Detection and Tracking of a Moving Target Using SAR Images with the Particle Filter-Based Track-Before-Detect Algorithm

PubMed Central

Gao, Han; Li, Jingwen

2014-01-01

A novel approach to detecting and tracking a moving target using synthetic aperture radar (SAR) images is proposed in this paper. Achieved with the particle filter (PF) based track-before-detect (TBD) algorithm, the approach is capable of detecting and tracking the low signal-to-noise ratio (SNR) moving target with SAR systems, which the traditional track-after-detect (TAD) approach is inadequate for. By incorporating the signal model of the SAR moving target into the algorithm, the ambiguity in target azimuth position and radial velocity is resolved while tracking, which leads directly to the true estimation. With the sub-area substituted for the whole area to calculate the likelihood ratio and a pertinent choice of the number of particles, the computational efficiency is improved with little loss in the detection and tracking performance. The feasibility of the approach is validated and the performance is evaluated with Monte Carlo trials. It is demonstrated that the proposed approach is capable to detect and track a moving target with SNR as low as 7 dB, and outperforms the traditional TAD approach when the SNR is below 14 dB. PMID:24949640

A multi-parametric particle-pairing algorithm for particle tracking in single and multiphase flows

NASA Astrophysics Data System (ADS)

Cardwell, Nicholas D.; Vlachos, Pavlos P.; Thole, Karen A.

2011-10-01

Multiphase flows (MPFs) offer a rich area of fundamental study with many practical applications. Examples of such flows range from the ingestion of foreign particulates in gas turbines to transport of particles within the human body. Experimental investigation of MPFs, however, is challenging, and requires techniques that simultaneously resolve both the carrier and discrete phases present in the flowfield. This paper presents a new multi-parametric particle-pairing algorithm for particle tracking velocimetry (MP3-PTV) in MPFs. MP3-PTV improves upon previous particle tracking algorithms by employing a novel variable pair-matching algorithm which utilizes displacement preconditioning in combination with estimated particle size and intensity to more effectively and accurately match particle pairs between successive images. To improve the method's efficiency, a new particle identification and segmentation routine was also developed. Validation of the new method was initially performed on two artificial data sets: a traditional single-phase flow published by the Visualization Society of Japan (VSJ) and an in-house generated MPF data set having a bi-modal distribution of particles diameters. Metrics of the measurement yield, reliability and overall tracking efficiency were used for method comparison. On the VSJ data set, the newly presented segmentation routine delivered a twofold improvement in identifying particles when compared to other published methods. For the simulated MPF data set, measurement efficiency of the carrier phases improved from 9% to 41% for MP3-PTV as compared to a traditional hybrid PTV. When employed on experimental data of a gas-solid flow, the MP3-PTV effectively identified the two particle populations and reported a vector efficiency and velocity measurement error comparable to measurements for the single-phase flow images. Simultaneous measurement of the dispersed particle and the carrier flowfield velocities allowed for the calculation of instantaneous particle slip velocities, illustrating the algorithm's strength to robustly and accurately resolve polydispersed MPFs.

Tracking Virus Particles in Fluorescence Microscopy Images Using Multi-Scale Detection and Multi-Frame Association.

PubMed

Jaiswal, Astha; Godinez, William J; Eils, Roland; Lehmann, Maik Jorg; Rohr, Karl

2015-11-01

Automatic fluorescent particle tracking is an essential task to study the dynamics of a large number of biological structures at a sub-cellular level. We have developed a probabilistic particle tracking approach based on multi-scale detection and two-step multi-frame association. The multi-scale detection scheme allows coping with particles in close proximity. For finding associations, we have developed a two-step multi-frame algorithm, which is based on a temporally semiglobal formulation as well as spatially local and global optimization. In the first step, reliable associations are determined for each particle individually in local neighborhoods. In the second step, the global spatial information over multiple frames is exploited jointly to determine optimal associations. The multi-scale detection scheme and the multi-frame association finding algorithm have been combined with a probabilistic tracking approach based on the Kalman filter. We have successfully applied our probabilistic tracking approach to synthetic as well as real microscopy image sequences of virus particles and quantified the performance. We found that the proposed approach outperforms previous approaches.

Real time tracking by LOPF algorithm with mixture model

NASA Astrophysics Data System (ADS)

Meng, Bo; Zhu, Ming; Han, Guangliang; Wu, Zhiguo

2007-11-01

A new particle filter-the Local Optimum Particle Filter (LOPF) algorithm is presented for tracking object accurately and steadily in visual sequences in real time which is a challenge task in computer vision field. In order to using the particles efficiently, we first use Sobel algorithm to extract the profile of the object. Then, we employ a new Local Optimum algorithm to auto-initialize some certain number of particles from these edge points as centre of the particles. The main advantage we do this in stead of selecting particles randomly in conventional particle filter is that we can pay more attentions on these more important optimum candidates and reduce the unnecessary calculation on those negligible ones, in addition we can overcome the conventional degeneracy phenomenon in a way and decrease the computational costs. Otherwise, the threshold is a key factor that affecting the results very much. So here we adapt an adaptive threshold choosing method to get the optimal Sobel result. The dissimilarities between the target model and the target candidates are expressed by a metric derived from the Bhattacharyya coefficient. Here, we use both the counter cue to select the particles and the color cur to describe the targets as the mixture target model. The effectiveness of our scheme is demonstrated by real visual tracking experiments. Results from simulations and experiments with real video data show the improved performance of the proposed algorithm when compared with that of the standard particle filter. The superior performance is evident when the target encountering the occlusion in real video where the standard particle filter usually fails.

Adaptive object tracking via both positive and negative models matching

NASA Astrophysics Data System (ADS)

Li, Shaomei; Gao, Chao; Wang, Yawen

2015-03-01

To improve tracking drift which often occurs in adaptive tracking, an algorithm based on the fusion of tracking and detection is proposed in this paper. Firstly, object tracking is posed as abinary classification problem and is modeled by partial least squares (PLS) analysis. Secondly, tracking object frame by frame via particle filtering. Thirdly, validating the tracking reliability based on both positive and negative models matching. Finally, relocating the object based on SIFT features matching and voting when drift occurs. Object appearance model is updated at the same time. The algorithm can not only sense tracking drift but also relocate the object whenever needed. Experimental results demonstrate that this algorithm outperforms state-of-the-art algorithms on many challenging sequences.

Application of a novel particle tracking algorithm in the flow visualization of an artificial abdominal aortic aneurysm.

PubMed

Zhang, Yang; Wang, Yuan; He, Wenbo; Yang, Bin

2014-01-01

A novel Particle Tracking Velocimetry (PTV) algorithm based on Voronoi Diagram (VD) is proposed and briefed as VD-PTV. The robustness of VD-PTV for pulsatile flow is verified through a test that includes a widely used artificial flow and a classic reference algorithm. The proposed algorithm is then applied to visualize the flow in an artificial abdominal aortic aneurysm included in a pulsatile circulation system that simulates the aortic blood flow in human body. Results show that, large particles tend to gather at the upstream boundary because of the backflow eddies that follow the pulsation. This qualitative description, together with VD-PTV, has laid a foundation for future works that demand high-level quantification.

The research on the mean shift algorithm for target tracking

NASA Astrophysics Data System (ADS)

CAO, Honghong

2017-06-01

The traditional mean shift algorithm for target tracking is effective and high real-time, but there still are some shortcomings. The traditional mean shift algorithm is easy to fall into local optimum in the tracking process, the effectiveness of the method is weak when the object is moving fast. And the size of the tracking window never changes, the method will fail when the size of the moving object changes, as a result, we come up with a new method. We use particle swarm optimization algorithm to optimize the mean shift algorithm for target tracking, Meanwhile, SIFT (scale-invariant feature transform) and affine transformation make the size of tracking window adaptive. At last, we evaluate the method by comparing experiments. Experimental result indicates that the proposed method can effectively track the object and the size of the tracking window changes.

PSO Algorithm Particle Filters for Improving the Performance of Lane Detection and Tracking Systems in Difficult Roads

PubMed Central

Cheng, Wen-Chang

2012-01-01

In this paper we propose a robust lane detection and tracking method by combining particle filters with the particle swarm optimization method. This method mainly uses the particle filters to detect and track the local optimum of the lane model in the input image and then seeks the global optimal solution of the lane model by a particle swarm optimization method. The particle filter can effectively complete lane detection and tracking in complicated or variable lane environments. However, the result obtained is usually a local optimal system status rather than the global optimal system status. Thus, the particle swarm optimization method is used to further refine the global optimal system status in all system statuses. Since the particle swarm optimization method is a global optimization algorithm based on iterative computing, it can find the global optimal lane model by simulating the food finding way of fish school or insects under the mutual cooperation of all particles. In verification testing, the test environments included highways and ordinary roads as well as straight and curved lanes, uphill and downhill lanes, lane changes, etc. Our proposed method can complete the lane detection and tracking more accurately and effectively then existing options. PMID:23235453

Automated Proton Track Identification in MicroBooNE Using Gradient Boosted Decision Trees

DOE Office of Scientific and Technical Information (OSTI.GOV)

Woodruff, Katherine

MicroBooNE is a liquid argon time projection chamber (LArTPC) neutrino experiment that is currently running in the Booster Neutrino Beam at Fermilab. LArTPC technology allows for high-resolution, three-dimensional representations of neutrino interactions. A wide variety of software tools for automated reconstruction and selection of particle tracks in LArTPCs are actively being developed. Short, isolated proton tracks, the signal for low- momentum-transfer neutral current (NC) elastic events, are easily hidden in a large cosmic background. Detecting these low-energy tracks will allow us to probe interesting regions of the proton's spin structure. An effective method for selecting NC elastic events is tomore » combine a highly efficient track reconstruction algorithm to find all candidate tracks with highly accurate particle identification using a machine learning algorithm. We present our work on particle track classification using gradient tree boosting software (XGBoost) and the performance on simulated neutrino data.« less

Visual Tracking via Sparse and Local Linear Coding.

PubMed

Wang, Guofeng; Qin, Xueying; Zhong, Fan; Liu, Yue; Li, Hongbo; Peng, Qunsheng; Yang, Ming-Hsuan

2015-11-01

The state search is an important component of any object tracking algorithm. Numerous algorithms have been proposed, but stochastic sampling methods (e.g., particle filters) are arguably one of the most effective approaches. However, the discretization of the state space complicates the search for the precise object location. In this paper, we propose a novel tracking algorithm that extends the state space of particle observations from discrete to continuous. The solution is determined accurately via iterative linear coding between two convex hulls. The algorithm is modeled by an optimal function, which can be efficiently solved by either convex sparse coding or locality constrained linear coding. The algorithm is also very flexible and can be combined with many generic object representations. Thus, we first use sparse representation to achieve an efficient searching mechanism of the algorithm and demonstrate its accuracy. Next, two other object representation models, i.e., least soft-threshold squares and adaptive structural local sparse appearance, are implemented with improved accuracy to demonstrate the flexibility of our algorithm. Qualitative and quantitative experimental results demonstrate that the proposed tracking algorithm performs favorably against the state-of-the-art methods in dynamic scenes.

Single-camera three-dimensional tracking of natural particulate and zooplankton

NASA Astrophysics Data System (ADS)

Troutman, Valerie A.; Dabiri, John O.

2018-07-01

We develop and characterize an image processing algorithm to adapt single-camera defocusing digital particle image velocimetry (DDPIV) for three-dimensional (3D) particle tracking velocimetry (PTV) of natural particulates, such as those present in the ocean. The conventional DDPIV technique is extended to facilitate tracking of non-uniform, non-spherical particles within a volume depth an order of magnitude larger than current single-camera applications (i.e. 10 cm  ×  10 cm  ×  24 cm depth) by a dynamic template matching method. This 2D cross-correlation method does not rely on precise determination of the centroid of the tracked objects. To accommodate the broad range of particle number densities found in natural marine environments, the performance of the measurement technique at higher particle densities has been improved by utilizing the time-history of tracked objects to inform 3D reconstruction. The developed processing algorithms were analyzed using synthetically generated images of flow induced by Hill’s spherical vortex, and the capabilities of the measurement technique were demonstrated empirically through volumetric reconstructions of the 3D trajectories of particles and highly non-spherical, 5 mm zooplankton.

Faint Debris Detection by Particle Based Track-Before-Detect Method

NASA Astrophysics Data System (ADS)

Uetsuhara, M.; Ikoma, N.

2014-09-01

This study proposes a particle method to detect faint debris, which is hardly seen in single frame, from an image sequence based on the concept of track-before-detect (TBD). The most widely used detection method is detect-before-track (DBT), which firstly detects signals of targets from single frame by distinguishing difference of intensity between foreground and background then associate the signals for each target between frames. DBT is capable of tracking bright targets but limited. DBT is necessary to consider presence of false signals and is difficult to recover from false association. On the other hand, TBD methods try to track targets without explicitly detecting the signals followed by evaluation of goodness of each track and obtaining detection results. TBD has an advantage over DBT in detecting weak signals around background level in single frame. However, conventional TBD methods for debris detection apply brute-force search over candidate tracks then manually select true one from the candidates. To reduce those significant drawbacks of brute-force search and not-fully automated process, this study proposes a faint debris detection algorithm by a particle based TBD method consisting of sequential update of target state and heuristic search of initial state. The state consists of position, velocity direction and magnitude, and size of debris over the image at a single frame. The sequential update process is implemented by a particle filter (PF). PF is an optimal filtering technique that requires initial distribution of target state as a prior knowledge. An evolutional algorithm (EA) is utilized to search the initial distribution. The EA iteratively applies propagation and likelihood evaluation of particles for the same image sequences and resulting set of particles is used as an initial distribution of PF. This paper describes the algorithm of the proposed faint debris detection method. The algorithm demonstrates performance on image sequences acquired during observation campaigns dedicated to GEO breakup fragments, which would contain a sufficient number of faint debris images. The results indicate the proposed method is capable of tracking faint debris with moderate computational costs at operational level.

Parallel computing of a digital hologram and particle searching for microdigital-holographic particle-tracking velocimetry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Satake, Shin-ichi; Kanamori, Hiroyuki; Kunugi, Tomoaki

2007-02-01

We have developed a parallel algorithm for microdigital-holographic particle-tracking velocimetry. The algorithm is used in (1) numerical reconstruction of a particle image computer using a digital hologram, and (2) searching for particles. The numerical reconstruction from the digital hologram makes use of the Fresnel diffraction equation and the FFT (fast Fourier transform),whereas the particle search algorithm looks for local maximum graduation in a reconstruction field represented by a 3D matrix. To achieve high performance computing for both calculations (reconstruction and particle search), two memory partitions are allocated to the 3D matrix. In this matrix, the reconstruction part consists of horizontallymore » placed 2D memory partitions on the x-y plane for the FFT, whereas, the particle search part consists of vertically placed 2D memory partitions set along the z axes.Consequently, the scalability can be obtained for the proportion of processor elements,where the benchmarks are carried out for parallel computation by a SGI Altix machine.« less

The artificial retina for track reconstruction at the LHC crossing rate

NASA Astrophysics Data System (ADS)

Abba, A.; Bedeschi, F.; Citterio, M.; Caponio, F.; Cusimano, A.; Geraci, A.; Marino, P.; Morello, M. J.; Neri, N.; Punzi, G.; Piucci, A.; Ristori, L.; Spinella, F.; Stracka, S.; Tonelli, D.

2016-04-01

We present the results of an R&D study for a specialized processor capable of precisely reconstructing events with hundreds of charged-particle tracks in pixel and silicon strip detectors at 40 MHz, thus suitable for processing LHC events at the full crossing frequency. For this purpose we design and test a massively parallel pattern-recognition algorithm, inspired to the current understanding of the mechanisms adopted by the primary visual cortex of mammals in the early stages of visual-information processing. The detailed geometry and charged-particle's activity of a large tracking detector are simulated and used to assess the performance of the artificial retina algorithm. We find that high-quality tracking in large detectors is possible with sub-microsecond latencies when the algorithm is implemented in modern, high-speed, high-bandwidth FPGA devices.

Adaptation of reference volumes for correlation-based digital holographic particle tracking

NASA Astrophysics Data System (ADS)

Hesseling, Christina; Peinke, Joachim; Gülker, Gerd

2018-04-01

Numerically reconstructed reference volumes tailored to particle images are used for particle position detection by means of three-dimensional correlation. After a first tracking of these positions, the experimentally recorded particle images are retrieved as a posteriori knowledge about the particle images in the system. This knowledge is used for a further refinement of the detected positions. A transparent description of the individual algorithm steps including the results retrieved with experimental data complete the paper. The work employs extraordinarily small particles, smaller than the pixel pitch of the camera sensor. It is the first approach known to the authors that combines numerical knowledge about particle images and particle images retrieved from the experimental system to an iterative particle tracking approach for digital holographic particle tracking velocimetry.

High-precision tracking of brownian boomerang colloidal particles confined in quasi two dimensions.

PubMed

Chakrabarty, Ayan; Wang, Feng; Fan, Chun-Zhen; Sun, Kai; Wei, Qi-Huo

2013-11-26

In this article, we present a high-precision image-processing algorithm for tracking the translational and rotational Brownian motion of boomerang-shaped colloidal particles confined in quasi-two-dimensional geometry. By measuring mean square displacements of an immobilized particle, we demonstrate that the positional and angular precision of our imaging and image-processing system can achieve 13 nm and 0.004 rad, respectively. By analyzing computer-simulated images, we demonstrate that the positional and angular accuracies of our image-processing algorithm can achieve 32 nm and 0.006 rad. Because of zero correlations between the displacements in neighboring time intervals, trajectories of different videos of the same particle can be merged into a very long time trajectory, allowing for long-time averaging of different physical variables. We apply this image-processing algorithm to measure the diffusion coefficients of boomerang particles of three different apex angles and discuss the angle dependence of these diffusion coefficients.

Robust and highly performant ring detection algorithm for 3d particle tracking using 2d microscope imaging

NASA Astrophysics Data System (ADS)

Afik, Eldad

2015-09-01

Three-dimensional particle tracking is an essential tool in studying dynamics under the microscope, namely, fluid dynamics in microfluidic devices, bacteria taxis, cellular trafficking. The 3d position can be determined using 2d imaging alone by measuring the diffraction rings generated by an out-of-focus fluorescent particle, imaged on a single camera. Here I present a ring detection algorithm exhibiting a high detection rate, which is robust to the challenges arising from ring occlusion, inclusions and overlaps, and allows resolving particles even when near to each other. It is capable of real time analysis thanks to its high performance and low memory footprint. The proposed algorithm, an offspring of the circle Hough transform, addresses the need to efficiently trace the trajectories of many particles concurrently, when their number in not necessarily fixed, by solving a classification problem, and overcomes the challenges of finding local maxima in the complex parameter space which results from ring clusters and noise. Several algorithmic concepts introduced here can be advantageous in other cases, particularly when dealing with noisy and sparse data. The implementation is based on open-source and cross-platform software packages only, making it easy to distribute and modify. It is implemented in a microfluidic experiment allowing real-time multi-particle tracking at 70 Hz, achieving a detection rate which exceeds 94% and only 1% false-detection.

Positron emission particle tracking and its application to granular media

NASA Astrophysics Data System (ADS)

Parker, D. J.

2017-05-01

Positron emission particle tracking (PEPT) is a technique for tracking a single radioactively labelled particle. Accurate 3D tracking is possible even when the particle is moving at high speed inside a dense opaque system. In many cases, tracking a single particle within a granular system provides sufficient information to determine the time-averaged behaviour of the entire granular system. After a general introduction, this paper describes the detector systems (PET scanners and positron cameras) used to record PEPT data, the techniques used to label particles, and the algorithms used to process the data. This paper concentrates on the use of PEPT for studying granular systems: the focus is mainly on work at Birmingham, but reference is also made to work from other centres, and options for wider diversification are suggested.

Particle tracking in drug and gene delivery research: State-of-the-art applications and methods.

PubMed

Schuster, Benjamin S; Ensign, Laura M; Allan, Daniel B; Suk, Jung Soo; Hanes, Justin

2015-08-30

Particle tracking is a powerful microscopy technique to quantify the motion of individual particles at high spatial and temporal resolution in complex fluids and biological specimens. Particle tracking's applications and impact in drug and gene delivery research have greatly increased during the last decade. Thanks to advances in hardware and software, this technique is now more accessible than ever, and can be reliably automated to enable rapid processing of large data sets, thereby further enhancing the role that particle tracking will play in drug and gene delivery studies in the future. We begin this review by discussing particle tracking-based advances in characterizing extracellular and cellular barriers to therapeutic nanoparticles and in characterizing nanoparticle size and stability. To facilitate wider adoption of the technique, we then present a user-friendly review of state-of-the-art automated particle tracking algorithms and methods of analysis. We conclude by reviewing technological developments for next-generation particle tracking methods, and we survey future research directions in drug and gene delivery where particle tracking may be useful. Copyright © 2015 Elsevier B.V. All rights reserved.

Particle Filtering with Region-based Matching for Tracking of Partially Occluded and Scaled Targets*

PubMed Central

Nakhmani, Arie; Tannenbaum, Allen

2012-01-01

Visual tracking of arbitrary targets in clutter is important for a wide range of military and civilian applications. We propose a general framework for the tracking of scaled and partially occluded targets, which do not necessarily have prominent features. The algorithm proposed in the present paper utilizes a modified normalized cross-correlation as the likelihood for a particle filter. The algorithm divides the template, selected by the user in the first video frame, into numerous patches. The matching process of these patches by particle filtering allows one to handle the target’s occlusions and scaling. Experimental results with fixed rectangular templates show that the method is reliable for videos with nonstationary, noisy, and cluttered background, and provides accurate trajectories in cases of target translation, scaling, and occlusion. PMID:22506088

Simulation and performance of an artificial retina for 40 MHz track reconstruction

DOE PAGES

Abba, A.; Bedeschi, F.; Citterio, M.; ...

2015-03-05

We present the results of a detailed simulation of the artificial retina pattern-recognition algorithm, designed to reconstruct events with hundreds of charged-particle tracks in pixel and silicon detectors at LHCb with LHC crossing frequency of 40 MHz. Performances of the artificial retina algorithm are assessed using the official Monte Carlo samples of the LHCb experiment. We found performances for the retina pattern-recognition algorithm comparable with the full LHCb reconstruction algorithm.

Object tracking with adaptive HOG detector and adaptive Rao-Blackwellised particle filter

NASA Astrophysics Data System (ADS)

Rosa, Stefano; Paleari, Marco; Ariano, Paolo; Bona, Basilio

2012-01-01

Scenarios for a manned mission to the Moon or Mars call for astronaut teams to be accompanied by semiautonomous robots. A prerequisite for human-robot interaction is the capability of successfully tracking humans and objects in the environment. In this paper we present a system for real-time visual object tracking in 2D images for mobile robotic systems. The proposed algorithm is able to specialize to individual objects and to adapt to substantial changes in illumination and object appearance during tracking. The algorithm is composed by two main blocks: a detector based on Histogram of Oriented Gradient (HOG) descriptors and linear Support Vector Machines (SVM), and a tracker which is implemented by an adaptive Rao-Blackwellised particle filter (RBPF). The SVM is re-trained online on new samples taken from previous predicted positions. We use the effective sample size to decide when the classifier needs to be re-trained. Position hypotheses for the tracked object are the result of a clustering procedure applied on the set of particles. The algorithm has been tested on challenging video sequences presenting strong changes in object appearance, illumination, and occlusion. Experimental tests show that the presented method is able to achieve near real-time performances with a precision of about 7 pixels on standard video sequences of dimensions 320 × 240.

Particle Filtering for Obstacle Tracking in UAS Sense and Avoid Applications

PubMed Central

Moccia, Antonio

2014-01-01

Obstacle detection and tracking is a key function for UAS sense and avoid applications. In fact, obstacles in the flight path must be detected and tracked in an accurate and timely manner in order to execute a collision avoidance maneuver in case of collision threat. The most important parameter for the assessment of a collision risk is the Distance at Closest Point of Approach, that is, the predicted minimum distance between own aircraft and intruder for assigned current position and speed. Since assessed methodologies can cause some loss of accuracy due to nonlinearities, advanced filtering methodologies, such as particle filters, can provide more accurate estimates of the target state in case of nonlinear problems, thus improving system performance in terms of collision risk estimation. The paper focuses on algorithm development and performance evaluation for an obstacle tracking system based on a particle filter. The particle filter algorithm was tested in off-line simulations based on data gathered during flight tests. In particular, radar-based tracking was considered in order to evaluate the impact of particle filtering in a single sensor framework. The analysis shows some accuracy improvements in the estimation of Distance at Closest Point of Approach, thus reducing the delay in collision detection. PMID:25105154

Improvements to the ShipIR/NTCS adaptive track gate algorithm and 3D flare particle model

NASA Astrophysics Data System (ADS)

Ramaswamy, Srinivasan; Vaitekunas, David A.; Gunter, Willem H.; February, Faith J.

2017-05-01

A key component in any image-based tracking system is the adaptive tracking algorithm used to segment the image into potential targets, rank-and-select the best candidate target, and gate the selected target to further improve tracker performance. Similarly, a key component in any soft-kill response to an incoming guided missile is the flare/chaff decoy used to distract or seduce the seeker homing system away from the naval platform. This paper describes the recent improvements to the naval threat countermeasure simulator (NTCS) of the NATO-standard ship signature model (ShipIR). Efforts to analyse and match the 3D flare particle model against actual IR measurements of the Chemring TALOS IR round resulted in further refinement of the 3D flare particle distribution. The changes in the flare model characteristics were significant enough to require an overhaul to the adaptive track gate (ATG) algorithm in the way it detects the presence of flare decoys and reacquires the target after flare separation. A series of test scenarios are used to demonstrate the impact of the new flare and ATG on IR tactics simulation.

A particle filter for multi-target tracking in track before detect context

NASA Astrophysics Data System (ADS)

Amrouche, Naima; Khenchaf, Ali; Berkani, Daoud

2016-10-01

The track-before-detect (TBD) approach can be used to track a single target in a highly noisy radar scene. This is because it makes use of unthresholded observations and incorporates a binary target existence variable into its target state estimation process when implemented as a particle filter (PF). This paper proposes the recursive PF-TBD approach to detect multiple targets in low-signal-to noise ratios (SNR). The algorithm's successful performance is demonstrated using a simulated two target example.

Conformal Electromagnetic Particle in Cell: A Review

DOE PAGES

Meierbachtol, Collin S.; Greenwood, Andrew D.; Verboncoeur, John P.; ...

2015-10-26

We review conformal (or body-fitted) electromagnetic particle-in-cell (EM-PIC) numerical solution schemes. Included is a chronological history of relevant particle physics algorithms often employed in these conformal simulations. We also provide brief mathematical descriptions of particle-tracking algorithms and current weighting schemes, along with a brief summary of major time-dependent electromagnetic solution methods. Several research areas are also highlighted for recommended future development of new conformal EM-PIC methods.

Time-resolved large-scale volumetric pressure fields of an impinging jet from dense Lagrangian particle tracking

NASA Astrophysics Data System (ADS)

Huhn, F.; Schanz, D.; Manovski, P.; Gesemann, S.; Schröder, A.

2018-05-01

Time-resolved volumetric pressure fields are reconstructed from Lagrangian particle tracking with high seeding concentration using the Shake-The-Box algorithm in a perpendicular impinging jet flow with exit velocity U=4 m/s (Re˜ 36,000) and nozzle-plate spacing H/D=5. Helium-filled soap bubbles are used as tracer particles which are illuminated with pulsed LED arrays. A large measurement volume has been covered (cloud of tracked particles in a volume of 54 L, ˜ 180,000 particles). The reconstructed pressure field has been validated against microphone recordings at the wall with high correlation coefficients up to 0.88. In a reduced measurement volume (13 L), dense Lagrangian particle tracking is shown to be feasable up to the maximal possible jet velocity of U=16 m/s.

Space debris tracking based on fuzzy running Gaussian average adaptive particle filter track-before-detect algorithm

NASA Astrophysics Data System (ADS)

Torteeka, Peerapong; Gao, Peng-Qi; Shen, Ming; Guo, Xiao-Zhang; Yang, Da-Tao; Yu, Huan-Huan; Zhou, Wei-Ping; Zhao, You

2017-02-01

Although tracking with a passive optical telescope is a powerful technique for space debris observation, it is limited by its sensitivity to dynamic background noise. Traditionally, in the field of astronomy, static background subtraction based on a median image technique has been used to extract moving space objects prior to the tracking operation, as this is computationally efficient. The main disadvantage of this technique is that it is not robust to variable illumination conditions. In this article, we propose an approach for tracking small and dim space debris in the context of a dynamic background via one of the optical telescopes that is part of the space surveillance network project, named the Asia-Pacific ground-based Optical Space Observation System or APOSOS. The approach combines a fuzzy running Gaussian average for robust moving-object extraction with dim-target tracking using a particle-filter-based track-before-detect method. The performance of the proposed algorithm is experimentally evaluated, and the results show that the scheme achieves a satisfactory level of accuracy for space debris tracking.

Track-before-detect labeled multi-bernoulli particle filter with label switching

NASA Astrophysics Data System (ADS)

Garcia-Fernandez, Angel F.

2016-10-01

This paper presents a multitarget tracking particle filter (PF) for general track-before-detect measurement models. The PF is presented in the random finite set framework and uses a labelled multi-Bernoulli approximation. We also present a label switching improvement algorithm based on Markov chain Monte Carlo that is expected to increase filter performance if targets get in close proximity for a sufficiently long time. The PF is tested in two challenging numerical examples.

Multi-object tracking of human spermatozoa

NASA Astrophysics Data System (ADS)

Sørensen, Lauge; Østergaard, Jakob; Johansen, Peter; de Bruijne, Marleen

2008-03-01

We propose a system for tracking of human spermatozoa in phase-contrast microscopy image sequences. One of the main aims of a computer-aided sperm analysis (CASA) system is to automatically assess sperm quality based on spermatozoa motility variables. In our case, the problem of assessing sperm quality is cast as a multi-object tracking problem, where the objects being tracked are the spermatozoa. The system combines a particle filter and Kalman filters for robust motion estimation of the spermatozoa tracks. Further, the combinatorial aspect of assigning observations to labels in the particle filter is formulated as a linear assignment problem solved using the Hungarian algorithm on a rectangular cost matrix, making the algorithm capable of handling missing or spurious observations. The costs are calculated using hidden Markov models that express the plausibility of an observation being the next position in the track history of the particle labels. Observations are extracted using a scale-space blob detector utilizing the fact that the spermatozoa appear as bright blobs in a phase-contrast microscope. The output of the system is the complete motion track of each of the spermatozoa. Based on these tracks, different CASA motility variables can be computed, for example curvilinear velocity or straight-line velocity. The performance of the system is tested on three different phase-contrast image sequences of varying complexity, both by visual inspection of the estimated spermatozoa tracks and by measuring the mean squared error (MSE) between the estimated spermatozoa tracks and manually annotated tracks, showing good agreement.

Exploring dynamics in living cells by tracking single particles.

PubMed

Levi, Valeria; Gratton, Enrico

2007-01-01

In the last years, significant advances in microscopy techniques and the introduction of a novel technology to label living cells with genetically encoded fluorescent proteins revolutionized the field of Cell Biology. Our understanding on cell dynamics built from snapshots on fixed specimens has evolved thanks to our actual capability to monitor in real time the evolution of processes in living cells. Among these new tools, single particle tracking techniques were developed to observe and follow individual particles. Hence, we are starting to unravel the mechanisms driving the motion of a wide variety of cellular components ranging from organelles to protein molecules by following their way through the cell. In this review, we introduce the single particle tracking technology to new users. We briefly describe the instrumentation and explain some of the algorithms commonly used to locate and track particles. Also, we present some common tools used to analyze trajectories and illustrate with some examples the applications of single particle tracking to study dynamics in living cells.

Online Tracking Algorithms on GPUs for the P̅ANDA Experiment at FAIR

NASA Astrophysics Data System (ADS)

Bianchi, L.; Herten, A.; Ritman, J.; Stockmanns, T.; Adinetz, A.; Kraus, J.; Pleiter, D.

2015-12-01

P̅ANDA is a future hadron and nuclear physics experiment at the FAIR facility in construction in Darmstadt, Germany. In contrast to the majority of current experiments, PANDA's strategy for data acquisition is based on event reconstruction from free-streaming data, performed in real time entirely by software algorithms using global detector information. This paper reports the status of the development of algorithms for the reconstruction of charged particle tracks, optimized online data processing applications, using General-Purpose Graphic Processing Units (GPU). Two algorithms for trackfinding, the Triplet Finder and the Circle Hough, are described, and details of their GPU implementations are highlighted. Average track reconstruction times of less than 100 ns are obtained running the Triplet Finder on state-of- the-art GPU cards. In addition, a proof-of-concept system for the dispatch of data to tracking algorithms using Message Queues is presented.

Accumulative Difference Image Protocol for Particle Tracking in Fluorescence Microscopy Tested in Mouse Lymphonodes

PubMed Central

Villa, Carlo E.; Caccia, Michele; Sironi, Laura; D'Alfonso, Laura; Collini, Maddalena; Rivolta, Ilaria; Miserocchi, Giuseppe; Gorletta, Tatiana; Zanoni, Ivan; Granucci, Francesca; Chirico, Giuseppe

2010-01-01

The basic research in cell biology and in medical sciences makes large use of imaging tools mainly based on confocal fluorescence and, more recently, on non-linear excitation microscopy. Substantially the aim is the recognition of selected targets in the image and their tracking in time. We have developed a particle tracking algorithm optimized for low signal/noise images with a minimum set of requirements on the target size and with no a priori knowledge of the type of motion. The image segmentation, based on a combination of size sensitive filters, does not rely on edge detection and is tailored for targets acquired at low resolution as in most of the in-vivo studies. The particle tracking is performed by building, from a stack of Accumulative Difference Images, a single 2D image in which the motion of the whole set of the particles is coded in time by a color level. This algorithm, tested here on solid-lipid nanoparticles diffusing within cells and on lymphocytes diffusing in lymphonodes, appears to be particularly useful for the cellular and the in-vivo microscopy image processing in which few a priori assumption on the type, the extent and the variability of particle motions, can be done. PMID:20808918

Accumulative difference image protocol for particle tracking in fluorescence microscopy tested in mouse lymphonodes.

PubMed

Villa, Carlo E; Caccia, Michele; Sironi, Laura; D'Alfonso, Laura; Collini, Maddalena; Rivolta, Ilaria; Miserocchi, Giuseppe; Gorletta, Tatiana; Zanoni, Ivan; Granucci, Francesca; Chirico, Giuseppe

2010-08-17

The basic research in cell biology and in medical sciences makes large use of imaging tools mainly based on confocal fluorescence and, more recently, on non-linear excitation microscopy. Substantially the aim is the recognition of selected targets in the image and their tracking in time. We have developed a particle tracking algorithm optimized for low signal/noise images with a minimum set of requirements on the target size and with no a priori knowledge of the type of motion. The image segmentation, based on a combination of size sensitive filters, does not rely on edge detection and is tailored for targets acquired at low resolution as in most of the in-vivo studies. The particle tracking is performed by building, from a stack of Accumulative Difference Images, a single 2D image in which the motion of the whole set of the particles is coded in time by a color level. This algorithm, tested here on solid-lipid nanoparticles diffusing within cells and on lymphocytes diffusing in lymphonodes, appears to be particularly useful for the cellular and the in-vivo microscopy image processing in which few a priori assumption on the type, the extent and the variability of particle motions, can be done.

Kassiopeia: a modern, extensible C++ particle tracking package

DOE Office of Scientific and Technical Information (OSTI.GOV)

Furse, Daniel; Groh, Stefan; Trost, Nikolaus

The Kassiopeia particle tracking framework is an object-oriented software package using modern C++ techniques, written originally to meet the needs of the KATRIN collaboration. Kassiopeia features a new algorithmic paradigm for particle tracking simulations which targets experiments containing complex geometries and electromagnetic fields, with high priority put on calculation efficiency, customizability, extensibility, and ease-of-use for novice programmers. To solve Kassiopeia's target physics problem the software is capable of simulating particle trajectories governed by arbitrarily complex differential equations of motion, continuous physics processes that may in part be modeled as terms perturbing that equation of motion, stochastic processes that occur inmore » flight such as bulk scattering and decay, and stochastic surface processes occurring at interfaces, including transmission and reflection effects. This entire set of computations takes place against the backdrop of a rich geometry package which serves a variety of roles, including initialization of electromagnetic field simulations and the support of state-dependent algorithm-swapping and behavioral changes as a particle's state evolves. Thanks to the very general approach taken by Kassiopeia it can be used by other experiments facing similar challenges when calculating particle trajectories in electromagnetic fields. It is publicly available at https://github.com/KATRIN-Experiment/Kassiopeia.« less

Kassiopeia: a modern, extensible C++ particle tracking package

DOE PAGES

Furse, Daniel; Groh, Stefan; Trost, Nikolaus; ...

2017-05-16

The Kassiopeia particle tracking framework is an object-oriented software package using modern C++ techniques, written originally to meet the needs of the KATRIN collaboration. Kassiopeia features a new algorithmic paradigm for particle tracking simulations which targets experiments containing complex geometries and electromagnetic fields, with high priority put on calculation efficiency, customizability, extensibility, and ease-of-use for novice programmers. To solve Kassiopeia's target physics problem the software is capable of simulating particle trajectories governed by arbitrarily complex differential equations of motion, continuous physics processes that may in part be modeled as terms perturbing that equation of motion, stochastic processes that occur inmore » flight such as bulk scattering and decay, and stochastic surface processes occurring at interfaces, including transmission and reflection effects. This entire set of computations takes place against the backdrop of a rich geometry package which serves a variety of roles, including initialization of electromagnetic field simulations and the support of state-dependent algorithm-swapping and behavioral changes as a particle's state evolves. Thanks to the very general approach taken by Kassiopeia it can be used by other experiments facing similar challenges when calculating particle trajectories in electromagnetic fields. It is publicly available at https://github.com/KATRIN-Experiment/Kassiopeia.« less

Guided filter and convolutional network based tracking for infrared dim moving target

NASA Astrophysics Data System (ADS)

Qian, Kun; Zhou, Huixin; Qin, Hanlin; Rong, Shenghui; Zhao, Dong; Du, Juan

2017-09-01

The dim moving target usually submerges in strong noise, and its motion observability is debased by numerous false alarms for low signal-to-noise ratio. A tracking algorithm that integrates the Guided Image Filter (GIF) and the Convolutional neural network (CNN) into the particle filter framework is presented to cope with the uncertainty of dim targets. First, the initial target template is treated as a guidance to filter incoming templates depending on similarities between the guidance and candidate templates. The GIF algorithm utilizes the structure in the guidance and performs as an edge-preserving smoothing operator. Therefore, the guidance helps to preserve the detail of valuable templates and makes inaccurate ones blurry, alleviating the tracking deviation effectively. Besides, the two-layer CNN method is adopted to obtain a powerful appearance representation. Subsequently, a Bayesian classifier is trained with these discriminative yet strong features. Moreover, an adaptive learning factor is introduced to prevent the update of classifier's parameters when a target undergoes sever background. At last, classifier responses of particles are utilized to generate particle importance weights and a re-sample procedure preserves samples according to the weight. In the predication stage, a 2-order transition model considers the target velocity to estimate current position. Experimental results demonstrate that the presented algorithm outperforms several relative algorithms in the accuracy.

Single and multiple object tracking using log-euclidean Riemannian subspace and block-division appearance model.

