Optical Enhancement of Exoskeleton-Based Estimation of Glenohumeral Angles

In Robot-Assisted Rehabilitation (RAR) the accurate estimation of the patient limb joint angles is critical for assessing therapy efficacy. In RAR, the use of classic motion capture systems (MOCAPs) (e.g., optical and electromagnetic) to estimate the Glenohumeral (GH) joint angles is hindered by the exoskeleton body, which causes occlusions and magnetic disturbances. Moreover, the exoskeleton posture does not accurately reflect limb posture, as their kinematic models differ. To address the said limitations in posture estimation, we propose installing the cameras of an optical marker-based MOCAP in the rehabilitation exoskeleton. Then, the GH joint angles are estimated by combining the estimated marker poses and exoskeleton Forward Kinematics. Such hybrid system prevents problems related to marker occlusions, reduced camera detection volume, and imprecise joint angle estimation due to the kinematic mismatch of the patient and exoskeleton models. This paper presents the formulation, simulation, and accuracy quantification of the proposed method with simulated human movements. In addition, a sensitivity analysis of the method accuracy to marker position estimation errors, due to system calibration errors and marker drifts, has been carried out. The results show that, even with significant errors in the marker position estimation, method accuracy is adequate for RAR.

In Situ Characterization of Optical Absorption by Carbonaceous Aerosols: Calibration and Measurement

Light absorption by aerosols has a great impact on climate change. A Photoacoustic spectrometer (PA) coupled with aerosol-based classification techniques represents an in situ method that can quantify the light absorption by aerosols in a real time, yet significant differences have been reported using this method versus filter based methods or the so-called difference method based upon light extinction and light scattering measurements. This dissertation focuses on developing calibration techniques for instruments used in measuring the light absorption cross section, including both particle diameter measurements by the differential mobility analyzer (DMA) and light absorption measurements by PA. Appropriate reference materials were explored for the calibration/validation of both measurements. The light absorption of carbonaceous aerosols was also investigated to provide fundamental understanding to the absorption mechanism. The first topic of interest in this dissertation is the development of calibration nanoparticles. In this study, bionanoparticles were confirmed to be a promising reference material for particle diameter as well as ion-mobility. Experimentally, bionanoparticles demonstrated outstanding homogeneity in mobility compared to currently used calibration particles. A numerical method was developed to calculate the true distribution and to explain the broadening of measured distribution. The high stability of bionanoparticles was also confirmed. For PA measurement, three aerosol with spherical or near spherical shapes were investigated as possible candidates for a reference standard: C60, copper and silver. Comparisons were made between experimental photoacoustic absorption data with Mie theory calculations. This resulted in the identification of C60 particles with a mobility diameter of 150 nm to 400 nm as an absorbing standard at wavelengths of 405 nm and 660 nm. Copper particles with a mobility diameter of 80 nm to 300 nm are also shown to be a promising reference candidate at wavelength of 405 nm. The second topic of this dissertation focuses on the investigation of light absorption by carbonaceous particles using PA. Optical absorption spectra of size and mass selected laboratory generated aerosols consisting of black carbon (BC), BC with non-absorbing coating (ammonium sulfate and sodium chloride) and BC with a weakly absorbing coating (brown carbon derived from humic acid) were measured across the visible to near-IR (500 nm to 840 nm). The manner in which BC mixed with each coating material was investigated. The absorption enhancement of BC was determined to be wavelength dependent. Optical absorption spectra were also taken for size and mass selected smoldering smoke produced from six types of commonly seen wood in a laboratory scale apparatus.

