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A systematic introduction to the concepts and techniques of computer image processing and recognition is presented. Consideration is given to such topics as image formation and perception; computer representation of images; image enhancement and restoration; reconstruction from projections; digital television, encoding, and data compression; scene understanding; scene matching and recognition; and processing techniques for linear systems.
The goal of the present study was to investigate the adaptive effects of variation in the direction of optic flow, experienced during linear treadmill walking, on modifying locomotor trajectory. Subjects (n = 30) walked on a motorized linear treadmill at 4.0 km/h for 24 minutes while viewing the interior of a 3D virtual scene projected onto a screen 1.5 m in front of them. The virtual scene depicted constant self-motion equivalent to either 1) walking around the perimeter of a room to one s left (Rotating Room group) 2) walking down the center of a hallway (Infinite Hallway group). The scene was static for the first 4 minutes, and then constant rate self-motion was simulated for the remaining 20 minutes. Before and after the treadmill locomotion adaptation period, subjects performed five stepping trials where in each trial they marched in place to the beat of a metronome at 90 steps/min while blindfolded in a quiet room. The subject s final heading direction (deg), final X (for-aft, cm) and final Y (medio-lateral, cm) positions were measured for each trial. During the treadmill locomotion adaptation period subject s 3D torso position was measured. We found that subjects in the Rotating Room group as compared to the Infinite Hallway group: 1) showed significantly greater deviation during post exposure testing in the heading direction and Y position opposite to the direction of optic flow experienced during treadmill walking 2) showed a significant monotonically increasing torso yaw angular rotation bias in the direction of optic flow during the treadmill adaptation exposure period. Subjects in both groups showed greater forward translation (in the +X direction) during the post treadmill stepping task that differed significantly from their pre exposure performance. Subjects in both groups reported no perceptual deviation in position during the stepping tasks. We infer that 3 viewing simulated rotary self-motion during treadmill locomotion causes adaptive modification of sensory-motor integration in the control of position and trajectory during locomotion which functionally reflects adaptive changes in the integration of visual, vestibular, and proprioceptive cues. Such an adaptation in the control of position and heading direction during locomotion due to the congruence of sensory information demonstrates the potential for adaptive transfer between sensorimotor systems and suggests a common neural site for the processing and self-motion perception and concurrent adaptation in motor output. This will result in lack of subjects perception of deviation of position and trajectory during the post treadmill step test while blind folded.
While at JSC for the summer of 2011, I was assigned to work on the sensor test for Orion relative-navigation risk mitigation (STORRM) development test objective (DTO). The STORRM DTO was flown on-board Endeavor during STS-134. The objective of the STORRM DTO is to test the visual navigation system (VNS), which will be used as the primary relative navigation sensor for the Orion spacecraft. The VNS is a flash lidar system intended to provide both line of sight and range information during rendezvous and proximity operations. The STORRM DTO also serves as a testbed for the high-resolution docking camera. This docking camera will be used to provide piloting cues for the crew during proximity operations. These instruments were mounted next to the trajectory control sensor (TCS) in Endeavour s payload bay. My principle objective for the summer was to generate a best estimated trajectory (BET) for Endeavor using the flight data collected by the VNS during rendezvous and the unprecedented re-rendezvous with the ISS. I processed the raw images from the VNS to produce range and bearing measurements. I then aggregated these measurements and extracted the measurements corresponding to individual reflectors. I combined the information contained in these measurements with data from the Endeavour's inertial sensors using Kalman smoothing techniques to ultimately produce a BET. This work culminated with a final presentation of the result to division management. Development of this tool required that traditional linear smoothing techniques be modified in a novel fashion to permit for the inclusion of non-linear measurements. This internship has greatly helped me further my career by providing exposure to real engineering projects. I also have benefited immensely from the mentorship of the engineers working on these projects. Many of the lessons I learned and experiences I had are of particular value because then can only be found in a place like JSC.