PubMed

Hu, Weiming; Li, Xi; Luo, Wenhan; Zhang, Xiaoqin; Maybank, Stephen; Zhang, Zhongfei

2012-12-01

Object appearance modeling is crucial for tracking objects, especially in videos captured by nonstationary cameras and for reasoning about occlusions between multiple moving objects. Based on the log-euclidean Riemannian metric on symmetric positive definite matrices, we propose an incremental log-euclidean Riemannian subspace learning algorithm in which covariance matrices of image features are mapped into a vector space with the log-euclidean Riemannian metric. Based on the subspace learning algorithm, we develop a log-euclidean block-division appearance model which captures both the global and local spatial layout information about object appearances. Single object tracking and multi-object tracking with occlusion reasoning are then achieved by particle filtering-based Bayesian state inference. During tracking, incremental updating of the log-euclidean block-division appearance model captures changes in object appearance. For multi-object tracking, the appearance models of the objects can be updated even in the presence of occlusions. Experimental results demonstrate that the proposed tracking algorithm obtains more accurate results than six state-of-the-art tracking algorithms.

A complete system for head tracking using motion-based particle filter and randomly perturbed active contour

NASA Astrophysics Data System (ADS)

Bouaynaya, N.; Schonfeld, Dan

2005-03-01

Many real world applications in computer and multimedia such as augmented reality and environmental imaging require an elastic accurate contour around a tracked object. In the first part of the paper we introduce a novel tracking algorithm that combines a motion estimation technique with the Bayesian Importance Sampling framework. We use Adaptive Block Matching (ABM) as the motion estimation technique. We construct the proposal density from the estimated motion vector. The resulting algorithm requires a small number of particles for efficient tracking. The tracking is adaptive to different categories of motion even with a poor a priori knowledge of the system dynamics. Particulary off-line learning is not needed. A parametric representation of the object is used for tracking purposes. In the second part of the paper, we refine the tracking output from a parametric sample to an elastic contour around the object. We use a 1D active contour model based on a dynamic programming scheme to refine the output of the tracker. To improve the convergence of the active contour, we perform the optimization over a set of randomly perturbed initial conditions. Our experiments are applied to head tracking. We report promising tracking results in complex environments.

Multiple hypothesis tracking for cluttered biological image sequences.

PubMed

Chenouard, Nicolas; Bloch, Isabelle; Olivo-Marin, Jean-Christophe

2013-11-01

In this paper, we present a method for simultaneously tracking thousands of targets in biological image sequences, which is of major importance in modern biology. The complexity and inherent randomness of the problem lead us to propose a unified probabilistic framework for tracking biological particles in microscope images. The framework includes realistic models of particle motion and existence and of fluorescence image features. For the track extraction process per se, the very cluttered conditions motivate the adoption of a multiframe approach that enforces tracking decision robustness to poor imaging conditions and to random target movements. We tackle the large-scale nature of the problem by adapting the multiple hypothesis tracking algorithm to the proposed framework, resulting in a method with a favorable tradeoff between the model complexity and the computational cost of the tracking procedure. When compared to the state-of-the-art tracking techniques for bioimaging, the proposed algorithm is shown to be the only method providing high-quality results despite the critically poor imaging conditions and the dense target presence. We thus demonstrate the benefits of advanced Bayesian tracking techniques for the accurate computational modeling of dynamical biological processes, which is promising for further developments in this domain.

Tri-track: free software for large-scale particle tracking.

PubMed

Vallotton, Pascal; Olivier, Sandra

2013-04-01

The ability to correctly track objects in time-lapse sequences is important in many applications of microscopy. Individual object motions typically display a level of dynamic regularity reflecting the existence of an underlying physics or biology. Best results are obtained when this local information is exploited. Additionally, if the particle number is known to be approximately constant, a large number of tracking scenarios may be rejected on the basis that they are not compatible with a known maximum particle velocity. This represents information of a global nature, which should ideally be exploited too. Some time ago, we devised an efficient algorithm that exploited both types of information. The tracking task was reduced to a max-flow min-cost problem instance through a novel graph structure that comprised vertices representing objects from three consecutive image frames. The algorithm is explained here for the first time. A user-friendly implementation is provided, and the specific relaxation mechanism responsible for the method's effectiveness is uncovered. The software is particularly competitive for complex dynamics such as dense antiparallel flows, or in situations where object displacements are considerable. As an application, we characterize a remarkable vortex structure formed by bacteria engaged in interstitial motility.

Multiple particle tracking in 3-D+t microscopy: method and application to the tracking of endocytosed quantum dots.

PubMed

Genovesio, Auguste; Liedl, Tim; Emiliani, Valentina; Parak, Wolfgang J; Coppey-Moisan, Maité; Olivo-Marin, Jean-Christophe

2006-05-01

We propose a method to detect and track multiple moving biological spot-like particles showing different kinds of dynamics in image sequences acquired through multidimensional fluorescence microscopy. It enables the extraction and analysis of information such as number, position, speed, movement, and diffusion phases of, e.g., endosomal particles. The method consists of several stages. After a detection stage performed by a three-dimensional (3-D) undecimated wavelet transform, we compute, for each detected spot, several predictions of its future state in the next frame. This is accomplished thanks to an interacting multiple model (IMM) algorithm which includes several models corresponding to different biologically realistic movement types. Tracks are constructed, thereafter, by a data association algorithm based on the maximization of the likelihood of each IMM. The last stage consists of updating the IMM filters in order to compute final estimations for the present image and to improve predictions for the next image. The performances of the method are validated on synthetic image data and used to characterize the 3-D movement of endocytic vesicles containing quantum dots.

Image computing techniques to extrapolate data for dust tracking in case of an experimental accident simulation in a nuclear fusion plant.

PubMed

Camplani, M; Malizia, A; Gelfusa, M; Barbato, F; Antonelli, L; Poggi, L A; Ciparisse, J F; Salgado, L; Richetta, M; Gaudio, P

2016-01-01

In this paper, a preliminary shadowgraph-based analysis of dust particles re-suspension due to loss of vacuum accident (LOVA) in ITER-like nuclear fusion reactors has been presented. Dust particles are produced through different mechanisms in nuclear fusion devices, one of the main issues is that dust particles are capable of being re-suspended in case of events such as LOVA. Shadowgraph is based on an expanded collimated beam of light emitted by a laser or a lamp that emits light transversely compared to the flow field direction. In the STARDUST facility, the dust moves in the flow, and it causes variations of refractive index that can be detected by using a CCD camera. The STARDUST fast camera setup allows to detect and to track dust particles moving in the vessel and then to obtain information about the velocity field of dust mobilized. In particular, the acquired images are processed such that per each frame the moving dust particles are detected by applying a background subtraction technique based on the mixture of Gaussian algorithm. The obtained foreground masks are eventually filtered with morphological operations. Finally, a multi-object tracking algorithm is used to track the detected particles along the experiment. For each particle, a Kalman filter-based tracker is applied; the particles dynamic is described by taking into account position, velocity, and acceleration as state variable. The results demonstrate that it is possible to obtain dust particles' velocity field during LOVA by automatically processing the data obtained with the shadowgraph approach.

Image computing techniques to extrapolate data for dust tracking in case of an experimental accident simulation in a nuclear fusion plant

NASA Astrophysics Data System (ADS)

Camplani, M.; Malizia, A.; Gelfusa, M.; Barbato, F.; Antonelli, L.; Poggi, L. A.; Ciparisse, J. F.; Salgado, L.; Richetta, M.; Gaudio, P.

2016-01-01

In this paper, a preliminary shadowgraph-based analysis of dust particles re-suspension due to loss of vacuum accident (LOVA) in ITER-like nuclear fusion reactors has been presented. Dust particles are produced through different mechanisms in nuclear fusion devices, one of the main issues is that dust particles are capable of being re-suspended in case of events such as LOVA. Shadowgraph is based on an expanded collimated beam of light emitted by a laser or a lamp that emits light transversely compared to the flow field direction. In the STARDUST facility, the dust moves in the flow, and it causes variations of refractive index that can be detected by using a CCD camera. The STARDUST fast camera setup allows to detect and to track dust particles moving in the vessel and then to obtain information about the velocity field of dust mobilized. In particular, the acquired images are processed such that per each frame the moving dust particles are detected by applying a background subtraction technique based on the mixture of Gaussian algorithm. The obtained foreground masks are eventually filtered with morphological operations. Finally, a multi-object tracking algorithm is used to track the detected particles along the experiment. For each particle, a Kalman filter-based tracker is applied; the particles dynamic is described by taking into account position, velocity, and acceleration as state variable. The results demonstrate that it is possible to obtain dust particles' velocity field during LOVA by automatically processing the data obtained with the shadowgraph approach.

An artificial retina processor for track reconstruction at the LHC crossing rate

DOE PAGES

Bedeschi, F.; Cenci, R.; Marino, P.; ...

2017-11-23

The goal of the INFN-RETINA R&D project is to develop and implement a computational methodology that allows to reconstruct events with a large number (> 100) of charged-particle tracks in pixel and silicon strip detectors at 40 MHz, thus matching the requirements for processing LHC events at the full bunch-crossing frequency. Our approach relies on a parallel pattern-recognition algorithm, dubbed artificial retina, inspired by the early stages of image processing by the brain. In order to demonstrate that a track-processing system based on this algorithm is feasible, we built a sizable prototype of a tracking processor tuned to 3 000more » patterns, based on already existing readout boards equipped with Altera Stratix III FPGAs. The detailed geometry and charged-particle activity of a large tracking detector currently in operation are used to assess its performances. Here, we report on the test results with such a prototype.« less

An artificial retina processor for track reconstruction at the LHC crossing rate

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bedeschi, F.; Cenci, R.; Marino, P.

The goal of the INFN-RETINA R&D project is to develop and implement a computational methodology that allows to reconstruct events with a large number (> 100) of charged-particle tracks in pixel and silicon strip detectors at 40 MHz, thus matching the requirements for processing LHC events at the full bunch-crossing frequency. Our approach relies on a parallel pattern-recognition algorithm, dubbed artificial retina, inspired by the early stages of image processing by the brain. In order to demonstrate that a track-processing system based on this algorithm is feasible, we built a sizable prototype of a tracking processor tuned to 3 000more » patterns, based on already existing readout boards equipped with Altera Stratix III FPGAs. The detailed geometry and charged-particle activity of a large tracking detector currently in operation are used to assess its performances. Here, we report on the test results with such a prototype.« less

TrackMate: An open and extensible platform for single-particle tracking.

PubMed

Tinevez, Jean-Yves; Perry, Nick; Schindelin, Johannes; Hoopes, Genevieve M; Reynolds, Gregory D; Laplantine, Emmanuel; Bednarek, Sebastian Y; Shorte, Spencer L; Eliceiri, Kevin W

2017-02-15

We present TrackMate, an open source Fiji plugin for the automated, semi-automated, and manual tracking of single-particles. It offers a versatile and modular solution that works out of the box for end users, through a simple and intuitive user interface. It is also easily scriptable and adaptable, operating equally well on 1D over time, 2D over time, 3D over time, or other single and multi-channel image variants. TrackMate provides several visualization and analysis tools that aid in assessing the relevance of results. The utility of TrackMate is further enhanced through its ability to be readily customized to meet specific tracking problems. TrackMate is an extensible platform where developers can easily write their own detection, particle linking, visualization or analysis algorithms within the TrackMate environment. This evolving framework provides researchers with the opportunity to quickly develop and optimize new algorithms based on existing TrackMate modules without the need of having to write de novo user interfaces, including visualization, analysis and exporting tools. The current capabilities of TrackMate are presented in the context of three different biological problems. First, we perform Caenorhabditis-elegans lineage analysis to assess how light-induced damage during imaging impairs its early development. Our TrackMate-based lineage analysis indicates the lack of a cell-specific light-sensitive mechanism. Second, we investigate the recruitment of NEMO (NF-κB essential modulator) clusters in fibroblasts after stimulation by the cytokine IL-1 and show that photodamage can generate artifacts in the shape of TrackMate characterized movements that confuse motility analysis. Finally, we validate the use of TrackMate for quantitative lifetime analysis of clathrin-mediated endocytosis in plant cells. Copyright © 2016 The Author(s). Published by Elsevier Inc. All rights reserved.

Kassiopeia: a modern, extensible C++ particle tracking package

NASA Astrophysics Data System (ADS)

Furse, Daniel; Groh, Stefan; Trost, Nikolaus; Babutzka, Martin; Barrett, John P.; Behrens, Jan; Buzinsky, Nicholas; Corona, Thomas; Enomoto, Sanshiro; Erhard, Moritz; Formaggio, Joseph A.; Glück, Ferenc; Harms, Fabian; Heizmann, Florian; Hilk, Daniel; Käfer, Wolfgang; Kleesiek, Marco; Leiber, Benjamin; Mertens, Susanne; Oblath, Noah S.; Renschler, Pascal; Schwarz, Johannes; Slocum, Penny L.; Wandkowsky, Nancy; Wierman, Kevin; Zacher, Michael

2017-05-01

The Kassiopeia particle tracking framework is an object-oriented software package using modern C++ techniques, written originally to meet the needs of the KATRIN collaboration. Kassiopeia features a new algorithmic paradigm for particle tracking simulations which targets experiments containing complex geometries and electromagnetic fields, with high priority put on calculation efficiency, customizability, extensibility, and ease-of-use for novice programmers. To solve Kassiopeia's target physics problem the software is capable of simulating particle trajectories governed by arbitrarily complex differential equations of motion, continuous physics processes that may in part be modeled as terms perturbing that equation of motion, stochastic processes that occur in flight such as bulk scattering and decay, and stochastic surface processes occurring at interfaces, including transmission and reflection effects. This entire set of computations takes place against the backdrop of a rich geometry package which serves a variety of roles, including initialization of electromagnetic field simulations and the support of state-dependent algorithm-swapping and behavioral changes as a particle’s state evolves. Thanks to the very general approach taken by Kassiopeia it can be used by other experiments facing similar challenges when calculating particle trajectories in electromagnetic fields. It is publicly available at https://github.com/KATRIN-Experiment/Kassiopeia.

A method to track rotational motion for use in single-molecule biophysics.

PubMed

Lipfert, Jan; Kerssemakers, Jacob J W; Rojer, Maylon; Dekker, Nynke H

2011-10-01

The double helical nature of DNA links many cellular processes such as DNA replication, transcription, and repair to rotational motion and the accumulation of torsional strain. Magnetic tweezers (MTs) are a single-molecule technique that enables the application of precisely calibrated stretching forces to nucleic acid tethers and to control their rotational motion. However, conventional magnetic tweezers do not directly monitor rotation or measure torque. Here, we describe a method to directly measure rotational motion of particles in MT. The method relies on attaching small, non-magnetic beads to the magnetic beads to act as fiducial markers for rotational tracking. CCD images of the beads are analyzed with a tracking algorithm specifically designed to minimize crosstalk between translational and rotational motion: first, the in-plane center position of the magnetic bead is determined with a kernel-based tracker, while subsequently the height and rotation angle of the bead are determined via correlation-based algorithms. Evaluation of the tracking algorithm using both simulated images and recorded images of surface-immobilized beads demonstrates a rotational resolution of 0.1°, while maintaining a translational resolution of 1-2 nm. Example traces of the rotational fluctuations exhibited by DNA-tethered beads confined in magnetic potentials of varying stiffness demonstrate the robustness of the method and the potential for simultaneous tracking of multiple beads. Our rotation tracking algorithm enables the extension of MTs to magnetic torque tweezers (MTT) to directly measure the torque in single molecules. In addition, we envision uses of the algorithm in a range of biophysical measurements, including further extensions of MT, tethered particle motion, and optical trapping measurements.

Online Multi-Modal Robust Non-Negative Dictionary Learning for Visual Tracking

PubMed Central

Zhang, Xiang; Guan, Naiyang; Tao, Dacheng; Qiu, Xiaogang; Luo, Zhigang

2015-01-01

Dictionary learning is a method of acquiring a collection of atoms for subsequent signal representation. Due to its excellent representation ability, dictionary learning has been widely applied in multimedia and computer vision. However, conventional dictionary learning algorithms fail to deal with multi-modal datasets. In this paper, we propose an online multi-modal robust non-negative dictionary learning (OMRNDL) algorithm to overcome this deficiency. Notably, OMRNDL casts visual tracking as a dictionary learning problem under the particle filter framework and captures the intrinsic knowledge about the target from multiple visual modalities, e.g., pixel intensity and texture information. To this end, OMRNDL adaptively learns an individual dictionary, i.e., template, for each modality from available frames, and then represents new particles over all the learned dictionaries by minimizing the fitting loss of data based on M-estimation. The resultant representation coefficient can be viewed as the common semantic representation of particles across multiple modalities, and can be utilized to track the target. OMRNDL incrementally learns the dictionary and the coefficient of each particle by using multiplicative update rules to respectively guarantee their non-negativity constraints. Experimental results on a popular challenging video benchmark validate the effectiveness of OMRNDL for visual tracking in both quantity and quality. PMID:25961715

Online multi-modal robust non-negative dictionary learning for visual tracking.

PubMed

Zhang, Xiang; Guan, Naiyang; Tao, Dacheng; Qiu, Xiaogang; Luo, Zhigang

2015-01-01

Dictionary learning is a method of acquiring a collection of atoms for subsequent signal representation. Due to its excellent representation ability, dictionary learning has been widely applied in multimedia and computer vision. However, conventional dictionary learning algorithms fail to deal with multi-modal datasets. In this paper, we propose an online multi-modal robust non-negative dictionary learning (OMRNDL) algorithm to overcome this deficiency. Notably, OMRNDL casts visual tracking as a dictionary learning problem under the particle filter framework and captures the intrinsic knowledge about the target from multiple visual modalities, e.g., pixel intensity and texture information. To this end, OMRNDL adaptively learns an individual dictionary, i.e., template, for each modality from available frames, and then represents new particles over all the learned dictionaries by minimizing the fitting loss of data based on M-estimation. The resultant representation coefficient can be viewed as the common semantic representation of particles across multiple modalities, and can be utilized to track the target. OMRNDL incrementally learns the dictionary and the coefficient of each particle by using multiplicative update rules to respectively guarantee their non-negativity constraints. Experimental results on a popular challenging video benchmark validate the effectiveness of OMRNDL for visual tracking in both quantity and quality.

Control strategy of grid-connected photovoltaic generation system based on GMPPT method

NASA Astrophysics Data System (ADS)

Wang, Zhongfeng; Zhang, Xuyang; Hu, Bo; Liu, Jun; Li, Ligang; Gu, Yongqiang; Zhou, Bowen

2018-02-01

There are multiple local maximum power points when photovoltaic (PV) array runs under partial shading condition (PSC).However, the traditional maximum power point tracking (MPPT) algorithm might be easily trapped in local maximum power points (MPPs) and cannot find the global maximum power point (GMPP). To solve such problem, a global maximum power point tracking method (GMPPT) is improved, combined with traditional MPPT method and particle swarm optimization (PSO) algorithm. Under different operating conditions of PV cells, different tracking algorithms are used. When the environment changes, the improved PSO algorithm is adopted to realize the global optimal search, and the variable step incremental conductance (INC) method is adopted to achieve MPPT in optimal local location. Based on the simulation model of the PV grid system built in Matlab/Simulink, comparative analysis of the tracking effect of MPPT by the proposed control algorithm and the traditional MPPT method under the uniform solar condition and PSC, validate the correctness, feasibility and effectiveness of the proposed control strategy.

Modeling Sediment Transport Using a Lagrangian Particle Tracking Algorithm Coupled with High-Resolution Large Eddy Simulations: a Critical Analysis of Model Limits and Sensitivity

NASA Astrophysics Data System (ADS)

Garcia, M. H.

2016-12-01

Modeling Sediment Transport Using a Lagrangian Particle Tracking Algorithm Coupled with High-Resolution Large Eddy Simulations: a Critical Analysis of Model Limits and Sensitivity Som Dutta1, Paul Fischer2, Marcelo H. Garcia11Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, Urbana, Il, 61801 2Department of Computer Science and Department of MechSE, University of Illinois at Urbana-Champaign, Urbana, Il, 61801 Since the seminal work of Niño and Garcia [1994], one-way coupled Lagrangian particle tracking has been used extensively for modeling sediment transport. Over time, the Lagrangian particle tracking method has been coupled with Eulerian flow simulations, ranging from Reynolds Averaged Navier-Stokes (RANS) based models to Detached Eddy Simulations (DES) [Escauriaza and Sotiropoulos, 2011]. Advent of high performance computing (HPC) platforms and faster algorithms have resulted in the work of Dutta et al. [2016], where Lagrangian particle tracking was coupled with high-resolution Large Eddy Simulations (LES) to model the complex and highly non-linear phenomenon of Bulle-Effect at diversions. Despite all the advancements in using Lagrangian particle tracking, there has not been a study that looks in detail at the limits of the model in the context of sediment transport, and also analyzes the sensitivity of the various force formulation in the force balance equation of the particles. Niño and Garcia [1994] did a similar analysis, but the vertical flow velocity distribution was modeled as the log-law. The current study extends the analysis by modeling the flow using high-resolution LES at a Reynolds number comparable to experiments of Niño et al. [1994]. Dutta et al., (2016), Large Eddy Simulation (LES) of flow and bedload transport at an idealized 90-degree diversion: insight into Bulle-Effect, River Flow 2016 - Constantinescu, Garcia & Hanes (Eds), Taylor & Francis Group, London, 101-109. Escauriaza and Sotiropoulos, (2011), Lagrangian model of bed-load transport in turbulent junction flows, Journal of Fluid Mechanics, 666,36-76. Niño and García, (1994), Gravel saltation: 2. Modeling, Water Resources Research, 30(6),1915-1924. Niño et al., (1994), Gravel saltation: 1. Experiments, Water Resources Research, 30(6), 1907-1914.

Precise 3D Track Reconstruction Algorithm for the ICARUS T600 Liquid Argon Time Projection Chamber Detector

DOE PAGES

Antonello, M.; Baibussinov, B.; Benetti, P.; ...

2013-01-15

Liquid Argon Time Projection Chamber (LAr TPC) detectors offer charged particle imaging capability with remarkable spatial resolution. Precise event reconstruction procedures are critical in order to fully exploit the potential of this technology. In this paper we present a new, general approach to 3D reconstruction for the LAr TPC with a practical application to the track reconstruction. The efficiency of the method is evaluated on a sample of simulated tracks. We present also the application of the method to the analysis of stopping particle tracks collected during the ICARUS T600 detector operation with the CNGS neutrino beam.

Optimum Value of Original Events on the Pept Technique

NASA Astrophysics Data System (ADS)

Sadremomtaz, Alireza; Taherparvar, Payvand

2011-12-01

Do Positron emission particle tracking (PEPT) has been used to track the motion of a single radioactively labeled tracer particle within a bed of similar particles. In this paper, the effect of the original event fraction on the results precise in two experiments has been reviewed. Results showed that the algorithm can no longer distinguish some corrupt trajectories, in addition to; further iteration reduces the statistical significance of the sample without improving its quality. Results show that the optimum value of trajectories depends on the type of experiment.

A Survey of Recent Advances in Particle Filters and Remaining Challenges for Multitarget Tracking

PubMed Central

Wang, Xuedong; Sun, Shudong; Corchado, Juan M.

2017-01-01

We review some advances of the particle filtering (PF) algorithm that have been achieved in the last decade in the context of target tracking, with regard to either a single target or multiple targets in the presence of false or missing data. The first part of our review is on remarkable achievements that have been made for the single-target PF from several aspects including importance proposal, computing efficiency, particle degeneracy/impoverishment and constrained/multi-modal systems. The second part of our review is on analyzing the intractable challenges raised within the general multitarget (multi-sensor) tracking due to random target birth and termination, false alarm, misdetection, measurement-to-track (M2T) uncertainty and track uncertainty. The mainstream multitarget PF approaches consist of two main classes, one based on M2T association approaches and the other not such as the finite set statistics-based PF. In either case, significant challenges remain due to unknown tracking scenarios and integrated tracking management. PMID:29168772

Tracking of Ball and Players in Beach Volleyball Videos

PubMed Central

Gomez, Gabriel; Herrera López, Patricia; Link, Daniel; Eskofier, Bjoern

2014-01-01

This paper presents methods for the determination of players' positions and contact time points by tracking the players and the ball in beach volleyball videos. Two player tracking methods are compared, a classical particle filter and a rigid grid integral histogram tracker. Due to mutual occlusion of the players and the camera perspective, results are best for the front players, with 74,6% and 82,6% of correctly tracked frames for the particle method and the integral histogram method, respectively. Results suggest an improved robustness against player confusion between different particle sets when tracking with a rigid grid approach. Faster processing and less player confusions make this method superior to the classical particle filter. Two different ball tracking methods are used that detect ball candidates from movement difference images using a background subtraction algorithm. Ball trajectories are estimated and interpolated from parabolic flight equations. The tracking accuracy of the ball is 54,2% for the trajectory growth method and 42,1% for the Hough line detection method. Tracking results of over 90% from the literature could not be confirmed. Ball contact frames were estimated from parabolic trajectory intersection, resulting in 48,9% of correctly estimated ball contact points. PMID:25426936

An evolutionary computation based algorithm for calculating solar differential rotation by automatic tracking of coronal bright points

NASA Astrophysics Data System (ADS)

Shahamatnia, Ehsan; Dorotovič, Ivan; Fonseca, Jose M.; Ribeiro, Rita A.

2016-03-01

Developing specialized software tools is essential to support studies of solar activity evolution. With new space missions such as Solar Dynamics Observatory (SDO), solar images are being produced in unprecedented volumes. To capitalize on that huge data availability, the scientific community needs a new generation of software tools for automatic and efficient data processing. In this paper a prototype of a modular framework for solar feature detection, characterization, and tracking is presented. To develop an efficient system capable of automatic solar feature tracking and measuring, a hybrid approach combining specialized image processing, evolutionary optimization, and soft computing algorithms is being followed. The specialized hybrid algorithm for tracking solar features allows automatic feature tracking while gathering characterization details about the tracked features. The hybrid algorithm takes advantages of the snake model, a specialized image processing algorithm widely used in applications such as boundary delineation, image segmentation, and object tracking. Further, it exploits the flexibility and efficiency of Particle Swarm Optimization (PSO), a stochastic population based optimization algorithm. PSO has been used successfully in a wide range of applications including combinatorial optimization, control, clustering, robotics, scheduling, and image processing and video analysis applications. The proposed tool, denoted PSO-Snake model, was already successfully tested in other works for tracking sunspots and coronal bright points. In this work, we discuss the application of the PSO-Snake algorithm for calculating the sidereal rotational angular velocity of the solar corona. To validate the results we compare them with published manual results performed by an expert.

Local characterization of hindered Brownian motion by using digital video microscopy and 3D particle tracking

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dettmer, Simon L.; Keyser, Ulrich F.; Pagliara, Stefano

In this article we present methods for measuring hindered Brownian motion in the confinement of complex 3D geometries using digital video microscopy. Here we discuss essential features of automated 3D particle tracking as well as diffusion data analysis. By introducing local mean squared displacement-vs-time curves, we are able to simultaneously measure the spatial dependence of diffusion coefficients, tracking accuracies and drift velocities. Such local measurements allow a more detailed and appropriate description of strongly heterogeneous systems as opposed to global measurements. Finite size effects of the tracking region on measuring mean squared displacements are also discussed. The use of thesemore » methods was crucial for the measurement of the diffusive behavior of spherical polystyrene particles (505 nm diameter) in a microfluidic chip. The particles explored an array of parallel channels with different cross sections as well as the bulk reservoirs. For this experiment we present the measurement of local tracking accuracies in all three axial directions as well as the diffusivity parallel to the channel axis while we observed no significant flow but purely Brownian motion. Finally, the presented algorithm is suitable also for tracking of fluorescently labeled particles and particles driven by an external force, e.g., electrokinetic or dielectrophoretic forces.« less

Improving maximum power point tracking of partially shaded photovoltaic system by using IPSO-BELBIC

NASA Astrophysics Data System (ADS)

Al-Alim El-Garhy, M. Abd; Mubarak, R. I.; El-Bably, M.

2017-08-01

Solar photovoltaic (PV) arrays in remote applications are often related to the rapid changes in the partial shading pattern. Rapid changes of the partial shading pattern make the tracking of maximum power point (MPP) of the global peak through the local ones too difficult. An essential need to make a fast and efficient algorithm to detect the peaks values which always vary as the sun irradiance changes. This paper presents two algorithms based on the improved particle swarm optimization technique one of them with PID controller (IPSO-PID), and the other one with Brain Emotional Learning Based Intelligent Controller (IPSO-BELBIC). These techniques improve the maximum power point (MPP) tracking capabilities for photovoltaic (PV) system under partial shading circumstances. The main aim of these improved algorithms is to accelerate the velocity of IPSO to reach to (MPP) and increase its efficiency. These algorithms also improve the tracking time under complex irradiance conditions. Based on these conditions, the tracking time of these presented techniques improves to 2 msec, with an efficiency of 100%.

A New Approach to Time-Resolved 3D-PTV

NASA Astrophysics Data System (ADS)

Boomsma, Aaron; Troolin, Dan; Bjorkquist, Dan; TSI Inc Team

2017-11-01

Volumetric three-component velocimetry via particle tracking is a powerful alternative to TomoPIV. It has been thoroughly documented that compared to TomoPIV, particle tracking velocimetry (PTV) methods (whether 2D or 3D) better resolve regions of high velocity gradient, identify fewer ghost particles, and are less computationally demanding, which results in shorter processing times. Recently, 3D-PTV has seen renewed interest in the PIV community with the availability of time-resolved data. Of course, advances in hardware are partly to thank for that availability-higher speed cameras, more effective memory management, and higher speed lasers. But in software, algorithms that utilize time resolved data to improve 3D particle reconstruction and particle tracking are also under development and advancing (e.g. shake-the-box, neighbor tracking reconstruction, etc.). .In the current study, we present a new 3D-PTV method that incorporates time-resolved data. We detail the method, its performance in terms of particle identification and reconstruction error and their relation to varying seeding densities, as well as computational performance.

Interface of the general fitting tool GENFIT2 in PandaRoot

NASA Astrophysics Data System (ADS)

Prencipe, Elisabetta; Spataro, Stefano; Stockmanns, Tobias; PANDA Collaboration

2017-10-01

\\bar{{{P}}}ANDA is a planned experiment at FAIR (Darmstadt) with a cooled antiproton beam in a range [1.5; 15] GeV/c, allowing a wide physics program in nuclear and particle physics. It is the only experiment worldwide, which combines a solenoid field (B=2T) and a dipole field (B=2Tm) in a spectrometer with a fixed target topology, in that energy regime. The tracking system of \\bar{{{P}}}ANDA involves the presence of a high performance silicon vertex detector, a GEM detector, a straw-tubes central tracker, a forward tracking system, and a luminosity monitor. The offline tracking algorithm is developed within the PandaRoot framework, which is a part of the FairRoot project. The tool here presented is based on algorithms containing the Kalman Filter equations and a deterministic annealing filter. This general fitting tool (GENFIT2) offers to users also a Runge-Kutta track representation, and interfaces with Millepede II (useful for alignment) and RAVE (vertex finder). It is independent on the detector geometry and the magnetic field map, and written in C++ object-oriented modular code. Several fitting algorithms are available with GENFIT2, with user-adjustable parameters; therefore the tool is of friendly usage. A check on the fit convergence is done by GENFIT2 as well. The Kalman-Filter-based algorithms have a wide range of applications; among those in particle physics they can perform extrapolations of track parameters and covariance matrices. The adoptions of the PandaRoot framework to connect to Genfit2 are described, and the impact of GENFIT2 on the physics simulations of \\bar{{{P}}}ANDA are shown: significant improvement is reported for those channels where a good low momentum tracking is required (pT < 400 MeV/c).

High-Performance Reactive Particle Tracking with Adaptive Representation

NASA Astrophysics Data System (ADS)

Schmidt, M.; Benson, D. A.; Pankavich, S.

2017-12-01

Lagrangian particle tracking algorithms have been shown to be effective tools for modeling chemical reactions in imperfectly-mixed media. One disadvantage of these algorithms is the possible need to employ large numbers of particles in simulations, depending on the concentration covariance structure, and these large particle numbers can lead to long computation times. Two distinct approaches have recently arisen to overcome this. One method employs spatial kernels that are related to a specified, reduced particle number; however, over-wide kernels, dictated by a very low particle number, lead to an excess of reaction calculations and cause a reduction in performance. Another formulation involves hybrid particles that carry multiple species of reactant, wherein each particle is treated as its own well-mixed volume, obviating the need for large numbers of particles for each species but still requiring a fixed number of hybrid particles. Here, we combine these two approaches and demonstrate an improved method for simulating a given system in a computationally efficient manner. Additionally, the independent nature of transport and reaction calculations in this approach allows for significant gains via parallelization in an MPI or OpenMP context. For benchmarking, we choose a CO2 injection simulation with dissolution and precipitation of calcite and dolomite, allowing us to derive the proper treatment of interaction between solid and aqueous phases.

Dispersion Analysis Using Particle Tracking Simulations Through Heterogeneity Based on Outcrop Lidar Imagery

NASA Astrophysics Data System (ADS)

Klise, K. A.; Weissmann, G. S.; McKenna, S. A.; Tidwell, V. C.; Frechette, J. D.; Wawrzyniec, T. F.

2007-12-01

Solute plumes are believed to disperse in a non-Fickian manner due to small-scale heterogeneity and variable velocities that create preferential pathways. In order to accurately predict dispersion in naturally complex geologic media, the connection between heterogeneity and dispersion must be better understood. Since aquifer properties can not be measured at every location, it is common to simulate small-scale heterogeneity with random field generators based on a two-point covariance (e.g., through use of sequential simulation algorithms). While these random fields can produce preferential flow pathways, it is unknown how well the results simulate solute dispersion through natural heterogeneous media. To evaluate the influence that complex heterogeneity has on dispersion, we utilize high-resolution terrestrial lidar to identify and model lithofacies from outcrop for application in particle tracking solute transport simulations using RWHet. The lidar scan data are used to produce a lab (meter) scale two-dimensional model that captures 2-8 mm scale natural heterogeneity. Numerical simulations utilize various methods to populate the outcrop structure captured by the lidar-based image with reasonable hydraulic conductivity values. The particle tracking simulations result in residence time distributions used to evaluate the nature of dispersion through complex media. Particle tracking simulations through conductivity fields produced from the lidar images are then compared to particle tracking simulations through hydraulic conductivity fields produced from sequential simulation algorithms. Based on this comparison, the study aims to quantify the difference in dispersion when using realistic and simplified representations of aquifer heterogeneity. Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

Infrared dim moving target tracking via sparsity-based discriminative classifier and convolutional network

NASA Astrophysics Data System (ADS)

Qian, Kun; Zhou, Huixin; Wang, Bingjian; Song, Shangzhen; Zhao, Dong

2017-11-01

Infrared dim and small target tracking is a great challenging task. The main challenge for target tracking is to account for appearance change of an object, which submerges in the cluttered background. An efficient appearance model that exploits both the global template and local representation over infrared image sequences is constructed for dim moving target tracking. A Sparsity-based Discriminative Classifier (SDC) and a Convolutional Network-based Generative Model (CNGM) are combined with a prior model. In the SDC model, a sparse representation-based algorithm is adopted to calculate the confidence value that assigns more weights to target templates than negative background templates. In the CNGM model, simple cell feature maps are obtained by calculating the convolution between target templates and fixed filters, which are extracted from the target region at the first frame. These maps measure similarities between each filter and local intensity patterns across the target template, therefore encoding its local structural information. Then, all the maps form a representation, preserving the inner geometric layout of a candidate template. Furthermore, the fixed target template set is processed via an efficient prior model. The same operation is applied to candidate templates in the CNGM model. The online update scheme not only accounts for appearance variations but also alleviates the migration problem. At last, collaborative confidence values of particles are utilized to generate particles' importance weights. Experiments on various infrared sequences have validated the tracking capability of the presented algorithm. Experimental results show that this algorithm runs in real-time and provides a higher accuracy than state of the art algorithms.

Iterative reconstruction of volumetric particle distribution

NASA Astrophysics Data System (ADS)

Wieneke, Bernhard

2013-02-01

For tracking the motion of illuminated particles in space and time several volumetric flow measurement techniques are available like 3D-particle tracking velocimetry (3D-PTV) recording images from typically three to four viewing directions. For higher seeding densities and the same experimental setup, tomographic PIV (Tomo-PIV) reconstructs voxel intensities using an iterative tomographic reconstruction algorithm (e.g. multiplicative algebraic reconstruction technique, MART) followed by cross-correlation of sub-volumes computing instantaneous 3D flow fields on a regular grid. A novel hybrid algorithm is proposed here that similar to MART iteratively reconstructs 3D-particle locations by comparing the recorded images with the projections calculated from the particle distribution in the volume. But like 3D-PTV, particles are represented by 3D-positions instead of voxel-based intensity blobs as in MART. Detailed knowledge of the optical transfer function and the particle image shape is mandatory, which may differ for different positions in the volume and for each camera. Using synthetic data it is shown that this method is capable of reconstructing densely seeded flows up to about 0.05 ppp with similar accuracy as Tomo-PIV. Finally the method is validated with experimental data.

RB Particle Filter Time Synchronization Algorithm Based on the DPM Model.

PubMed

Guo, Chunsheng; Shen, Jia; Sun, Yao; Ying, Na

2015-09-03

Time synchronization is essential for node localization, target tracking, data fusion, and various other Wireless Sensor Network (WSN) applications. To improve the estimation accuracy of continuous clock offset and skew of mobile nodes in WSNs, we propose a novel time synchronization algorithm, the Rao-Blackwellised (RB) particle filter time synchronization algorithm based on the Dirichlet process mixture (DPM) model. In a state-space equation with a linear substructure, state variables are divided into linear and non-linear variables by the RB particle filter algorithm. These two variables can be estimated using Kalman filter and particle filter, respectively, which improves the computational efficiency more so than if only the particle filter was used. In addition, the DPM model is used to describe the distribution of non-deterministic delays and to automatically adjust the number of Gaussian mixture model components based on the observational data. This improves the estimation accuracy of clock offset and skew, which allows achieving the time synchronization. The time synchronization performance of this algorithm is also validated by computer simulations and experimental measurements. The results show that the proposed algorithm has a higher time synchronization precision than traditional time synchronization algorithms.

Phytoplankton as Particles - A New Approach to Modeling Algal Blooms

DTIC Science & Technology

2013-07-01

68  Figure 69. Amplitudes of lunar semi-diurnal and diurnal harmonics of observed and computed...particle behavior when the trajectory takes a particle outside the model domain. The rules associated with the present particle-tracking algorithms are... land - ward, although occasional reversals occurred. Amplitude of the current fluctuations was ≈ 20 cm s-1. Model residual currents for one year were

Fast human pose estimation using 3D Zernike descriptors

NASA Astrophysics Data System (ADS)

Berjón, Daniel; Morán, Francisco

2012-03-01

Markerless video-based human pose estimation algorithms face a high-dimensional problem that is frequently broken down into several lower-dimensional ones by estimating the pose of each limb separately. However, in order to do so they need to reliably locate the torso, for which they typically rely on time coherence and tracking algorithms. Their losing track usually results in catastrophic failure of the process, requiring human intervention and thus precluding their usage in real-time applications. We propose a very fast rough pose estimation scheme based on global shape descriptors built on 3D Zernike moments. Using an articulated model that we configure in many poses, a large database of descriptor/pose pairs can be computed off-line. Thus, the only steps that must be done on-line are the extraction of the descriptors for each input volume and a search against the database to get the most likely poses. While the result of such process is not a fine pose estimation, it can be useful to help more sophisticated algorithms to regain track or make more educated guesses when creating new particles in particle-filter-based tracking schemes. We have achieved a performance of about ten fps on a single computer using a database of about one million entries.

Particle Tracking Model Transport Process Verification: Diffusion Algorithm

DTIC Science & Technology

2015-07-01

sediment densities in space and time along with final particle fates (Demirbilek et al. 2004; Davies et al. 2005; McDonald et al. 2006; Lackey and... McDonald 2007). Although a versatile model currently utilized in various coastal, estuarine, and riverine applications, PTM is specifically designed to...Algorithm 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR( S ) 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 7

Monte Carlo charged-particle tracking and energy deposition on a Lagrangian mesh.