Texture-Detail Preservation Measurement in Camera Phones: An Updated Approach

Recent advances in mobile phone cameras have poised them to take over compact hand-held cameras as the consumer’s preferred camera option. Along with advances in the number of pixels, motion blur removal, face-tracking, and noise reduction algorithms have significant roles in the internal processing of the devices. An undesired effect of severe noise reduction is the loss of texture (i.e. low-contrast fine details) of the original scene. Current established methods for resolution measurement fail to accurately portray the texture loss incurred in a camera system. The development of an accurate objective method to identify the texture preservation or texture reproduction capability of a camera device is important in this regard. The ‘Dead Leaves’ target has been used extensively as a method to measure the modulation transfer function (MTF) of cameras that employ highly non-linear noise-reduction methods. This stochastic model consists of a series of overlapping circles with radii r distributed as r−3, and having uniformly distributed gray level, which gives an accurate model of occlusion in a natural setting and hence mimics a natural scene. This target can be used to model the texture transfer through a camera system when a natural scene is captured. In the first part of our study we identify various factors that affect the MTF measured using the ‘Dead Leaves’ chart. These include variations in illumination, distance, exposure time and ISO sensitivity among others. We discuss the main differences of this method with the existing resolution measurement techniques and identify the advantages. In the second part of this study, we propose an improvement to the current texture MTF measurement algorithm. High frequency residual noise in the processed image contains the same frequency content as fine texture detail, and is sometimes reported as such, thereby leading to inaccurate results. A wavelet thresholding based denoising technique is utilized for modeling the noise present in the final captured image. This updated noise model is then used for calculating an accurate texture MTF. We present comparative results for both algorithms under various image capture conditions.

Guided Bus Rapid Transit

Electrical Bus Rapid Transit (eBRT) is a charging electrical public transport which brings a clean, high performance, and affordable cost alternative from the conventional traffic vehicles which work with combustion and hybrid technology. These buses charge the battery in every bus stop to arrive at the next station. But, this charging system needs an appropriate infrastructure called pantograph, and it requires a high precision bus location to maintain battery lifetime, energy saving and charging time. To overcome this issue Vicomtech and Datik has planned a project based on computer vision to help to the driver to locate the vehicle in the correct place. In this document, we present a mono camera bus driver guided fast algorithm because these vehicles embedded computers do not support high computation and precision operations. In addition to the frequent lane sign, there are more accurate geometric beacons painted on the road to bring metric information to the vision system. This method uses segmentation to binarize the image discriminating the background space. Besides it detects, tracks and counts different lane mark contours in addition to classify each special painted mark. Besides it does not need any calibration task to calculate longitudinal and cross distances because we know the lane mark sizes.

TEST-ANALYSIS MODEL CORRELATION AND CALIBRATION OF A MULTI-COMPONENT PLASTIC PART

The goal of this project is to learn the necessary steps to create a finite element model, which can accurately predict the dynamic response of a Kohler Engines Heavy Duty Air Cleaner (HDAC). This air cleaner is composed of three glass reinforced plastic components and two air filters. Several uncertainties arose in the finite element (FE) model due to the HDAC’s component material properties and assembly conditions. To help understand and mitigate these uncertainties, analytical and experimental modal models were created concurrently to perform a model correlation and calibration. Over the course of the project simple and practical methods were found for future FE model creation. Similarly, an experimental method for the optimal acquisition of experimental modal data was arrived upon. After the model correlation and calibration was performed a validation experiment was used to confirm the FE models predictive capabilities.

The Development of Calibrants through Characterization of Volatile Organic Compounds from Peroxide Based Explosives and a Non-target Chemical Calibration Compound

Detection canines represent the fastest and most versatile means of illicit material detection. This research endeavor in its most simplistic form is the improvement of detection canines through training, training aids, and calibration. This study focuses on developing a universal calibration compound for which all detection canines, regardless of detection substance, can be tested daily to ensure that they are working with acceptable parameters. Surrogate continuation aids (SCAs) were developed for peroxide based explosives along with the validation of the SCAs already developed within the International Forensic Research Institute (IFRI) prototype surrogate explosives kit. Storage parameters of the SCAs were evaluated to give recommendations to the detection canine community on the best possible training aid storage solution that minimizes the likelihood of contamination. Two commonly used and accepted detection canine imprinting methods were also evaluated for the speed in which the canine is trained and their reliability. As a result of the completion of this study, SCAs have been developed for explosive detection canine use covering: peroxide based explosives, TNT based explosives, nitroglycerin based explosives, tagged explosives, plasticized explosives, and smokeless powders. Through the use of these surrogate continuation aids a more uniform and reliable system of training can be implemented in the field than is currently used today. By examining the storage parameters of the SCAs, an ideal storage system has been developed using three levels of containment for the reduction of possible contamination. The developed calibration compound will ease the growing concerns over the legality and reliability of detection canine use by detailing the daily working parameters of the canine, allowing for Daubert rules of evidence admissibility to be applied. Through canine field testing, it has been shown that the IFRI SCAs outperform other commercially available training aids on the market. Additionally, of the imprinting methods tested, no difference was found in the speed in which the canines are trained or their reliability to detect illicit materials. Therefore, if the recommendations discovered in this study are followed, the detection canine community will greatly benefit through the use of scientifically validated training techniques and training aids.