A compact long-wave infrared (LWIR) channeled spectro-polarimeter (IRCSP) has been developed for integration into the NASA Earth Science Technology Office (ESTO) funded submm-wave and LWIR polarimeters project to measure the microphysical properties of cloud ice. Once deployed, the IRCSP will produce the first linear Stokes measurements ( S0 , S1 , S2 ) of upper-tropospheric cirrus clouds from 8.5 to 12.5 μm. For the first time, a compact, light-weight, and uncooled LWIR polarimeter with off-the-shelf thermal optical components is demonstrated. We report narrowband calibration measurements which quantify metrics of polarimetric system performance. The response of the system to linearly polarized light is shown to agree with both a Mueller matrix model and modulation function for narrowband calibration measurements with an R2 > 0.98 from 8 to 11 μm. The polarimetric efficiency is >0.8 from 8 to 11 μm for narrowband measurements indicating satisfactory performance of the polarization optics. Beyond 11 μm, the agreement is significantly reduced as thermal noise compounds with reduced detector response. Ultimately, the observed system performance is limited by the spectral response of the detector past 11 μm in addition to the thermal noise inherent for the measurements at room temperature.
Our planet’s energy balance is sensitive to spatial inhomogeneities in sea surface temperature and sea ice changes, but this is typically ignored in climate projections. Here, we show the energy budget during recent decades can be closed by combining changes in effective radiative forcing, linear radiative damping and this pattern effect. The pattern effect is of comparable magnitude but opposite sign to Earth’s net energy imbalance in the 2000s, indicating its importance when predicting the future climate on the basis of observations. Additionally, after the pattern effect is accounted for, the best-estimate value of committed global warming at present-day forcing rises from 1.31 K (0.99–2.33 K, 5th–95th percentile) to over 2 K, and committed warming in 2100 with constant long-lived forcing increases from 1.32 K (0.94–2.03 K) to over 1.5 K, although the magnitude is sensitive to sea surface temperature dataset. Further constraints on the pattern effect are needed to reduce climate projection uncertainty.
A new type of real-time radiation monitoring device, RRMD-III, consisting of three double-sided silicon strip detectors (DSSDs), has been developed and tested on-board the Space Shuttle mission STS-84. The test succeeded in measuring the linear energy transfer (LET) distribution over the range of 0.2 keV/micrometer to 600 keV/micrometer for 178 h. The Shuttle cruised at an altitude of 300 to 400 km and an inclination angle of 51.6 degrees for 221.3 h, which is equivalent to the International Space Station orbit. The LET distribution obtained for particles was investigated by separating it into galactic cosmic ray (GCR) particles and trapped particles in the South Atlantic Anomaly (SAA) region. The result shows that the contribution in dose-equivalent due to GCR particles is almost equal to that from trapped particles. The total absorbed dose rate during the mission was 0.611 mGy/day; the effective quality factor, 1.64; and the dose equivalent rate, 0.998 mSv/day. The average absorbed dose rates are 0.158 mGy/min for GCR particles and 3.67 mGy/min for trapped particles. The effective quality factors are 2.48 for GCR particles and 1.19 for trapped particles. The absorbed doses obtained by the RRMD-III and a conventional method using TLD (Mg(2)SiO(4)), which was placed around the RRMD-III were compared. It was found that the TLDs showed a lower efficiency, just 58% of absorbed dose registered by the RRMD-III.