PubMed

Yuan, J; Moses, G A; McKenty, P W

2005-10-01

A Monte Carlo algorithm for alpha particle tracking and energy deposition on a cylindrical computational mesh in a Lagrangian hydrodynamics code used for inertial confinement fusion (ICF) simulations is presented. The straight line approximation is used to follow propagation of "Monte Carlo particles" which represent collections of alpha particles generated from thermonuclear deuterium-tritium (DT) reactions. Energy deposition in the plasma is modeled by the continuous slowing down approximation. The scheme addresses various aspects arising in the coupling of Monte Carlo tracking with Lagrangian hydrodynamics; such as non-orthogonal severely distorted mesh cells, particle relocation on the moving mesh and particle relocation after rezoning. A comparison with the flux-limited multi-group diffusion transport method is presented for a polar direct drive target design for the National Ignition Facility. Simulations show the Monte Carlo transport method predicts about earlier ignition than predicted by the diffusion method, and generates higher hot spot temperature. Nearly linear speed-up is achieved for multi-processor parallel simulations.

Classification of nanoparticle diffusion processes in vital cells by a multifeature random forests approach: application to simulated data, darkfield, and confocal laser scanning microscopy

NASA Astrophysics Data System (ADS)

Wagner, Thorsten; Kroll, Alexandra; Wiemann, Martin; Lipinski, Hans-Gerd

2016-04-01

Darkfield and confocal laser scanning microscopy both allow for a simultaneous observation of live cells and single nanoparticles. Accordingly, a characterization of nanoparticle uptake and intracellular mobility appears possible within living cells. Single particle tracking makes it possible to characterize the particle and the surrounding cell. In case of free diffusion, the mean squared displacement for each trajectory of a nanoparticle can be measured which allows computing the corresponding diffusion coefficient and, if desired, converting it into the hydrodynamic diameter using the Stokes-Einstein equation and the viscosity of the fluid. However, within the more complex system of a cell's cytoplasm unrestrained diffusion is scarce and several other types of movements may occur. Thus, confined or anomalous diffusion (e.g. diffusion in porous media), active transport, and combinations thereof were described by several authors. To distinguish between these types of particle movement we developed an appropriate classification method, and simulated three types of particle motion in a 2D plane using a Monte Carlo approach: (1) normal diffusion, using random direction and step-length, (2) subdiffusion, using confinements like a reflective boundary with defined radius or reflective objects in the closer vicinity, and (3) superdiffusion, using a directed flow added to the normal diffusion. To simulate subdiffusion we devised a new method based on tracks of different length combined with equally probable obstacle interaction. Next we estimated the fractal dimension, elongation and the ratio of long-time / short-time diffusion coefficients. These features were used to train a random forests classification algorithm. The accuracy for simulated trajectories with 180 steps was 97% (95%-CI: 0.9481-0.9884). The balanced accuracy was 94%, 99% and 98% for normal-, sub- and superdiffusion, respectively. Nanoparticle tracking analysis was used with 100 nm polystyrene particles to get trajectories for normal diffusion. As a next step we identified diffusion types of nanoparticles in vital cells and incubated V79 fibroblasts with 50 nm gold nanoparticles, which appeared as intensely bright objects due to their surface plasmon resonance. The movement of particles in both the extracellular and intracellular space was observed by dark field and confocal laser scanning microscopy. After reducing background noise from the video it became possible to identify individual particle spots by a maximum detection algorithm and trace them using the robust single-particle tracking algorithm proposed by Jaqaman, which is able to handle motion heterogeneity and particle disappearance. The particle trajectories inside cells indicated active transport (superdiffusion) as well as subdiffusion. Eventually, the random forest classification algorithm, after being trained by the above simulations, successfully classified the trajectories observed in live cells.

Efficient Spatiotemporal Clutter Rejection and Nonlinear Filtering-based Dim Resolved and Unresolved Object Tracking Algorithms

NASA Astrophysics Data System (ADS)

Tartakovsky, A.; Tong, M.; Brown, A. P.; Agh, C.

2013-09-01

We develop efficient spatiotemporal image processing algorithms for rejection of non-stationary clutter and tracking of multiple dim objects using non-linear track-before-detect methods. For clutter suppression, we include an innovative image alignment (registration) algorithm. The images are assumed to contain elements of the same scene, but taken at different angles, from different locations, and at different times, with substantial clutter non-stationarity. These challenges are typical for space-based and surface-based IR/EO moving sensors, e.g., highly elliptical orbit or low earth orbit scenarios. The algorithm assumes that the images are related via a planar homography, also known as the projective transformation. The parameters are estimated in an iterative manner, at each step adjusting the parameter vector so as to achieve improved alignment of the images. Operating in the parameter space rather than in the coordinate space is a new idea, which makes the algorithm more robust with respect to noise as well as to large inter-frame disturbances, while operating at real-time rates. For dim object tracking, we include new advancements to a particle non-linear filtering-based track-before-detect (TrbD) algorithm. The new TrbD algorithm includes both real-time full image search for resolved objects not yet in track and joint super-resolution and tracking of individual objects in closely spaced object (CSO) clusters. The real-time full image search provides near-optimal detection and tracking of multiple extremely dim, maneuvering objects/clusters. The super-resolution and tracking CSO TrbD algorithm provides efficient near-optimal estimation of the number of unresolved objects in a CSO cluster, as well as the locations, velocities, accelerations, and intensities of the individual objects. We demonstrate that the algorithm is able to accurately estimate the number of CSO objects and their locations when the initial uncertainty on the number of objects is large. We demonstrate performance of the TrbD algorithm both for satellite-based and surface-based EO/IR surveillance scenarios.

Comparing Models and Methods for the Delineation of Stream Baseflow Contribution Areas

NASA Astrophysics Data System (ADS)

Chow, R.; Frind, M.; Frind, E. O.; Jones, J. P.; Sousa, M.; Rudolph, D. L.; Nowak, W.

2016-12-01

This study addresses the delineation of areas that contribute baseflow to a stream reach, also known as stream capture zones. Such areas can be delineated using standard well capture zone delineation methods, with three important differences: (1) natural gradients are smaller compared to those produced by supply wells and are therefore subject to greater numerical errors, (2) stream discharge varies seasonally, and (3) stream discharge varies spatially. This study focuses on model-related uncertainties due to parameter non-uniqueness, discretization schemes, and particle tracking algorithms. The methodology is applied to the Alder Creek watershed in southwestern Ontario. Four different model codes are compared: HydroGeoSphere, WATFLOW, MODFLOW, and FEFLOW. In addition, two delineation methods are compared: reverse particle tracking and reverse transport, where the latter considers local-scale parameter uncertainty by using a macrodispersion term to produce a capture probability plume. The results from this study indicate that different models can calibrate acceptably well to the same data and produce very similar distributions of hydraulic head, but can produce different capture zones. The stream capture zone is found to be highly sensitive to the particle tracking algorithm. It was also found that particle tracking by itself, if applied to complex systems such as the Alder Creek watershed, would require considerable subjective judgement in the delineation of stream capture zones. Reverse transport is an alternate approach that provides probability intervals for the baseflow contribution areas. In situations where the two approaches agree, the confidence in the delineation is reinforced.

Particle identification algorithms for the PANDA Endcap Disc DIRC

NASA Astrophysics Data System (ADS)

Schmidt, M.; Ali, A.; Belias, A.; Dzhygadlo, R.; Gerhardt, A.; Götzen, K.; Kalicy, G.; Krebs, M.; Lehmann, D.; Nerling, F.; Patsyuk, M.; Peters, K.; Schepers, G.; Schmitt, L.; Schwarz, C.; Schwiening, J.; Traxler, M.; Böhm, M.; Eyrich, W.; Lehmann, A.; Pfaffinger, M.; Uhlig, F.; Düren, M.; Etzelmüller, E.; Föhl, K.; Hayrapetyan, A.; Kreutzfeld, K.; Merle, O.; Rieke, J.; Wasem, T.; Achenbach, P.; Cardinali, M.; Hoek, M.; Lauth, W.; Schlimme, S.; Sfienti, C.; Thiel, M.

2017-12-01

The Endcap Disc DIRC has been developed to provide an excellent particle identification for the future PANDA experiment by separating pions and kaons up to a momentum of 4 GeV/c with a separation power of 3 standard deviations in the polar angle region from 5o to 22o. This goal will be achieved using dedicated particle identification algorithms based on likelihood methods and will be applied in an offline analysis and online event filtering. This paper evaluates the resulting PID performance using Monte-Carlo simulations to study basic single track PID as well as the analysis of complex physics channels. The online reconstruction algorithm has been tested with a Virtex4 FGPA card and optimized regarding the resulting constraints.

Thermal tracking in mobile robots for leak inspection activities.

PubMed

Ibarguren, Aitor; Molina, Jorge; Susperregi, Loreto; Maurtua, Iñaki

2013-10-09

Maintenance tasks are crucial for all kind of industries, especially in extensive industrial plants, like solar thermal power plants. The incorporation of robots is a key issue for automating inspection activities, as it will allow a constant and regular control over the whole plant. This paper presents an autonomous robotic system to perform pipeline inspection for early detection and prevention of leakages in thermal power plants, based on the work developed within the MAINBOT (http://www.mainbot.eu) European project. Based on the information provided by a thermographic camera, the system is able to detect leakages in the collectors and pipelines. Beside the leakage detection algorithms, the system includes a particle filter-based tracking algorithm to keep the target in the field of view of the camera and to avoid the irregularities of the terrain while the robot patrols the plant. The information provided by the particle filter is further used to command a robot arm, which handles the camera and ensures that the target is always within the image. The obtained results show the suitability of the proposed approach, adding a tracking algorithm to improve the performance of the leakage detection system.

Thermal Tracking in Mobile Robots for Leak Inspection Activities

PubMed Central

Ibarguren, Aitor; Molina, Jorge; Susperregi, Loreto; Maurtua, Iñaki

2013-01-01

Maintenance tasks are crucial for all kind of industries, especially in extensive industrial plants, like solar thermal power plants. The incorporation of robots is a key issue for automating inspection activities, as it will allow a constant and regular control over the whole plant. This paper presents an autonomous robotic system to perform pipeline inspection for early detection and prevention of leakages in thermal power plants, based on the work developed within the MAINBOT (http://www.mainbot.eu) European project. Based on the information provided by a thermographic camera, the system is able to detect leakages in the collectors and pipelines. Beside the leakage detection algorithms, the system includes a particle filter-based tracking algorithm to keep the target in the field of view of the camera and to avoid the irregularities of the terrain while the robot patrols the plant. The information provided by the particle filter is further used to command a robot arm, which handles the camera and ensures that the target is always within the image. The obtained results show the suitability of the proposed approach, adding a tracking algorithm to improve the performance of the leakage detection system. PMID:24113684

Comparison of particle tracking algorithms in commercial CFD packages: sedimentation and diffusion.

PubMed

Robinson, Risa J; Snyder, Pam; Oldham, Michael J

2007-05-01

Computational fluid dynamic modeling software has enabled microdosimetry patterns of inhaled toxins and toxicants to be predicted and visualized, and is being used in inhalation toxicology and risk assessment. These predicted microdosimetry patterns in airway structures are derived from predicted airflow patterns within these airways and particle tracking algorithms used in computational fluid dynamics (CFD) software packages. Although these commercial CFD codes have been tested for accuracy under various conditions, they have not been well tested for respiratory flows in general. Nor has their particle tracking algorithm accuracy been well studied. In this study, three software packages, Fluent Discrete Phase Model (DPM), Fluent Fine Particle Model (FPM), and ANSYS CFX, were evaluated. Sedimentation and diffusion were each isolated in a straight tube geometry and tested for accuracy. A range of flow rates corresponding to adult low activity (minute ventilation = 10 L/min) and to heavy exertion (minute ventilation = 60 L/min) were tested by varying the range of dimensionless diffusion and sedimentation parameters found using the Weibel symmetric 23 generation lung morphology. Numerical results for fully developed parabolic and uniform (slip) profiles were compared respectively, to Pich (1972) and Yu (1977) analytical sedimentation solutions. Schum and Yeh (1980) equations for sedimentation were also compared. Numerical results for diffusional deposition were compared to analytical solutions of Ingham (1975) for parabolic and uniform profiles. Significant differences were found among the various CFD software packages and between numerical and analytical solutions. Therefore, it is prudent to validate CFD predictions against analytical solutions in idealized geometry before tackling the complex geometries of the respiratory tract.

Coherent structure coloring: identification of coherent structures from sparse flow trajectories using graph theory

NASA Astrophysics Data System (ADS)

Schlueter, Kristy; Dabiri, John

2016-11-01

Coherent structure identification is important in many fluid dynamics applications, including transport phenomena in ocean flows and mixing and diffusion in turbulence. However, many of the techniques currently available for measuring such flows, including ocean drifter datasets and particle tracking velocimetry, only result in sparse velocity data. This is often insufficient for the use of current coherent structure detection algorithms based on analysis of the deformation gradient. Here, we present a frame-invariant method for detecting coherent structures from Lagrangian flow trajectories that can be sparse in number. The method, based on principles used in graph coloring algorithms, examines a measure of the kinematic dissimilarity of all pairs of flow trajectories, either measured experimentally, e.g. using particle tracking velocimetry; or numerically, by advecting fluid particles in the Eulerian velocity field. Coherence is assigned to groups of particles whose kinematics remain similar throughout the time interval for which trajectory data is available, regardless of their physical proximity to one another. Through the use of several analytical and experimental validation cases, this algorithm is shown to robustly detect coherent structures using significantly less flow data than is required by existing methods. This research was supported by the Department of Defense (DoD) through the National Defense Science & Engineering Graduate Fellowship (NDSEG) Program.

Integrating Geochemical Reactions with a Particle-Tracking Approach to Simulate Nitrogen Transport and Transformation in Aquifers

NASA Astrophysics Data System (ADS)

Cui, Z.; Welty, C.; Maxwell, R. M.

2011-12-01

Lagrangian, particle-tracking models are commonly used to simulate solute advection and dispersion in aquifers. They are computationally efficient and suffer from much less numerical dispersion than grid-based techniques, especially in heterogeneous and advectively-dominated systems. Although particle-tracking models are capable of simulating geochemical reactions, these reactions are often simplified to first-order decay and/or linear, first-order kinetics. Nitrogen transport and transformation in aquifers involves both biodegradation and higher-order geochemical reactions. In order to take advantage of the particle-tracking approach, we have enhanced an existing particle-tracking code SLIM-FAST, to simulate nitrogen transport and transformation in aquifers. The approach we are taking is a hybrid one: the reactive multispecies transport process is operator split into two steps: (1) the physical movement of the particles including the attachment/detachment to solid surfaces, which is modeled by a Lagrangian random-walk algorithm; and (2) multispecies reactions including biodegradation are modeled by coupling multiple Monod equations with other geochemical reactions. The coupled reaction system is solved by an ordinary differential equation solver. In order to solve the coupled system of equations, after step 1, the particles are converted to grid-based concentrations based on the mass and position of the particles, and after step 2 the newly calculated concentration values are mapped back to particles. The enhanced particle-tracking code is capable of simulating subsurface nitrogen transport and transformation in a three-dimensional domain with variably saturated conditions. Potential application of the enhanced code is to simulate subsurface nitrogen loading to the Chesapeake Bay and its tributaries. Implementation details, verification results of the enhanced code with one-dimensional analytical solutions and other existing numerical models will be presented in addition to a discussion of implementation challenges.

The HEP.TrkX Project: deep neural networks for HL-LHC online and offline tracking

DOE PAGES

Farrell, Steven; Anderson, Dustin; Calafiura, Paolo; ...

2017-08-08

Particle track reconstruction in dense environments such as the detectors of the High Luminosity Large Hadron Collider (HL-LHC) is a challenging pattern recognition problem. Traditional tracking algorithms such as the combinatorial Kalman Filter have been used with great success in LHC experiments for years. However, these state-of-the-art techniques are inherently sequential and scale poorly with the expected increases in detector occupancy in the HL-LHC conditions. The HEP.TrkX project is a pilot project with the aim to identify and develop cross-experiment solutions based on machine learning algorithms for track reconstruction. Machine learning algorithms bring a lot of potential to this problemmore » thanks to their capability to model complex non-linear data dependencies, to learn effective representations of high-dimensional data through training, and to parallelize easily on high-throughput architectures such as GPUs. This contribution will describe our initial explorations into this relatively unexplored idea space. Furthermore, we will discuss the use of recurrent (LSTM) and convolutional neural networks to find and fit tracks in toy detector data.« less

The HEP.TrkX Project: deep neural networks for HL-LHC online and offline tracking

DOE Office of Scientific and Technical Information (OSTI.GOV)

Farrell, Steven; Anderson, Dustin; Calafiura, Paolo

Particle track reconstruction in dense environments such as the detectors of the High Luminosity Large Hadron Collider (HL-LHC) is a challenging pattern recognition problem. Traditional tracking algorithms such as the combinatorial Kalman Filter have been used with great success in LHC experiments for years. However, these state-of-the-art techniques are inherently sequential and scale poorly with the expected increases in detector occupancy in the HL-LHC conditions. The HEP.TrkX project is a pilot project with the aim to identify and develop cross-experiment solutions based on machine learning algorithms for track reconstruction. Machine learning algorithms bring a lot of potential to this problemmore » thanks to their capability to model complex non-linear data dependencies, to learn effective representations of high-dimensional data through training, and to parallelize easily on high-throughput architectures such as GPUs. This contribution will describe our initial explorations into this relatively unexplored idea space. Furthermore, we will discuss the use of recurrent (LSTM) and convolutional neural networks to find and fit tracks in toy detector data.« less

The HEP.TrkX Project: deep neural networks for HL-LHC online and offline tracking

NASA Astrophysics Data System (ADS)

Farrell, Steven; Anderson, Dustin; Calafiura, Paolo; Cerati, Giuseppe; Gray, Lindsey; Kowalkowski, Jim; Mudigonda, Mayur; Prabhat; Spentzouris, Panagiotis; Spiropoulou, Maria; Tsaris, Aristeidis; Vlimant, Jean-Roch; Zheng, Stephan

2017-08-01

Particle track reconstruction in dense environments such as the detectors of the High Luminosity Large Hadron Collider (HL-LHC) is a challenging pattern recognition problem. Traditional tracking algorithms such as the combinatorial Kalman Filter have been used with great success in LHC experiments for years. However, these state-of-the-art techniques are inherently sequential and scale poorly with the expected increases in detector occupancy in the HL-LHC conditions. The HEP.TrkX project is a pilot project with the aim to identify and develop cross-experiment solutions based on machine learning algorithms for track reconstruction. Machine learning algorithms bring a lot of potential to this problem thanks to their capability to model complex non-linear data dependencies, to learn effective representations of high-dimensional data through training, and to parallelize easily on high-throughput architectures such as GPUs. This contribution will describe our initial explorations into this relatively unexplored idea space. We will discuss the use of recurrent (LSTM) and convolutional neural networks to find and fit tracks in toy detector data.

STABILITY OF THE NEUTRON DOSE DETERMINATION ALGORITHM FOR PERSONAL NEUTRON DOSEMETERS AT DIFFERENT RADON GAS EXPOSURES.

PubMed

Mayer, Sabine; Boschung, Markus; Butterweck, Gernot; Assenmacher, Frank; Hohmann, Eike

2016-09-01

Since 2008 the Paul Scherrer Institute (PSI) has been using a microscope-based automatic scanning system for assessing personal neutron doses with a dosemeter based on PADC. This scanning system, known as TASLImage, includes a comprehensive characterisation of tracks. The distributions of several specific track characteristics such as size, shape and optical density are compared with a reference set to discriminate tracks of alpha particles and non-track background. Due to the dosemeter design at PSI, it is anticipated that radon should not significantly contribute to the creation of additional tracks in the PADC detector. The present study tests the stability of the neutron dose determination algorithm of the personal neutron dosemeter system in operation at PSI at different radon gas exposures. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

A new maximum power tracking in PV system during partially shaded conditions based on shuffled frog leap algorithm

NASA Astrophysics Data System (ADS)

Sridhar, R.; Jeevananthan, S.; Dash, S. S.; Vishnuram, Pradeep

2017-05-01

Maximum Power Point Trackers (MPPTs) are power electronic conditioners used in photovoltaic (PV) system to ensure that PV structures feed maximum power for the given ambient temperature and sun's irradiation. When the PV panels are shaded by a fraction due to any environment hindrances then, conventional MPPT trackers may fail in tracking the appropriate peak power as there will be multi power peaks. In this work, a shuffled frog leap algorithm (SFLA) is proposed and it successfully identifies the global maximum power point among other local maxima. The SFLA MPPT is compared with a well-entrenched conventional perturb and observe (P&O) MPPT algorithm and a global search particle swarm optimisation (PSO) MPPT. The simulation results reveal that the proposed algorithm is highly advantageous than P&O, as it tracks nearly 30% more power for a given shading pattern. The credible nature of the proposed SFLA is ensured when it outplays PSO MPPT in convergence. The whole system is realised in MATLAB/Simulink environment.

Tracking multiple particles in fluorescence time-lapse microscopy images via probabilistic data association.

PubMed

Godinez, William J; Rohr, Karl

2015-02-01

Tracking subcellular structures as well as viral structures displayed as 'particles' in fluorescence microscopy images yields quantitative information on the underlying dynamical processes. We have developed an approach for tracking multiple fluorescent particles based on probabilistic data association. The approach combines a localization scheme that uses a bottom-up strategy based on the spot-enhancing filter as well as a top-down strategy based on an ellipsoidal sampling scheme that uses the Gaussian probability distributions computed by a Kalman filter. The localization scheme yields multiple measurements that are incorporated into the Kalman filter via a combined innovation, where the association probabilities are interpreted as weights calculated using an image likelihood. To track objects in close proximity, we compute the support of each image position relative to the neighboring objects of a tracked object and use this support to recalculate the weights. To cope with multiple motion models, we integrated the interacting multiple model algorithm. The approach has been successfully applied to synthetic 2-D and 3-D images as well as to real 2-D and 3-D microscopy images, and the performance has been quantified. In addition, the approach was successfully applied to the 2-D and 3-D image data of the recent Particle Tracking Challenge at the IEEE International Symposium on Biomedical Imaging (ISBI) 2012.

Semi-Supervised Tensor-Based Graph Embedding Learning and Its Application to Visual Discriminant Tracking.

PubMed

Hu, Weiming; Gao, Jin; Xing, Junliang; Zhang, Chao; Maybank, Stephen

2017-01-01

An appearance model adaptable to changes in object appearance is critical in visual object tracking. In this paper, we treat an image patch as a two-order tensor which preserves the original image structure. We design two graphs for characterizing the intrinsic local geometrical structure of the tensor samples of the object and the background. Graph embedding is used to reduce the dimensions of the tensors while preserving the structure of the graphs. Then, a discriminant embedding space is constructed. We prove two propositions for finding the transformation matrices which are used to map the original tensor samples to the tensor-based graph embedding space. In order to encode more discriminant information in the embedding space, we propose a transfer-learning- based semi-supervised strategy to iteratively adjust the embedding space into which discriminative information obtained from earlier times is transferred. We apply the proposed semi-supervised tensor-based graph embedding learning algorithm to visual tracking. The new tracking algorithm captures an object's appearance characteristics during tracking and uses a particle filter to estimate the optimal object state. Experimental results on the CVPR 2013 benchmark dataset demonstrate the effectiveness of the proposed tracking algorithm.

Delineating baseflow contribution areas for streams - A model and methods comparison

NASA Astrophysics Data System (ADS)

Chow, Reynold; Frind, Michael E.; Frind, Emil O.; Jones, Jon P.; Sousa, Marcelo R.; Rudolph, David L.; Molson, John W.; Nowak, Wolfgang

2016-12-01

This study addresses the delineation of areas that contribute baseflow to a stream reach, also known as stream capture zones. Such areas can be delineated using standard well capture zone delineation methods, with three important differences: (1) natural gradients are smaller compared to those produced by supply wells and are therefore subject to greater numerical errors, (2) stream discharge varies seasonally, and (3) stream discharge varies spatially. This study focuses on model-related uncertainties due to model characteristics, discretization schemes, delineation methods, and particle tracking algorithms. The methodology is applied to the Alder Creek watershed in southwestern Ontario. Four different model codes are compared: HydroGeoSphere, WATFLOW, MODFLOW, and FEFLOW. In addition, two delineation methods are compared: reverse particle tracking and reverse transport, where the latter considers local-scale parameter uncertainty by using a macrodispersion term to produce a capture probability plume. The results from this study indicate that different models can calibrate acceptably well to the same data and produce very similar distributions of hydraulic head, but can produce different capture zones. The stream capture zone is found to be highly sensitive to the particle tracking algorithm. It was also found that particle tracking by itself, if applied to complex systems such as the Alder Creek watershed, would require considerable subjective judgement in the delineation of stream capture zones. Reverse transport is an alternative and more reliable approach that provides probability intervals for the baseflow contribution areas, taking uncertainty into account. The two approaches can be used together to enhance the confidence in the final outcome.

Visual tracking based on the sparse representation of the PCA subspace

NASA Astrophysics Data System (ADS)

Chen, Dian-bing; Zhu, Ming; Wang, Hui-li

2017-09-01

We construct a collaborative model of the sparse representation and the subspace representation. First, we represent the tracking target in the principle component analysis (PCA) subspace, and then we employ an L 1 regularization to restrict the sparsity of the residual term, an L 2 regularization term to restrict the sparsity of the representation coefficients, and an L 2 norm to restrict the distance between the reconstruction and the target. Then we implement the algorithm in the particle filter framework. Furthermore, an iterative method is presented to get the global minimum of the residual and the coefficients. Finally, an alternative template update scheme is adopted to avoid the tracking drift which is caused by the inaccurate update. In the experiment, we test the algorithm on 9 sequences, and compare the results with 5 state-of-art methods. According to the results, we can conclude that our algorithm is more robust than the other methods.

A Protocol for Real-time 3D Single Particle Tracking.

PubMed

Hou, Shangguo; Welsher, Kevin

2018-01-03

Real-time three-dimensional single particle tracking (RT-3D-SPT) has the potential to shed light on fast, 3D processes in cellular systems. Although various RT-3D-SPT methods have been put forward in recent years, tracking high speed 3D diffusing particles at low photon count rates remains a challenge. Moreover, RT-3D-SPT setups are generally complex and difficult to implement, limiting their widespread application to biological problems. This protocol presents a RT-3D-SPT system named 3D Dynamic Photon Localization Tracking (3D-DyPLoT), which can track particles with high diffusive speed (up to 20 µm 2 /s) at low photon count rates (down to 10 kHz). 3D-DyPLoT employs a 2D electro-optic deflector (2D-EOD) and a tunable acoustic gradient (TAG) lens to drive a single focused laser spot dynamically in 3D. Combined with an optimized position estimation algorithm, 3D-DyPLoT can lock onto single particles with high tracking speed and high localization precision. Owing to the single excitation and single detection path layout, 3D-DyPLoT is robust and easy to set up. This protocol discusses how to build 3D-DyPLoT step by step. First, the optical layout is described. Next, the system is calibrated and optimized by raster scanning a 190 nm fluorescent bead with the piezoelectric nanopositioner. Finally, to demonstrate real-time 3D tracking ability, 110 nm fluorescent beads are tracked in water.

Beam-induced motion correction for sub-megadalton cryo-EM particles.

PubMed

Scheres, Sjors Hw

2014-08-13

In electron cryo-microscopy (cryo-EM), the electron beam that is used for imaging also causes the sample to move. This motion blurs the images and limits the resolution attainable by single-particle analysis. In a previous Research article (Bai et al., 2013) we showed that correcting for this motion by processing movies from fast direct-electron detectors allowed structure determination to near-atomic resolution from 35,000 ribosome particles. In this Research advance article, we show that an improved movie processing algorithm is applicable to a much wider range of specimens. The new algorithm estimates straight movement tracks by considering multiple particles that are close to each other in the field of view, and models the fall-off of high-resolution information content by radiation damage in a dose-dependent manner. Application of the new algorithm to four data sets illustrates its potential for significantly improving cryo-EM structures, even for particles that are smaller than 200 kDa. Copyright © 2014, Scheres.

Particle tracking and extended object imaging by interferometric super resolution microscopy

NASA Astrophysics Data System (ADS)

Gdor, Itay; Yoo, Seunghwan; Wang, Xiaolei; Daddysman, Matthew; Wilton, Rosemarie; Ferrier, Nicola; Hereld, Mark; Cossairt, Oliver (Ollie); Katsaggelos, Aggelos; Scherer, Norbert F.

2018-02-01

An interferometric fluorescent microscope and a novel theoretic image reconstruction approach were developed and used to obtain super-resolution images of live biological samples and to enable dynamic real time tracking. The tracking utilizes the information stored in the interference pattern of both the illuminating incoherent light and the emitted light. By periodically shifting the interferometer phase and a phase retrieval algorithm we obtain information that allow localization with sub-2 nm axial resolution at 5 Hz.

Pyroclast Tracking Velocimetry: A particle tracking velocimetry-based tool for the study of Strombolian explosive eruptions

NASA Astrophysics Data System (ADS)

Gaudin, Damien; Moroni, Monica; Taddeucci, Jacopo; Scarlato, Piergiorgio; Shindler, Luca

2014-07-01

Image-based techniques enable high-resolution observation of the pyroclasts ejected during Strombolian explosions and drawing inferences on the dynamics of volcanic activity. However, data extraction from high-resolution videos is time consuming and operator dependent, while automatic analysis is often challenging due to the highly variable quality of images collected in the field. Here we present a new set of algorithms to automatically analyze image sequences of explosive eruptions: the pyroclast tracking velocimetry (PyTV) toolbox. First, a significant preprocessing is used to remove the image background and to detect the pyroclasts. Then, pyroclast tracking is achieved with a new particle tracking velocimetry algorithm, featuring an original predictor of velocity based on the optical flow equation. Finally, postprocessing corrects the systematic errors of measurements. Four high-speed videos of Strombolian explosions from Yasur and Stromboli volcanoes, representing various observation conditions, have been used to test the efficiency of the PyTV against manual analysis. In all cases, >106 pyroclasts have been successfully detected and tracked by PyTV, with a precision of 1 m/s for the velocity and 20% for the size of the pyroclast. On each video, more than 1000 tracks are several meters long, enabling us to study pyroclast properties and trajectories. Compared to manual tracking, 3 to 100 times more pyroclasts are analyzed. PyTV, by providing time-constrained information, links physical properties and motion of individual pyroclasts. It is a powerful tool for the study of explosive volcanic activity, as well as an ideal complement for other geological and geophysical volcano observation systems.

Tracking of multiple targets using online learning for reference model adaptation.

PubMed

Pernkopf, Franz

2008-12-01

Recently, much work has been done in multiple object tracking on the one hand and on reference model adaptation for a single-object tracker on the other side. In this paper, we do both tracking of multiple objects (faces of people) in a meeting scenario and online learning to incrementally update the models of the tracked objects to account for appearance changes during tracking. Additionally, we automatically initialize and terminate tracking of individual objects based on low-level features, i.e., face color, face size, and object movement. Many methods unlike our approach assume that the target region has been initialized by hand in the first frame. For tracking, a particle filter is incorporated to propagate sample distributions over time. We discuss the close relationship between our implemented tracker based on particle filters and genetic algorithms. Numerous experiments on meeting data demonstrate the capabilities of our tracking approach. Additionally, we provide an empirical verification of the reference model learning during tracking of indoor and outdoor scenes which supports a more robust tracking. Therefore, we report the average of the standard deviation of the trajectories over numerous tracking runs depending on the learning rate.

Performance of the ATLAS track reconstruction algorithms in dense environments in LHC Run 2.

PubMed

Aaboud, M; Aad, G; Abbott, B; Abdallah, J; Abdinov, O; Abeloos, B; Abidi, S H; AbouZeid, O S; Abraham, N L; Abramowicz, H; Abreu, H; Abreu, R; Abulaiti, Y; Acharya, B S; Adachi, S; Adamczyk, L; Adelman, J; Adersberger, M; Adye, T; Affolder, A A; Agatonovic-Jovin, T; Agheorghiesei, C; Aguilar-Saavedra, J A; Ahlen, S P; Ahmadov, F; Aielli, G; Akatsuka, S; Akerstedt, H; Åkesson, T P A; Akimov, A V; Alberghi, G L; Albert, J; Albicocco, P; Alconada Verzini, M J; Aleksa, M; Aleksandrov, I N; Alexa, C; Alexander, G; Alexopoulos, T; Alhroob, M; Ali, B; Aliev, M; Alimonti, G; Alison, J; Alkire, S P; Allbrooke, B M M; Allen, B W; Allport, P P; Aloisio, A; Alonso, A; Alonso, F; Alpigiani, C; Alshehri, A A; Alstaty, M; Alvarez Gonzalez, B; Álvarez Piqueras, D; Alviggi, M G; Amadio, B T; Amaral Coutinho, Y; Amelung, C; Amidei, D; Santos, S P Amor Dos; Amorim, A; Amoroso, S; Amundsen, G; Anastopoulos, C; Ancu, L S; Andari, N; Andeen, T; Anders, C F; Anders, J K; Anderson, K J; Andreazza, A; Andrei, V; 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2017-01-01

With the increase in energy of the Large Hadron Collider to a centre-of-mass energy of 13 [Formula: see text] for Run 2, events with dense environments, such as in the cores of high-energy jets, became a focus for new physics searches as well as measurements of the Standard Model. These environments are characterized by charged-particle separations of the order of the tracking detectors sensor granularity. Basic track quantities are compared between 3.2 fb[Formula: see text] of data collected by the ATLAS experiment and simulation of proton-proton collisions producing high-transverse-momentum jets at a centre-of-mass energy of 13 [Formula: see text]. The impact of charged-particle separations and multiplicities on the track reconstruction performance is discussed. The track reconstruction efficiency in the cores of jets with transverse momenta between 200 and 1600 [Formula: see text] is quantified using a novel, data-driven, method. The method uses the energy loss, [Formula: see text], to identify pixel clusters originating from two charged particles. Of the charged particles creating these clusters, the measured fraction that fail to be reconstructed is [Formula: see text] and [Formula: see text] for jet transverse momenta of 200-400 [Formula: see text] and 1400-1600 [Formula: see text], respectively.

Random Walk Particle Tracking For Multiphase Heat Transfer

NASA Astrophysics Data System (ADS)

Lattanzi, Aaron; Yin, Xiaolong; Hrenya, Christine

2017-11-01

As computing capabilities have advanced, direct numerical simulation (DNS) has become a highly effective tool for quantitatively predicting the heat transfer within multiphase flows. Here we utilize a hybrid DNS framework that couples the lattice Boltzmann method (LBM) to the random walk particle tracking (RWPT) algorithm. The main challenge of such a hybrid is that discontinuous fields pose a significant challenge to the RWPT framework and special attention must be given to the handling of interfaces. We derive a method for addressing discontinuities in the diffusivity field, arising at the interface between two phases. Analytical means are utilized to develop an interfacial tracer balance and modify the RWPT algorithm. By expanding the modulus of the stochastic (diffusive) step and only allowing a subset of the tracers within the high diffusivity medium to undergo a diffusive step, the correct equilibrium state can be restored (globally homogeneous tracer distribution). The new RWPT algorithm is implemented within the SUSP3D code and verified against a variety of systems: effective diffusivity of a static gas-solids mixture, hot sphere in unbounded diffusion, cooling sphere in unbounded diffusion, and uniform flow past a hot sphere.

Estimation of contour motion and deformation for nonrigid object tracking

NASA Astrophysics Data System (ADS)

Shao, Jie; Porikli, Fatih; Chellappa, Rama

2007-08-01

We present an algorithm for nonrigid contour tracking in heavily cluttered background scenes. Based on the properties of nonrigid contour movements, a sequential framework for estimating contour motion and deformation is proposed. We solve the nonrigid contour tracking problem by decomposing it into three subproblems: motion estimation, deformation estimation, and shape regulation. First, we employ a particle filter to estimate the global motion parameters of the affine transform between successive frames. Then we generate a probabilistic deformation map to deform the contour. To improve robustness, multiple cues are used for deformation probability estimation. Finally, we use a shape prior model to constrain the deformed contour. This enables us to retrieve the occluded parts of the contours and accurately track them while allowing shape changes specific to the given object types. Our experiments show that the proposed algorithm significantly improves the tracker performance.

Object Tracking and Target Reacquisition Based on 3-D Range Data for Moving Vehicles

PubMed Central

Lee, Jehoon; Lankton, Shawn; Tannenbaum, Allen

2013-01-01

In this paper, we propose an approach for tracking an object of interest based on 3-D range data. We employ particle filtering and active contours to simultaneously estimate the global motion of the object and its local deformations. The proposed algorithm takes advantage of range information to deal with the challenging (but common) situation in which the tracked object disappears from the image domain entirely and reappears later. To cope with this problem, a method based on principle component analysis (PCA) of shape information is proposed. In the proposed method, if the target disappears out of frame, shape similarity energy is used to detect target candidates that match a template shape learned online from previously observed frames. Thus, we require no a priori knowledge of the target’s shape. Experimental results show the practical applicability and robustness of the proposed algorithm in realistic tracking scenarios. PMID:21486717

TH-A-19A-04: Latent Uncertainties and Performance of a GPU-Implemented Pre-Calculated Track Monte Carlo Method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Renaud, M; Seuntjens, J; Roberge, D

Purpose: Assessing the performance and uncertainty of a pre-calculated Monte Carlo (PMC) algorithm for proton and electron transport running on graphics processing units (GPU). While PMC methods have been described in the past, an explicit quantification of the latent uncertainty arising from recycling a limited number of tracks in the pre-generated track bank is missing from the literature. With a proper uncertainty analysis, an optimal pre-generated track bank size can be selected for a desired dose calculation uncertainty. Methods: Particle tracks were pre-generated for electrons and protons using EGSnrc and GEANT4, respectively. The PMC algorithm for track transport was implementedmore » on the CUDA programming framework. GPU-PMC dose distributions were compared to benchmark dose distributions simulated using general-purpose MC codes in the same conditions. A latent uncertainty analysis was performed by comparing GPUPMC dose values to a “ground truth” benchmark while varying the track bank size and primary particle histories. Results: GPU-PMC dose distributions and benchmark doses were within 1% of each other in voxels with dose greater than 50% of Dmax. In proton calculations, a submillimeter distance-to-agreement error was observed at the Bragg Peak. Latent uncertainty followed a Poisson distribution with the number of tracks per energy (TPE) and a track bank of 20,000 TPE produced a latent uncertainty of approximately 1%. Efficiency analysis showed a 937× and 508× gain over a single processor core running DOSXYZnrc for 16 MeV electrons in water and bone, respectively. Conclusion: The GPU-PMC method can calculate dose distributions for electrons and protons to a statistical uncertainty below 1%. The track bank size necessary to achieve an optimal efficiency can be tuned based on the desired uncertainty. Coupled with a model to calculate dose contributions from uncharged particles, GPU-PMC is a candidate for inverse planning of modulated electron radiotherapy and scanned proton beams. This work was supported in part by FRSQ-MSSS (Grant No. 22090), NSERC RG (Grant No. 432290) and CIHR MOP (Grant No. MOP-211360)« less

Latent uncertainties of the precalculated track Monte Carlo method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Renaud, Marc-André; Seuntjens, Jan; Roberge, David

Purpose: While significant progress has been made in speeding up Monte Carlo (MC) dose calculation methods, they remain too time-consuming for the purpose of inverse planning. To achieve clinically usable calculation speeds, a precalculated Monte Carlo (PMC) algorithm for proton and electron transport was developed to run on graphics processing units (GPUs). The algorithm utilizes pregenerated particle track data from conventional MC codes for different materials such as water, bone, and lung to produce dose distributions in voxelized phantoms. While PMC methods have been described in the past, an explicit quantification of the latent uncertainty arising from the limited numbermore » of unique tracks in the pregenerated track bank is missing from the paper. With a proper uncertainty analysis, an optimal number of tracks in the pregenerated track bank can be selected for a desired dose calculation uncertainty. Methods: Particle tracks were pregenerated for electrons and protons using EGSnrc and GEANT4 and saved in a database. The PMC algorithm for track selection, rotation, and transport was implemented on the Compute Unified Device Architecture (CUDA) 4.0 programming framework. PMC dose distributions were calculated in a variety of media and compared to benchmark dose distributions simulated from the corresponding general-purpose MC codes in the same conditions. A latent uncertainty metric was defined and analysis was performed by varying the pregenerated track bank size and the number of simulated primary particle histories and comparing dose values to a “ground truth” benchmark dose distribution calculated to 0.04% average uncertainty in voxels with dose greater than 20% of D{sub max}. Efficiency metrics were calculated against benchmark MC codes on a single CPU core with no variance reduction. Results: Dose distributions generated using PMC and benchmark MC codes were compared and found to be within 2% of each other in voxels with dose values greater than 20% of the maximum dose. In proton calculations, a small (≤1 mm) distance-to-agreement error was observed at the Bragg peak. Latent uncertainty was characterized for electrons and found to follow a Poisson distribution with the number of unique tracks per energy. A track bank of 12 energies and 60000 unique tracks per pregenerated energy in water had a size of 2.4 GB and achieved a latent uncertainty of approximately 1% at an optimal efficiency gain over DOSXYZnrc. Larger track banks produced a lower latent uncertainty at the cost of increased memory consumption. Using an NVIDIA GTX 590, efficiency analysis showed a 807 × efficiency increase over DOSXYZnrc for 16 MeV electrons in water and 508 × for 16 MeV electrons in bone. Conclusions: The PMC method can calculate dose distributions for electrons and protons to a statistical uncertainty of 1% with a large efficiency gain over conventional MC codes. Before performing clinical dose calculations, models to calculate dose contributions from uncharged particles must be implemented. Following the successful implementation of these models, the PMC method will be evaluated as a candidate for inverse planning of modulated electron radiation therapy and scanned proton beams.« less

Latent uncertainties of the precalculated track Monte Carlo method.