Atmospheric calibration for sub-millimeter radio astronomy

This thesis is focused on improving the calibration accuracy of sub-millimeter astronomical observations. The wavelength range covered by observational radio astronomy has been extended to sub-millimeter and far infrared with the advancement of receiver technology in recent years. Sub-millimeter observations carried out with airborne and ground-based telescopes typically suffer from 10% to 90% attenuation of the astronomical source signals by the terrestrial atmosphere. The amount of attenuation can be derived from the measured brightness of the atmospheric emission. In order to do this, the knowledge of the atmospheric temperature and chemical composition, as well as the frequency-dependent optical depth at each place along the line of sight is required. The altitude-dependent air temperature and composition are estimated using a parametrized static atmospheric model, which is described in Chapter 2, because direct measurements are technically and financially infeasible. The frequency dependent optical depth of the atmosphere is computed with a radiative transfer model based on the theories of quantum mechanics and, in addition, some empirical formulae. The choice, application, and improvement of third party radiative transfer models are discussed in Chapter 3. The application of the calibration procedure, which is described in Chapter 4, to the astronomical data observed with the SubMillimeter Array Receiver for Two Frequencies (SMART), and the German REceiver for Astronomy at Terahertz Frequencies (GREAT), is presented in Chapters 5 and 6. The brightnesses of atmospheric emission were fitted consistently to the simultaneous multi-band observation data from GREAT at 1.2 ∼ 1.4 and 1.8 ∼ 1.9 THz with a single set of parameters of the static atmospheric model. On the other hand, the cause of the inconsistency between the model parameters fitted from the 490 and 810 GHz data of SMART is found to be the lack of calibration of the effective cold load temperature. Besides the correctness of atmospheric modeling, the stability of the receiver is also important to achieving optimal calibration accuracy. The stabilities of SMART and GREAT are analyzed with a special calibration procedure, namely the “load calibration". The effects of the drift and fluctuation of the receiver gain and noise temperature on calibration accuracy are discussed in Chapters 5 and 6. Alternative observing strategies are proposed to combat receiver instability. The methods and conclusions presented in this thesis are applicable to the atmospheric calibration of sub-millimeter astronomical observations up to at least 4.7 THz (the H channel frequency of GREAT) for observations carried out from ∼ 4 to 14 km altitude. The procedures for receiver gain calibration and stability test are applicable to other instruments using the same calibration approach as that for SMART and GREAT. The structure of the high performance, modular, and extensible calibration program used and further developed for this thesis work is presented in the Appendix C.

Calibration of Grassmaster II to estimate green and dry matter yield in Mediterranean pastures: effects of pasture moisture content

Accurate assessment of standing pasture biomass in livestock production systems is a major factor for improving feed planning. Several tools are available to achieve this, including the GrassMaster II capacitance meter. This tool relies on an electrical signal, which is modified by the surrounding pasture. There is limited knowledge on how this capacitance meter performs in Mediterranean pastures. Therefore, we evaluated the GrassMaster II under Mediterranean conditions to determine (i) the effect of pasture moisture content (PMC) on the meter’s ability to estimate pasture green matter (GM) and dry matter (DM) yields, and (ii) the spatial variability and temporal stability of corrected meter readings (CMR) and DM in a bio-diverse pasture. Field tests were carried out with typical pastures of the southern region of Portugal (grasses, legumes, mixture and volunteer annual species) and at different phenological stages (and different PMC). There were significant positive linear relations between CMR and GM (r2 = 0.60, P < 0.01) and CMR and DM (r2 = 0.35, P < 0.05) for all locations (n = 347). Weak relationships were found for PMC (%) v. slope and coefficient of determination for both GM and DM. A significant linear relation existed for CMR v. GM and DM for PMC >80% (r2= 0.57, P < 0.01, RMSE = 2856.7 kg ha–1, CVRMSE=17.1% to GM; and r2= 0.51, P < 0.01,RMSE = 353.7 kg ha–1, CVRMSE = 14.3% to DM). Therefore, under the conditions of this current study there exists an optimum PMC (%) for estimating both GM and DM with the GrassMaster II. Repeated-measurements taken at the same location on different dates and conditions in a bio-diverse pasture showed similar and stable patterns between CMR and DM (r2= 0.67, P < 0.01, RMSE = 136.1 kg ha–1, CVRMSE = 6.5%). The results indicate that the GrassMaster II in-situ technique could play a crucial role in assessing pasture mass to improve feed planning under Mediterranean conditions.