This project evaluated and developed new mathematical and algorithmic techniques capable of handling (in real-time) the growing amounts of data generated by modern fusion research. While existing numerical linear algebra (NLA) methods provide the backbone to classical data analysis and algorithms, these methods fundamentally do not port to distributed architectures nor do they allow low-latency data reduction for control. Motivated by the needs for modern fusion reactors, this project explored and implemented new numerical methods to characterize plasma dynamics, respond in real-time to discharge evolution, and to process massive-scale data accurately and rapidly more fully. This project links expertise in multiple-sensor diagnostics of tokamak plasma dynamics from Columbia University’s Plasma Physics Laboratory with expertise in massive-scale data reduction and extreme data control algorithms at Columbia University’s Data Science Institute. This interdisciplinary project (i) applied machine learning methods, (ii) implemented a properly-trained neural-network for very fast processing of high-speed plasma videography, and (ii) developed the applied mathematical methods, based on randomized-NLA (rNLA) routines, for data analysis, reduction, and real-time control. The Columbia University High Beta Tokamak-Extended Pulse (HBT-EP) facility provided data to test new algorithms and partnership with Columbia University's Data Sciences Institute evaluated the broader use of new algorithms for many challenging control applications.
On a high level, the larger project in question, HydroGEN, aims to develop software used for finding equations of state (EOS) to optimize catalyst configuration for H 2 production through water splitting. In particular, this summer project focused on solving the nonlinear equations used in fitting the equations. This problem involved using Python to solve a linear system with nonlinear constraints. In order for this to be achieved, Pyomo was used to build a model and the solver Ipopt, interior point optimizer, was used. Pyomo is a Python-based language developed at Sandia; it is an optimization modeling language. Rather than solving the entire problem at once, a toy problem was created, simplifying the problem down to the most important focus. This problem had a known solution, comparable to the calculated solution to assess accuracy and as progress was made towards finding solutions, complexity was gradually added to the problem. After building and solving the toy problem, it was found that it gave reasonably accurate solutions, better compared to the two existing solvers previously used with this project in terms of functionality. The solver is now ready for implementation into the project’s main software.
Fermilab has a project to improve the proton beam energy which is called PIP-II (the 2nd Proton Improvement Plan). There is a superconducting linear accelerator, LINAC, to improve the proton beam power and the LINAC consists of 5 types of cryomodules (CM), 1 HWR CM, 2 SSR1 CM, 4 SSR2 CM, LB650 CM, and HB650 CM. The prototypes of these cryomodules are being tested at Fermilab’s CryoModule Test Facility (CMTF). Heat load measurements are an important part of the prototype CM testing. The CMTF cryogenic control system was developed based on the ACNET (Accelerator Control NETwork) for CM testing for other projects, but the PIP-II cryogenic control system will be implemented using the Experimental Physics and Industrial Control System (EPICS). As part of the prototype CM testing campaign an EPICS based control system has been implemented at CMTF. This EPICS cryogenic control system includes real time heat load calculation software utilizing the Fortran implementation of Hepak. This paper details the real time heat load calculation software developed for the prototype CM testing including the first results from the HB 650 CM.
Fermilab has a project to improve the proton beam energy which is called PIP-II (the 2nd Proton Improvement Plan). There is a superconducting linear accelerator, LINAC, to improve the proton beam power and the LINAC consists of 5 types of cryomodules (CM), 1 HWR CM, 2 SSR1 CM, 4 SSR2 CM, LB650 CM, and HB650 CM. The prototypes of these cryomodules are being tested at Fermilab’s CryoModule Test Facility (CMTF). Heat load measurements are an important part of the prototype CM testing. The CMTF cryogenic control system was developed based on the ACNET (Accelerator Control NETwork) for CM testing for other projects, but the PIP-II cryogenic control system will be implemented using the Experimental Physics and Industrial Control System (EPICS). As part of the prototype CM testing campaign, an EPICS based control system has been implemented at CMTF. This EPICS cryogenic control system includes real-time heat load calculation software utilizing the Fortran implementation of Hepak. This paper details the real time heat load calculation software developed for the prototype CM testing including the first results from the HB650 CM.