PubMed

Renaud, Marc-André; Roberge, David; Seuntjens, Jan

2015-01-01

While significant progress has been made in speeding up Monte Carlo (MC) dose calculation methods, they remain too time-consuming for the purpose of inverse planning. To achieve clinically usable calculation speeds, a precalculated Monte Carlo (PMC) algorithm for proton and electron transport was developed to run on graphics processing units (GPUs). The algorithm utilizes pregenerated particle track data from conventional MC codes for different materials such as water, bone, and lung to produce dose distributions in voxelized phantoms. While PMC methods have been described in the past, an explicit quantification of the latent uncertainty arising from the limited number of unique tracks in the pregenerated track bank is missing from the paper. With a proper uncertainty analysis, an optimal number of tracks in the pregenerated track bank can be selected for a desired dose calculation uncertainty. Particle tracks were pregenerated for electrons and protons using EGSnrc and geant4 and saved in a database. The PMC algorithm for track selection, rotation, and transport was implemented on the Compute Unified Device Architecture (cuda) 4.0 programming framework. PMC dose distributions were calculated in a variety of media and compared to benchmark dose distributions simulated from the corresponding general-purpose MC codes in the same conditions. A latent uncertainty metric was defined and analysis was performed by varying the pregenerated track bank size and the number of simulated primary particle histories and comparing dose values to a "ground truth" benchmark dose distribution calculated to 0.04% average uncertainty in voxels with dose greater than 20% of Dmax. Efficiency metrics were calculated against benchmark MC codes on a single CPU core with no variance reduction. Dose distributions generated using PMC and benchmark MC codes were compared and found to be within 2% of each other in voxels with dose values greater than 20% of the maximum dose. In proton calculations, a small (≤ 1 mm) distance-to-agreement error was observed at the Bragg peak. Latent uncertainty was characterized for electrons and found to follow a Poisson distribution with the number of unique tracks per energy. A track bank of 12 energies and 60000 unique tracks per pregenerated energy in water had a size of 2.4 GB and achieved a latent uncertainty of approximately 1% at an optimal efficiency gain over DOSXYZnrc. Larger track banks produced a lower latent uncertainty at the cost of increased memory consumption. Using an NVIDIA GTX 590, efficiency analysis showed a 807 × efficiency increase over DOSXYZnrc for 16 MeV electrons in water and 508 × for 16 MeV electrons in bone. The PMC method can calculate dose distributions for electrons and protons to a statistical uncertainty of 1% with a large efficiency gain over conventional MC codes. Before performing clinical dose calculations, models to calculate dose contributions from uncharged particles must be implemented. Following the successful implementation of these models, the PMC method will be evaluated as a candidate for inverse planning of modulated electron radiation therapy and scanned proton beams.

Delineating baseflow contribution areas for streams - A model and methods comparison.

PubMed

Chow, Reynold; Frind, Michael E; Frind, Emil O; Jones, Jon P; Sousa, Marcelo R; Rudolph, David L; Molson, John W; Nowak, Wolfgang

2016-12-01

This study addresses the delineation of areas that contribute baseflow to a stream reach, also known as stream capture zones. Such areas can be delineated using standard well capture zone delineation methods, with three important differences: (1) natural gradients are smaller compared to those produced by supply wells and are therefore subject to greater numerical errors, (2) stream discharge varies seasonally, and (3) stream discharge varies spatially. This study focuses on model-related uncertainties due to model characteristics, discretization schemes, delineation methods, and particle tracking algorithms. The methodology is applied to the Alder Creek watershed in southwestern Ontario. Four different model codes are compared: HydroGeoSphere, WATFLOW, MODFLOW, and FEFLOW. In addition, two delineation methods are compared: reverse particle tracking and reverse transport, where the latter considers local-scale parameter uncertainty by using a macrodispersion term to produce a capture probability plume. The results from this study indicate that different models can calibrate acceptably well to the same data and produce very similar distributions of hydraulic head, but can produce different capture zones. The stream capture zone is found to be highly sensitive to the particle tracking algorithm. It was also found that particle tracking by itself, if applied to complex systems such as the Alder Creek watershed, would require considerable subjective judgement in the delineation of stream capture zones. Reverse transport is an alternative and more reliable approach that provides probability intervals for the baseflow contribution areas, taking uncertainty into account. The two approaches can be used together to enhance the confidence in the final outcome. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Description and performance of track and primary-vertex reconstruction with the CMS tracker

DOE PAGES

Chatrchyan, Serguei

2014-10-16

A description is provided of the software algorithms developed for the CMS tracker both for reconstructing charged-particle trajectories in proton-proton interactions and for using the resulting tracks to estimate the positions of the LHC luminous region and individual primary-interaction vertices. Despite the very hostile environment at the LHC, the performance obtained with these algorithms is found to be excellent. For tbar t events under typical 2011 pileup conditions, the average track-reconstruction efficiency for promptly-produced charged particles with transverse momenta of p T > 0.9GeV is 94% for pseudorapidities of |η| < 0.9 and 85% for 0.9 < |η| < 2.5.more » The inefficiency is caused mainly by hadrons that undergo nuclear interactions in the tracker material. For isolated muons, the corresponding efficiencies are essentially 100%. For isolated muons of p T = 100GeV emitted at |η| < 1.4, the resolutions are approximately 2.8% in p T, and respectively, 10μm and 30μm in the transverse and longitudinal impact parameters. The position resolution achieved for reconstructed primary vertices that correspond to interesting pp collisions is 10–12μm in each of the three spatial dimensions. The tracking and vertexing software is fast and flexible, and easily adaptable to other functions, such as fast tracking for the trigger, or dedicated tracking for electrons that takes into account bremsstrahlung.« less

An efficient quasi-3D particle tracking-based approach for transport through fractures with application to dynamic dispersion calculation.

PubMed

Wang, Lichun; Cardenas, M Bayani

2015-08-01

The quantitative study of transport through fractured media has continued for many decades, but has often been constrained by observational and computational challenges. Here, we developed an efficient quasi-3D random walk particle tracking (RWPT) algorithm to simulate solute transport through natural fractures based on a 2D flow field generated from the modified local cubic law (MLCL). As a reference, we also modeled the actual breakthrough curves (BTCs) through direct simulations with the 3D advection-diffusion equation (ADE) and Navier-Stokes equations. The RWPT algorithm along with the MLCL accurately reproduced the actual BTCs calculated with the 3D ADE. The BTCs exhibited non-Fickian behavior, including early arrival and long tails. Using the spatial information of particle trajectories, we further analyzed the dynamic dispersion process through moment analysis. From this, asymptotic time scales were determined for solute dispersion to distinguish non-Fickian from Fickian regimes. This analysis illustrates the advantage and benefit of using an efficient combination of flow modeling and RWPT. Copyright © 2015 Elsevier B.V. All rights reserved.

A nowcasting technique based on application of the particle filter blending algorithm

NASA Astrophysics Data System (ADS)

Chen, Yuanzhao; Lan, Hongping; Chen, Xunlai; Zhang, Wenhai

2017-10-01

To improve the accuracy of nowcasting, a new extrapolation technique called particle filter blending was configured in this study and applied to experimental nowcasting. Radar echo extrapolation was performed by using the radar mosaic at an altitude of 2.5 km obtained from the radar images of 12 S-band radars in Guangdong Province, China. The first bilateral filter was applied in the quality control of the radar data; an optical flow method based on the Lucas-Kanade algorithm and the Harris corner detection algorithm were used to track radar echoes and retrieve the echo motion vectors; then, the motion vectors were blended with the particle filter blending algorithm to estimate the optimal motion vector of the true echo motions; finally, semi-Lagrangian extrapolation was used for radar echo extrapolation based on the obtained motion vector field. A comparative study of the extrapolated forecasts of four precipitation events in 2016 in Guangdong was conducted. The results indicate that the particle filter blending algorithm could realistically reproduce the spatial pattern, echo intensity, and echo location at 30- and 60-min forecast lead times. The forecasts agreed well with observations, and the results were of operational significance. Quantitative evaluation of the forecasts indicates that the particle filter blending algorithm performed better than the cross-correlation method and the optical flow method. Therefore, the particle filter blending method is proved to be superior to the traditional forecasting methods and it can be used to enhance the ability of nowcasting in operational weather forecasts.

Particle image velocimetry for the Surface Tension Driven Convection Experiment using a particle displacement tracking technique

NASA Technical Reports Server (NTRS)

Wernet, Mark P.; Pline, Alexander D.

1991-01-01

The Surface Tension Driven Convection Experiment (STDCE) is a Space Transportation System flight experiment to study both transient and steady thermocapillary fluid flows aboard the USML-1 Spacelab mission planned for 1992. One of the components of data collected during the experiment is a video record of the flow field. This qualitative data is then quantified using an all electronic, two-dimensional particle image velocimetry technique called particle displacement tracking (PDT) which uses a simple space domain particle tracking algorithm. The PDT system is successful in producing velocity vector fields from the raw video data. Application of the PDT technique to a sample data set yielded 1606 vectors in 30 seconds of processing time. A bottom viewing optical arrangement is used to image the illuminated plane, which causes keystone distortion in the final recorded image. A coordinate transformation was incorporated into the system software to correct this viewing angle distortion. PDT processing produced 1.8 percent false identifications, due to random particle locations. A highly successful routine for removing the false identifications was also incorporated, reducing the number of false identifications to 0.2 percent.

Particle image velocimetry for the surface tension driven convection experiment using a particle displacement tracking technique

NASA Technical Reports Server (NTRS)

Wernet, Mark P.; Pline, Alexander D.

1991-01-01

The Surface Tension Driven Convection Experiment (STDCE) is a Space Transportation System flight experiment to study both transient and steady thermocapillary fluid flows aboard the USML-1 Spacelab mission planned for 1992. One of the components of data collected during the experiment is a video record of the flow field. This qualitative data is then quantified using an all electronic, two-dimensional particle image velocimetry technique called particle displacement tracking (PDT) which uses a simple space domain particle tracking algorithm. The PDT system is successful in producing velocity vector fields from the raw video data. Application of the PDT technique to a sample data set yielded 1606 vectors in 30 seconds of processing time. A bottom viewing optical arrangement is used to image the illuminated plane, which causes keystone distortion in the final recorded image. A coordinate transformation was incorporated into the system software to correct this viewing angle distortion. PDT processing produced 1.8 percent false identifications, due to random particle locations. A highly successful routine for removing the false identifications was also incorporated, reducing the number of false identifications to 0.2 percent.

Reconstruction software of the silicon tracker of DAMPE mission

NASA Astrophysics Data System (ADS)

Tykhonov, A.; Gallo, V.; Wu, X.; Zimmer, S.

2017-10-01

DAMPE is a satellite-borne experiment aimed to probe astroparticle physics in the GeV-TeV energy range. The Silicon tracker (STK) is one of the key components of DAMPE, which allows the reconstruction of trajectories (tracks) of detected particles. The non-negligible amount of material in the tracker poses a challenge to its reconstruction and alignment. In this paper we describe methods to address this challenge. We present the track reconstruction algorithm and give insight into the alignment algorithm. We also present our CAD-to-GDML converter, an in-house tool for implementing detector geometry in the software from the CAD drawings of the detector.

Data decomposition of Monte Carlo particle transport simulations via tally servers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Romano, Paul K.; Siegel, Andrew R.; Forget, Benoit

An algorithm for decomposing large tally data in Monte Carlo particle transport simulations is developed, analyzed, and implemented in a continuous-energy Monte Carlo code, OpenMC. The algorithm is based on a non-overlapping decomposition of compute nodes into tracking processors and tally servers. The former are used to simulate the movement of particles through the domain while the latter continuously receive and update tally data. A performance model for this approach is developed, suggesting that, for a range of parameters relevant to LWR analysis, the tally server algorithm should perform with minimal overhead on contemporary supercomputers. An implementation of the algorithmmore » in OpenMC is then tested on the Intrepid and Titan supercomputers, supporting the key predictions of the model over a wide range of parameters. We thus conclude that the tally server algorithm is a successful approach to circumventing classical on-node memory constraints en route to unprecedentedly detailed Monte Carlo reactor simulations.« less

Optimizing the Shunting Schedule of Electric Multiple Units Depot Using an Enhanced Particle Swarm Optimization Algorithm

PubMed Central

Jin, Junchen

2016-01-01

The shunting schedule of electric multiple units depot (SSED) is one of the essential plans for high-speed train maintenance activities. This paper presents a 0-1 programming model to address the problem of determining an optimal SSED through automatic computing. The objective of the model is to minimize the number of shunting movements and the constraints include track occupation conflicts, shunting routes conflicts, time durations of maintenance processes, and shunting running time. An enhanced particle swarm optimization (EPSO) algorithm is proposed to solve the optimization problem. Finally, an empirical study from Shanghai South EMU Depot is carried out to illustrate the model and EPSO algorithm. The optimization results indicate that the proposed method is valid for the SSED problem and that the EPSO algorithm outperforms the traditional PSO algorithm on the aspect of optimality. PMID:27436998

Parallelized Kalman-Filter-Based Reconstruction of Particle Tracks on Many-Core Architectures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cerati, Giuseppe; Elmer, Peter; Krutelyov, Slava

Faced with physical and energy density limitations on clock speed, contemporary microprocessor designers have increasingly turned to on-chip parallelism for performance gains. Examples include the Intel Xeon Phi, GPGPUs, and similar technologies. Algorithms should accordingly be designed with ample amounts of fine-grained parallelism if they are to realize the full performance of the hardware. This requirement can be challenging for algorithms that are naturally expressed as a sequence of small-matrix operations, such as the Kalman filter methods widely in use in high-energy physics experiments. In the High-Luminosity Large Hadron Collider (HL-LHC), for example, one of the dominant computational problems ismore » expected to be finding and fitting charged-particle tracks during event reconstruction; today, the most common track-finding methods are those based on the Kalman filter. Experience at the LHC, both in the trigger and offline, has shown that these methods are robust and provide high physics performance. Previously we reported the significant parallel speedups that resulted from our efforts to adapt Kalman-filter-based tracking to many-core architectures such as Intel Xeon Phi. Here we report on how effectively those techniques can be applied to more realistic detector configurations and event complexity.« less

Uncertainty quantification of seabed parameters for large data volumes along survey tracks with a tempered particle filter

NASA Astrophysics Data System (ADS)

Dettmer, J.; Quijano, J. E.; Dosso, S. E.; Holland, C. W.; Mandolesi, E.

2016-12-01

Geophysical seabed properties are important for the detection and classification of unexploded ordnance. However, current surveying methods such as vertical seismic profiling, coring, or inversion are of limited use when surveying large areas with high spatial sampling density. We consider surveys based on a source and receiver array towed by an autonomous vehicle which produce large volumes of seabed reflectivity data that contain unprecedented and detailed seabed information. The data are analyzed with a particle filter, which requires efficient reflection-coefficient computation, efficient inversion algorithms and efficient use of computer resources. The filter quantifies information content of multiple sequential data sets by considering results from previous data along the survey track to inform the importance sampling at the current point. Challenges arise from environmental changes along the track where the number of sediment layers and their properties change. This is addressed by a trans-dimensional model in the filter which allows layering complexity to change along a track. Efficiency is improved by likelihood tempering of various particle subsets and including exchange moves (parallel tempering). The filter is implemented on a hybrid computer that combines central processing units (CPUs) and graphics processing units (GPUs) to exploit three levels of parallelism: (1) fine-grained parallel computation of spherical reflection coefficients with a GPU implementation of Levin integration; (2) updating particles by concurrent CPU processes which exchange information using automatic load balancing (coarse grained parallelism); (3) overlapping CPU-GPU communication (a major bottleneck) with GPU computation by staggering CPU access to the multiple GPUs. The algorithm is applied to spherical reflection coefficients for data sets along a 14-km track on the Malta Plateau, Mediterranean Sea. We demonstrate substantial efficiency gains over previous methods. [This research was supported in part by the U.S. Dept of Defense, thought the Strategic Environmental Research and Development Program (SERDP).

Kalman Filter Tracking on Parallel Architectures

NASA Astrophysics Data System (ADS)

Cerati, Giuseppe; Elmer, Peter; Krutelyov, Slava; Lantz, Steven; Lefebvre, Matthieu; McDermott, Kevin; Riley, Daniel; Tadel, Matevž; Wittich, Peter; Würthwein, Frank; Yagil, Avi

2016-11-01

Power density constraints are limiting the performance improvements of modern CPUs. To address this we have seen the introduction of lower-power, multi-core processors such as GPGPU, ARM and Intel MIC. In order to achieve the theoretical performance gains of these processors, it will be necessary to parallelize algorithms to exploit larger numbers of lightweight cores and specialized functions like large vector units. Track finding and fitting is one of the most computationally challenging problems for event reconstruction in particle physics. At the High-Luminosity Large Hadron Collider (HL-LHC), for example, this will be by far the dominant problem. The need for greater parallelism has driven investigations of very different track finding techniques such as Cellular Automata or Hough Transforms. The most common track finding techniques in use today, however, are those based on a Kalman filter approach. Significant experience has been accumulated with these techniques on real tracking detector systems, both in the trigger and offline. They are known to provide high physics performance, are robust, and are in use today at the LHC. Given the utility of the Kalman filter in track finding, we have begun to port these algorithms to parallel architectures, namely Intel Xeon and Xeon Phi. We report here on our progress towards an end-to-end track reconstruction algorithm fully exploiting vectorization and parallelization techniques in a simplified experimental environment.

Accurate and efficient spin integration for particle accelerators

DOE PAGES

Abell, Dan T.; Meiser, Dominic; Ranjbar, Vahid H.; ...

2015-02-01

Accurate spin tracking is a valuable tool for understanding spin dynamics in particle accelerators and can help improve the performance of an accelerator. In this paper, we present a detailed discussion of the integrators in the spin tracking code GPUSPINTRACK. We have implemented orbital integrators based on drift-kick, bend-kick, and matrix-kick splits. On top of the orbital integrators, we have implemented various integrators for the spin motion. These integrators use quaternions and Romberg quadratures to accelerate both the computation and the convergence of spin rotations.We evaluate their performance and accuracy in quantitative detail for individual elements as well as formore » the entire RHIC lattice. We exploit the inherently data-parallel nature of spin tracking to accelerate our algorithms on graphics processing units.« less

A Wireless Sensor Network with Soft Computing Localization Techniques for Track Cycling Applications.

PubMed

Gharghan, Sadik Kamel; Nordin, Rosdiadee; Ismail, Mahamod

2016-08-06

In this paper, we propose two soft computing localization techniques for wireless sensor networks (WSNs). The two techniques, Neural Fuzzy Inference System (ANFIS) and Artificial Neural Network (ANN), focus on a range-based localization method which relies on the measurement of the received signal strength indicator (RSSI) from the three ZigBee anchor nodes distributed throughout the track cycling field. The soft computing techniques aim to estimate the distance between bicycles moving on the cycle track for outdoor and indoor velodromes. In the first approach the ANFIS was considered, whereas in the second approach the ANN was hybridized individually with three optimization algorithms, namely Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), and Backtracking Search Algorithm (BSA). The results revealed that the hybrid GSA-ANN outperforms the other methods adopted in this paper in terms of accuracy localization and distance estimation accuracy. The hybrid GSA-ANN achieves a mean absolute distance estimation error of 0.02 m and 0.2 m for outdoor and indoor velodromes, respectively.

A Wireless Sensor Network with Soft Computing Localization Techniques for Track Cycling Applications

PubMed Central

Gharghan, Sadik Kamel; Nordin, Rosdiadee; Ismail, Mahamod

2016-01-01

In this paper, we propose two soft computing localization techniques for wireless sensor networks (WSNs). The two techniques, Neural Fuzzy Inference System (ANFIS) and Artificial Neural Network (ANN), focus on a range-based localization method which relies on the measurement of the received signal strength indicator (RSSI) from the three ZigBee anchor nodes distributed throughout the track cycling field. The soft computing techniques aim to estimate the distance between bicycles moving on the cycle track for outdoor and indoor velodromes. In the first approach the ANFIS was considered, whereas in the second approach the ANN was hybridized individually with three optimization algorithms, namely Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), and Backtracking Search Algorithm (BSA). The results revealed that the hybrid GSA-ANN outperforms the other methods adopted in this paper in terms of accuracy localization and distance estimation accuracy. The hybrid GSA-ANN achieves a mean absolute distance estimation error of 0.02 m and 0.2 m for outdoor and indoor velodromes, respectively. PMID:27509495

Motion-compensated speckle tracking via particle filtering

NASA Astrophysics Data System (ADS)

Liu, Lixin; Yagi, Shin-ichi; Bian, Hongyu

2015-07-01

Recently, an improved motion compensation method that uses the sum of absolute differences (SAD) has been applied to frame persistence utilized in conventional ultrasonic imaging because of its high accuracy and relative simplicity in implementation. However, high time consumption is still a significant drawback of this space-domain method. To seek for a more accelerated motion compensation method and verify if it is possible to eliminate conventional traversal correlation, motion-compensated speckle tracking between two temporally adjacent B-mode frames based on particle filtering is discussed. The optimal initial density of particles, the least number of iterations, and the optimal transition radius of the second iteration are analyzed from simulation results for the sake of evaluating the proposed method quantitatively. The speckle tracking results obtained using the optimized parameters indicate that the proposed method is capable of tracking the micromotion of speckle throughout the region of interest (ROI) that is superposed with global motion. The computational cost of the proposed method is reduced by 25% compared with that of the previous algorithm and further improvement is necessary.

Online Hierarchical Sparse Representation of Multifeature for Robust Object Tracking

PubMed Central

Qu, Shiru

2016-01-01

Object tracking based on sparse representation has given promising tracking results in recent years. However, the trackers under the framework of sparse representation always overemphasize the sparse representation and ignore the correlation of visual information. In addition, the sparse coding methods only encode the local region independently and ignore the spatial neighborhood information of the image. In this paper, we propose a robust tracking algorithm. Firstly, multiple complementary features are used to describe the object appearance; the appearance model of the tracked target is modeled by instantaneous and stable appearance features simultaneously. A two-stage sparse-coded method which takes the spatial neighborhood information of the image patch and the computation burden into consideration is used to compute the reconstructed object appearance. Then, the reliability of each tracker is measured by the tracking likelihood function of transient and reconstructed appearance models. Finally, the most reliable tracker is obtained by a well established particle filter framework; the training set and the template library are incrementally updated based on the current tracking results. Experiment results on different challenging video sequences show that the proposed algorithm performs well with superior tracking accuracy and robustness. PMID:27630710

Noniterative implicit method for tracking particles in mixed Lagrangian-Eulerian formulations

NASA Technical Reports Server (NTRS)

Shih, T. I.-P.; Dasgupta, A.

1993-01-01

The existing implicit methods for the current initial value problems (IVPs) concerning particle-laden flows are complicated and iterative in nature. This paper presents a noniterative implicit method which can be used with pressure-based as well as with density-based algorithms. The method is illustrated by analyzing a dilute dispersion of noninteracting solid particles in an isothermal flow in a passage bounded by one straight wall and one wavy wall, in which all particles are spherical and have a finite velociy relative to the continuum phase at the inflow boundary.

Four-dimensional (4D) tracking of high-temperature microparticles

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Zhehui, E-mail: zwang@lanl.gov; Liu, Q.; Waganaar, W.

High-speed tracking of hot and molten microparticles in motion provides rich information about burning plasmas in magnetic fusion. An exploding-wire apparatus is used to produce moving high-temperature metallic microparticles and to develop four-dimensional (4D) or time-resolved 3D particle tracking techniques. The pinhole camera model and algorithms developed for computer vision are used for scene calibration and 4D reconstructions. 3D positions and velocities are then derived for different microparticles. Velocity resolution approaches 0.1 m/s by using the local constant velocity approximation.

Four-dimensional (4D) tracking of high-temperature microparticles

NASA Astrophysics Data System (ADS)

Wang, Zhehui; Liu, Q.; Waganaar, W.; Fontanese, J.; James, D.; Munsat, T.

2016-11-01

High-speed tracking of hot and molten microparticles in motion provides rich information about burning plasmas in magnetic fusion. An exploding-wire apparatus is used to produce moving high-temperature metallic microparticles and to develop four-dimensional (4D) or time-resolved 3D particle tracking techniques. The pinhole camera model and algorithms developed for computer vision are used for scene calibration and 4D reconstructions. 3D positions and velocities are then derived for different microparticles. Velocity resolution approaches 0.1 m/s by using the local constant velocity approximation.

Four-dimensional (4D) tracking of high-temperature microparticles

DOE PAGES

Wang, Zhehui; Liu, Qiuguang; Waganaar, Bill; ...

2016-07-08

High-speed tracking of hot and molten microparticles in motion provides rich information about burning plasmas in magnetic fusion. An exploding-wire apparatus is used to produce moving high-temperature metallic microparticles and to develop four-dimensional (4D) or time-resolved 3D particle tracking techniques. The pinhole camera model and algorithms developed for computer vision are used for scene calibration and 4D reconstructions. 3D positions and velocities are then derived for different microparticles. As a result, velocity resolution approaches 0.1 m/s by using the local constant velocity approximation.

Four-dimensional (4D) tracking of high-temperature microparticles.

PubMed

Wang, Zhehui; Liu, Q; Waganaar, W; Fontanese, J; James, D; Munsat, T

2016-11-01

High-speed tracking of hot and molten microparticles in motion provides rich information about burning plasmas in magnetic fusion. An exploding-wire apparatus is used to produce moving high-temperature metallic microparticles and to develop four-dimensional (4D) or time-resolved 3D particle tracking techniques. The pinhole camera model and algorithms developed for computer vision are used for scene calibration and 4D reconstructions. 3D positions and velocities are then derived for different microparticles. Velocity resolution approaches 0.1 m/s by using the local constant velocity approximation.

Validation of a track repeating algorithm for intensity modulated proton therapy: clinical cases study

NASA Astrophysics Data System (ADS)

Yepes, Pablo P.; Eley, John G.; Liu, Amy; Mirkovic, Dragan; Randeniya, Sharmalee; Titt, Uwe; Mohan, Radhe

2016-04-01

Monte Carlo (MC) methods are acknowledged as the most accurate technique to calculate dose distributions. However, due its lengthy calculation times, they are difficult to utilize in the clinic or for large retrospective studies. Track-repeating algorithms, based on MC-generated particle track data in water, accelerate dose calculations substantially, while essentially preserving the accuracy of MC. In this study, we present the validation of an efficient dose calculation algorithm for intensity modulated proton therapy, the fast dose calculator (FDC), based on a track-repeating technique. We validated the FDC algorithm for 23 patients, which included 7 brain, 6 head-and-neck, 5 lung, 1 spine, 1 pelvis and 3 prostate cases. For validation, we compared FDC-generated dose distributions with those from a full-fledged Monte Carlo based on GEANT4 (G4). We compared dose-volume-histograms, 3D-gamma-indices and analyzed a series of dosimetric indices. More than 99% of the voxels in the voxelized phantoms describing the patients have a gamma-index smaller than unity for the 2%/2 mm criteria. In addition the difference relative to the prescribed dose between the dosimetric indices calculated with FDC and G4 is less than 1%. FDC reduces the calculation times from 5 ms per proton to around 5 μs.

Particle tracking velocimetry using echocardiographic data resolves flow in the left ventricle

NASA Astrophysics Data System (ADS)

Sampath, Kaushik; Abd, Thura T.; George, Richard T.; Katz, Joseph

2015-11-01

Two dimensional contrast echocardiography was performed on patients with a history of left ventricular (LV) thrombus. The 636 x 434 pixels electrocardiograms were recorded using a GE Vivid 9E system with (M5S-D and 4V-D) probes in a 2-D mode at a magnification of 0.3 mm/pix. The concentration of 2-4.5 micron seed bubbles was adjusted to obtain individually discernable traces, and a data acquisition rate of 60-90 fps kept the inter-frame displacements suitable for matching traces, and calculating vectors, but yet low enough to allow a scanning depth and width of upto 13 cm and 60 degrees respectively. Particle tracking velocimetry (PTV) guided by initial particle image velocimetry (PIV) was used to obtain the velocity distributions inside the LV with vector spacing of 3-5 mm. The data quality was greatly enhanced by implementing an iterative particle specific enhancement and tracking algorithm. Data covering 20 heart beats facilitated phase averaging. The results elucidated blood flow in the intra-ventricular septal region, lateral wall region, the apex of the LV and the mitral valve region.

High throughput on-chip analysis of high-energy charged particle tracks using lensfree imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Luo, Wei; Shabbir, Faizan; Gong, Chao

2015-04-13

We demonstrate a high-throughput charged particle analysis platform, which is based on lensfree on-chip microscopy for rapid ion track analysis using allyl diglycol carbonate, i.e., CR-39 plastic polymer as the sensing medium. By adopting a wide-area opto-electronic image sensor together with a source-shifting based pixel super-resolution technique, a large CR-39 sample volume (i.e., 4 cm × 4 cm × 0.1 cm) can be imaged in less than 1 min using a compact lensfree on-chip microscope, which detects partially coherent in-line holograms of the ion tracks recorded within the CR-39 detector. After the image capture, using highly parallelized reconstruction and ion track analysis algorithms running on graphics processingmore » units, we reconstruct and analyze the entire volume of a CR-39 detector within ∼1.5 min. This significant reduction in the entire imaging and ion track analysis time not only increases our throughput but also allows us to perform time-resolved analysis of the etching process to monitor and optimize the growth of ion tracks during etching. This computational lensfree imaging platform can provide a much higher throughput and more cost-effective alternative to traditional lens-based scanning optical microscopes for ion track analysis using CR-39 and other passive high energy particle detectors.« less

Predicting drifter trajectories and particle dispersion in the Caribbean using a high resolution coastal ocean forecasting system

NASA Astrophysics Data System (ADS)

Solano, M.

2016-02-01

The present study discusses the accuracy of a high-resolution ocean forecasting system in predicting floating drifter trajectories and the uncertainty of modeled particle dispersion in coastal areas. Trajectories were calculated using an offline particle-tracking algorithm coupled to the operational model developed for the region of Puerto Rico by CariCOOS. Both, a simple advection algorithm as well as the Larval TRANSport (LTRANS) model, a more sophisticated offline particle-tracking application, were coupled to the ocean model. Numerical results are compared with 12 floating drifters deployed in the near-shore of Puerto Rico during February and March 2015, and tracked for several days using Global Positioning Systems mounted on the drifters. In addition the trajectories have also been calculated with the AmSeas Navy Coastal Ocean Model (NCOM). The operational model is based on the Regional Ocean Modeling System (ROMS) with a uniform horizontal resolution of 1/100 degrees (1.1km). Initial, surface and open boundary conditions are taken from NCOM, except for wind stress, which is computed using winds from the National Digital Forecasting Database. Probabilistic maps were created to quantify the uncertainty of particle trajectories at different locations. Results show that the forecasted trajectories are location dependent, with tidally active regions having the largest error. The predicted trajectories by both the ROMS and NCOM models show good agreement on average, however both perform differently at particular locations. The effect of wind stress on the drifter trajectories is investigated to account for wind slippage. Furthermore, a real case scenario is presented where simulated trajectories show good agreement when compared to the actual drifter trajectories.

Performance of the ATLAS track reconstruction algorithms in dense environments in LHC Run 2

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aaboud, M.; Aad, G.; Abbott, B.

With the increase in energy of the Large Hadron Collider to a centre-of-mass energy of 13 TeV for Run 2, events with dense environments, such as in the cores of high-energy jets, became a focus for new physics searches as well as measurements of the Standard Model. These environments are characterized by charged-particle separations of the order of the tracking detectors sensor granularity. Basic track quantities are compared between 3.2 fb -1 of data collected by the ATLAS experiment and simulation of proton–proton collisions producing high-transverse-momentum jets at a centre-of-mass energy of 13 TeV. The impact of charged-particle separations andmore » multiplicities on the track reconstruction performance is discussed. The track reconstruction efficiency in the cores of jets with transverse momenta between 200 and 1600 GeV is quantified using a novel, data-driven, method. The method uses the energy loss, dE/dx, to identify pixel clusters originating from two charged particles. Of the charged particles creating these clusters, the measured fraction that fail to be reconstructed is 0.061±0.006 (stat.)±0.014 (syst.) and 0.093±0.017 (stat.)±0.021 (syst.) for jet transverse momenta of 200–400 GeV and 1400–1600 GeV, respectively.« less

Performance of the ATLAS track reconstruction algorithms in dense environments in LHC Run 2

DOE PAGES

Aaboud, M.; Aad, G.; Abbott, B.; ...

2017-10-11

With the increase in energy of the Large Hadron Collider to a centre-of-mass energy of 13 TeV for Run 2, events with dense environments, such as in the cores of high-energy jets, became a focus for new physics searches as well as measurements of the Standard Model. These environments are characterized by charged-particle separations of the order of the tracking detectors sensor granularity. Basic track quantities are compared between 3.2 fb -1 of data collected by the ATLAS experiment and simulation of proton–proton collisions producing high-transverse-momentum jets at a centre-of-mass energy of 13 TeV. The impact of charged-particle separations andmore » multiplicities on the track reconstruction performance is discussed. The track reconstruction efficiency in the cores of jets with transverse momenta between 200 and 1600 GeV is quantified using a novel, data-driven, method. The method uses the energy loss, dE/dx, to identify pixel clusters originating from two charged particles. Of the charged particles creating these clusters, the measured fraction that fail to be reconstructed is 0.061±0.006 (stat.)±0.014 (syst.) and 0.093±0.017 (stat.)±0.021 (syst.) for jet transverse momenta of 200–400 GeV and 1400–1600 GeV, respectively.« less

Combining Particle Filters and Consistency-Based Approaches for Monitoring and Diagnosis of Stochastic Hybrid Systems

NASA Technical Reports Server (NTRS)

Narasimhan, Sriram; Dearden, Richard; Benazera, Emmanuel

2004-01-01

Fault detection and isolation are critical tasks to ensure correct operation of systems. When we consider stochastic hybrid systems, diagnosis algorithms need to track both the discrete mode and the continuous state of the system in the presence of noise. Deterministic techniques like Livingstone cannot deal with the stochasticity in the system and models. Conversely Bayesian belief update techniques such as particle filters may require many computational resources to get a good approximation of the true belief state. In this paper we propose a fault detection and isolation architecture for stochastic hybrid systems that combines look-ahead Rao-Blackwellized Particle Filters (RBPF) with the Livingstone 3 (L3) diagnosis engine. In this approach RBPF is used to track the nominal behavior, a novel n-step prediction scheme is used for fault detection and L3 is used to generate a set of candidates that are consistent with the discrepant observations which then continue to be tracked by the RBPF scheme.

ACTS: from ATLAS software towards a common track reconstruction software

NASA Astrophysics Data System (ADS)

Gumpert, C.; Salzburger, A.; Kiehn, M.; Hrdinka, J.; Calace, N.; ATLAS Collaboration

2017-10-01

Reconstruction of charged particles’ trajectories is a crucial task for most particle physics experiments. The high instantaneous luminosity achieved at the LHC leads to a high number of proton-proton collisions per bunch crossing, which has put the track reconstruction software of the LHC experiments through a thorough test. Preserving track reconstruction performance under increasingly difficult experimental conditions, while keeping the usage of computational resources at a reasonable level, is an inherent problem for many HEP experiments. Exploiting concurrent algorithms and using multivariate techniques for track identification are the primary strategies to achieve that goal. Starting from current ATLAS software, the ACTS project aims to encapsulate track reconstruction software into a generic, framework- and experiment-independent software package. It provides a set of high-level algorithms and data structures for performing track reconstruction tasks as well as fast track simulation. The software is developed with special emphasis on thread-safety to support parallel execution of the code and data structures are optimised for vectorisation to speed up linear algebra operations. The implementation is agnostic to the details of the detection technologies and magnetic field configuration which makes it applicable to many different experiments.

A full field, 3-D velocimeter for microgravity crystallization experiments

NASA Technical Reports Server (NTRS)

Brodkey, Robert S.; Russ, Keith M.

1991-01-01

The programming and algorithms needed for implementing a full-field, 3-D velocimeter for laminar flow systems and the appropriate hardware to fully implement this ultimate system are discussed. It appears that imaging using a synched pair of video cameras and digitizer boards with synched rails for camera motion will provide a viable solution to the laminar tracking problem. The algorithms given here are simple, which should speed processing. On a heavily loaded VAXstation 3100 the particle identification can take 15 to 30 seconds, with the tracking taking less than one second. It seeems reasonable to assume that four image pairs can thus be acquired and analyzed in under one minute.

Neutron Radiography of Fluid Flow for Geothermal Energy Research

NASA Astrophysics Data System (ADS)

Bingham, P.; Polsky, Y.; Anovitz, L.; Carmichael, J.; Bilheux, H.; Jacobsen, D.; Hussey, D.

Enhanced geothermal systems seek to expand the potential for geothermal energy by engineering heat exchange systems within the earth. A neutron radiography imaging method has been developed for the study of fluid flow through rock under environmental conditions found in enhanced geothermal energy systems. For this method, a pressure vessel suitable for neutron radiography was designed and fabricated, modifications to imaging instrument setups were tested, multiple contrast agents were tested, and algorithms developed for tracking of flow. The method has shown success for tracking of single phase flow through a manufactured crack in a 3.81 cm (1.5 inch) diameter core within a pressure vessel capable of confinement up to 69 MPa (10,000 psi) using a particle tracking approach with bubbles of fluorocarbon-based fluid as the ;particles; and imaging with 10 ms exposures.

Comparative assessment of pressure field reconstructions from particle image velocimetry measurements and Lagrangian particle tracking

NASA Astrophysics Data System (ADS)

van Gent, P. L.; Michaelis, D.; van Oudheusden, B. W.; Weiss, P.-É.; de Kat, R.; Laskari, A.; Jeon, Y. J.; David, L.; Schanz, D.; Huhn, F.; Gesemann, S.; Novara, M.; McPhaden, C.; Neeteson, N. J.; Rival, D. E.; Schneiders, J. F. G.; Schrijer, F. F. J.

