human health currently, and the researches about it is a focus topic worldwide.
Aim of the study: In this study, we will collect some laboratory results of the patients with coronavirus disease (COVID-19) to assess the function of liver, heart, kidney and even pancreas.
Subjects and Methods: Laboratory results of the patients with COVID-19 are collected. The biochemical indices are classified and used to assess the according function of liver, heart, kidney; meantime, and blood glucose is also observed and taken as an index to roughly evaluate pancreas.
Results: There were some in
... Show MoreBeta-irradiation effects on the microstructure of LDPE samples have been investigated
using Positron Annihilation Lifetime Technique (PALT). These effects on the orthopositronium
(o-Ps) Lifetime t3, the free positron annihilation lifetime 2 t , the free-volume
hole size (Vh) and the free volume fraction (fh) were measured as functions of Beta
irradiation - dose up to a total dose of 30.28 kGy.
The results show that the values of t3, Vh and fh increase gradually with increasing Beta
dose up to a total dose of 1.289 kGy, and reach a maximum increment of 17.4%, 32.8% and
5.86%, respectively, while t2 reachs maximum increment of 211.9% at a total dose of 1.59
kGy. Above these doses, the values show nonlinear changes u
A sensitive and selective method have been developed for the determination of palladium (II)and platinum (II) . A new reagent and two complexes have been prepared in ethanolic solutions .The method is based on the chelation of metal ions with 4-(4?- pyrazolon azo) resorcinol (APAR) to form intense color soluble products, that are stable and have a maximum absorption at 595 nm and at 463 nm and ?max of 1.11×10 4 and.1.35 ×104 Lmole-1cm-1 for Pd(II) Pt(II) respectively. A linear correlation of (1.4 – 0.2) and (3.2 -0.4 ) ppm for pd(II) pt(II) respectively .The stability constants , relative errors , a relative standard deviations for Pd(II) and Pt(II) were 0.40×105 , 0.4×104 L mol-1 ,0.34 - 0.21% and 2.4 – 0.91% respectively.
... Show MoreThis paper study two stratified quantile regression models of the marginal and the conditional varieties. We estimate the quantile functions of these models by using two nonparametric methods of smoothing spline (B-spline) and kernel regression (Nadaraya-Watson). The estimates can be obtained by solve nonparametric quantile regression problem which means minimizing the quantile regression objective functions and using the approach of varying coefficient models. The main goal is discussing the comparison between the estimators of the two nonparametric methods and adopting the best one between them
In this study, the results of x-ray diffraction methods were used to determine the Crystallite size and Lattice strain of Cu2O nanoparticles then to compare the results obtained by using variance analysis method, Scherrer method and Williamson-Hall method. The results of these methods of the same powder which is cuprous oxide, using equations during the determination the crystallite size and lattice strain, It was found that the results obtained the values of the crystallite size (28.302nm) and the lattice strain (0.03541) of the variance analysis method respectively and for the Williamson-Hall method were the results of the crystallite size (21.678nm) and lattice strain (0.00317) respectively, and Scherrer method which gives the value of c
... Show MoreBiological samples of mother's milk were collected from Iraqi southern provinces(Basrah,Messan,al-Muthana,Thikar)and Baghdad province to measure uranium concentration of the samples by using track technique of fission fragments as a result from uranium atom fission with thermal neutrons from neutrons source 24 I Am-Be with activity 16Ci and neutron flux of 5000 n/cm2.s on using nuclear track detector CR-39 It was found that the high percentage of depleted uranium concentration on the samples from Muthana province , which accounted as 4.183ppm therefore the samples was taken from the provinces (Thikar,Basrah,Baghdad),which was accounted the depleted uranium concentration as following (1.243,2.172,2.875) ppm respectively, with appear a small
... Show MoreIron oxide(Fe3O4) nanoparticles of different sizes and shapes were synthesized by solve-hydrothermal reaction assisted by microwave irradiation using ferrous ammonium sulfate as a metal precursor, oleic acid as dispersing agent, ethanol as reducing agent and NaOH as precipitating agent at pH=12. The synthesized Fe3O4 nano particles were characterized by X-ray diffraction (XRD), FTIR and thermal analysis TG-DTG. Sizes and shapes of Fe3O4 nanoparticles were characterized by Scanning Electron Microscopy (SEM), and atomic force microscopy (AFM).