Compliance of member States to the Treaty on the Non-Proliferation of Nuclear Weapons is monitored through nuclear safeguards. The Passive Gamma Emission Tomography (PGET) system is a novel instrument developed within the framework of the International Atomic Energy Agency (IAEA) project JNT 1510, which included the European Commission, Finland, Hungary and Sweden. The PGET is used for the verification of spent nuclear fuel stored in water pools. Advanced image reconstruction techniques are crucial for obtaining high-quality cross-sectional images of the spent-fuel bundle to allow inspectors of the IAEA to monitor nuclear material and promptly identify its diversion. In this work, we have developed a software suite to accurately reconstruct the spent-fuel cross sectional image, automatically identify present fuel rods, and estimate their activity. Unique image reconstruction challenges are posed by the measurement of spent fuel, due to its high activity and the self-attenuation. While the former is mitigated by detector physical collimation, we implemented a linear forward model to model the detector responses to the fuel rods inside the PGET, to account for the latter. The image reconstruction is performed by solving a regularized linear inverse problem using the fast-iterative shrinkage-thresholding algorithm. We have also implemented the traditional filtered back projection (FBP) method based on the inverse Radon transform for comparison and applied both methods to reconstruct images of simulated mockup fuel assemblies. Higher image resolution and fewer reconstruction artifacts were obtained with the inverse-problem approach, with the mean-square-error reduced by 50%, and the structural-similarity improved by 200%. We then used a convolutional neural network (CNN) to automatically identify the bundle type and extract the pin locations from the images; the estimated activity levels finally being compared with the ground truth. The proposed computational methods accurately estimated the activity levels of the present pins, with an associated uncertainty of approximately 5%.
Rh3(PbS)2 crystallizes in the trigonal R-3m space group. The structure is three-dimensional. Rh is bonded in a distorted linear geometry to four Pb and two equivalent S atoms. There are two shorter (2.89 Å) and two longer (2.91 Å) Rh–Pb bond lengths. Both Rh–S bond lengths are 2.34 Å. There are two inequivalent Pb sites. In the first Pb site, Pb is bonded to six equivalent Rh and two equivalent S atoms to form corner-sharing PbRh6S2 hexagonal bipyramids. Both Pb–S bond lengths are 3.08 Å. In the second Pb site, Pb is bonded in a hexagonal planar geometry to six equivalent Rh atoms. S is bonded in a 4-coordinate geometry to three equivalent Rh and one Pb atom.
Pd3(PbS)2 crystallizes in the trigonal R-3m space group. The structure is three-dimensional. Pd is bonded in a distorted linear geometry to four Pb and two equivalent S atoms. There are two shorter (2.93 Å) and two longer (3.04 Å) Pd–Pb bond lengths. Both Pd–S bond lengths are 2.36 Å. There are two inequivalent Pb sites. In the first Pb site, Pb is bonded to six equivalent Pd and two equivalent S atoms to form corner-sharing PbPd6S2 hexagonal bipyramids. Both Pb–S bond lengths are 3.11 Å. In the second Pb site, Pb is bonded in a hexagonal planar geometry to six equivalent Pd atoms. S is bonded in a 4-coordinate geometry to three equivalent Pd and one Pb atom.
LiSr3Ta4(O6F)2 crystallizes in the trigonal R-3m space group. The structure is three-dimensional. Li1+ is bonded in a distorted linear geometry to six equivalent O2- and two equivalent F1- atoms. All Li–O bond lengths are 2.76 Å. Both Li–F bond lengths are 1.97 Å. Sr2+ is bonded to six O2- and two equivalent F1- atoms to form distorted SrO6F2 hexagonal bipyramids that share edges with four equivalent SrO6F2 hexagonal bipyramids and edges with six TaO6 octahedra. There are four shorter (2.67 Å) and two longer (2.69 Å) Sr–O bond lengths. Both Sr–F bond lengths are 2.43 Å. There are two inequivalent Ta+4.75+ sites. In the first Ta+4.75+ site, Ta+4.75+ is bonded to six O2- atoms to form TaO6 octahedra that share corners with six TaO6 octahedra and edges with four equivalent SrO6F2 hexagonal bipyramids. The corner-sharing octahedra tilt angles range from 39–45°. There are four shorter (2.01 Å) and two longer (2.02 Å) Ta–O bond lengths. In the second Ta+4.75+ site, Ta+4.75+ is bonded to six equivalent O2- atoms to form TaO6 octahedra that share corners with six equivalent TaO6 octahedra and edges with six equivalent SrO6F2 hexagonal bipyramids. The corner-sharing octahedral tilt angles are 45°. All Ta–O bond lengths are 2.03 Å. There are two inequivalent O2- sites. In the first O2- site, O2- is bonded in a 4-coordinate geometry to two equivalent Sr2+ and two Ta+4.75+ atoms. In the second O2- site, O2- is bonded in a 2-coordinate geometry to one Li1+, one Sr2+, and two equivalent Ta+4.75+ atoms. F1- is bonded to one Li1+ and three equivalent Sr2+ atoms to form distorted corner-sharing FSr3Li tetrahedra.