2017-04-01

A test case for pressure field reconstruction from particle image velocimetry (PIV) and Lagrangian particle tracking (LPT) has been developed by constructing a simulated experiment from a zonal detached eddy simulation for an axisymmetric base flow at Mach 0.7. The test case comprises sequences of four subsequent particle images (representing multi-pulse data) as well as continuous time-resolved data which can realistically only be obtained for low-speed flows. Particle images were processed using tomographic PIV processing as well as the LPT algorithm `Shake-The-Box' (STB). Multiple pressure field reconstruction techniques have subsequently been applied to the PIV results (Eulerian approach, iterative least-square pseudo-tracking, Taylor's hypothesis approach, and instantaneous Vortex-in-Cell) and LPT results (FlowFit, Vortex-in-Cell-plus, Voronoi-based pressure evaluation, and iterative least-square pseudo-tracking). All methods were able to reconstruct the main features of the instantaneous pressure fields, including methods that reconstruct pressure from a single PIV velocity snapshot. Highly accurate reconstructed pressure fields could be obtained using LPT approaches in combination with more advanced techniques. In general, the use of longer series of time-resolved input data, when available, allows more accurate pressure field reconstruction. Noise in the input data typically reduces the accuracy of the reconstructed pressure fields, but none of the techniques proved to be critically sensitive to the amount of noise added in the present test case.

Application of importance sampling to the computation of large deviations in nonequilibrium processes.

PubMed

Kundu, Anupam; Sabhapandit, Sanjib; Dhar, Abhishek

2011-03-01

We present an algorithm for finding the probabilities of rare events in nonequilibrium processes. The algorithm consists of evolving the system with a modified dynamics for which the required event occurs more frequently. By keeping track of the relative weight of phase-space trajectories generated by the modified and the original dynamics one can obtain the required probabilities. The algorithm is tested on two model systems of steady-state particle and heat transport where we find a huge improvement from direct simulation methods.

Traditional Tracking with Kalman Filter on Parallel Architectures

NASA Astrophysics Data System (ADS)

Cerati, Giuseppe; Elmer, Peter; Lantz, Steven; MacNeill, Ian; McDermott, Kevin; Riley, Dan; Tadel, Matevž; Wittich, Peter; Würthwein, Frank; Yagil, Avi

2015-05-01

Power density constraints are limiting the performance improvements of modern CPUs. To address this, we have seen the introduction of lower-power, multi-core processors, but the future will be even more exciting. In order to stay within the power density limits but still obtain Moore's Law performance/price gains, it will be necessary to parallelize algorithms to exploit larger numbers of lightweight cores and specialized functions like large vector units. Example technologies today include Intel's Xeon Phi and GPGPUs. Track finding and fitting is one of the most computationally challenging problems for event reconstruction in particle physics. At the High Luminosity LHC, for example, this will be by far the dominant problem. The most common track finding techniques in use today are however those based on the Kalman Filter. Significant experience has been accumulated with these techniques on real tracking detector systems, both in the trigger and offline. We report the results of our investigations into the potential and limitations of these algorithms on the new parallel hardware.

The Hadron Blind Ring Imaging Cherenkov Detector

NASA Astrophysics Data System (ADS)

Blatnik, Marie; Zajac, Stephanie; Hemmick, Tom

2013-10-01

Heavy Ion Collisions in the Relativistic Heavy Ion Collider (RHIC) at Brookhaven Lab have hinted at the existence of a new form of matter at high gluon density, the Color Glass Condensate. High energy electron scattering off of nuclei, focusing on the low-x components of the nuclear wave function, will definitively measure this state of matter. However, when a nucleus contributes a low x parton, the reaction products are highly focused in the electron-going direction and have large momentum in the lab system. High-momentum particle identification is particularly challenging. A particle is identifiable by its mass, but tracking algorithms only yield a particle's momentum based on its track's curvature. The particle's velocity is needed to identify the particle. A ring-imaging Cerenkov detector is being developed for the forward angle particle identification from the technological advancements of PHENIX's Hadron-Blind Detector (HBD), which uses Gas Electron Multipliers (GEMs) and pixelated pad planes to detect Cerenkov photons. The new HBD will focus the Cerenkov photons into a ring to determine the parent particle's velocity. Results from the pad plane simulations, construction tests, and test beam run will be presented.

A measurement of material in the ATLAS tracker using secondary hadronic interactions in 7 TeV pp collisions

DOE PAGES

Aaboud, M.; Aad, G.; Abbott, B.; ...

2016-11-30

Knowledge of the material in the ATLAS inner tracking detector is crucial in understanding the reconstruction of charged-particle tracks, the performance of algorithms that identify jets containing b-hadrons and is also essential to reduce background in searches for exotic particles that can decay within the inner detector volume. Interactions of primary hadrons produced in pp collisions with the material in the inner detector are used to map the location and amount of this material. The hadronic interactions of primary particles may result in secondary vertices, which in this analysis are reconstructed by an inclusive vertex-finding algorithm. Data were collected usingmore » minimum-bias triggers by the ATLAS detector operating at the LHC during 2010 at centre-of-mass energy √s = 7 TeV, and correspond to an integrated luminosity of 19 nb -1. Kinematic properties of these secondary vertices are used to study the validity of the modelling of hadronic interactions in simulation. Finally, secondary-vertex yields are compared between data and simulation over a volume of about 0.7 m 3 around the interaction point, and agreement is found within overall uncertainties.« less

A measurement of material in the ATLAS tracker using secondary hadronic interactions in 7 TeV pp collisions

NASA Astrophysics Data System (ADS)

Aaboud, M.; Aad, G.; Abbott, B.; Abdallah, J.; Abdinov, O.; Abeloos, B.; Aben, R.; AbouZeid, O. S.; Abraham, N. L.; Abramowicz, H.; Abreu, H.; Abreu, R.; Abulaiti, Y.; Acharya, B. S.; Adamczyk, L.; Adams, D. L.; Adelman, J.; Adomeit, S.; Adye, T.; Affolder, A. A.; Agatonovic-Jovin, T.; Agricola, J.; Aguilar-Saavedra, J. A.; Ahlen, S. P.; Ahmadov, F.; Aielli, G.; Akerstedt, H.; Åkesson, T. P. A.; Akimov, A. V.; Alberghi, G. L.; Albert, J.; Albrand, S.; Alconada Verzini, M. J.; Aleksa, M.; Aleksandrov, I. N.; Alexa, C.; Alexander, G.; Alexopoulos, T.; Alhroob, M.; Ali, B.; Aliev, M.; Alimonti, G.; Alison, J.; Alkire, S. P.; Allbrooke, B. M. M.; Allen, B. W.; Allport, P. P.; Aloisio, A.; Alonso, A.; Alonso, F.; Alpigiani, C.; Alstaty, M.; Alvarez Gonzalez, B.; Álvarez Piqueras, D.; Alviggi, M. G.; Amadio, B. T.; Amako, K.; Amaral Coutinho, Y.; Amelung, C.; Amidei, D.; Amor Dos Santos, S. P.; Amorim, A.; Amoroso, S.; Amundsen, G.; Anastopoulos, C.; Ancu, L. S.; Andari, N.; Andeen, T.; Anders, C. F.; Anders, G.; Anders, J. K.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Angelidakis, S.; Angelozzi, I.; Anger, P.; Angerami, A.; Anghinolfi, F.; Anisenkov, A. V.; Anjos, N.; Annovi, A.; Antel, C.; Antonelli, M.; Antonov, A.; Anulli, F.; Aoki, M.; Aperio Bella, L.; Arabidze, G.; Arai, Y.; Araque, J. P.; Arce, A. T. H.; Arduh, F. A.; Arguin, J.-F.; Argyropoulos, S.; Arik, M.; Armbruster, A. J.; Armitage, L. J.; Arnaez, O.; Arnold, H.; Arratia, M.; Arslan, O.; Artamonov, A.; Artoni, G.; Artz, S.; Asai, S.; Asbah, N.; Ashkenazi, A.; Åsman, B.; Asquith, L.; Assamagan, K.; Astalos, R.; Atkinson, M.; Atlay, N. B.; Augsten, K.; Avolio, G.; Axen, B.; Ayoub, M. K.; Azuelos, G.; Baak, M. A.; Baas, A. E.; Baca, M. J.; Bachacou, H.; Bachas, K.; Backes, M.; Backhaus, M.; Bagiacchi, P.; Bagnaia, P.; Bai, Y.; Baines, J. T.; Baker, O. K.; Baldin, E. M.; Balek, P.; Balestri, T.; Balli, F.; Balunas, W. K.; Banas, E.; Banerjee, Sw.; Bannoura, A. A. E.; Barak, L.; Barberio, E. L.; Barberis, D.; Barbero, M.; Barillari, T.; Barisits, M.-S.; Barklow, T.; Barlow, N.; Barnes, S. L.; Barnett, B. M.; Barnett, R. M.; Barnovska, Z.; Baroncelli, A.; Barone, G.; Barr, A. J.; Barranco Navarro, L.; Barreiro, F.; Barreiro Guimarães da Costa, J.; Bartoldus, R.; Barton, A. E.; Bartos, P.; Basalaev, A.; Bassalat, A.; Bates, R. L.; Batista, S. J.; Batley, J. R.; Battaglia, M.; Bauce, M.; Bauer, F.; Bawa, H. S.; Beacham, J. B.; Beattie, M. D.; Beau, T.; Beauchemin, P. H.; Bechtle, P.; Beck, H. P.; Becker, K.; Becker, M.; Beckingham, M.; Becot, C.; Beddall, A. J.; Beddall, A.; Bednyakov, V. A.; Bedognetti, M.; Bee, C. P.; Beemster, L. J.; Beermann, T. A.; Begel, M.; Behr, J. K.; Belanger-Champagne, C.; Bell, A. S.; Bella, G.; Bellagamba, L.; Bellerive, A.; Bellomo, M.; Belotskiy, K.; Beltramello, O.; Belyaev, N. L.; Benary, O.; Benchekroun, D.; Bender, M.; Bendtz, K.; Benekos, N.; Benhammou, Y.; Benhar Noccioli, E.; Benitez, J.; Benjamin, D. P.; Bensinger, J. R.; Bentvelsen, S.; Beresford, L.; Beretta, M.; Berge, D.; Bergeaas Kuutmann, E.; Berger, N.; Beringer, J.; Berlendis, S.; Bernard, N. R.; Bernius, C.; Bernlochner, F. U.; Berry, T.; Berta, P.; Bertella, C.; Bertoli, G.; Bertolucci, F.; Bertram, I. A.; Bertsche, C.; Bertsche, D.; Besjes, G. J.; Bessidskaia Bylund, O.; Bessner, M.; Besson, N.; Betancourt, C.; Bethani, A.; Bethke, S.; Bevan, A. J.; Bianchi, R. M.; Bianchini, L.; Bianco, M.; Biebel, O.; Biedermann, D.; Bielski, R.; Biesuz, N. V.; Biglietti, M.; Bilbao De Mendizabal, J.; Billoud, T. R. V.; Bilokon, H.; Bindi, M.; Binet, S.; Bingul, A.; Bini, C.; Biondi, S.; Bisanz, T.; Bjergaard, D. M.; Black, C. W.; Black, J. E.; Black, K. M.; Blackburn, D.; Blair, R. E.; Blanchard, J.-B.; Blazek, T.; Bloch, I.; Blocker, C.; Blum, W.; Blumenschein, U.; Blunier, S.; Bobbink, G. J.; Bobrovnikov, V. S.; Bocchetta, S. S.; Bocci, A.; Bock, C.; Boehler, M.; Boerner, D.; Bogaerts, J. A.; Bogavac, D.; Bogdanchikov, A. G.; Bohm, C.; Boisvert, V.; Bokan, P.; Bold, T.; Boldyrev, A. S.; Bomben, M.; Bona, M.; Boonekamp, M.; Borisov, A.; Borissov, G.; Bortfeldt, J.; Bortoletto, D.; Bortolotto, V.; Bos, K.; Boscherini, D.; Bosman, M.; Bossio Sola, J. D.; Boudreau, J.; Bouffard, J.; Bouhova-Thacker, E. V.; Boumediene, D.; Bourdarios, C.; Boutle, S. K.; Boveia, A.; Boyd, J.; Boyko, I. R.; Bracinik, J.; Brandt, A.; Brandt, G.; Brandt, O.; Bratzler, U.; Brau, B.; Brau, J. E.; Braun, H. M.; Breaden Madden, W. D.; Brendlinger, K.; Brennan, A. J.; Brenner, L.; Brenner, R.; Bressler, S.; Bristow, T. M.; Britton, D.; Britzger, D.; Brochu, F. M.; Brock, I.; Brock, R.; Brooijmans, G.; Brooks, T.; Brooks, W. K.; Brosamer, J.; Brost, E.; Broughton, J. H.; Bruckman de Renstrom, P. A.; Bruncko, D.; Bruneliere, R.; Bruni, A.; Bruni, G.; Bruni, L. S.; Brunt, BH; Bruschi, M.; Bruscino, N.; Bryant, P.; Bryngemark, L.; Buanes, T.; Buat, Q.; Buchholz, P.; Buckley, A. G.; Budagov, I. A.; Buehrer, F.; Bugge, M. K.; Bulekov, O.; Bullock, D.; Burckhart, H.; Burdin, S.; Burgard, C. D.; Burghgrave, B.; Burka, K.; Burke, S.; Burmeister, I.; Burr, J. T. P.; Busato, E.; Büscher, D.; Büscher, V.; Bussey, P.; Butler, J. M.; Buttar, C. M.; Butterworth, J. M.; Butti, P.; Buttinger, W.; Buzatu, A.; Buzykaev, A. R.; Cabrera Urbán, S.; Caforio, D.; Cairo, V. M.; Cakir, O.; Calace, N.; Calafiura, P.; Calandri, A.; Calderini, G.; Calfayan, P.; Callea, G.; Caloba, L. P.; Calvente Lopez, S.; Calvet, D.; Calvet, S.; Calvet, T. P.; Camacho Toro, R.; Camarda, S.; Camarri, P.; Cameron, D.; Caminal Armadans, R.; Camincher, C.; Campana, S.; Campanelli, M.; Camplani, A.; Campoverde, A.; Canale, V.; Canepa, A.; Cano Bret, M.; Cantero, J.; Cantrill, R.; Cao, T.; Capeans Garrido, M. D. M.; Caprini, I.; Caprini, M.; Capua, M.; Caputo, R.; Carbone, R. M.; Cardarelli, R.; Cardillo, F.; Carli, I.; Carli, T.; Carlino, G.; Carminati, L.; Caron, S.; Carquin, E.; Carrillo-Montoya, G. D.; Carter, J. R.; Carvalho, J.; Casadei, D.; Casado, M. P.; Casolino, M.; Casper, D. W.; Castaneda-Miranda, E.; Castelijn, R.; Castelli, A.; Castillo Gimenez, V.; Castro, N. F.; Catinaccio, A.; Catmore, J. R.; Cattai, A.; Caudron, J.; Cavaliere, V.; Cavallaro, E.; Cavalli, D.; Cavalli-Sforza, M.; Cavasinni, V.; Ceradini, F.; Cerda Alberich, L.; Cerio, B. C.; Cerqueira, A. S.; Cerri, A.; Cerrito, L.; Cerutti, F.; Cerv, M.; Cervelli, A.; Cetin, S. A.; Chafaq, A.; Chakraborty, D.; Chan, S. K.; Chan, Y. L.; Chang, P.; Chapman, J. D.; Charlton, D. G.; Chatterjee, A.; Chau, C. C.; Chavez Barajas, C. A.; Che, S.; Cheatham, S.; Chegwidden, A.; Chekanov, S.; Chekulaev, S. V.; Chelkov, G. A.; Chelstowska, M. A.; Chen, C.; Chen, H.; Chen, K.; Chen, S.; Chen, S.; Chen, X.; Chen, Y.; Cheng, H. C.; Cheng, H. J.; Cheng, Y.; Cheplakov, A.; Cheremushkina, E.; Cherkaoui El Moursli, R.; Chernyatin, V.; Cheu, E.; Chevalier, L.; Chiarella, V.; Chiarelli, G.; Chiodini, G.; Chisholm, A. S.; Chitan, A.; Chizhov, M. V.; Choi, K.; Chomont, A. R.; Chouridou, S.; Chow, B. K. B.; Christodoulou, V.; Chromek-Burckhart, D.; Chudoba, J.; Chuinard, A. J.; Chwastowski, J. J.; Chytka, L.; Ciapetti, G.; Ciftci, A. K.; Cinca, D.; Cindro, V.; Cioara, I. A.; Ciocca, C.; Ciocio, A.; Cirotto, F.; Citron, Z. H.; Citterio, M.; Ciubancan, M.; Clark, A.; Clark, B. L.; Clark, M. R.; Clark, P. J.; Clarke, R. N.; Clement, C.; Coadou, Y.; Cobal, M.; Coccaro, A.; Cochran, J.; Colasurdo, L.; Cole, B.; Colijn, A. P.; Collot, J.; Colombo, T.; Compostella, G.; Conde Muiño, P.; Coniavitis, E.; Connell, S. H.; Connelly, I. A.; Consorti, V.; Constantinescu, S.; Conti, G.; Conventi, F.; Cooke, M.; Cooper, B. D.; Cooper-Sarkar, A. M.; Cormier, K. J. R.; Cornelissen, T.; Corradi, M.; Corriveau, F.; Corso-Radu, A.; Cortes-Gonzalez, A.; Cortiana, G.; Costa, G.; Costa, M. J.; Costanzo, D.; Cottin, G.; Cowan, G.; Cox, B. E.; Cranmer, K.; Crawley, S. J.; Cree, G.; Crépé-Renaudin, S.; Crescioli, F.; Cribbs, W. 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C.; Unno, Y.; Unverdorben, C.; Urban, J.; Urquijo, P.; Urrejola, P.; Usai, G.; Usanova, A.; Vacavant, L.; Vacek, V.; Vachon, B.; Valderanis, C.; Valdes Santurio, E.; Valencic, N.; Valentinetti, S.; Valero, A.; Valery, L.; Valkar, S.; Valls Ferrer, J. A.; Van Den Wollenberg, W.; Van Der Deijl, P. C.; van der Graaf, H.; van Eldik, N.; van Gemmeren, P.; Van Nieuwkoop, J.; van Vulpen, I.; van Woerden, M. C.; Vanadia, M.; Vandelli, W.; Vanguri, R.; Vaniachine, A.; Vankov, P.; Vardanyan, G.; Vari, R.; Varnes, E. W.; Varol, T.; Varouchas, D.; Vartapetian, A.; Varvell, K. E.; Vasquez, J. G.; Vazeille, F.; Vazquez Schroeder, T.; Veatch, J.; Veeraraghavan, V.; Veloce, L. M.; Veloso, F.; Veneziano, S.; Ventura, A.; Venturi, M.; Venturi, N.; Venturini, A.; Vercesi, V.; Verducci, M.; Verkerke, W.; Vermeulen, J. C.; Vest, A.; Vetterli, M. C.; Viazlo, O.; Vichou, I.; Vickey, T.; Boeriu, O. E. Vickey; Viehhauser, G. H. 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2016-11-01

Knowledge of the material in the ATLAS inner tracking detector is crucial in understanding the reconstruction of charged-particle tracks, the performance of algorithms that identify jets containing b-hadrons and is also essential to reduce background in searches for exotic particles that can decay within the inner detector volume. Interactions of primary hadrons produced in pp collisions with the material in the inner detector are used to map the location and amount of this material. The hadronic interactions of primary particles may result in secondary vertices, which in this analysis are reconstructed by an inclusive vertex-finding algorithm. Data were collected using minimum-bias triggers by the ATLAS detector operating at the LHC during 2010 at centre-of-mass energy √s = 7 TeV, and correspond to an integrated luminosity of 19 nb-1. Kinematic properties of these secondary vertices are used to study the validity of the modelling of hadronic interactions in simulation. Secondary-vertex yields are compared between data and simulation over a volume of about 0.7 m3 around the interaction point, and agreement is found within overall uncertainties.

3-D model-based tracking for UAV indoor localization.

PubMed

Teulière, Céline; Marchand, Eric; Eck, Laurent

2015-05-01

This paper proposes a novel model-based tracking approach for 3-D localization. One main difficulty of standard model-based approach lies in the presence of low-level ambiguities between different edges. In this paper, given a 3-D model of the edges of the environment, we derive a multiple hypotheses tracker which retrieves the potential poses of the camera from the observations in the image. We also show how these candidate poses can be integrated into a particle filtering framework to guide the particle set toward the peaks of the distribution. Motivated by the UAV indoor localization problem where GPS signal is not available, we validate the algorithm on real image sequences from UAV flights.

Human tracking in thermal images using adaptive particle filters with online random forest learning

NASA Astrophysics Data System (ADS)

Ko, Byoung Chul; Kwak, Joon-Young; Nam, Jae-Yeal

2013-11-01

This paper presents a fast and robust human tracking method to use in a moving long-wave infrared thermal camera under poor illumination with the existence of shadows and cluttered backgrounds. To improve the human tracking performance while minimizing the computation time, this study proposes an online learning of classifiers based on particle filters and combination of a local intensity distribution (LID) with oriented center-symmetric local binary patterns (OCS-LBP). Specifically, we design a real-time random forest (RF), which is the ensemble of decision trees for confidence estimation, and confidences of the RF are converted into a likelihood function of the target state. First, the target model is selected by the user and particles are sampled. Then, RFs are generated using the positive and negative examples with LID and OCS-LBP features by online learning. The learned RF classifiers are used to detect the most likely target position in the subsequent frame in the next stage. Then, the RFs are learned again by means of fast retraining with the tracked object and background appearance in the new frame. The proposed algorithm is successfully applied to various thermal videos as tests and its tracking performance is better than those of other methods.

Reconstructing the flight kinematics of swarming and mating in wild mosquitoes

PubMed Central

Butail, Sachit; Manoukis, Nicholas; Diallo, Moussa; Ribeiro, José M.; Lehmann, Tovi; Paley, Derek A.

2012-01-01

We describe a novel tracking system for reconstructing three-dimensional tracks of individual mosquitoes in wild swarms and present the results of validating the system by filming swarms and mating events of the malaria mosquito Anopheles gambiae in Mali. The tracking system is designed to address noisy, low frame-rate (25 frames per second) video streams from a stereo camera system. Because flying A. gambiae move at 1–4 m s−1, they appear as faded streaks in the images or sometimes do not appear at all. We provide an adaptive algorithm to search for missing streaks and a likelihood function that uses streak endpoints to extract velocity information. A modified multi-hypothesis tracker probabilistically addresses occlusions and a particle filter estimates the trajectories. The output of the tracking algorithm is a set of track segments with an average length of 0.6–1 s. The segments are verified and combined under human supervision to create individual tracks up to the duration of the video (90 s). We evaluate tracking performance using an established metric for multi-target tracking and validate the accuracy using independent stereo measurements of a single swarm. Three-dimensional reconstructions of A. gambiae swarming and mating events are presented. PMID:22628212

Sequential bearings-only-tracking initiation with particle filtering method.

PubMed

Liu, Bin; Hao, Chengpeng

2013-01-01

The tracking initiation problem is examined in the context of autonomous bearings-only-tracking (BOT) of a single appearing/disappearing target in the presence of clutter measurements. In general, this problem suffers from a combinatorial explosion in the number of potential tracks resulted from the uncertainty in the linkage between the target and the measurement (a.k.a the data association problem). In addition, the nonlinear measurements lead to a non-Gaussian posterior probability density function (pdf) in the optimal Bayesian sequential estimation framework. The consequence of this nonlinear/non-Gaussian context is the absence of a closed-form solution. This paper models the linkage uncertainty and the nonlinear/non-Gaussian estimation problem jointly with solid Bayesian formalism. A particle filtering (PF) algorithm is derived for estimating the model's parameters in a sequential manner. Numerical results show that the proposed solution provides a significant benefit over the most commonly used methods, IPDA and IMMPDA. The posterior Cramér-Rao bounds are also involved for performance evaluation.

Least Squares Approach to the Alignment of the Generic High Precision Tracking System

NASA Astrophysics Data System (ADS)

de Renstrom, Pawel Brückman; Haywood, Stephen

2006-04-01

A least squares method to solve a generic alignment problem of a high granularity tracking system is presented. The algorithm is based on an analytical linear expansion and allows for multiple nested fits, e.g. imposing a common vertex for groups of particle tracks is of particular interest. We present a consistent and complete recipe to impose constraints on either implicit or explicit parameters. The method has been applied to the full simulation of a subset of the ATLAS silicon tracking system. The ultimate goal is to determine ≈35,000 degrees of freedom (DoF's). We present a limited scale exercise exploring various aspects of the solution.

WE-H-BRA-08: A Monte Carlo Cell Nucleus Model for Assessing Cell Survival Probability Based On Particle Track Structure Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, B; Georgia Institute of Technology, Atlanta, GA; Wang, C

Purpose: To correlate the damage produced by particles of different types and qualities to cell survival on the basis of nanodosimetric analysis and advanced DNA structures in the cell nucleus. Methods: A Monte Carlo code was developed to simulate subnuclear DNA chromatin fibers (CFs) of 30nm utilizing a mean-free-path approach common to radiation transport. The cell nucleus was modeled as a spherical region containing 6000 chromatin-dense domains (CDs) of 400nm diameter, with additional CFs modeled in a sparser interchromatin region. The Geant4-DNA code was utilized to produce a particle track database representing various particles at different energies and dose quantities.more » These tracks were used to stochastically position the DNA structures based on their mean free path to interaction with CFs. Excitation and ionization events intersecting CFs were analyzed using the DBSCAN clustering algorithm for assessment of the likelihood of producing DSBs. Simulated DSBs were then assessed based on their proximity to one another for a probability of inducing cell death. Results: Variations in energy deposition to chromatin fibers match expectations based on differences in particle track structure. The quality of damage to CFs based on different particle types indicate more severe damage by high-LET radiation than low-LET radiation of identical particles. In addition, the model indicates more severe damage by protons than of alpha particles of same LET, which is consistent with differences in their track structure. Cell survival curves have been produced showing the L-Q behavior of sparsely ionizing radiation. Conclusion: Initial results indicate the feasibility of producing cell survival curves based on the Monte Carlo cell nucleus method. Accurate correlation between simulated DNA damage to cell survival on the basis of nanodosimetric analysis can provide insight into the biological responses to various radiation types. Current efforts are directed at producing cell survival curves for high-LET radiation.« less

Analysis of relativistic nucleus-nucleus interactions in emulsion chambers

NASA Technical Reports Server (NTRS)

Mcguire, Stephen C.

1987-01-01

The development of a computer-assisted method is reported for the determination of the angular distribution data for secondary particles produced in relativistic nucleus-nucleus collisions in emulsions. The method is applied to emulsion detectors that were placed in a constant, uniform magnetic field and exposed to beams of 60 and 200 GeV/nucleon O-16 ions at the Super Proton Synchrotron (SPS) of the European Center for Nuclear Research (CERN). Linear regression analysis is used to determine the azimuthal and polar emission angles from measured track coordinate data. The software, written in BASIC, is designed to be machine independent, and adaptable to an automated system for acquiring the track coordinates. The fitting algorithm is deterministic, and takes into account the experimental uncertainty in the measured points. Further, a procedure for using the track data to estimate the linear momenta of the charged particles observed in the detectors is included.

Design of a new tracking device for on-line beam range monitor in carbon therapy.

PubMed

Traini, Giacomo; Battistoni, Giuseppe; Bollella, Angela; Collamati, Francesco; De Lucia, Erika; Faccini, Riccardo; Ferroni, Fernando; Frallicciardi, Paola Maria; Mancini-Terracciano, Carlo; Marafini, Michela; Mattei, Ilaria; Miraglia, Federico; Muraro, Silvia; Paramatti, Riccardo; Piersanti, Luca; Pinci, Davide; Rucinski, Antoni; Russomando, Andrea; Sarti, Alessio; Sciubba, Adalberto; Senzacqua, Martina; Solfaroli-Camillocci, Elena; Toppi, Marco; Voena, Cecilia; Patera, Vincenzo

2017-02-01

Charged particle therapy is a technique for cancer treatment that exploits hadron beams, mostly protons and carbon ions. A critical issue is the monitoring of the beam range so to check the correct dose deposition to the tumor and surrounding tissues. The design of a new tracking device for beam range real-time monitoring in pencil beam carbon ion therapy is presented. The proposed device tracks secondary charged particles produced by beam interactions in the patient tissue and exploits the correlation of the charged particle emission profile with the spatial dose deposition and the Bragg peak position. The detector, currently under construction, uses the information provided by 12 layers of scintillating fibers followed by a plastic scintillator and a pixelated Lutetium Fine Silicate (LFS) crystal calorimeter. An algorithm to account and correct for emission profile distortion due to charged secondaries absorption inside the patient tissue is also proposed. Finally detector reconstruction efficiency for charged particle emission profile is evaluated using a Monte Carlo simulation considering a quasi-realistic case of a non-homogenous phantom. Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Streamflow Observations From Cameras: Large-Scale Particle Image Velocimetry or Particle Tracking Velocimetry?

NASA Astrophysics Data System (ADS)

Tauro, F.; Piscopia, R.; Grimaldi, S.

2017-12-01

Image-based methodologies, such as large scale particle image velocimetry (LSPIV) and particle tracking velocimetry (PTV), have increased our ability to noninvasively conduct streamflow measurements by affording spatially distributed observations at high temporal resolution. However, progress in optical methodologies has not been paralleled by the implementation of image-based approaches in environmental monitoring practice. We attribute this fact to the sensitivity of LSPIV, by far the most frequently adopted algorithm, to visibility conditions and to the occurrence of visible surface features. In this work, we test both LSPIV and PTV on a data set of 12 videos captured in a natural stream wherein artificial floaters are homogeneously and continuously deployed. Further, we apply both algorithms to a video of a high flow event on the Tiber River, Rome, Italy. In our application, we propose a modified PTV approach that only takes into account realistic trajectories. Based on our findings, LSPIV largely underestimates surface velocities with respect to PTV in both favorable (12 videos in a natural stream) and adverse (high flow event in the Tiber River) conditions. On the other hand, PTV is in closer agreement than LSPIV with benchmark velocities in both experimental settings. In addition, the accuracy of PTV estimations can be directly related to the transit of physical objects in the field of view, thus providing tangible data for uncertainty evaluation.

Optimizing Likelihood Models for Particle Trajectory Segmentation in Multi-State Systems.

PubMed

Young, Dylan Christopher; Scrimgeour, Jan

2018-06-19

Particle tracking offers significant insight into the molecular mechanics that govern the behav- ior of living cells. The analysis of molecular trajectories that transition between different motive states, such as diffusive, driven and tethered modes, is of considerable importance, with even single trajectories containing significant amounts of information about a molecule's environment and its interactions with cellular structures. Hidden Markov models (HMM) have been widely adopted to perform the segmentation of such complex tracks. In this paper, we show that extensive analysis of hidden Markov model outputs using data derived from multi-state Brownian dynamics simulations can be used both for the optimization of the likelihood models used to describe the states of the system and for characterization of the technique's failure mechanisms. This analysis was made pos- sible by the implementation of parallelized adaptive direct search algorithm on a Nvidia graphics processing unit. This approach provides critical information for the visualization of HMM failure and successful design of particle tracking experiments where trajectories contain multiple mobile states. © 2018 IOP Publishing Ltd.

UmUTracker: A versatile MATLAB program for automated particle tracking of 2D light microscopy or 3D digital holography data

NASA Astrophysics Data System (ADS)

Zhang, Hanqing; Stangner, Tim; Wiklund, Krister; Rodriguez, Alvaro; Andersson, Magnus

2017-10-01

We present a versatile and fast MATLAB program (UmUTracker) that automatically detects and tracks particles by analyzing video sequences acquired by either light microscopy or digital in-line holographic microscopy. Our program detects the 2D lateral positions of particles with an algorithm based on the isosceles triangle transform, and reconstructs their 3D axial positions by a fast implementation of the Rayleigh-Sommerfeld model using a radial intensity profile. To validate the accuracy and performance of our program, we first track the 2D position of polystyrene particles using bright field and digital holographic microscopy. Second, we determine the 3D particle position by analyzing synthetic and experimentally acquired holograms. Finally, to highlight the full program features, we profile the microfluidic flow in a 100 μm high flow chamber. This result agrees with computational fluid dynamic simulations. On a regular desktop computer UmUTracker can detect, analyze, and track multiple particles at 5 frames per second for a template size of 201 ×201 in a 1024 × 1024 image. To enhance usability and to make it easy to implement new functions we used object-oriented programming. UmUTracker is suitable for studies related to: particle dynamics, cell localization, colloids and microfluidic flow measurement. Program Files doi : http://dx.doi.org/10.17632/fkprs4s6xp.1 Licensing provisions : Creative Commons by 4.0 (CC by 4.0) Programming language : MATLAB Nature of problem: 3D multi-particle tracking is a common technique in physics, chemistry and biology. However, in terms of accuracy, reliable particle tracking is a challenging task since results depend on sample illumination, particle overlap, motion blur and noise from recording sensors. Additionally, the computational performance is also an issue if, for example, a computationally expensive process is executed, such as axial particle position reconstruction from digital holographic microscopy data. Versatile robust tracking programs handling these concerns and providing a powerful post-processing option are significantly limited. Solution method: UmUTracker is a multi-functional tool to extract particle positions from long video sequences acquired with either light microscopy or digital holographic microscopy. The program provides an easy-to-use graphical user interface (GUI) for both tracking and post-processing that does not require any programming skills to analyze data from particle tracking experiments. UmUTracker first conduct automatic 2D particle detection even under noisy conditions using a novel circle detector based on the isosceles triangle sampling technique with a multi-scale strategy. To reduce the computational load for 3D tracking, it uses an efficient implementation of the Rayleigh-Sommerfeld light propagation model. To analyze and visualize the data, an efficient data analysis step, which can for example show 4D flow visualization using 3D trajectories, is included. Additionally, UmUTracker is easy to modify with user-customized modules due to the object-oriented programming style Additional comments: Program obtainable from https://sourceforge.net/projects/umutracker/

High-speed (20 kHz) digital in-line holography for transient particle tracking and sizing in multiphase flows

DOE PAGES

Guildenbecher, Daniel R.; Cooper, Marcia A.; Sojka, Paul E.

2016-04-05

High-speed (20 kHz) digital in-line holography (DIH) is applied for 3D quantification of the size and velocity of fragments formed from the impact of a single water drop onto a thin film of water and burning aluminum particles from the combustion of a solid rocket propellant. To address the depth-of-focus problem in DIH, a regression-based multiframe tracking algorithm is employed, and out-of-plane experimental displacement accuracy is shown to be improved by an order-of-magnitude. Comparison of the results with previous DIH measurements using low-speed recording shows improved positional accuracy with the added advantage of detailed resolution of transient dynamics from singlemore » experimental realizations. Furthermore, the method is shown to be particularly advantageous for quantification of particle mass flow rates. For the investigated particle fields, the mass flows rates, which have been automatically measured from single experimental realizations, are found to be within 8% of the expected values.« less

Determining residual reduction algorithm kinematic tracking weights for a sidestep cut via numerical optimization.

PubMed

Samaan, Michael A; Weinhandl, Joshua T; Bawab, Sebastian Y; Ringleb, Stacie I

2016-12-01

Musculoskeletal modeling allows for the determination of various parameters during dynamic maneuvers by using in vivo kinematic and ground reaction force (GRF) data as inputs. Differences between experimental and model marker data and inconsistencies in the GRFs applied to these musculoskeletal models may not produce accurate simulations. Therefore, residual forces and moments are applied to these models in order to reduce these differences. Numerical optimization techniques can be used to determine optimal tracking weights of each degree of freedom of a musculoskeletal model in order to reduce differences between the experimental and model marker data as well as residual forces and moments. In this study, the particle swarm optimization (PSO) and simplex simulated annealing (SIMPSA) algorithms were used to determine optimal tracking weights for the simulation of a sidestep cut. The PSO and SIMPSA algorithms were able to produce model kinematics that were within 1.4° of experimental kinematics with residual forces and moments of less than 10 N and 18 Nm, respectively. The PSO algorithm was able to replicate the experimental kinematic data more closely and produce more dynamically consistent kinematic data for a sidestep cut compared to the SIMPSA algorithm. Future studies should use external optimization routines to determine dynamically consistent kinematic data and report the differences between experimental and model data for these musculoskeletal simulations.

Analysis of Video-Based Microscopic Particle Trajectories Using Kalman Filtering

PubMed Central

Wu, Pei-Hsun; Agarwal, Ashutosh; Hess, Henry; Khargonekar, Pramod P.; Tseng, Yiider

2010-01-01

Abstract The fidelity of the trajectories obtained from video-based particle tracking determines the success of a variety of biophysical techniques, including in situ single cell particle tracking and in vitro motility assays. However, the image acquisition process is complicated by system noise, which causes positioning error in the trajectories derived from image analysis. Here, we explore the possibility of reducing the positioning error by the application of a Kalman filter, a powerful algorithm to estimate the state of a linear dynamic system from noisy measurements. We show that the optimal Kalman filter parameters can be determined in an appropriate experimental setting, and that the Kalman filter can markedly reduce the positioning error while retaining the intrinsic fluctuations of the dynamic process. We believe the Kalman filter can potentially serve as a powerful tool to infer a trajectory of ultra-high fidelity from noisy images, revealing the details of dynamic cellular processes. PMID:20550894

An algorithm for the detection and characterisation of volcanic plumes using thermal camera imagery

NASA Astrophysics Data System (ADS)

Bombrun, Maxime; Jessop, David; Harris, Andrew; Barra, Vincent

2018-02-01

Volcanic plumes are turbulent mixtures of particles and gas which are injected into the atmosphere during a volcanic eruption. Depending on the intensity of the eruption, plumes can rise from a few tens of metres up to many tens of kilometres above the vent and thus, present a major hazard for the surrounding population. Currently, however, few if any algorithms are available for automated plume tracking and assessment. Here, we present a new image processing algorithm for segmentation, tracking and parameters extraction of convective plume recorded with thermal cameras. We used thermal video of two volcanic eruptions and two plumes simulated in laboratory to develop and test an efficient technique for analysis of volcanic plumes. We validated our method by two different approaches. First, we compare our segmentation method to previously published algorithms. Next, we computed plume parameters, such as height, width and spreading angle at regular intervals of time. These parameters allowed us to calculate an entrainment coefficient and obtain information about the entrainment efficiency in Strombolian eruptions. Our proposed algorithm is rapid, automated while producing better visual outlines compared to the other segmentation algorithms, and provides output that is at least as accurate as manual measurements of plumes.

In-vivo study of blood flow in capillaries using μPIV method

NASA Astrophysics Data System (ADS)

Kurochkin, Maxim A.; Fedosov, Ivan V.; Tuchin, Valery V.

2014-01-01

A digital optical system for intravital capillaroscopy has been developed. It implements the particle image velocimetry (PIV) based approach for measurements of red blood cells velocity in individual capillary of human nailfold. We propose to use a digital real time stabilization technique for compensation of impact of involuntary movements of a finger on results of measurements. Image stabilization algorithm is based on correlation of feature tracking. The efficiency of designed image stabilization algorithm was experimentally demonstrated.

Iterative Reconstruction of Volumetric Particle Distribution for 3D Velocimetry

NASA Astrophysics Data System (ADS)

Wieneke, Bernhard; Neal, Douglas

2011-11-01

A number of different volumetric flow measurement techniques exist for following the motion of illuminated particles. For experiments that have lower seeding densities, 3D-PTV uses recorded images from typically 3-4 cameras and then tracks the individual particles in space and time. This technique is effective in flows that have lower seeding densities. For flows that have a higher seeding density, tomographic PIV uses a tomographic reconstruction algorithm (e.g. MART) to reconstruct voxel intensities of the recorded volume followed by the cross-correlation of subvolumes to provide the instantaneous 3D vector fields on a regular grid. A new hybrid algorithm is presented which iteratively reconstructs the 3D-particle distribution directly using particles with certain imaging properties instead of voxels as base functions. It is shown with synthetic data that this method is capable of reconstructing densely seeded flows up to 0.05 particles per pixel (ppp) with the same or higher accuracy than 3D-PTV and tomographic PIV. Finally, this new method is validated using experimental data on a turbulent jet.