Cloud Base Height Measurement System Based on Stereo Vision with Automatic Calibration

Clouds are important in weather prediction, climate studies and aviation safety. Important parameters include cloud height, type and cover percentage. In this paper, the recent improvements in the development of a low-cost cloud height measurement setup are described. It is based on stereo vision with consumer digital cameras. The cameras positioning is calibrated using the position of stars in the night sky. An experimental uncertainty analysis of the calibration parameters is performed. Cloud height measurement results are presented and compared with LIDAR measurements.

Calibration of the maximum carboxylation velocity (Vcmax) using data mining techniques and ecophysiological data from the Brazilian Semiarid region, for use in Dynamic Global Vegetation Models.

The semiarid region of northeastern Brazil, the Caatinga, is extremely important due to its biodiversity and endemism. Measurements of plant physiology are crucial to the calibration of Dynamic Global Vegetation Models (DGVMs) that are currently used to simulate the responses of vegetation in face of global changes. In a field work realized in an area of preserved Caatinga forest located in Petrolina, Pernambuco, measurements of carbon assimilation (in response to light and CO2) were performed on 11 individuals of Poincianella microphylla, a native species that is abundant in this region. These data were used to calibrate the maximum carboxylation velocity (Vcmax) used in the INLAND model. The calibration techniques used were Multiple Linear Regression (MLR), and data mining techniques as the Classification And Regression Tree (CART) and K-MEANS. The results were compared to the UNCALIBRATED model. It was found that simulated Gross Primary Productivity (GPP) reached 72% of observed GPP when using the calibrated Vcmax values, whereas the UNCALIBRATED approach accounted for 42% of observed GPP. Thus, this work shows the benefits of calibrating DGVMs using field ecophysiological measurements, especially in areas where field data is scarce or non-existent, such as in the Caatinga

Inertial and magnetic sensors for upper limb kinematics: modeling, calibration, sensor fusion and clinical applications

The primary aim of the research activity presented in this PhD thesis was the development of an innovative hardware and software solution for creating a unique tool for kinematics and electromyographic analysis of the human body in an ecological setting. For this purpose, innovative algorithms have been proposed regarding different aspects of inertial and magnetic data elaboration: magnetometer calibration and magnetic field mapping (Chapter 2), data calibration (Chapter 3) and sensor-fusion algorithm. Topics that may conflict with the confidentiality agreement between University of Bologna and NCS Lab will not be covered in this thesis. After developing and testing the wireless platform, research activities were focused on its clinical validation. The first clinical study aimed to evaluate the intra and interobserver reproducibility in order to evaluate three-dimensional humero-scapulo-thoracic kinematics in an outpatient setting (Chapter 4). A second study aimed to evaluate the effect of Latissimus Dorsi Tendon Transfer on shoulder kinematics and Latissimus Dorsi activation in humerus intra - extra rotations (Chapter 5). Results from both clinical studies have demonstrated the ability of the developed platform to enter into daily clinical practice, providing useful information for patients' rehabilitation.

Virtual Calibration of CO2 and Pollutant Emissions of a High-Performance PHEV using Model-in-the-Loop Methodology

The study analyses the calibration process of a newly developed high-performance plug-in hybrid electric passenger car powertrain. The complexity of modern powertrains and the more and more restrictive regulations regarding pollutant emissions are the primary challenges for the calibration of a vehicle’s powertrain. In addition, the managers of OEM need to know as earlier as possible if the vehicle under development will meet the target technical features (emission included). This leads to the necessity for advanced calibration methodologies, in order to keep the development of the powertrain robust, time and cost effective. The suggested solution is the virtual calibration, that allows the tuning of control functions of a powertrain before having it built. The aim of this study is to calibrate virtually the hybrid control unit functions in order to optimize the pollutant emissions and the fuel consumption. Starting from the model of the conventional vehicle, the powertrain is then hybridized and integrated with emissions and aftertreatments models. After its validation, the hybrid control unit strategies are optimized using the Model-in-the-Loop testing methodology. The calibration activities will proceed thanks to the implementation of a Hardware-in-the-Loop environment, that will allow to test and calibrate the Engine and Transmission control units effectively, besides in a time and cost saving manner.