Pd3(PbSe)2 crystallizes in the trigonal R-3m space group. The structure is three-dimensional. Pd is bonded in a distorted linear geometry to four Pb and two equivalent Se atoms. There are two shorter (3.03 Å) and two longer (3.04 Å) Pd–Pb bond lengths. Both Pd–Se bond lengths are 2.48 Å. There are two inequivalent Pb sites. In the first Pb site, Pb is bonded to six equivalent Pd and two equivalent Se atoms to form corner-sharing PbPd6Se2 hexagonal bipyramids. Both Pb–Se bond lengths are 3.18 Å. In the second Pb site, Pb is bonded in a hexagonal planar geometry to six equivalent Pd atoms. Se is bonded in a 4-coordinate geometry to three equivalent Pd and one Pb atom.
Rh3(PbSe)2 crystallizes in the trigonal R-3m space group. The structure is three-dimensional. Rh is bonded in a distorted linear geometry to four Pb and two equivalent Se atoms. There are two shorter (2.91 Å) and two longer (2.98 Å) Rh–Pb bond lengths. Both Rh–Se bond lengths are 2.45 Å. There are two inequivalent Pb sites. In the first Pb site, Pb is bonded to six equivalent Rh and two equivalent Se atoms to form corner-sharing PbRh6Se2 hexagonal bipyramids. Both Pb–Se bond lengths are 3.14 Å. In the second Pb site, Pb is bonded in a 6-coordinate geometry to six equivalent Rh atoms. Se is bonded in a 4-coordinate geometry to three equivalent Rh and one Pb atom.
A key challenge in inverse problems is the selection of sensors to gather the most effective data. In this paper, we consider the problem of inferring the initial condition to a linear dynamical system and develop an efficient control-theoretical approach for greedily selecting sensors. Our method employs a Galerkin projection to reduce the size of the inverse problem, resulting in a computationally efficient algorithm for sensor selection. As a byproduct of our algorithm, we obtain a preconditioner for the inverse problem that enables the rapid recovery of the initial condition. Here, we analyze the theoretical performance of our greedy sensor selection algorithm as well as the performance of the associated preconditioner. Finally, we verify our theoretical results on various inverse problems involving partial differential equations.
This paper proposes a novel approach for learning a data-driven quadratic manifold from high-dimensional data, then employing this quadratic manifold to derive efficient physics-based reduced-order models. The key ingredient of the approach is a polynomial mapping between high-dimensional states and a low-dimensional embedding. This mapping consists of two parts: a representation in a linear subspace (computed in this work using the proper orthogonal decomposition) and a quadratic component. The approach can be viewed as a form of data-driven closure modeling, since the quadratic component introduces directions into the approximation that lie in the orthogonal complement of the linear subspace, but without introducing any additional degrees of freedom to the low-dimensional representation. Combining the quadratic manifold approximation with the operator inference method for projection-based model reduction leads to a scalable non-intrusive approach for learning reduced-order models of dynamical systems. Further, applying the new approach to transport-dominated systems of partial differential equations illustrates the gains in efficiency that can be achieved over approximation in a linear subspace.