The artificial retina processor for track reconstruction at the LHC crossing rate

DOE PAGES

Abba, A.; Bedeschi, F.; Citterio, M.; ...

2015-03-16

We present results of an R&D study for a specialized processor capable of precisely reconstructing, in pixel detectors, hundreds of charged-particle tracks from high-energy collisions at 40 MHz rate. We apply a highly parallel pattern-recognition algorithm, inspired by studies of the processing of visual images by the brain as it happens in nature, and describe in detail an efficient hardware implementation in high-speed, high-bandwidth FPGA devices. This is the first detailed demonstration of reconstruction of offline-quality tracks at 40 MHz and makes the device suitable for processing Large Hadron Collider events at the full crossing frequency.

OpenCV and TYZX : video surveillance for tracking.

DOE Office of Scientific and Technical Information (OSTI.GOV)

He, Jim; Spencer, Andrew; Chu, Eric

2008-08-01

As part of the National Security Engineering Institute (NSEI) project, several sensors were developed in conjunction with an assessment algorithm. A camera system was developed in-house to track the locations of personnel within a secure room. In addition, a commercial, off-the-shelf (COTS) tracking system developed by TYZX was examined. TYZX is a Bay Area start-up that has developed its own tracking hardware and software which we use as COTS support for robust tracking. This report discusses the pros and cons of each camera system, how they work, a proposed data fusion method, and some visual results. Distributed, embedded image processingmore » solutions show the most promise in their ability to track multiple targets in complex environments and in real-time. Future work on the camera system may include three-dimensional volumetric tracking by using multiple simple cameras, Kalman or particle filtering, automated camera calibration and registration, and gesture or path recognition.« less

Parallelized Kalman-Filter-Based Reconstruction of Particle Tracks on Many-Core Processors and GPUs

NASA Astrophysics Data System (ADS)

Cerati, Giuseppe; Elmer, Peter; Krutelyov, Slava; Lantz, Steven; Lefebvre, Matthieu; Masciovecchio, Mario; McDermott, Kevin; Riley, Daniel; Tadel, Matevž; Wittich, Peter; Würthwein, Frank; Yagil, Avi

2017-08-01

For over a decade now, physical and energy constraints have limited clock speed improvements in commodity microprocessors. Instead, chipmakers have been pushed into producing lower-power, multi-core processors such as Graphical Processing Units (GPU), ARM CPUs, and Intel MICs. Broad-based efforts from manufacturers and developers have been devoted to making these processors user-friendly enough to perform general computations. However, extracting performance from a larger number of cores, as well as specialized vector or SIMD units, requires special care in algorithm design and code optimization. One of the most computationally challenging problems in high-energy particle experiments is finding and fitting the charged-particle tracks during event reconstruction. This is expected to become by far the dominant problem at the High-Luminosity Large Hadron Collider (HL-LHC), for example. Today the most common track finding methods are those based on the Kalman filter. Experience with Kalman techniques on real tracking detector systems has shown that they are robust and provide high physics performance. This is why they are currently in use at the LHC, both in the trigger and offine. Previously we reported on the significant parallel speedups that resulted from our investigations to adapt Kalman filters to track fitting and track building on Intel Xeon and Xeon Phi. Here, we discuss our progresses toward the understanding of these processors and the new developments to port the Kalman filter to NVIDIA GPUs.

Novel Approaches to Improve Iris Recognition System Performance Based on Local Quality Evaluation and Feature Fusion

PubMed Central

2014-01-01

For building a new iris template, this paper proposes a strategy to fuse different portions of iris based on machine learning method to evaluate local quality of iris. There are three novelties compared to previous work. Firstly, the normalized segmented iris is divided into multitracks and then each track is estimated individually to analyze the recognition accuracy rate (RAR). Secondly, six local quality evaluation parameters are adopted to analyze texture information of each track. Besides, particle swarm optimization (PSO) is employed to get the weights of these evaluation parameters and corresponding weighted coefficients of different tracks. Finally, all tracks' information is fused according to the weights of different tracks. The experimental results based on subsets of three public and one private iris image databases demonstrate three contributions of this paper. (1) Our experimental results prove that partial iris image cannot completely replace the entire iris image for iris recognition system in several ways. (2) The proposed quality evaluation algorithm is a self-adaptive algorithm, and it can automatically optimize the parameters according to iris image samples' own characteristics. (3) Our feature information fusion strategy can effectively improve the performance of iris recognition system. PMID:24693243

Novel approaches to improve iris recognition system performance based on local quality evaluation and feature fusion.

PubMed

Chen, Ying; Liu, Yuanning; Zhu, Xiaodong; Chen, Huiling; He, Fei; Pang, Yutong

2014-01-01

For building a new iris template, this paper proposes a strategy to fuse different portions of iris based on machine learning method to evaluate local quality of iris. There are three novelties compared to previous work. Firstly, the normalized segmented iris is divided into multitracks and then each track is estimated individually to analyze the recognition accuracy rate (RAR). Secondly, six local quality evaluation parameters are adopted to analyze texture information of each track. Besides, particle swarm optimization (PSO) is employed to get the weights of these evaluation parameters and corresponding weighted coefficients of different tracks. Finally, all tracks' information is fused according to the weights of different tracks. The experimental results based on subsets of three public and one private iris image databases demonstrate three contributions of this paper. (1) Our experimental results prove that partial iris image cannot completely replace the entire iris image for iris recognition system in several ways. (2) The proposed quality evaluation algorithm is a self-adaptive algorithm, and it can automatically optimize the parameters according to iris image samples' own characteristics. (3) Our feature information fusion strategy can effectively improve the performance of iris recognition system.

Design and Construction of Detector and Data Acquisition Elements for Proton Computed Tomography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fermi Research Alliance; Northern Illinois University

2015-07-15

Proton computed tomography (pCT) offers an alternative to x-ray imaging with potential for three-dimensional imaging, reduced radiation exposure, and in-situ imaging. Northern Illinois University (NIU) is developing a second-generation proton computed tomography system with a goal of demonstrating the feasibility of three-dimensional imaging within clinically realistic imaging times. The second-generation pCT system is comprised of a tracking system, a calorimeter, data acquisition, a computing farm, and software algorithms. The proton beam encounters the upstream tracking detectors, the patient or phantom, the downstream tracking detectors, and a calorimeter. The schematic layout of the PCT system is shown. The data acquisition sendsmore » the proton scattering information to an offline computing farm. Major innovations of the second generation pCT project involve an increased data acquisition rate ( MHz range) and development of three-dimensional imaging algorithms. The Fermilab Particle Physics Division and Northern Illinois Center for Accelerator and Detector Development at Northern Illinois University worked together to design and construct the tracking detectors, calorimeter, readout electronics and detector mounting system.« less

Development of a Vision-Based Particle Tracking Velocimetry Method and Post-Processing of Scattered Velocity Data

DTIC Science & Technology

2012-01-01

the performance of the VB-PTV algorithm. Particle yield is changed subtly from the definition above and defined as the number of matches made over the...methods have been developed for use in fields as varied as cosmology (Bernardeau and van de Weygaert, 1996; Schaap and van de Weygaert, 2000) and...becomes a long list of equations and variable definitions , interested readers are referred to Gunes et al., (2006); Sacks et al., (1989); and Lophaven

Accelerating navigation in the VecGeom geometry modeller

NASA Astrophysics Data System (ADS)

Wenzel, Sandro; Zhang, Yang; pre="for the"> VecGeom Developers,

2017-10-01

The VecGeom geometry library is a relatively recent effort aiming to provide a modern and high performance geometry service for particle detector simulation in hierarchical detector geometries common to HEP experiments. One of its principal targets is the efficient use of vector SIMD hardware instructions to accelerate geometry calculations for single track as well as multi-track queries. Previously, excellent performance improvements compared to Geant4/ROOT could be reported for elementary geometry algorithms at the level of single shape queries. In this contribution, we will focus on the higher level navigation algorithms in VecGeom, which are the most important components as seen from the simulation engines. We will first report on our R&D effort and developments to implement SIMD enhanced data structures to speed up the well-known “voxelised” navigation algorithms, ubiquitously used for particle tracing in complex detector modules consisting of many daughter parts. Second, we will discuss complementary new approaches to improve navigation algorithms in HEP. These ideas are based on a systematic exploitation of static properties of the detector layout as well as automatic code generation and specialisation of the C++ navigator classes. Such specialisations reduce the overhead of generic- or virtual function based algorithms and enhance the effectiveness of the SIMD vector units. These novel approaches go well beyond the existing solutions available in Geant4 or TGeo/ROOT, achieve a significantly superior performance, and might be of interest for a wide range of simulation backends (GeantV, Geant4). We exemplify this with concrete benchmarks for the CMS and ALICE detectors.

A fully-automated multiscale kernel graph cuts based particle localization scheme for temporal focusing two-photon microscopy

NASA Astrophysics Data System (ADS)

Huang, Xia; Li, Chunqiang; Xiao, Chuan; Sun, Wenqing; Qian, Wei

2017-03-01

The temporal focusing two-photon microscope (TFM) is developed to perform depth resolved wide field fluorescence imaging by capturing frames sequentially. However, due to strong nonignorable noises and diffraction rings surrounding particles, further researches are extremely formidable without a precise particle localization technique. In this paper, we developed a fully-automated scheme to locate particles positions with high noise tolerance. Our scheme includes the following procedures: noise reduction using a hybrid Kalman filter method, particle segmentation based on a multiscale kernel graph cuts global and local segmentation algorithm, and a kinematic estimation based particle tracking method. Both isolated and partial-overlapped particles can be accurately identified with removal of unrelated pixels. Based on our quantitative analysis, 96.22% isolated particles and 84.19% partial-overlapped particles were successfully detected.

Adaptive track scheduling to optimize concurrency and vectorization in GeantV

DOE PAGES

Apostolakis, J.; Bandieramonte, M.; Bitzes, G.; ...

2015-05-22

The GeantV project is focused on the R&D of new particle transport techniques to maximize parallelism on multiple levels, profiting from the use of both SIMD instructions and co-processors for the CPU-intensive calculations specific to this type of applications. In our approach, vectors of tracks belonging to multiple events and matching different locality criteria must be gathered and dispatched to algorithms having vector signatures. While the transport propagates tracks and changes their individual states, data locality becomes harder to maintain. The scheduling policy has to be changed to maintain efficient vectors while keeping an optimal level of concurrency. The modelmore » has complex dynamics requiring tuning the thresholds to switch between the normal regime and special modes, i.e. prioritizing events to allow flushing memory, adding new events in the transport pipeline to boost locality, dynamically adjusting the particle vector size or switching between vector to single track mode when vectorization causes only overhead. Lastly, this work requires a comprehensive study for optimizing these parameters to make the behaviour of the scheduler self-adapting, presenting here its initial results.« less

A New Method for Tracking Individual Particles During Bed Load Transport in a Gravel-Bed River

NASA Astrophysics Data System (ADS)

Tremblay, M.; Marquis, G. A.; Roy, A. G.; Chaire de Recherche Du Canada En Dynamique Fluviale

2010-12-01

Many particle tracers (passive or active) have been developed to study gravel movement in rivers. It remains difficult, however, to document resting and moving periods and to know how particles travel from one deposition site to another. Our new tracking method uses the Hobo Pendant G acceleration Data Logger to quantitatively describe the motion of individual particles from the initiation of movement, through the displacement and to the rest, in a natural gravel river. The Hobo measures the acceleration in three dimensions at a chosen temporal frequency. The Hobo was inserted into 11 artificial rocks. The rocks were seeded in Ruisseau Béard, a small gravel-bed river in the Yamaska drainage basin (Québec) where the hydraulics, particle sizes and bed characteristics are well known. The signals recorded during eight floods (Summer and Fall 2008-2009) allowed us to develop an algorithm which classifies the periods of rest and motion. We can differentiate two types of motion: sliding and rolling. The particles can also vibrate while remaining in the same position. The examination of the movement and vibration periods with respect to the hydraulic conditions (discharge, shear stress, stream power) showed that vibration occurred mostly before the rise of hydrograph and allowed us to establish movement threshold and response times. In all cases, particle movements occurred during floods but not always in direct response to increased bed shear stress and stream power. This method offers great potential to track individual particles and to establish a spatiotemporal sequence of the intermittent transport of the particle during a flood and to test theories concerning the resting periods of particles on a gravel bed.

Lagrangian Fluid Element Tracking and Estimation of Local Displacement Speeds in Turbulent Premixed Flames

NASA Astrophysics Data System (ADS)

Ramji, Sarah Ann

Improved understanding of turbulence-flame interactions in premixed combustion can be achieved using fully 3D time-resolved multi-kHz multi-scalar experimental measurements. These interactions may be represented by the evolution of various Lagrangian quantities described by theoretical Lagrangian Fluid Elements (LFEs). The data used in this work came from two experimental campaigns that used simultaneous T-PIV and OH/CH2O PLIF, at Sandia National Labs and the Air Force Research Lab at Wright-Patterson. In this thesis, an algorithm to accurately track LFEs through this 4D experimental space has been developed and verified by cross-correlation with the T-PIV seed particle fields. A novel method to measure the local instantaneous displacement speed in 3D has been developed, using this algorithm to track control masses of fluid that interact with the flame front. Statistics of the displacement speed have been presented, and the effects of local turbulence and flame topological properties on the displacement speed have been studied.

Feature aided Monte Carlo probabilistic data association filter for ballistic missile tracking

NASA Astrophysics Data System (ADS)

Ozdemir, Onur; Niu, Ruixin; Varshney, Pramod K.; Drozd, Andrew L.; Loe, Richard

2011-05-01

The problem of ballistic missile tracking in the presence of clutter is investigated. Probabilistic data association filter (PDAF) is utilized as the basic filtering algorithm. We propose to use sequential Monte Carlo methods, i.e., particle filters, aided with amplitude information (AI) in order to improve the tracking performance of a single target in clutter when severe nonlinearities exist in the system. We call this approach "Monte Carlo probabilistic data association filter with amplitude information (MCPDAF-AI)." Furthermore, we formulate a realistic problem in the sense that we use simulated radar cross section (RCS) data for a missile warhead and a cylinder chaff using Lucernhammer1, a state of the art electromagnetic signature prediction software, to model target and clutter amplitude returns as additional amplitude features which help to improve data association and tracking performance. A performance comparison is carried out between the extended Kalman filter (EKF) and the particle filter under various scenarios using single and multiple sensors. The results show that, when only one sensor is used, the MCPDAF performs significantly better than the EKF in terms of tracking accuracy under severe nonlinear conditions for ballistic missile tracking applications. However, when the number of sensors is increased, even under severe nonlinear conditions, the EKF performs as well as the MCPDAF.

Wavelet and Multiresolution Analysis for Finite Element Networking Paradigms

NASA Technical Reports Server (NTRS)

Kurdila, Andrew J.; Sharpley, Robert C.

1999-01-01

This paper presents a final report on Wavelet and Multiresolution Analysis for Finite Element Networking Paradigms. The focus of this research is to derive and implement: 1) Wavelet based methodologies for the compression, transmission, decoding, and visualization of three dimensional finite element geometry and simulation data in a network environment; 2) methodologies for interactive algorithm monitoring and tracking in computational mechanics; and 3) Methodologies for interactive algorithm steering for the acceleration of large scale finite element simulations. Also included in this report are appendices describing the derivation of wavelet based Particle Image Velocity algorithms and reduced order input-output models for nonlinear systems by utilizing wavelet approximations.

Distributed multi-sensor particle filter for bearings-only tracking

NASA Astrophysics Data System (ADS)

Zhang, Jungen; Ji, Hongbing

2012-02-01

In this article, the classical bearings-only tracking (BOT) problem for a single target is addressed, which belongs to the general class of non-linear filtering problems. Due to the fact that the radial distance observability of the target is poor, the algorithm-based sequential Monte-Carlo (particle filtering, PF) methods generally show instability and filter divergence. A new stable distributed multi-sensor PF method is proposed for BOT. The sensors process their measurements at their sites using a hierarchical PF approach, which transforms the BOT problem from Cartesian coordinate to the logarithmic polar coordinate and separates the observable components from the unobservable components of the target. In the fusion centre, the target state can be estimated by utilising the multi-sensor optimal information fusion rule. Furthermore, the computation of a theoretical Cramer-Rao lower bound is given for the multi-sensor BOT problem. Simulation results illustrate that the proposed tracking method can provide better performances than the traditional PF method.

Simulations in the Analysis of Experimental Data Measured by BM@N Drift Chambers

NASA Astrophysics Data System (ADS)

Fedorišin, Ján

2018-02-01

The drift chambers (DCH's) are an important part of the tracking system of the BM@N experiment designed to study the production of baryonic matter at the Nuclotron energies. The method of particle hit and track reconstruction in the drift chambers has been already proposed and tested on the BM@N deuteron beam data. In this study the DCH's are first locally and globally aligned, and subsequently the consistency of the track reconstruction chain is tested by two methods. The first one is based on the backward extrapolation of the DCH reconstructed deuteron beam to a position where its deflection in the BM@N magnetic field begins. The second method reconstructs the deuteron beam momentum through its deflection angle. Both methods confirm correctness of the track reconstruction algorithm.

Kalman Filter Tracking on Parallel Architectures

NASA Astrophysics Data System (ADS)

Cerati, Giuseppe; Elmer, Peter; Lantz, Steven; McDermott, Kevin; Riley, Dan; Tadel, Matevž; Wittich, Peter; Würthwein, Frank; Yagil, Avi

2015-12-01

Power density constraints are limiting the performance improvements of modern CPUs. To address this we have seen the introduction of lower-power, multi-core processors, but the future will be even more exciting. In order to stay within the power density limits but still obtain Moore's Law performance/price gains, it will be necessary to parallelize algorithms to exploit larger numbers of lightweight cores and specialized functions like large vector units. Example technologies today include Intel's Xeon Phi and GPGPUs. Track finding and fitting is one of the most computationally challenging problems for event reconstruction in particle physics. At the High Luminosity LHC, for example, this will be by far the dominant problem. The need for greater parallelism has driven investigations of very different track finding techniques including Cellular Automata or returning to Hough Transform. The most common track finding techniques in use today are however those based on the Kalman Filter [2]. Significant experience has been accumulated with these techniques on real tracking detector systems, both in the trigger and offline. They are known to provide high physics performance, are robust and are exactly those being used today for the design of the tracking system for HL-LHC. Our previous investigations showed that, using optimized data structures, track fitting with Kalman Filter can achieve large speedup both with Intel Xeon and Xeon Phi. We report here our further progress towards an end-to-end track reconstruction algorithm fully exploiting vectorization and parallelization techniques in a realistic simulation setup.

Research on target tracking algorithm based on spatio-temporal context

NASA Astrophysics Data System (ADS)

Li, Baiping; Xu, Sanmei; Kang, Hongjuan

2017-07-01

In this paper, a novel target tracking algorithm based on spatio-temporal context is proposed. During the tracking process, the camera shaking or occlusion may lead to the failure of tracking. The proposed algorithm can solve this problem effectively. The method use the spatio-temporal context algorithm as the main research object. We get the first frame's target region via mouse. Then the spatio-temporal context algorithm is used to get the tracking targets of the sequence of frames. During this process a similarity measure function based on perceptual hash algorithm is used to judge the tracking results. If tracking failed, reset the initial value of Mean Shift algorithm for the subsequent target tracking. Experiment results show that the proposed algorithm can achieve real-time and stable tracking when camera shaking or target occlusion.

ML-Space: Hybrid Spatial Gillespie and Particle Simulation of Multi-Level Rule-Based Models in Cell Biology.

PubMed

Bittig, Arne T; Uhrmacher, Adelinde M

2017-01-01

Spatio-temporal dynamics of cellular processes can be simulated at different levels of detail, from (deterministic) partial differential equations via the spatial Stochastic Simulation algorithm to tracking Brownian trajectories of individual particles. We present a spatial simulation approach for multi-level rule-based models, which includes dynamically hierarchically nested cellular compartments and entities. Our approach ML-Space combines discrete compartmental dynamics, stochastic spatial approaches in discrete space, and particles moving in continuous space. The rule-based specification language of ML-Space supports concise and compact descriptions of models and to adapt the spatial resolution of models easily.

Image reconstruction of muon tomographic data using a density-based clustering method

NASA Astrophysics Data System (ADS)

Perry, Kimberly B.

Muons are subatomic particles capable of reaching the Earth's surface before decaying. When these particles collide with an object that has a high atomic number (Z), their path of travel changes substantially. Tracking muon movement through shielded containers can indicate what types of materials lie inside. This thesis proposes using a density-based clustering algorithm called OPTICS to perform image reconstructions using muon tomographic data. The results show that this method is capable of detecting high-Z materials quickly, and can also produce detailed reconstructions with large amounts of data.

A binary link tracker for the BaBar level 1 trigger system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Berenyi, A.; Chen, H.K.; Dao, K.

1999-08-01

The BaBar detector at PEP-II will operate in a high-luminosity e{sup +}e{sup {minus}} collider environment near the {Upsilon}(4S) resonance with the primary goal of studying CP violation in the B meson system. In this environment, typical physics events of interest involve multiple charged particles. These events are identified by counting these tracks in a fast first level (Level 1) trigger system, by reconstructing the tracks in real time. For this purpose, a Binary Link Tracker Module (BLTM) was designed and fabricated for the BaBar Level 1 Drift Chamber trigger system. The BLTM is responsible for linking track segments, constructed bymore » the Track Segment Finder Modules (TSFM), into complete tracks. A single BLTM module processes a 360 MBytes/s stream of segment hit data, corresponding to information from the entire Drift Chamber, and implements a fast and robust algorithm that tolerates high hit occupancies as well as local inefficiencies of the Drift Chamber. The algorithms and the necessary control logic of the BLTM were implemented in Field Programmable Gate Arrays (FPGAs), using the VHDL hardware description language. The finished 9U x 400 mm Euro-format board contains roughly 75,000 gates of programmable logic or about 10,000 lines of VHDL code synthesized into five FPGAs.« less

Simulating pathways of subsurface oil in the Faroe-Shetland Channel using an ocean general circulation model.

PubMed

Main, C E; Yool, A; Holliday, N P; Popova, E E; Jones, D O B; Ruhl, H A

2017-01-15

Little is known about the fate of subsurface hydrocarbon plumes from deep-sea oil well blowouts and their effects on processes and communities. As deepwater drilling expands in the Faroe-Shetland Channel (FSC), oil well blowouts are a possibility, and the unusual ocean circulation of this region presents challenges to understanding possible subsurface oil pathways in the event of a spill. Here, an ocean general circulation model was used with a particle tracking algorithm to assess temporal variability of the oil-plume distribution from a deep-sea oil well blowout in the FSC. The drift of particles was first tracked for one year following release. Then, ambient model temperatures were used to simulate temperature-mediated biodegradation, truncating the trajectories of particles accordingly. Release depth of the modeled subsurface plumes affected both their direction of transport and distance travelled from their release location, and there was considerable interannual variability in transport. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

An efficient and reliable predictive method for fluidized bed simulation

DOE PAGES

Lu, Liqiang; Benyahia, Sofiane; Li, Tingwen

2017-06-13

In past decades, the continuum approach was the only practical technique to simulate large-scale fluidized bed reactors because discrete approaches suffer from the cost of tracking huge numbers of particles and their collisions. This study significantly improved the computation speed of discrete particle methods in two steps: First, the time-driven hard-sphere (TDHS) algorithm with a larger time-step is proposed allowing a speedup of 20-60 times; second, the number of tracked particles is reduced by adopting the coarse-graining technique gaining an additional 2-3 orders of magnitude speedup of the simulations. A new velocity correction term was introduced and validated in TDHSmore » to solve the over-packing issue in dense granular flow. The TDHS was then coupled with the coarse-graining technique to simulate a pilot-scale riser. The simulation results compared well with experiment data and proved that this new approach can be used for efficient and reliable simulations of large-scale fluidized bed systems.« less

Muon Trigger for Mobile Phones

NASA Astrophysics Data System (ADS)

Borisyak, M.; Usvyatsov, M.; Mulhearn, M.; Shimmin, C.; Ustyuzhanin, A.

2017-10-01

The CRAYFIS experiment proposes to use privately owned mobile phones as a ground detector array for Ultra High Energy Cosmic Rays. Upon interacting with Earth’s atmosphere, these events produce extensive particle showers which can be detected by cameras on mobile phones. A typical shower contains minimally-ionizing particles such as muons. As these particles interact with CMOS image sensors, they may leave tracks of faintly-activated pixels that are sometimes hard to distinguish from random detector noise. Triggers that rely on the presence of very bright pixels within an image frame are not efficient in this case. We present a trigger algorithm based on Convolutional Neural Networks which selects images containing such tracks and are evaluated in a lazy manner: the response of each successive layer is computed only if activation of the current layer satisfies a continuation criterion. Usage of neural networks increases the sensitivity considerably comparable with image thresholding, while the lazy evaluation allows for execution of the trigger under the limited computational power of mobile phones.

An efficient and reliable predictive method for fluidized bed simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lu, Liqiang; Benyahia, Sofiane; Li, Tingwen

2017-06-29

In past decades, the continuum approach was the only practical technique to simulate large-scale fluidized bed reactors because discrete approaches suffer from the cost of tracking huge numbers of particles and their collisions. This study significantly improved the computation speed of discrete particle methods in two steps: First, the time-driven hard-sphere (TDHS) algorithm with a larger time-step is proposed allowing a speedup of 20-60 times; second, the number of tracked particles is reduced by adopting the coarse-graining technique gaining an additional 2-3 orders of magnitude speedup of the simulations. A new velocity correction term was introduced and validated in TDHSmore » to solve the over-packing issue in dense granular flow. The TDHS was then coupled with the coarse-graining technique to simulate a pilot-scale riser. The simulation results compared well with experiment data and proved that this new approach can be used for efficient and reliable simulations of large-scale fluidized bed systems.« less

A difference tracking algorithm based on discrete sine transform

NASA Astrophysics Data System (ADS)

Liu, HaoPeng; Yao, Yong; Lei, HeBing; Wu, HaoKun

2018-04-01

Target tracking is an important field of computer vision. The template matching tracking algorithm based on squared difference matching (SSD) and standard correlation coefficient (NCC) matching is very sensitive to the gray change of image. When the brightness or gray change, the tracking algorithm will be affected by high-frequency information. Tracking accuracy is reduced, resulting in loss of tracking target. In this paper, a differential tracking algorithm based on discrete sine transform is proposed to reduce the influence of image gray or brightness change. The algorithm that combines the discrete sine transform and the difference algorithm maps the target image into a image digital sequence. The Kalman filter predicts the target position. Using the Hamming distance determines the degree of similarity between the target and the template. The window closest to the template is determined the target to be tracked. The target to be tracked updates the template. Based on the above achieve target tracking. The algorithm is tested in this paper. Compared with SSD and NCC template matching algorithms, the algorithm tracks target stably when image gray or brightness change. And the tracking speed can meet the read-time requirement.

Multiparticle imaging technique for two-phase fluid flows using pulsed laser speckle velocimetry. Final report, September 1988--November 1992

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hassan, T.A.

1992-12-01

The practical use of Pulsed Laser Velocimetry (PLV) requires the use of fast, reliable computer-based methods for tracking numerous particles suspended in a fluid flow. Two methods for performing tracking are presented. One method tracks a particle through multiple sequential images (minimum of four required) by prediction and verification of particle displacement and direction. The other method, requiring only two sequential images uses a dynamic, binary, spatial, cross-correlation technique. The algorithms are tested on computer-generated synthetic data and experimental data which was obtained with traditional PLV methods. This allowed error analysis and testing of the algorithms on real engineering flows.more » A novel method is proposed which eliminates tedious, undersirable, manual, operator assistance in removing erroneous vectors. This method uses an iterative process involving an interpolated field produced from the most reliable vectors. Methods are developed to allow fast analysis and presentation of sets of PLV image data. Experimental investigation of a two-phase, horizontal, stratified, flow regime was performed to determine the interface drag force, and correspondingly, the drag coefficient. A horizontal, stratified flow test facility using water and air was constructed to allow interface shear measurements with PLV techniques. The experimentally obtained local drag measurements were compared with theoretical results given by conventional interfacial drag theory. Close agreement was shown when local conditions near the interface were similar to space-averaged conditions. However, theory based on macroscopic, space-averaged flow behavior was shown to give incorrect results if the local gas velocity near the interface as unstable, transient, and dissimilar from the average gas velocity through the test facility.« less

Multiparticle imaging technique for two-phase fluid flows using pulsed laser speckle velocimetry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hassan, T.A.

1992-12-01

The practical use of Pulsed Laser Velocimetry (PLV) requires the use of fast, reliable computer-based methods for tracking numerous particles suspended in a fluid flow. Two methods for performing tracking are presented. One method tracks a particle through multiple sequential images (minimum of four required) by prediction and verification of particle displacement and direction. The other method, requiring only two sequential images uses a dynamic, binary, spatial, cross-correlation technique. The algorithms are tested on computer-generated synthetic data and experimental data which was obtained with traditional PLV methods. This allowed error analysis and testing of the algorithms on real engineering flows.more » A novel method is proposed which eliminates tedious, undersirable, manual, operator assistance in removing erroneous vectors. This method uses an iterative process involving an interpolated field produced from the most reliable vectors. Methods are developed to allow fast analysis and presentation of sets of PLV image data. Experimental investigation of a two-phase, horizontal, stratified, flow regime was performed to determine the interface drag force, and correspondingly, the drag coefficient. A horizontal, stratified flow test facility using water and air was constructed to allow interface shear measurements with PLV techniques. The experimentally obtained local drag measurements were compared with theoretical results given by conventional interfacial drag theory. Close agreement was shown when local conditions near the interface were similar to space-averaged conditions. However, theory based on macroscopic, space-averaged flow behavior was shown to give incorrect results if the local gas velocity near the interface as unstable, transient, and dissimilar from the average gas velocity through the test facility.« less

TU-AB-201-04: Optimizing the Number of Catheter Implants and Their Tracks for Prostate HDR Brachytherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Riofrio, D; Luan, S; Zhou, J

Purpose: In prostate HDR brachytherapy, interstitial implants are placed manually on the fly. The aim for this research is to develop a computer algorithm to find optimal and reliable implant trajectories using minimal number of implants. Methods: Our new algorithm mainly uses these key ideas: (1) positive charged static particles are uniformly placed on the surface of prostate and critical structures such as urethra, bladder, and rectum. (2) Positive charged kinetic particles are placed at a cross-section of the prostate with an initial velocity parallel to the principal implant direction. (3) The kinetic particles move through the prostate, interacting withmore » each other, spreading out, while staying away from the prostate surface and critical structures. The initial velocity ensures that the trajectories observe the curvature constraints of typical implant procedures. (4) The finial trajectories of kinetic particles are smoothed using a third-degree polynomial regression, which become the implant trajectories. (5) The dwelling times and final dose distribution are calculated using least-distance programming. Results: (1) We experimented with previously treated cases. Our plan achieves all prescription goals while reducing the number of implants by 41%! Our plan also has less uniform target dose, which implies a higher dose is delivered to the prostate. (2) We expect future implant procedures will be performed under the guidance of such pre-calculated trajectories. To assess the applicability, we randomly perturb the tracks to mimic the manual implant errors. Our studies showed the impact of these perturbations are negligible, which is compensated by the least distance programming. Conclusions: We developed a new inverse planning system for prostate HDR therapy that can find optimal implant trajectories while minimizing the number of implants. For future work, we plan to integrate our new inverse planning system with an existing needle tracking system.« less

Automated 3D trajectory measuring of large numbers of moving particles.

PubMed

Wu, Hai Shan; Zhao, Qi; Zou, Danping; Chen, Yan Qiu

2011-04-11

Complex dynamics of natural particle systems, such as insect swarms, bird flocks, fish schools, has attracted great attention of scientists for years. Measuring 3D trajectory of each individual in a group is vital for quantitative study of their dynamic properties, yet such empirical data is rare mainly due to the challenges of maintaining the identities of large numbers of individuals with similar visual features and frequent occlusions. We here present an automatic and efficient algorithm to track 3D motion trajectories of large numbers of moving particles using two video cameras. Our method solves this problem by formulating it as three linear assignment problems (LAP). For each video sequence, the first LAP obtains 2D tracks of moving targets and is able to maintain target identities in the presence of occlusions; the second one matches the visually similar targets across two views via a novel technique named maximum epipolar co-motion length (MECL), which is not only able to effectively reduce matching ambiguity but also further diminish the influence of frequent occlusions; the last one links 3D track segments into complete trajectories via computing a globally optimal assignment based on temporal and kinematic cues. Experiment results on simulated particle swarms with various particle densities validated the accuracy and robustness of the proposed method. As real-world case, our method successfully acquired 3D flight paths of fruit fly (Drosophila melanogaster) group comprising hundreds of freely flying individuals. © 2011 Optical Society of America

Measuring charged particle multiplicity with early ATLAS public data

NASA Astrophysics Data System (ADS)

Üstün, G.; Barut, E.; Bektaş, E.; Özcan, V. E.

2017-07-01

We study 100 images of early LHC collisions that were recorded by the ATLAS experiment and made public for outreach purposes, and extract the charged particle multiplicity as a function of momentum for proton-proton collisions at a centre-of-mass energy of 7 TeV. As these collisions have already been pre-processed by the ATLAS Collaboration, the particle tracks are visible, but are available to the public only in the form of low-resolution bitmaps. We describe two separate image processing methods, one based on the industry-standard OpenCV library and C++, another based on self-developed algorithms in Python. We present our analysis of the transverse momentum and azimuthal angle distributions of the particles, in agreement with the literature.

Detection of confinement and jumps in single-molecule membrane trajectories

NASA Astrophysics Data System (ADS)

Meilhac, N.; Le Guyader, L.; Salomé, L.; Destainville, N.

2006-01-01

We propose a variant of the algorithm by [R. Simson, E. D. Sheets, and K. Jacobson, Biophys. 69, 989 (1995)]. Their algorithm was developed to detect transient confinement zones in experimental single-particle tracking trajectories of diffusing membrane proteins or lipids. We show that our algorithm is able to detect confinement in a wider class of confining potential shapes than that of Simson Furthermore, it enables to detect not only temporary confinement but also jumps between confinement zones. Jumps are predicted by membrane skeleton fence and picket models. In the case of experimental trajectories of μ -opioid receptors, which belong to the family of G-protein-coupled receptors involved in a signal transduction pathway, this algorithm confirms that confinement cannot be explained solely by rigid fences.

Plugin-docking system for autonomous charging using particle filter

NASA Astrophysics Data System (ADS)

Koyasu, Hiroshi; Wada, Masayoshi

2017-03-01

Autonomous charging of the robot battery is one of the key functions for the sake of expanding working areas of the robots. To realize it, most of existing systems use custom docking stations or artificial markers. By the other words, they can only charge on a few specific outlets. If the limit can be removed, working areas of the robots significantly expands. In this paper, we describe a plugin-docking system for the autonomous charging, which does not require any custom docking stations or artificial markers. A single camera is used for recognizing the 3D position of an outlet socket. A particle filter-based image tracking algorithm which is robust to the illumination change is applied. The algorithm is implemented on a robot with an omnidirectional moving system. The experimental results show the effectiveness of our system.

A moment projection method for population balance dynamics with a shrinkage term

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, Shaohua; Yapp, Edward K.Y.; Akroyd, Jethro

A new method of moments for solving the population balance equation is developed and presented. The moment projection method (MPM) is numerically simple and easy to implement and attempts to address the challenge of particle shrinkage due to processes such as oxidation, evaporation or dissolution. It directly solves the moment transport equation for the moments and tracks the number of the smallest particles using the algorithm by Blumstein and Wheeler (1973) . The performance of the new method is measured against the method of moments (MOM) and the hybrid method of moments (HMOM). The results suggest that MPM performs muchmore » better than MOM and HMOM where shrinkage is dominant. The new method predicts mean quantities which are almost as accurate as a high-precision stochastic method calculated using the established direct simulation algorithm (DSA).« less

A Comparison of 3D3C Velocity Measurement Techniques

NASA Astrophysics Data System (ADS)

La Foy, Roderick; Vlachos, Pavlos

2013-11-01

The velocity measurement fidelity of several 3D3C PIV measurement techniques including tomographic PIV, synthetic aperture PIV, plenoptic PIV, defocusing PIV, and 3D PTV are compared in simulations. A physically realistic ray-tracing algorithm is used to generate synthetic images of a standard calibration grid and of illuminated particle fields advected by homogeneous isotropic turbulence. The simulated images for the tomographic, synthetic aperture, and plenoptic PIV cases are then used to create three-dimensional reconstructions upon which cross-correlations are performed to yield the measured velocity field. Particle tracking algorithms are applied to the images for the defocusing PIV and 3D PTV to directly yield the three-dimensional velocity field. In all cases the measured velocity fields are compared to one-another and to the true velocity field using several metrics.

TrackArt: the user friendly interface for single molecule tracking data analysis and simulation applied to complex diffusion in mica supported lipid bilayers.

PubMed

Matysik, Artur; Kraut, Rachel S

2014-05-01

Single molecule tracking (SMT) analysis of fluorescently tagged lipid and protein probes is an attractive alternative to ensemble averaged methods such as fluorescence correlation spectroscopy (FCS) or fluorescence recovery after photobleaching (FRAP) for measuring diffusion in artificial and plasma membranes. The meaningful estimation of diffusion coefficients and their errors is however not straightforward, and is heavily dependent on sample type, acquisition method, and equipment used. Many approaches require advanced computing and programming skills for their implementation. Here we present TrackArt software, an accessible graphic interface for simulation and complex analysis of multiple particle paths. Imported trajectories can be filtered to eliminate spurious or corrupted tracks, and are then analyzed using several previously described methodologies, to yield single or multiple diffusion coefficients, their population fractions, and estimated errors. We use TrackArt to analyze the single-molecule diffusion behavior of a sphingolipid analog SM-Atto647N, in mica supported DOPC (1,2-dioleoyl-sn-glycero-3-phosphocholine) bilayers. Fitting with a two-component diffusion model confirms the existence of two separate populations of diffusing particles in these bilayers on mica. As a demonstration of the TrackArt workflow, we characterize and discuss the effective activation energies required to increase the diffusion rates of these populations, obtained from Arrhenius plots of temperature-dependent diffusion. Finally, TrackArt provides a simulation module, allowing the user to generate models with multiple particle trajectories, diffusing with different characteristics. Maps of domains, acting as impermeable or permeable obstacles for particles diffusing with given rate constants and diffusion coefficients, can be simulated or imported from an image. Importantly, this allows one to use simulated data with a known diffusion behavior as a comparison for results acquired using particular algorithms on actual, "natural" samples whose diffusion behavior is to be extracted. It can also serve as a tool for demonstrating diffusion principles. TrackArt is an open source, platform-independent, Matlab-based graphical user interface, and is easy to use even for those unfamiliar with the Matlab programming environment. TrackArt can be used for accurate simulation and analysis of complex diffusion data, such as diffusion in lipid bilayers, providing publication-quality formatted results.

Proton radiography and fluoroscopy of lung tumors: A Monte Carlo study using patient-specific 4DCT phantoms

PubMed Central

Han, Bin; Xu, X. George; Chen, George T. Y.

2011-01-01

Purpose: Monte Carlo methods are used to simulate and optimize a time-resolved proton range telescope (TRRT) in localization of intrafractional and interfractional motions of lung tumor and in quantification of proton range variations. Methods: The Monte Carlo N-Particle eXtended (MCNPX) code with a particle tracking feature was employed to evaluate the TRRT performance, especially in visualizing and quantifying proton range variations during respiration. Protons of 230 MeV were tracked one by one as they pass through position detectors, patient 4DCT phantom, and finally scintillator detectors that measured residual ranges. The energy response of the scintillator telescope was investigated. Mass density and elemental composition of tissues were defined for 4DCT data. Results: Proton water equivalent length (WEL) was deduced by a reconstruction algorithm that incorporates linear proton track and lateral spatial discrimination to improve the image quality. 4DCT data for three patients were used to visualize and measure tumor motion and WEL variations. The tumor trajectories extracted from the WEL map were found to be within ∼1 mm agreement with direct 4DCT measurement. Quantitative WEL variation studies showed that the proton radiograph is a good representation of WEL changes from entrance to distal of the target. Conclusions:MCNPX simulation results showed that TRRT can accurately track the motion of the tumor and detect the WEL variations. Image quality was optimized by choosing proton energy, testing parameters of image reconstruction algorithm, and comparing to ground truth 4DCT. The future study will demonstrate the feasibility of using the time resolved proton radiography as an imaging tool for proton treatments of lung tumors. PMID:21626923

Application of Gauss's law space-charge limited emission model in iterative particle tracking method

NASA Astrophysics Data System (ADS)

Altsybeyev, V. V.; Ponomarev, V. A.

2016-11-01

The particle tracking method with a so-called gun iteration for modeling the space charge is discussed in the following paper. We suggest to apply the emission model based on the Gauss's law for the calculation of the space charge limited current density distribution using considered method. Based on the presented emission model we have developed a numerical algorithm for this calculations. This approach allows us to perform accurate and low time consumpting numerical simulations for different vacuum sources with the curved emitting surfaces and also in the presence of additional physical effects such as bipolar flows and backscattered electrons. The results of the simulations of the cylindrical diode and diode with elliptical emitter with the use of axysimmetric coordinates are presented. The high efficiency and accuracy of the suggested approach are confirmed by the obtained results and comparisons with the analytical solutions.

Global Linking of Cell Tracks Using the Viterbi Algorithm

PubMed Central

Jaldén, Joakim; Gilbert, Penney M.; Blau, Helen M.

2016-01-01

Automated tracking of living cells in microscopy image sequences is an important and challenging problem. With this application in mind, we propose a global track linking algorithm, which links cell outlines generated by a segmentation algorithm into tracks. The algorithm adds tracks to the image sequence one at a time, in a way which uses information from the complete image sequence in every linking decision. This is achieved by finding the tracks which give the largest possible increases to a probabilistically motivated scoring function, using the Viterbi algorithm. We also present a novel way to alter previously created tracks when new tracks are created, thus mitigating the effects of error propagation. The algorithm can handle mitosis, apoptosis, and migration in and out of the imaged area, and can also deal with false positives, missed detections, and clusters of jointly segmented cells. The algorithm performance is demonstrated on two challenging datasets acquired using bright-field microscopy, but in principle, the algorithm can be used with any cell type and any imaging technique, presuming there is a suitable segmentation algorithm. PMID:25415983

Adaptive block online learning target tracking based on super pixel segmentation

NASA Astrophysics Data System (ADS)

Cheng, Yue; Li, Jianzeng

2018-04-01

Video target tracking technology under the unremitting exploration of predecessors has made big progress, but there are still lots of problems not solved. This paper proposed a new algorithm of target tracking based on image segmentation technology. Firstly we divide the selected region using simple linear iterative clustering (SLIC) algorithm, after that, we block the area with the improved density-based spatial clustering of applications with noise (DBSCAN) clustering algorithm. Each sub-block independently trained classifier and tracked, then the algorithm ignore the failed tracking sub-block while reintegrate the rest of the sub-blocks into tracking box to complete the target tracking. The experimental results show that our algorithm can work effectively under occlusion interference, rotation change, scale change and many other problems in target tracking compared with the current mainstream algorithms.

Memory-Based Multiagent Coevolution Modeling for Robust Moving Object Tracking

PubMed Central

Wang, Yanjiang; Qi, Yujuan; Li, Yongping

2013-01-01

The three-stage human brain memory model is incorporated into a multiagent coevolutionary process for finding the best match of the appearance of an object, and a memory-based multiagent coevolution algorithm for robust tracking the moving objects is presented in this paper. Each agent can remember, retrieve, or forget the appearance of the object through its own memory system by its own experience. A number of such memory-based agents are randomly distributed nearby the located object region and then mapped onto a 2D lattice-like environment for predicting the new location of the object by their coevolutionary behaviors, such as competition, recombination, and migration. Experimental results show that the proposed method can deal with large appearance changes and heavy occlusions when tracking a moving object. It can locate the correct object after the appearance changed or the occlusion recovered and outperforms the traditional particle filter-based tracking methods. PMID:23843739

Memory-based multiagent coevolution modeling for robust moving object tracking.

PubMed

Wang, Yanjiang; Qi, Yujuan; Li, Yongping

2013-01-01

The three-stage human brain memory model is incorporated into a multiagent coevolutionary process for finding the best match of the appearance of an object, and a memory-based multiagent coevolution algorithm for robust tracking the moving objects is presented in this paper. Each agent can remember, retrieve, or forget the appearance of the object through its own memory system by its own experience. A number of such memory-based agents are randomly distributed nearby the located object region and then mapped onto a 2D lattice-like environment for predicting the new location of the object by their coevolutionary behaviors, such as competition, recombination, and migration. Experimental results show that the proposed method can deal with large appearance changes and heavy occlusions when tracking a moving object. It can locate the correct object after the appearance changed or the occlusion recovered and outperforms the traditional particle filter-based tracking methods.

Audio Tracking in Noisy Environments by Acoustic Map and Spectral Signature.

PubMed

Crocco, Marco; Martelli, Samuele; Trucco, Andrea; Zunino, Andrea; Murino, Vittorio

2018-05-01

A novel method is proposed for generic target tracking by audio measurements from a microphone array. To cope with noisy environments characterized by persistent and high energy interfering sources, a classification map (CM) based on spectral signatures is calculated by means of a machine learning algorithm. Next, the CM is combined with the acoustic map, describing the spatial distribution of sound energy, in order to obtain a cleaned joint map in which contributions from the disturbing sources are removed. A likelihood function is derived from this map and fed to a particle filter yielding the target location estimation on the acoustic image. The method is tested on two real environments, addressing both speaker and vehicle tracking. The comparison with a couple of trackers, relying on the acoustic map only, shows a sharp improvement in performance, paving the way to the application of audio tracking in real challenging environments.

Optimal Appearance Model for Visual Tracking

PubMed Central

Wang, Yuru; Jiang, Longkui; Liu, Qiaoyuan; Yin, Minghao

2016-01-01

Many studies argue that integrating multiple cues in an adaptive way increases tracking performance. However, what is the definition of adaptiveness and how to realize it remains an open issue. On the premise that the model with optimal discriminative ability is also optimal for tracking the target, this work realizes adaptiveness and robustness through the optimization of multi-cue integration models. Specifically, based on prior knowledge and current observation, a set of discrete samples are generated to approximate the foreground and background distribution. With the goal of optimizing the classification margin, an objective function is defined, and the appearance model is optimized by introducing optimization algorithms. The proposed optimized appearance model framework is embedded into a particle filter for a field test, and it is demonstrated to be robust against various kinds of complex tracking conditions. This model is general and can be easily extended to other parameterized multi-cue models. PMID:26789639

KiT: a MATLAB package for kinetochore tracking.

PubMed

Armond, Jonathan W; Vladimirou, Elina; McAinsh, Andrew D; Burroughs, Nigel J

2016-06-15

During mitosis, chromosomes are attached to the mitotic spindle via large protein complexes called kinetochores. The motion of kinetochores throughout mitosis is intricate and automated quantitative tracking of their motion has already revealed many surprising facets of their behaviour. Here, we present 'KiT' (Kinetochore Tracking)-an easy-to-use, open-source software package for tracking kinetochores from live-cell fluorescent movies. KiT supports 2D, 3D and multi-colour movies, quantification of fluorescence, integrated deconvolution, parallel execution and multiple algorithms for particle localization. KiT is free, open-source software implemented in MATLAB and runs on all MATLAB supported platforms. KiT can be downloaded as a package from http://www.mechanochemistry.org/mcainsh/software.php The source repository is available at https://bitbucket.org/jarmond/kit and under continuing development. Supplementary data are available at Bioinformatics online. jonathan.armond@warwick.ac.uk. © The Author 2016. Published by Oxford University Press.

Infrared measurement and composite tracking algorithm for air-breathing hypersonic vehicles

NASA Astrophysics Data System (ADS)

Zhang, Zhao; Gao, Changsheng; Jing, Wuxing

2018-03-01

Air-breathing hypersonic vehicles have capabilities of hypersonic speed and strong maneuvering, and thus pose a significant challenge to conventional tracking methodologies. To achieve desirable tracking performance for hypersonic targets, this paper investigates the problems related to measurement model design and tracking model mismatching. First, owing to the severe aerothermal effect of hypersonic motion, an infrared measurement model in near space is designed and analyzed based on target infrared radiation and an atmospheric model. Second, using information from infrared sensors, a composite tracking algorithm is proposed via a combination of the interactive multiple models (IMM) algorithm, fitting dynamics model, and strong tracking filter. During the procedure, the IMMs algorithm generates tracking data to establish a fitting dynamics model of the target. Then, the strong tracking unscented Kalman filter is employed to estimate the target states for suppressing the impact of target maneuvers. Simulations are performed to verify the feasibility of the presented composite tracking algorithm. The results demonstrate that the designed infrared measurement model effectively and continuously observes hypersonic vehicles, and the proposed composite tracking algorithm accurately and stably tracks these targets.

Interplanetary Dust Observations by the Juno MAG Investigation

NASA Astrophysics Data System (ADS)

Jørgensen, John; Benn, Mathias; Denver, Troelz; Connerney, Jack; Jørgensen, Peter; Bolton, Scott; Brauer, Peter; Levin, Steven; Oliversen, Ronald

2017-04-01

The spin-stabilized and solar powered Juno spacecraft recently concluded a 5-year voyage through the solar system en route to Jupiter, arriving on July 4th, 2016. During the cruise phase from Earth to the Jovian system, the Magnetometer investigation (MAG) operated two magnetic field sensors and four co-located imaging systems designed to provide accurate attitude knowledge for the MAG sensors. One of these four imaging sensors - camera "D" of the Advanced Stellar Compass (ASC) - was operated in a mode designed to detect all luminous objects in its field of view, recording and characterizing those not found in the on-board star catalog. The capability to detect and track such objects ("non-stellar objects", or NSOs) provides a unique opportunity to sense and characterize interplanetary dust particles. The camera's detection threshold was set to MV9 to minimize false detections and discourage tracking of known objects. On-board filtering algorithms selected only those objects tracked through more than 5 consecutive images and moving with an apparent angular rate between 15"/s and 10,000"/s. The coordinates (RA, DEC), intensity, and apparent velocity of such objects were stored for eventual downlink. Direct detection of proximate dust particles is precluded by their large (10-30 km/s) relative velocity and extreme angular rates, but their presence may be inferred using the collecting area of Juno's large ( 55m2) solar arrays. Dust particles impact the spacecraft at high velocity, creating an expanding plasma cloud and ejecta with modest (few m/s) velocities. These excavated particles are revealed in reflected sunlight and tracked moving away from the spacecraft from the point of impact. Application of this novel detection method during Juno's traversal of the solar system provides new information on the distribution of interplanetary (µm-sized) dust.

Applied estimation for hybrid dynamical systems using perceptional information

NASA Astrophysics Data System (ADS)

Plotnik, Aaron M.

This dissertation uses the motivating example of robotic tracking of mobile deep ocean animals to present innovations in robotic perception and estimation for hybrid dynamical systems. An approach to estimation for hybrid systems is presented that utilizes uncertain perceptional information about the system's mode to improve tracking of its mode and continuous states. This results in significant improvements in situations where previously reported methods of estimation for hybrid systems perform poorly due to poor distinguishability of the modes. The specific application that motivates this research is an automatic underwater robotic observation system that follows and films individual deep ocean animals. A first version of such a system has been developed jointly by the Stanford Aerospace Robotics Laboratory and Monterey Bay Aquarium Research Institute (MBARI). This robotic observation system is successfully fielded on MBARI's ROVs, but agile specimens often evade the system. When a human ROV pilot performs this task, one advantage that he has over the robotic observation system in these situations is the ability to use visual perceptional information about the target, immediately recognizing any changes in the specimen's behavior mode. With the approach of the human pilot in mind, a new version of the robotic observation system is proposed which is extended to (a) derive perceptional information (visual cues) about the behavior mode of the tracked specimen, and (b) merge this dissimilar, discrete and uncertain information with more traditional continuous noisy sensor data by extending existing algorithms for hybrid estimation. These performance enhancements are enabled by integrating techniques in hybrid estimation, computer vision and machine learning. First, real-time computer vision and classification algorithms extract a visual observation of the target's behavior mode. Existing hybrid estimation algorithms are extended to admit this uncertain but discrete observation, complementing the information available from more traditional sensors. State tracking is achieved using a new form of Rao-Blackwellized particle filter called the mode-observed Gaussian Particle Filter. Performance is demonstrated using data from simulation and data collected on actual specimens in the ocean. The framework for estimation using both traditional and perceptional information is easily extensible to other stochastic hybrid systems with mode-related perceptional observations available.

From Image Analysis to Computer Vision: Motives, Methods, and Milestones.

DTIC Science & Technology

1998-07-01

images. Initially, work on digital image analysis dealt with specific classes of images such as text, photomicrographs, nuclear particle tracks, and aerial...photographs; but by the 1960’s, general algorithms and paradigms for image analysis began to be formulated. When the artificial intelligence...scene, but eventually from image sequences obtained by a moving camera; at this stage, image analysis had become scene analysis or computer vision

Parallelized Kalman-Filter-Based Reconstruction of Particle Tracks on Many-Core Processors and GPUs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cerati, Giuseppe; Elmer, Peter; Krutelyov, Slava

2017-01-01

For over a decade now, physical and energy constraints have limited clock speed improvements in commodity microprocessors. Instead, chipmakers have been pushed into producing lower-power, multi-core processors such as Graphical Processing Units (GPU), ARM CPUs, and Intel MICs. Broad-based efforts from manufacturers and developers have been devoted to making these processors user-friendly enough to perform general computations. However, extracting performance from a larger number of cores, as well as specialized vector or SIMD units, requires special care in algorithm design and code optimization. One of the most computationally challenging problems in high-energy particle experiments is finding and fitting the charged-particlemore » tracks during event reconstruction. This is expected to become by far the dominant problem at the High-Luminosity Large Hadron Collider (HL-LHC), for example. Today the most common track finding methods are those based on the Kalman filter. Experience with Kalman techniques on real tracking detector systems has shown that they are robust and provide high physics performance. This is why they are currently in use at the LHC, both in the trigger and offine. Previously we reported on the significant parallel speedups that resulted from our investigations to adapt Kalman filters to track fitting and track building on Intel Xeon and Xeon Phi. Here, we discuss our progresses toward the understanding of these processors and the new developments to port the Kalman filter to NVIDIA GPUs.« less

Three dimensional δf simulations of beams in the SSC

NASA Astrophysics Data System (ADS)

Koga, J.; Tajima, T.; Machida, S.

1993-12-01

A three dimensional δf strong-strong algorithm has been developed to apply to the study of such effects as space charge and beam-beam interaction phenomena in the Superconducting Super Collider (SSC). The algorithm is obtained from the merging of the particle tracking code Simpsons used for 3 dimensional space charge effects and a δf code. The δf method is used to follow the evolution of the non-gaussian part of the beam distribution. The advantages of this method are twofold. First, the Simpsons code utilizes a realistic accelerator model including synchrotron oscillations and energy ramping in 6 dimensional phase space with electromagnetic fields of the beams calculated using a realistic 3 dimensional field solver. Second, the beams are evolving in the fully self-consistent strong-strong sense with finite particle fluctuation noise is greatly reduced as opposed to the weak-strong models where one beam is fixed.

Multiple feature fusion via covariance matrix for visual tracking

NASA Astrophysics Data System (ADS)

Jin, Zefenfen; Hou, Zhiqiang; Yu, Wangsheng; Wang, Xin; Sun, Hui

2018-04-01

Aiming at the problem of complicated dynamic scenes in visual target tracking, a multi-feature fusion tracking algorithm based on covariance matrix is proposed to improve the robustness of the tracking algorithm. In the frame-work of quantum genetic algorithm, this paper uses the region covariance descriptor to fuse the color, edge and texture features. It also uses a fast covariance intersection algorithm to update the model. The low dimension of region covariance descriptor, the fast convergence speed and strong global optimization ability of quantum genetic algorithm, and the fast computation of fast covariance intersection algorithm are used to improve the computational efficiency of fusion, matching, and updating process, so that the algorithm achieves a fast and effective multi-feature fusion tracking. The experiments prove that the proposed algorithm can not only achieve fast and robust tracking but also effectively handle interference of occlusion, rotation, deformation, motion blur and so on.

Tracking single particle rotation: Probing dynamics in four dimensions

DOE PAGES

Anthony, Stephen Michael; Yu, Yan

2015-04-29

Direct visualization and tracking of small particles at high spatial and temporal resolution provides a powerful approach to probing complex dynamics and interactions in chemical and biological processes. Analysis of the rotational dynamics of particles adds a new dimension of information that is otherwise impossible to obtain with conventional 3-D particle tracking. In this review, we survey recent advances in single-particle rotational tracking, with highlights on the rotational tracking of optically anisotropic Janus particles. Furthermore, strengths and weaknesses of the various particle tracking methods, and their applications are discussed.

Dynamic discrete tomography

NASA Astrophysics Data System (ADS)

Alpers, Andreas; Gritzmann, Peter

2018-03-01

We consider the problem of reconstructing the paths of a set of points over time, where, at each of a finite set of moments in time the current positions of points in space are only accessible through some small number of their x-rays. This particular particle tracking problem, with applications, e.g. in plasma physics, is the basic problem in dynamic discrete tomography. We introduce and analyze various different algorithmic models. In particular, we determine the computational complexity of the problem (and various of its relatives) and derive algorithms that can be used in practice. As a byproduct we provide new results on constrained variants of min-cost flow and matching problems.

Phase retrieval and 3D imaging in gold nanoparticles based fluorescence microscopy (Conference Presentation)

NASA Astrophysics Data System (ADS)

Ilovitsh, Tali; Ilovitsh, Asaf; Weiss, Aryeh M.; Meir, Rinat; Zalevsky, Zeev

2017-02-01

Optical sectioning microscopy can provide highly detailed three dimensional (3D) images of biological samples. However, it requires acquisition of many images per volume, and is therefore time consuming, and may not be suitable for live cell 3D imaging. We propose the use of the modified Gerchberg-Saxton phase retrieval algorithm to enable full 3D imaging of gold nanoparticles tagged sample using only two images. The reconstructed field is free space propagated to all other focus planes using post processing, and the 2D z-stack is merged to create a 3D image of the sample with high fidelity. Because we propose to apply the phase retrieving on nano particles, the regular ambiguities typical to the Gerchberg-Saxton algorithm, are eliminated. The proposed concept is then further enhanced also for tracking of single fluorescent particles within a three dimensional (3D) cellular environment based on image processing algorithms that can significantly increases localization accuracy of the 3D point spread function in respect to regular Gaussian fitting. All proposed concepts are validated both on simulated data as well as experimentally.

Seismic noise attenuation using an online subspace tracking algorithm

NASA Astrophysics Data System (ADS)

Zhou, Yatong; Li, Shuhua; Zhang, Dong; Chen, Yangkang

2018-02-01

We propose a new low-rank based noise attenuation method using an efficient algorithm for tracking subspaces from highly corrupted seismic observations. The subspace tracking algorithm requires only basic linear algebraic manipulations. The algorithm is derived by analysing incremental gradient descent on the Grassmannian manifold of subspaces. When the multidimensional seismic data are mapped to a low-rank space, the subspace tracking algorithm can be directly applied to the input low-rank matrix to estimate the useful signals. Since the subspace tracking algorithm is an online algorithm, it is more robust to random noise than traditional truncated singular value decomposition (TSVD) based subspace tracking algorithm. Compared with the state-of-the-art algorithms, the proposed denoising method can obtain better performance. More specifically, the proposed method outperforms the TSVD-based singular spectrum analysis method in causing less residual noise and also in saving half of the computational cost. Several synthetic and field data examples with different levels of complexities demonstrate the effectiveness and robustness of the presented algorithm in rejecting different types of noise including random noise, spiky noise, blending noise, and coherent noise.

Infrared small target tracking based on SOPC

NASA Astrophysics Data System (ADS)

Hu, Taotao; Fan, Xiang; Zhang, Yu-Jin; Cheng, Zheng-dong; Zhu, Bin

2011-01-01

The paper presents a low cost FPGA based solution for a real-time infrared small target tracking system. A specialized architecture is presented based on a soft RISC processor capable of running kernel based mean shift tracking algorithm. Mean shift tracking algorithm is realized in NIOS II soft-core with SOPC (System on a Programmable Chip) technology. Though mean shift algorithm is widely used for target tracking, the original mean shift algorithm can not be directly used for infrared small target tracking. As infrared small target only has intensity information, so an improved mean shift algorithm is presented in this paper. How to describe target will determine whether target can be tracked by mean shift algorithm. Because color target can be tracked well by mean shift algorithm, imitating color image expression, spatial component and temporal component are advanced to describe target, which forms pseudo-color image. In order to improve the processing speed parallel technology and pipeline technology are taken. Two RAM are taken to stored images separately by ping-pong technology. A FLASH is used to store mass temp data. The experimental results show that infrared small target is tracked stably in complicated background.

On the Impact of Localization and Density Control Algorithms in Target Tracking Applications for Wireless Sensor Networks

PubMed Central

Campos, Andre N.; Souza, Efren L.; Nakamura, Fabiola G.; Nakamura, Eduardo F.; Rodrigues, Joel J. P. C.

2012-01-01

Target tracking is an important application of wireless sensor networks. The networks' ability to locate and track an object is directed linked to the nodes' ability to locate themselves. Consequently, localization systems are essential for target tracking applications. In addition, sensor networks are often deployed in remote or hostile environments. Therefore, density control algorithms are used to increase network lifetime while maintaining its sensing capabilities. In this work, we analyze the impact of localization algorithms (RPE and DPE) and density control algorithms (GAF, A3 and OGDC) on target tracking applications. We adapt the density control algorithms to address the k-coverage problem. In addition, we analyze the impact of network density, residual integration with density control, and k-coverage on both target tracking accuracy and network lifetime. Our results show that DPE is a better choice for target tracking applications than RPE. Moreover, among the evaluated density control algorithms, OGDC is the best option among the three. Although the choice of the density control algorithm has little impact on the tracking precision, OGDC outperforms GAF and A3 in terms of tracking time. PMID:22969329

Research on infrared small-target tracking technology under complex background

NASA Astrophysics Data System (ADS)

Liu, Lei; Wang, Xin; Chen, Jilu; Pan, Tao

2012-10-01

In this paper, some basic principles and the implementing flow charts of a series of algorithms for target tracking are described. On the foundation of above works, a moving target tracking software base on the OpenCV is developed by the software developing platform MFC. Three kinds of tracking algorithms are integrated in this software. These two tracking algorithms are Kalman Filter tracking method and Camshift tracking method. In order to explain the software clearly, the framework and the function are described in this paper. At last, the implementing processes and results are analyzed, and those algorithms for tracking targets are evaluated from the two aspects of subjective and objective. This paper is very significant in the application of the infrared target tracking technology.

Simulation of ultra-high energy photon propagation with PRESHOWER 2.0

NASA Astrophysics Data System (ADS)

Homola, P.; Engel, R.; Pysz, A.; Wilczyński, H.

2013-05-01

In this paper we describe a new release of the PRESHOWER program, a tool for Monte Carlo simulation of propagation of ultra-high energy photons in the magnetic field of the Earth. The PRESHOWER program is designed to calculate magnetic pair production and bremsstrahlung and should be used together with other programs to simulate extensive air showers induced by photons. The main new features of the PRESHOWER code include a much faster algorithm applied in the procedures of simulating the processes of gamma conversion and bremsstrahlung, update of the geomagnetic field model, and a minor correction. The new simulation procedure increases the flexibility of the code so that it can also be applied to other magnetic field configurations such as, for example, encountered in the vicinity of the sun or neutron stars. Program summaryProgram title: PRESHOWER 2.0 Catalog identifier: ADWG_v2_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADWG_v2_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 3968 No. of bytes in distributed program, including test data, etc.: 37198 Distribution format: tar.gz Programming language: C, FORTRAN 77. Computer: Intel-Pentium based PC. Operating system: Linux or Unix. RAM:< 100 kB Classification: 1.1. Does the new version supercede the previous version?: Yes Catalog identifier of previous version: ADWG_v1_0 Journal reference of previous version: Comput. Phys. Comm. 173 (2005) 71 Nature of problem: Simulation of a cascade of particles initiated by UHE photon in magnetic field. Solution method: The primary photon is tracked until its conversion into an e+ e- pair. If conversion occurs each individual particle in the resultant preshower is checked for either bremsstrahlung radiation (electrons) or secondary gamma conversion (photons). Reasons for new version: Slow and outdated algorithm in the old version (a significant speed up is possible); Extension of the program to allow simulations also for extraterrestrial magnetic field configurations (e.g. neutron stars) and very long path lengths. Summary of revisions: A veto algorithm was introduced in the gamma conversion and bremsstrahlung tracking procedures. The length of the tracking step is now variable along the track and depends on the probability of the process expected to occur. The new algorithm reduces significantly the number of tracking steps and speeds up the execution of the program. The geomagnetic field model has been updated to IGRF-11, allowing for interpolations up to the year 2015. Numerical Recipes procedures to calculate modified Bessel functions have been replaced with an open source CERN routine DBSKA. One minor bug has been fixed. Restrictions: Gamma conversion into particles other than an electron pair is not considered. Spatial structure of the cascade is neglected. Additional comments: The following routines are supplied in the package, IGRF [1, 2], DBSKA [3], ran2 [4] Running time: 100 preshower events with primary energy 1020 eV require a 2.66 GHz CPU time of about 200 sec.; at the energy of 1021 eV, 600 sec.

Real-time measurements of radon activity with the Timepix-based RADONLITE and RADONPIX detectors

NASA Astrophysics Data System (ADS)

Caresana, M.; Garlati, L.; Murtas, F.; Romano, S.; Severino, C. T.; Silari, M.

2014-11-01

Radon gas is the most important source of ionizing radiation among those of natural origin. Two new systems for radon measurement based on the Timepix silicon detector were developed. The positively charged radon daughters are electrostatically collected on the surface of the Si detector and their energy spectrum measured. Pattern recognition of the tracks on the sensor and particle identification are used to determine number and energy of the alpha particles and to subtract the background, allowing for efficient radon detection. The systems include an algorithm for real-time measurement of the radon concentration and the calculation of the effective dose to the lungs.

Real-time calibration and alignment of the LHCb RICH detectors

NASA Astrophysics Data System (ADS)

HE, Jibo

2017-12-01

In 2015, the LHCb experiment established a new and unique software trigger strategy with the purpose of increasing the purity of the signal events by applying the same algorithms online and offline. To achieve this, real-time calibration and alignment of all LHCb sub-systems is needed to provide vertexing, tracking, and particle identification of the best possible quality. The calibration of the refractive index of the RICH radiators, the calibration of the Hybrid Photon Detector image, and the alignment of the RICH mirror system, are reported in this contribution. The stability of the RICH performance and the particle identification performance are also discussed.

Improving Memory for Optimization and Learning in Dynamic Environments

DTIC Science & Technology

2011-07-01

algorithm uses simple, in- cremental clustering to separate solutions into memory entries. The cluster centers are used as the models in the memory. This is...entire days of traffic with realistic traffic de - mands and turning ratios on a 32 intersection network modeled on downtown Pittsburgh, Pennsyl- vania...early/tardy problem. Management Science, 35(2):177–191, 1989. [78] Daniel Parrott and Xiaodong Li. A particle swarm model for tracking multiple peaks in

Radar Detection of Marine Mammals

DTIC Science & Technology

2011-09-30

BFT-BPT algorithm for use with our radar data. This track - before - detect algorithm had been effective in enhancing small but persistent signatures in...will be possible with the detect before track algorithm. 4 We next evaluated the track before detect algorithm, the BFT-BPT, on the CEDAR data

First Results of an “Artificial Retina” Processor Prototype

DOE PAGES

Cenci, Riccardo; Bedeschi, Franco; Marino, Pietro; ...

2016-11-15

We report on the performance of a specialized processor capable of reconstructing charged particle tracks in a realistic LHC silicon tracker detector, at the same speed of the readout and with sub-microsecond latency. The processor is based on an innovative pattern-recognition algorithm, called “artificial retina algorithm”, inspired from the vision system of mammals. A prototype of the processor has been designed, simulated, and implemented on Tel62 boards equipped with high-bandwidth Altera Stratix III FPGA devices. Also, the prototype is the first step towards a real-time track reconstruction device aimed at processing complex events of high-luminosity LHC experiments at 40 MHzmore » crossing rate.« less

Radar for tracer particles

NASA Astrophysics Data System (ADS)

Ott, Felix; Herminghaus, Stephan; Huang, Kai

2017-05-01

We introduce a radar system capable of tracking a 5 mm spherical target continuously in three dimensions. The 10 GHz (X-band) radar system has a transmission power of 1 W and operates in the near field of the horn antennae. By comparing the phase shift of the electromagnetic wave traveling through the free space with an IQ-mixer, we obtain the relative movement of the target with respect to the antennae. From the azimuth and inclination angles of the receiving antennae obtained in the calibration, we reconstruct the target trajectory in a three-dimensional Cartesian system. Finally, we test the tracking algorithm with target moving in circular as well as in pendulum motions and discuss the capability of the radar system.

First Results of an “Artificial Retina” Processor Prototype

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cenci, Riccardo; Bedeschi, Franco; Marino, Pietro

We report on the performance of a specialized processor capable of reconstructing charged particle tracks in a realistic LHC silicon tracker detector, at the same speed of the readout and with sub-microsecond latency. The processor is based on an innovative pattern-recognition algorithm, called “artificial retina algorithm”, inspired from the vision system of mammals. A prototype of the processor has been designed, simulated, and implemented on Tel62 boards equipped with high-bandwidth Altera Stratix III FPGA devices. Also, the prototype is the first step towards a real-time track reconstruction device aimed at processing complex events of high-luminosity LHC experiments at 40 MHzmore » crossing rate.« less

A versatile pitch tracking algorithm: from human speech to killer whale vocalizations.

PubMed

Shapiro, Ari Daniel; Wang, Chao

2009-07-01

In this article, a pitch tracking algorithm [named discrete logarithmic Fourier transformation-pitch detection algorithm (DLFT-PDA)], originally designed for human telephone speech, was modified for killer whale vocalizations. The multiple frequency components of some of these vocalizations demand a spectral (rather than temporal) approach to pitch tracking. The DLFT-PDA algorithm derives reliable estimations of pitch and the temporal change of pitch from the harmonic structure of the vocal signal. Scores from both estimations are combined in a dynamic programming search to find a smooth pitch track. The algorithm is capable of tracking killer whale calls that contain simultaneous low and high frequency components and compares favorably across most signal to noise ratio ranges to the peak-picking and sidewinder algorithms that have been used for tracking killer whale vocalizations previously.

Novel joint TOA/RSSI-based WCE location tracking method without prior knowledge of biological human body tissues.

PubMed

Ito, Takahiro; Anzai, Daisuke; Jianqing Wang

2014-01-01

This paper proposes a novel joint time of arrival (TOA)/received signal strength indicator (RSSI)-based wireless capsule endoscope (WCE) location tracking method without prior knowledge of biological human tissues. Generally, TOA-based localization can achieve much higher localization accuracy than other radio frequency-based localization techniques, whereas wireless signals transmitted from a WCE pass through various kinds of human body tissues, as a result, the propagation velocity inside a human body should be different from one in free space. Because the variation of propagation velocity is mainly affected by the relative permittivity of human body tissues, instead of pre-measurement for the relative permittivity in advance, we simultaneously estimate not only the WCE location but also the relative permittivity information. For this purpose, this paper first derives the relative permittivity estimation model with measured RSSI information. Then, we pay attention to a particle filter algorithm with the TOA-based localization and the RSSI-based relative permittivity estimation. Our computer simulation results demonstrates that the proposed tracking methods with the particle filter can accomplish an excellent localization accuracy of around 2 mm without prior information of the relative permittivity of the human body tissues.

Multi-Complementary Model for Long-Term Tracking

PubMed Central

Zhang, Deng; Zhang, Junchang; Xia, Chenyang

2018-01-01

In recent years, video target tracking algorithms have been widely used. However, many tracking algorithms do not achieve satisfactory performance, especially when dealing with problems such as object occlusions, background clutters, motion blur, low illumination color images, and sudden illumination changes in real scenes. In this paper, we incorporate an object model based on contour information into a Staple tracker that combines the correlation filter model and color model to greatly improve the tracking robustness. Since each model is responsible for tracking specific features, the three complementary models combine for more robust tracking. In addition, we propose an efficient object detection model with contour and color histogram features, which has good detection performance and better detection efficiency compared to the traditional target detection algorithm. Finally, we optimize the traditional scale calculation, which greatly improves the tracking execution speed. We evaluate our tracker on the Object Tracking Benchmarks 2013 (OTB-13) and Object Tracking Benchmarks 2015 (OTB-15) benchmark datasets. With the OTB-13 benchmark datasets, our algorithm is improved by 4.8%, 9.6%, and 10.9% on the success plots of OPE, TRE and SRE, respectively, in contrast to another classic LCT (Long-term Correlation Tracking) algorithm. On the OTB-15 benchmark datasets, when compared with the LCT algorithm, our algorithm achieves 10.4%, 12.5%, and 16.1% improvement on the success plots of OPE, TRE, and SRE, respectively. At the same time, it needs to be emphasized that, due to the high computational efficiency of the color model and the object detection model using efficient data structures, and the speed advantage of the correlation filters, our tracking algorithm could still achieve good tracking speed. PMID:29425170

Research on polarization imaging information parsing method

NASA Astrophysics Data System (ADS)

Yuan, Hongwu; Zhou, Pucheng; Wang, Xiaolong

2016-11-01

Polarization information parsing plays an important role in polarization imaging detection. This paper focus on the polarization information parsing method: Firstly, the general process of polarization information parsing is given, mainly including polarization image preprocessing, multiple polarization parameters calculation, polarization image fusion and polarization image tracking, etc.; And then the research achievements of the polarization information parsing method are presented, in terms of polarization image preprocessing, the polarization image registration method based on the maximum mutual information is designed. The experiment shows that this method can improve the precision of registration and be satisfied the need of polarization information parsing; In terms of multiple polarization parameters calculation, based on the omnidirectional polarization inversion model is built, a variety of polarization parameter images are obtained and the precision of inversion is to be improve obviously; In terms of polarization image fusion , using fuzzy integral and sparse representation, the multiple polarization parameters adaptive optimal fusion method is given, and the targets detection in complex scene is completed by using the clustering image segmentation algorithm based on fractal characters; In polarization image tracking, the average displacement polarization image characteristics of auxiliary particle filtering fusion tracking algorithm is put forward to achieve the smooth tracking of moving targets. Finally, the polarization information parsing method is applied to the polarization imaging detection of typical targets such as the camouflage target, the fog and latent fingerprints.

SU-G-JeP1-12: Head-To-Head Performance Characterization of Two Multileaf Collimator Tracking Algorithms for Radiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Caillet, V; Colvill, E; Royal North Shore Hospital, St Leonards, Sydney

2016-06-15

Purpose: Multi-leaf collimator (MLC) tracking is being clinically pioneered to continuously compensate for thoracic and abdominal motion during radiotherapy. The purpose of this work is to characterize the performance of two MLC tracking algorithms for cancer radiotherapy, based on a direct optimization and a piecewise leaf fitting approach respectively. Methods: To test the algorithms, both physical and in silico experiments were performed. Previously published high and low modulation VMAT plans for lung and prostate cancer cases were used along with eight patient-measured organ-specific trajectories. For both MLC tracking algorithm, the plans were run with their corresponding patient trajectories. The physicalmore » experiments were performed on a Trilogy Varian linac and a programmable phantom (HexaMotion platform). For each MLC tracking algorithm, plan and patient trajectory, the tracking accuracy was quantified as the difference in aperture area between ideal and fitted MLC. To compare algorithms, the average cumulative tracking error area for each experiment was calculated. The two-sample Kolmogorov-Smirnov (KS) test was used to evaluate the cumulative tracking errors between algorithms. Results: Comparison of tracking errors for the physical and in silico experiments showed minor differences between the two algorithms. The KS D-statistics for the physical experiments were below 0.05 denoting no significant differences between the two distributions pattern and the average error area (direct optimization/piecewise leaf-fitting) were comparable (66.64 cm2/65.65 cm2). For the in silico experiments, the KS D-statistics were below 0.05 and the average errors area were also equivalent (49.38 cm2/48.98 cm2). Conclusion: The comparison between the two leaf fittings algorithms demonstrated no significant differences in tracking errors, neither in a clinically realistic environment nor in silico. The similarities in the two independent algorithms give confidence in the use of either algorithm for clinical implementation.« less

FPGA Online Tracking Algorithm for the PANDA Straw Tube Tracker

NASA Astrophysics Data System (ADS)

Liang, Yutie; Ye, Hua; Galuska, Martin J.; Gessler, Thomas; Kuhn, Wolfgang; Lange, Jens Soren; Wagner, Milan N.; Liu, Zhen'an; Zhao, Jingzhou

2017-06-01

A novel FPGA based online tracking algorithm for helix track reconstruction in a solenoidal field, developed for the PANDA spectrometer, is described. Employing the Straw Tube Tracker detector with 4636 straw tubes, the algorithm includes a complex track finder, and a track fitter. Implemented in VHDL, the algorithm is tested on a Xilinx Virtex-4 FX60 FPGA chip with different types of events, at different event rates. A processing time of 7 $\\mu$s per event for an average of 6 charged tracks is obtained. The momentum resolution is about 3\\% (4\\%) for $p_t$ ($p_z$) at 1 GeV/c. Comparing to the algorithm running on a CPU chip (single core Intel Xeon E5520 at 2.26 GHz), an improvement of 3 orders of magnitude in processing time is obtained. The algorithm can handle severe overlapping of events which are typical for interaction rates above 10 MHz.

An experimental comparison of online object-tracking algorithms

NASA Astrophysics Data System (ADS)

Wang, Qing; Chen, Feng; Xu, Wenli; Yang, Ming-Hsuan

2011-09-01

This paper reviews and evaluates several state-of-the-art online object tracking algorithms. Notwithstanding decades of efforts, object tracking remains a challenging problem due to factors such as illumination, pose, scale, deformation, motion blur, noise, and occlusion. To account for appearance change, most recent tracking algorithms focus on robust object representations and effective state prediction. In this paper, we analyze the components of each tracking method and identify their key roles in dealing with specific challenges, thereby shedding light on how to choose and design algorithms for different situations. We compare state-of-the-art online tracking methods including the IVT,1 VRT,2 FragT,3 BoostT,4 SemiT,5 BeSemiT,6 L1T,7 MILT,8 VTD9 and TLD10 algorithms on numerous challenging sequences, and evaluate them with different performance metrics. The qualitative and quantitative comparative results demonstrate the strength and weakness of these algorithms.

Multi-Target State Extraction for the SMC-PHD Filter

PubMed Central

Si, Weijian; Wang, Liwei; Qu, Zhiyu

2016-01-01

The sequential Monte Carlo probability hypothesis density (SMC-PHD) filter has been demonstrated to be a favorable method for multi-target tracking. However, the time-varying target states need to be extracted from the particle approximation of the posterior PHD, which is difficult to implement due to the unknown relations between the large amount of particles and the PHD peaks representing potential target locations. To address this problem, a novel multi-target state extraction algorithm is proposed in this paper. By exploiting the information of measurements and particle likelihoods in the filtering stage, we propose a validation mechanism which aims at selecting effective measurements and particles corresponding to detected targets. Subsequently, the state estimates of the detected and undetected targets are performed separately: the former are obtained from the particle clusters directed by effective measurements, while the latter are obtained from the particles corresponding to undetected targets via clustering method. Simulation results demonstrate that the proposed method yields better estimation accuracy and reliability compared to existing methods. PMID:27322274

Experimental Studies of the Brownian Diffusion of Boomerang Colloidal Particle in a Confined Geometry

NASA Astrophysics Data System (ADS)

Chakrabarty, Ayan; Wang, Feng; Joshi, Bhuwan; Wei, Qi-Huo

2011-03-01

Recent studies shows that the boomerang shaped molecules can form various kinds of liquid crystalline phases. One debated topic related to boomerang molecules is the existence of biaxial nematic liquid crystalline phase. Developing and optical microscopic studies of colloidal systems of boomerang particles would allow us to gain better understanding of orientation ordering and dynamics at ``single molecule'' level. Here we report the fabrication and experimental studies of the Brownian motion of individual boomerang colloidal particles confined between two glass plates. We used dark-field optical microscopy to directly visualize the Brownian motion of the single colloidal particles in a quasi two dimensional geometry. An EMCCD was used to capture the motion in real time. An indigenously developed imaging processing algorithm based on MatLab program was used to precisely track the position and orientation of the particles with sub-pixel accuracy. The experimental finding of the Brownian diffusion of a single boomerang colloidal particle will be discussed.

Uncertainty in simulated groundwater-quality trends in transient flow

USGS Publications Warehouse

Starn, J. Jeffrey; Bagtzoglou, Amvrossios; Robbins, Gary A.

2013-01-01

In numerical modeling of groundwater flow, the result of a given solution method is affected by the way in which transient flow conditions and geologic heterogeneity are simulated. An algorithm is demonstrated that simulates breakthrough curves at a pumping well by convolution-based particle tracking in a transient flow field for several synthetic basin-scale aquifers. In comparison to grid-based (Eulerian) methods, the particle (Lagrangian) method is better able to capture multimodal breakthrough caused by changes in pumping at the well, although the particle method may be apparently nonlinear because of the discrete nature of particle arrival times. Trial-and-error choice of number of particles and release times can perhaps overcome the apparent nonlinearity. Heterogeneous aquifer properties tend to smooth the effects of transient pumping, making it difficult to separate their effects in parameter estimation. Porosity, a new parameter added for advective transport, can be accurately estimated using both grid-based and particle-based methods, but predictions can be highly uncertain, even in the simple, nonreactive case.

Nondestructive 3D confocal laser imaging with deconvolution of seven whole stardust tracks with complementary XRF and quantitative analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Greenberg, M.; Ebel, D.S.

2009-03-19

We present a nondestructive 3D system for analysis of whole Stardust tracks, using a combination of Laser Confocal Scanning Microscopy and synchrotron XRF. 3D deconvolution is used for optical corrections, and results of quantitative analyses of several tracks are presented. The Stardust mission to comet Wild 2 trapped many cometary and ISM particles in aerogel, leaving behind 'tracks' of melted silica aerogel on both sides of the collector. Collected particles and their tracks range in size from submicron to millimeter scale. Interstellar dust collected on the obverse of the aerogel collector is thought to have an average track length ofmore » {approx}15 {micro}m. It has been our goal to perform a total non-destructive 3D textural and XRF chemical analysis on both types of tracks. To that end, we use a combination of Laser Confocal Scanning Microscopy (LCSM) and X Ray Florescence (XRF) spectrometry. Utilized properly, the combination of 3D optical data and chemical data provides total nondestructive characterization of full tracks, prior to flattening or other destructive analysis methods. Our LCSM techniques allow imaging at 0.075 {micro}m/pixel, without the use of oil-based lenses. A full textural analysis on track No.82 is presented here as well as analysis of 6 additional tracks contained within 3 keystones (No.128, No.129 and No.140). We present a method of removing the axial distortion inherent in LCSM images, by means of a computational 3D Deconvolution algorithm, and present some preliminary experiments with computed point spread functions. The combination of 3D LCSM data and XRF data provides invaluable information, while preserving the integrity of the samples for further analysis. It is imperative that these samples, the first extraterrestrial solids returned since the Apollo era, be fully mapped nondestructively in 3D, to preserve the maximum amount of information prior to other, destructive analysis.« less

Multiple objects tracking with HOGs matching in circular windows

NASA Astrophysics Data System (ADS)

Miramontes-Jaramillo, Daniel; Kober, Vitaly; Díaz-Ramírez, Víctor H.

2014-09-01

In recent years tracking applications with development of new technologies like smart TVs, Kinect, Google Glass and Oculus Rift become very important. When tracking uses a matching algorithm, a good prediction algorithm is required to reduce the search area for each object to be tracked as well as processing time. In this work, we analyze the performance of different tracking algorithms based on prediction and matching for a real-time tracking multiple objects. The used matching algorithm utilizes histograms of oriented gradients. It carries out matching in circular windows, and possesses rotation invariance and tolerance to viewpoint and scale changes. The proposed algorithm is implemented in a personal computer with GPU, and its performance is analyzed in terms of processing time in real scenarios. Such implementation takes advantage of current technologies and helps to process video sequences in real-time for tracking several objects at the same time.

GPU/MIC Acceleration of the LHC High Level Trigger to Extend the Physics Reach at the LHC

DOE Office of Scientific and Technical Information (OSTI.GOV)

Halyo, Valerie; Tully, Christopher

The quest for rare new physics phenomena leads the PI [3] to propose evaluation of coprocessors based on Graphics Processing Units (GPUs) and the Intel Many Integrated Core (MIC) architecture for integration into the trigger system at LHC. This will require development of a new massively parallel implementation of the well known Combinatorial Track Finder which uses the Kalman Filter to accelerate processing of data from the silicon pixel and microstrip detectors and reconstruct the trajectory of all charged particles down to momentums of 100 MeV. It is expected to run at least one order of magnitude faster than anmore » equivalent algorithm on a quad core CPU for extreme pileup scenarios of 100 interactions per bunch crossing. The new tracking algorithms will be developed and optimized separately on the GPU and Intel MIC and then evaluated against each other for performance and power efficiency. The results will be used to project the cost of the proposed hardware architectures for the HLT server farm, taking into account the long term projections of the main vendors in the market (AMD, Intel, and NVIDIA) over the next 10 years. Extensive experience and familiarity of the PI with the LHC tracker and trigger requirements led to the development of a complementary tracking algorithm that is described in [arxiv: 1305.4855], [arxiv: 1309.6275] and preliminary results accepted to JINST.« less

Continuous Firefly Algorithm for Optimal Tuning of Pid Controller in Avr System

NASA Astrophysics Data System (ADS)

Bendjeghaba, Omar

2014-01-01

This paper presents a tuning approach based on Continuous firefly algorithm (CFA) to obtain the proportional-integral- derivative (PID) controller parameters in Automatic Voltage Regulator system (AVR). In the tuning processes the CFA is iterated to reach the optimal or the near optimal of PID controller parameters when the main goal is to improve the AVR step response characteristics. Conducted simulations show the effectiveness and the efficiency of the proposed approach. Furthermore the proposed approach can improve the dynamic of the AVR system. Compared with particle swarm optimization (PSO), the new CFA tuning method has better control system performance in terms of time domain specifications and set-point tracking.

Object-oriented feature-tracking algorithms for SAR images of the marginal ice zone

NASA Technical Reports Server (NTRS)

Daida, Jason; Samadani, Ramin; Vesecky, John F.

1990-01-01

An unsupervised method that chooses and applies the most appropriate tracking algorithm from among different sea-ice tracking algorithms is reported. In contrast to current unsupervised methods, this method chooses and applies an algorithm by partially examining a sequential image pair to draw inferences about what was examined. Based on these inferences the reported method subsequently chooses which algorithm to apply to specific areas of the image pair where that algorithm should work best.

Application of optical correlation techniques to particle imaging velocimetry

NASA Technical Reports Server (NTRS)

Wernet, Mark P.; Edwards, Robert V.

1988-01-01

Pulsed laser sheet velocimetry yields nonintrusive measurements of velocity vectors across an extended 2-dimensional region of the flow field. The application of optical correlation techniques to the analysis of multiple exposure laser light sheet photographs can reduce and/or simplify the data reduction time and hardware. Here, Matched Spatial Filters (MSF) are used in a pattern recognition system. Usually MSFs are used to identify the assembly line parts. In this application, the MSFs are used to identify the iso-velocity vector contours in the flow. The patterns to be recognized are the recorded particle images in a pulsed laser light sheet photograph. Measurement of the direction of the partical image displacements between exposures yields the velocity vector. The particle image exposure sequence is designed such that the velocity vector direction is determined unambiguously. A global analysis technique is used in comparison to the more common particle tracking algorithms and Young's fringe analysis technique.

Final Technical Report for ``Paths to Discovery at the LHC : Dark Matter and Track Triggering"

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hahn, Kristian

Particle Dark Matter (DM) is perhaps the most compelling and experimentally well-motivated new physics scenario anticipated at the Large Hadron Collider (LHC). The DE-SC0014073 award allowed the PI to define and pursue a path to the discovery of Dark Matter in Run-2 of the LHC with the Compact Muon Solenoid (CMS) experiment. CMS can probe regions of Dark Matter phase-space that direct and indirect detection experiments are unable to constrain. The PI’s team initiated the exploration of these regions, searching specifically for the associated production of Dark Matter with top quarks. The effort focuses on the high-yield, hadronic decays ofmore » W bosons produced in top decay, which provides the highest sensitivity to DM produced via through low-mass spin-0 mediators. The group developed identification algorithms that achieve high efficiency and purity in the selection of hadronic top decays, and analysis techniques that provide powerful signal discrimination in Run-2. The ultimate reach of new physics searches with CMS will be established at the high-luminosity LHC (HL-LHC). To fully realize the sensitivity the HL-LHC promises, CMS must minimize the impact of soft, inelastic (“pileup”) interactions on the real-time “trigger” system the experiment uses for data refinement. Charged particle trajectory information (“tracking”) will be essential for pileup mitigation at the HL-LHC. The award allowed the PI’s team to develop firmware-based data delivery and track fitting algorithms for an unprecedented, real-time tracking trigger to sustain the experiment’s sensitivity to new physics in the next decade.« less

An autoregressive model-based particle filtering algorithms for extraction of respiratory rates as high as 90 breaths per minute from pulse oximeter.

PubMed

Lee, Jinseok; Chon, Ki H

2010-09-01

We present particle filtering (PF) algorithms for an accurate respiratory rate extraction from pulse oximeter recordings over a broad range: 12-90 breaths/min. These methods are based on an autoregressive (AR) model, where the aim is to find the pole angle with the highest magnitude as it corresponds to the respiratory rate. However, when SNR is low, the pole angle with the highest magnitude may not always lead to accurate estimation of the respiratory rate. To circumvent this limitation, we propose a probabilistic approach, using a sequential Monte Carlo method, named PF, which is combined with the optimal parameter search (OPS) criterion for an accurate AR model-based respiratory rate extraction. The PF technique has been widely adopted in many tracking applications, especially for nonlinear and/or non-Gaussian problems. We examine the performances of five different likelihood functions of the PF algorithm: the strongest neighbor, nearest neighbor (NN), weighted nearest neighbor (WNN), probability data association (PDA), and weighted probability data association (WPDA). The performance of these five combined OPS-PF algorithms was measured against a solely OPS-based AR algorithm for respiratory rate extraction from pulse oximeter recordings. The pulse oximeter data were collected from 33 healthy subjects with breathing rates ranging from 12 to 90 breaths/ min. It was found that significant improvement in accuracy can be achieved by employing particle filters, and that the combined OPS-PF employing either the NN or WNN likelihood function achieved the best results for all respiratory rates considered in this paper. The main advantage of the combined OPS-PF with either the NN or WNN likelihood function is that for the first time, respiratory rates as high as 90 breaths/min can be accurately extracted from pulse oximeter recordings.

Trans-dimensional MCMC methods for fully automatic motion analysis in tagged MRI.

PubMed

Smal, Ihor; Carranza-Herrezuelo, Noemí; Klein, Stefan; Niessen, Wiro; Meijering, Erik

2011-01-01

Tagged magnetic resonance imaging (tMRI) is a well-known noninvasive method allowing quantitative analysis of regional heart dynamics. Its clinical use has so far been limited, in part due to the lack of robustness and accuracy of existing tag tracking algorithms in dealing with low (and intrinsically time-varying) image quality. In this paper, we propose a novel probabilistic method for tag tracking, implemented by means of Bayesian particle filtering and a trans-dimensional Markov chain Monte Carlo (MCMC) approach, which efficiently combines information about the imaging process and tag appearance with prior knowledge about the heart dynamics obtained by means of non-rigid image registration. Experiments using synthetic image data (with ground truth) and real data (with expert manual annotation) from preclinical (small animal) and clinical (human) studies confirm that the proposed method yields higher consistency, accuracy, and intrinsic tag reliability assessment in comparison with other frequently used tag tracking methods.

Online track detection in triggerless mode for INO

NASA Astrophysics Data System (ADS)

Jain, A.; Padmini, S.; Joseph, A. N.; Mahesh, P.; Preetha, N.; Behere, A.; Sikder, S. S.; Majumder, G.; Behera, S. P.

2018-03-01

The India based Neutrino Observatory (INO) is a proposed particle physics research project to study the atmospheric neutrinos. INO-Iron Calorimeter (ICAL) will consist of 28,800 detectors having 3.6 million electronic channels expected to activate with 100 Hz single rate, producing data at a rate of 3 GBps. Data collected contains a few real hits generated by muon tracks and the remaining noise-induced spurious hits. Estimated reduction factor after filtering out data of interest from generated data is of the order of 103. This makes trigger generation critical for efficient data collection and storage. Trigger is generated by detecting coincidence across multiple channels satisfying trigger criteria, within a small window of 200 ns in the trigger region. As the probability of neutrino interaction is very low, track detection algorithm has to be efficient and fast enough to process 5 × 106 events-candidates/s without introducing significant dead time, so that not even a single neutrino event is missed out. A hardware based trigger system is presently proposed for on-line track detection considering stringent timing requirements. Though the trigger system can be designed with scalability, a lot of hardware devices and interconnections make it a complex and expensive solution with limited flexibility. A software based track detection approach working on the hit information offers an elegant solution with possibility of varying trigger criteria for selecting various potentially interesting physics events. An event selection approach for an alternative triggerless readout scheme has been developed. The algorithm is mathematically simple, robust and parallelizable. It has been validated by detecting simulated muon events for energies of the range of 1 GeV-10 GeV with 100% efficiency at a processing rate of 60 μs/event on a 16 core machine. The algorithm and result of a proof-of-concept for its faster implementation over multiple cores is presented. The paper also discusses about harnessing the computing capabilities of multi-core computing farm, thereby optimizing number of nodes required for the proposed system.

Research on UAV Intelligent Obstacle Avoidance Technology During Inspection of Transmission Line

NASA Astrophysics Data System (ADS)

Wei, Chuanhu; Zhang, Fei; Yin, Chaoyuan; Liu, Yue; Liu, Liang; Li, Zongyu; Wang, Wanguo

Autonomous obstacle avoidance of unmanned aerial vehicle (hereinafter referred to as UAV) in electric power line inspection process has important significance for operation safety and economy for UAV intelligent inspection system of transmission line as main content of UAV intelligent inspection system on transmission line. In the paper, principles of UAV inspection obstacle avoidance technology of transmission line are introduced. UAV inspection obstacle avoidance technology based on particle swarm global optimization algorithm is proposed after common obstacle avoidance technologies are studied. Stimulation comparison is implemented with traditional UAV inspection obstacle avoidance technology which adopts artificial potential field method. Results show that UAV inspection strategy of particle swarm optimization algorithm, adopted in the paper, is prominently better than UAV inspection strategy of artificial potential field method in the aspects of obstacle avoidance effect and the ability of returning to preset inspection track after passing through the obstacle. An effective method is provided for UAV inspection obstacle avoidance of transmission line.

UltraTrack: Software for semi-automated tracking of muscle fascicles in sequences of B-mode ultrasound images.

PubMed

Farris, Dominic James; Lichtwark, Glen A

2016-05-01

Dynamic measurements of human muscle fascicle length from sequences of B-mode ultrasound images have become increasingly prevalent in biomedical research. Manual digitisation of these images is time consuming and algorithms for automating the process have been developed. Here we present a freely available software implementation of a previously validated algorithm for semi-automated tracking of muscle fascicle length in dynamic ultrasound image recordings, "UltraTrack". UltraTrack implements an affine extension to an optic flow algorithm to track movement of the muscle fascicle end-points throughout dynamically recorded sequences of images. The underlying algorithm has been previously described and its reliability tested, but here we present the software implementation with features for: tracking multiple fascicles in multiple muscles simultaneously; correcting temporal drift in measurements; manually adjusting tracking results; saving and re-loading of tracking results and loading a range of file formats. Two example runs of the software are presented detailing the tracking of fascicles from several lower limb muscles during a squatting and walking activity. We have presented a software implementation of a validated fascicle-tracking algorithm and made the source code and standalone versions freely available for download. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Chaos Quantum-Behaved Cat Swarm Optimization Algorithm and Its Application in the PV MPPT

PubMed Central

2017-01-01

Cat Swarm Optimization (CSO) algorithm was put forward in 2006. Despite a faster convergence speed compared with Particle Swarm Optimization (PSO) algorithm, the application of CSO is greatly limited by the drawback of “premature convergence,” that is, the possibility of trapping in local optimum when dealing with nonlinear optimization problem with a large number of local extreme values. In order to surmount the shortcomings of CSO, Chaos Quantum-behaved Cat Swarm Optimization (CQCSO) algorithm is proposed in this paper. Firstly, Quantum-behaved Cat Swarm Optimization (QCSO) algorithm improves the accuracy of the CSO algorithm, because it is easy to fall into the local optimum in the later stage. Chaos Quantum-behaved Cat Swarm Optimization (CQCSO) algorithm is proposed by introducing tent map for jumping out of local optimum in this paper. Secondly, CQCSO has been applied in the simulation of five different test functions, showing higher accuracy and less time consumption than CSO and QCSO. Finally, photovoltaic MPPT model and experimental platform are established and global maximum power point tracking control strategy is achieved by CQCSO algorithm, the effectiveness and efficiency of which have been verified by both simulation and experiment. PMID:29181020

Chaos Quantum-Behaved Cat Swarm Optimization Algorithm and Its Application in the PV MPPT.

PubMed

Nie, Xiaohua; Wang, Wei; Nie, Haoyao

2017-01-01

Cat Swarm Optimization (CSO) algorithm was put forward in 2006. Despite a faster convergence speed compared with Particle Swarm Optimization (PSO) algorithm, the application of CSO is greatly limited by the drawback of "premature convergence," that is, the possibility of trapping in local optimum when dealing with nonlinear optimization problem with a large number of local extreme values. In order to surmount the shortcomings of CSO, Chaos Quantum-behaved Cat Swarm Optimization (CQCSO) algorithm is proposed in this paper. Firstly, Quantum-behaved Cat Swarm Optimization (QCSO) algorithm improves the accuracy of the CSO algorithm, because it is easy to fall into the local optimum in the later stage. Chaos Quantum-behaved Cat Swarm Optimization (CQCSO) algorithm is proposed by introducing tent map for jumping out of local optimum in this paper. Secondly, CQCSO has been applied in the simulation of five different test functions, showing higher accuracy and less time consumption than CSO and QCSO. Finally, photovoltaic MPPT model and experimental platform are established and global maximum power point tracking control strategy is achieved by CQCSO algorithm, the effectiveness and efficiency of which have been verified by both simulation and experiment.

Multiple electrokinetic actuators for feedback control of colloidal crystal size.

PubMed

Juárez, Jaime J; Mathai, Pramod P; Liddle, J Alexander; Bevan, Michael A

2012-10-21

We report a feedback control method to precisely target the number of colloidal particles in quasi-2D ensembles and their subsequent assembly into crystals in a quadrupole electrode. Our approach relies on tracking the number of particles within a quadrupole electrode, which is used in a real-time feedback control algorithm to dynamically actuate competing electrokinetic transport mechanisms. Particles are removed from the quadrupole using DC-field mediated electrophoretic-electroosmotic transport, while high-frequency AC-field mediated dielectrophoretic transport is used to concentrate and assemble colloidal crystals. Our results show successful control of the size of crystals containing 20 to 250 colloidal particles with less than 10% error. Assembled crystals are characterized by their radius of gyration, crystallinity, and number of edge particles, and demonstrate the expected size-dependent properties. Our findings demonstrate successful ensemble feedback control of the assembly of different sized colloidal crystals using multiple actuators, which has broad implications for control over nano- and micro- scale assembly processes involving colloidal components.

Temporal Restricted Visual Tracking Via Reverse-Low-Rank Sparse Learning.

PubMed

Yang, Yehui; Hu, Wenrui; Xie, Yuan; Zhang, Wensheng; Zhang, Tianzhu

2017-02-01

An effective representation model, which aims to mine the most meaningful information in the data, plays an important role in visual tracking. Some recent particle-filter-based trackers achieve promising results by introducing the low-rank assumption into the representation model. However, their assumed low-rank structure of candidates limits the robustness when facing severe challenges such as abrupt motion. To avoid the above limitation, we propose a temporal restricted reverse-low-rank learning algorithm for visual tracking with the following advantages: 1) the reverse-low-rank model jointly represents target and background templates via candidates, which exploits the low-rank structure among consecutive target observations and enforces the temporal consistency of target in a global level; 2) the appearance consistency may be broken when target suffers from sudden changes. To overcome this issue, we propose a local constraint via l 1,2 mixed-norm, which can not only ensures the local consistency of target appearance, but also tolerates the sudden changes between two adjacent frames; and 3) to alleviate the inference of unreasonable representation values due to outlier candidates, an adaptive weighted scheme is designed to improve the robustness of the tracker. By evaluating on 26 challenge video sequences, the experiments show the effectiveness and favorable performance of the proposed algorithm against 12 state-of-the-art visual trackers.

Introduction to Vector Field Visualization

NASA Technical Reports Server (NTRS)

Kao, David; Shen, Han-Wei

2010-01-01

Vector field visualization techniques are essential to help us understand the complex dynamics of flow fields. These can be found in a wide range of applications such as study of flows around an aircraft, the blood flow in our heart chambers, ocean circulation models, and severe weather predictions. The vector fields from these various applications can be visually depicted using a number of techniques such as particle traces and advecting textures. In this tutorial, we present several fundamental algorithms in flow visualization including particle integration, particle tracking in time-dependent flows, and seeding strategies. For flows near surfaces, a wide variety of synthetic texture-based algorithms have been developed to depict near-body flow features. The most common approach is based on the Line Integral Convolution (LIC) algorithm. There also exist extensions of LIC to support more flexible texture generations for 3D flow data. This tutorial reviews these algorithms. Tensor fields are found in several real-world applications and also require the aid of visualization to help users understand their data sets. Examples where one can find tensor fields include mechanics to see how material respond to external forces, civil engineering and geomechanics of roads and bridges, and the study of neural pathway via diffusion tensor imaging. This tutorial will provide an overview of the different tensor field visualization techniques, discuss basic tensor decompositions, and go into detail on glyph based methods, deformation based methods, and streamline based methods. Practical examples will be used when presenting the methods; and applications from some case studies will be used as part of the motivation.

Non linear predictive control of a LEGO mobile robot

NASA Astrophysics Data System (ADS)

Merabti, H.; Bouchemal, B.; Belarbi, K.; Boucherma, D.; Amouri, A.

2014-10-01

Metaheuristics are general purpose heuristics which have shown a great potential for the solution of difficult optimization problems. In this work, we apply the meta heuristic, namely particle swarm optimization, PSO, for the solution of the optimization problem arising in NLMPC. This algorithm is easy to code and may be considered as alternatives for the more classical solution procedures. The PSO- NLMPC is applied to control a mobile robot for the tracking trajectory and obstacles avoidance. Experimental results show the strength of this approach.

Flow-rate control for managing communications in tracking and surveillance networks

NASA Astrophysics Data System (ADS)

Miller, Scott A.; Chong, Edwin K. P.

2007-09-01

This paper describes a primal-dual distributed algorithm for managing communications in a bandwidth-limited sensor network for tracking and surveillance. The algorithm possesses some scale-invariance properties and adaptive gains that make it more practical for applications such as tracking where the conditions change over time. A simulation study comparing this algorithm with a priority-queue-based approach in a network tracking scenario shows significant improvement in the resulting track quality when using flow control to manage communications.

Tracking tumor boundary in MV-EPID images without implanted markers: A feasibility study.

PubMed

Zhang, Xiaoyong; Homma, Noriyasu; Ichiji, Kei; Takai, Yoshihiro; Yoshizawa, Makoto

2015-05-01

To develop a markerless tracking algorithm to track the tumor boundary in megavoltage (MV)-electronic portal imaging device (EPID) images for image-guided radiation therapy. A level set method (LSM)-based algorithm is developed to track tumor boundary in EPID image sequences. Given an EPID image sequence, an initial curve is manually specified in the first frame. Driven by a region-scalable energy fitting function, the initial curve automatically evolves toward the tumor boundary and stops on the desired boundary while the energy function reaches its minimum. For the subsequent frames, the tracking algorithm updates the initial curve by using the tracking result in the previous frame and reuses the LSM to detect the tumor boundary in the subsequent frame so that the tracking processing can be continued without user intervention. The tracking algorithm is tested on three image datasets, including a 4-D phantom EPID image sequence, four digitally deformable phantom image sequences with different noise levels, and four clinical EPID image sequences acquired in lung cancer treatment. The tracking accuracy is evaluated based on two metrics: centroid localization error (CLE) and volume overlap index (VOI) between the tracking result and the ground truth. For the 4-D phantom image sequence, the CLE is 0.23 ± 0.20 mm, and VOI is 95.6% ± 0.2%. For the digital phantom image sequences, the total CLE and VOI are 0.11 ± 0.08 mm and 96.7% ± 0.7%, respectively. In addition, for the clinical EPID image sequences, the proposed algorithm achieves 0.32 ± 0.77 mm in the CLE and 72.1% ± 5.5% in the VOI. These results demonstrate the effectiveness of the authors' proposed method both in tumor localization and boundary tracking in EPID images. In addition, compared with two existing tracking algorithms, the proposed method achieves a higher accuracy in tumor localization. In this paper, the authors presented a feasibility study of tracking tumor boundary in EPID images by using a LSM-based algorithm. Experimental results conducted on phantom and clinical EPID images demonstrated the effectiveness of the tracking algorithm for visible tumor target. Compared with previous tracking methods, the authors' algorithm has the potential to improve the tracking accuracy in radiation therapy. In addition, real-time tumor boundary information within the irradiation field will be potentially useful for further applications, such as adaptive beam delivery, dose evaluation.

Experiments with conjugate gradient algorithms for homotopy curve tracking

NASA Technical Reports Server (NTRS)

Irani, Kashmira M.; Ribbens, Calvin J.; Watson, Layne T.; Kamat, Manohar P.; Walker, Homer F.

1991-01-01

There are algorithms for finding zeros or fixed points of nonlinear systems of equations that are globally convergent for almost all starting points, i.e., with probability one. The essence of all such algorithms is the construction of an appropriate homotopy map and then tracking some smooth curve in the zero set of this homotopy map. HOMPACK is a mathematical software package implementing globally convergent homotopy algorithms with three different techniques for tracking a homotopy zero curve, and has separate routines for dense and sparse Jacobian matrices. The HOMPACK algorithms for sparse Jacobian matrices use a preconditioned conjugate gradient algorithm for the computation of the kernel of the homotopy Jacobian matrix, a required linear algebra step for homotopy curve tracking. Here, variants of the conjugate gradient algorithm are implemented in the context of homotopy curve tracking and compared with Craig's preconditioned conjugate gradient method used in HOMPACK. The test problems used include actual large scale, sparse structural mechanics problems.

A maximum power point tracking algorithm for buoy-rope-drum wave energy converters

NASA Astrophysics Data System (ADS)

Wang, J. Q.; Zhang, X. C.; Zhou, Y.; Cui, Z. C.; Zhu, L. S.

2016-08-01

The maximum power point tracking control is the key link to improve the energy conversion efficiency of wave energy converters (WEC). This paper presents a novel variable step size Perturb and Observe maximum power point tracking algorithm with a power classification standard for control of a buoy-rope-drum WEC. The algorithm and simulation model of the buoy-rope-drum WEC are presented in details, as well as simulation experiment results. The results show that the algorithm tracks the maximum power point of the WEC fast and accurately.

Large scale tracking algorithms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hansen, Ross L.; Love, Joshua Alan; Melgaard, David Kennett

2015-01-01

Low signal-to-noise data processing algorithms for improved detection, tracking, discrimination and situational threat assessment are a key research challenge. As sensor technologies progress, the number of pixels will increase signi cantly. This will result in increased resolution, which could improve object discrimination, but unfortunately, will also result in a significant increase in the number of potential targets to track. Many tracking techniques, like multi-hypothesis trackers, suffer from a combinatorial explosion as the number of potential targets increase. As the resolution increases, the phenomenology applied towards detection algorithms also changes. For low resolution sensors, "blob" tracking is the norm. For highermore » resolution data, additional information may be employed in the detection and classfication steps. The most challenging scenarios are those where the targets cannot be fully resolved, yet must be tracked and distinguished for neighboring closely spaced objects. Tracking vehicles in an urban environment is an example of such a challenging scenario. This report evaluates several potential tracking algorithms for large-scale tracking in an urban environment.« less

UWB Tracking Algorithms: AOA and TDOA

NASA Technical Reports Server (NTRS)

Ni, Jianjun David; Arndt, D.; Ngo, P.; Gross, J.; Refford, Melinda

2006-01-01

Ultra-Wideband (UWB) tracking prototype systems are currently under development at NASA Johnson Space Center for various applications on space exploration. For long range applications, a two-cluster Angle of Arrival (AOA) tracking method is employed for implementation of the tracking system; for close-in applications, a Time Difference of Arrival (TDOA) positioning methodology is exploited. Both AOA and TDOA are chosen to utilize the achievable fine time resolution of UWB signals. This talk presents a brief introduction to AOA and TDOA methodologies. The theoretical analysis of these two algorithms reveal the affecting parameters impact on the tracking resolution. For the AOA algorithm, simulations show that a tracking resolution less than 0.5% of the range can be achieved with the current achievable time resolution of UWB signals. For the TDOA algorithm used in close-in applications, simulations show that the (sub-inch) high tracking resolution is achieved with a chosen tracking baseline configuration. The analytical and simulated results provide insightful guidance for the UWB tracking system design.

Improving z-tracking accuracy in the two-photon single-particle tracking microscope.

PubMed

Liu, C; Liu, Y-L; Perillo, E P; Jiang, N; Dunn, A K; Yeh, H-C

2015-10-12

Here, we present a method that can improve the z-tracking accuracy of the recently invented TSUNAMI (Tracking of Single particles Using Nonlinear And Multiplexed Illumination) microscope. This method utilizes a maximum likelihood estimator (MLE) to determine the particle's 3D position that maximizes the likelihood of the observed time-correlated photon count distribution. Our Monte Carlo simulations show that the MLE-based tracking scheme can improve the z-tracking accuracy of TSUNAMI microscope by 1.7 fold. In addition, MLE is also found to reduce the temporal correlation of the z-tracking error. Taking advantage of the smaller and less temporally correlated z-tracking error, we have precisely recovered the hybridization-melting kinetics of a DNA model system from thousands of short single-particle trajectories in silico . Our method can be generally applied to other 3D single-particle tracking techniques.

Improving z-tracking accuracy in the two-photon single-particle tracking microscope

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, C.; Liu, Y.-L.; Perillo, E. P.

Here, we present a method that can improve the z-tracking accuracy of the recently invented TSUNAMI (Tracking of Single particles Using Nonlinear And Multiplexed Illumination) microscope. This method utilizes a maximum likelihood estimator (MLE) to determine the particle's 3D position that maximizes the likelihood of the observed time-correlated photon count distribution. Our Monte Carlo simulations show that the MLE-based tracking scheme can improve the z-tracking accuracy of TSUNAMI microscope by 1.7 fold. In addition, MLE is also found to reduce the temporal correlation of the z-tracking error. Taking advantage of the smaller and less temporally correlated z-tracking error, we havemore » precisely recovered the hybridization-melting kinetics of a DNA model system from thousands of short single-particle trajectories in silico. Our method can be generally applied to other 3D single-particle tracking techniques.« less

Visualization and Hierarchical Analysis of Flow in Discrete Fracture Network Models

NASA Astrophysics Data System (ADS)

Aldrich, G. A.; Gable, C. W.; Painter, S. L.; Makedonska, N.; Hamann, B.; Woodring, J.

2013-12-01

Flow and transport in low permeability fractured rock is primary in interconnected fracture networks. Prediction and characterization of flow and transport in fractured rock has important implications in underground repositories for hazardous materials (eg. nuclear and chemical waste), contaminant migration and remediation, groundwater resource management, and hydrocarbon extraction. We have developed methods to explicitly model flow in discrete fracture networks and track flow paths using passive particle tracking algorithms. Visualization and analysis of particle trajectory through the fracture network is important to understanding fracture connectivity, flow patterns, potential contaminant pathways and fast paths through the network. However, occlusion due to the large number of highly tessellated and intersecting fracture polygons preclude the effective use of traditional visualization methods. We would also like quantitative analysis methods to characterize the trajectory of a large number of particle paths. We have solved these problems by defining a hierarchal flow network representing the topology of particle flow through the fracture network. This approach allows us to analyses the flow and the dynamics of the system as a whole. We are able to easily query the flow network, and use paint-and-link style framework to filter the fracture geometry and particle traces based on the flow analytics. This allows us to greatly reduce occlusion while emphasizing salient features such as the principal transport pathways. Examples are shown that demonstrate the methodology and highlight how use of this new method allows quantitative analysis and characterization of flow and transport in a number of representative fracture networks.

Forward-backward multiplicity correlations of target fragments in nucleus-emulsion collisions at a few hundred MeV/u

NASA Astrophysics Data System (ADS)

Zhang, Dong-Hai; Chen, Yan-Ling; Wang, Guo-Rong; Li, Wang-Dong; Wang, Qing; Yao, Ji-Jie; Zhou, Jian-Guo; Li, Rong; Li, Jun-Sheng; Li, Hui-Ling

2015-01-01

The forward-backward multiplicity and correlations of a target evaporated fragment (black track particle) and target recoiled proton (grey track particle) emitted from 150 A MeV 4He, 290 A MeV 12C, 400 A MeV 12C, 400 A MeV 20Ne and 500 A MeV 56Fe induced different types of nuclear emulsion target interactions are investigated. It is found that the forward and backward averaged multiplicity of a grey, black and heavily ionized track particle increases with the increase of the target size. The averaged multiplicity of a forward black track particle, backward black track particle, and backward grey track particle do not depend on the projectile size and energy, but the averaged multiplicity of a forward grey track particle increases with an increase of projectile size and energy. The backward grey track particle multiplicity distribution follows an exponential decay law and the decay constant decreases with an increase of target size. The backward-forward multiplicity correlations follow linear law which is independent of the projectile size and energy, and the saturation effect is observed in some heavy target data sets.

Real-time particle tracking for studying intracellular trafficking of pharmaceutical nanocarriers.

PubMed

Huang, Feiran; Watson, Erin; Dempsey, Christopher; Suh, Junghae

2013-01-01

Real-time particle tracking is a technique that combines fluorescence microscopy with object tracking and computing and can be used to extract quantitative transport parameters for small particles inside cells. Since the success of a nanocarrier can often be determined by how effectively it delivers cargo to the target organelle, understanding the complex intracellular transport of pharmaceutical nanocarriers is critical. Real-time particle tracking provides insight into the dynamics of the intracellular behavior of nanoparticles, which may lead to significant improvements in the design and development of novel delivery systems. Unfortunately, this technique is not often fully understood, limiting its implementation by researchers in the field of nanomedicine. In this chapter, one of the most complicated aspects of particle tracking, the mean square displacement (MSD) calculation, is explained in a simple manner designed for the novice particle tracker. Pseudo code for performing the MSD calculation in MATLAB is also provided. This chapter contains clear and comprehensive instructions for a series of basic procedures in the technique of particle tracking. Instructions for performing confocal microscopy of nanoparticle samples are provided, and two methods of determining particle trajectories that do not require commercial particle-tracking software are provided. Trajectory analysis and determination of the tracking resolution are also explained. By providing comprehensive instructions needed to perform particle-tracking experiments, this chapter will enable researchers to gain new insight into the intracellular dynamics of nanocarriers, potentially leading to the development of more effective and intelligent therapeutic delivery vectors.

Electro-optic tracking R&D for defense surveillance

NASA Astrophysics Data System (ADS)

Sutherland, Stuart; Woodruff, Chris J.

1995-09-01

Two aspects of work on automatic target detection and tracking for electro-optic (EO) surveillance are described. Firstly, a detection and tracking algorithm test-bed developed by DSTO and running on a PC under Windows NT is being used to assess candidate algorithms for unresolved and minimally resolved target detection. The structure of this test-bed is described and examples are given of its user interfaces and outputs. Secondly, a development by Australian industry under a Defence-funded contract, of a reconfigurable generic track processor (GTP) is outlined. The GTP will include reconfigurable image processing stages and target tracking algorithms. It will be used to demonstrate to the Australian Defence Force automatic detection and tracking capabilities, and to serve as a hardware base for real time algorithm refinement.

Tracking tumor boundary in MV-EPID images without implanted markers: A feasibility study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Xiaoyong, E-mail: xiaoyong@ieee.org; Homma, Noriyasu, E-mail: homma@ieee.org; Ichiji, Kei, E-mail: ichiji@yoshizawa.ecei.tohoku.ac.jp

2015-05-15

Purpose: To develop a markerless tracking algorithm to track the tumor boundary in megavoltage (MV)-electronic portal imaging device (EPID) images for image-guided radiation therapy. Methods: A level set method (LSM)-based algorithm is developed to track tumor boundary in EPID image sequences. Given an EPID image sequence, an initial curve is manually specified in the first frame. Driven by a region-scalable energy fitting function, the initial curve automatically evolves toward the tumor boundary and stops on the desired boundary while the energy function reaches its minimum. For the subsequent frames, the tracking algorithm updates the initial curve by using the trackingmore » result in the previous frame and reuses the LSM to detect the tumor boundary in the subsequent frame so that the tracking processing can be continued without user intervention. The tracking algorithm is tested on three image datasets, including a 4-D phantom EPID image sequence, four digitally deformable phantom image sequences with different noise levels, and four clinical EPID image sequences acquired in lung cancer treatment. The tracking accuracy is evaluated based on two metrics: centroid localization error (CLE) and volume overlap index (VOI) between the tracking result and the ground truth. Results: For the 4-D phantom image sequence, the CLE is 0.23 ± 0.20 mm, and VOI is 95.6% ± 0.2%. For the digital phantom image sequences, the total CLE and VOI are 0.11 ± 0.08 mm and 96.7% ± 0.7%, respectively. In addition, for the clinical EPID image sequences, the proposed algorithm achieves 0.32 ± 0.77 mm in the CLE and 72.1% ± 5.5% in the VOI. These results demonstrate the effectiveness of the authors’ proposed method both in tumor localization and boundary tracking in EPID images. In addition, compared with two existing tracking algorithms, the proposed method achieves a higher accuracy in tumor localization. Conclusions: In this paper, the authors presented a feasibility study of tracking tumor boundary in EPID images by using a LSM-based algorithm. Experimental results conducted on phantom and clinical EPID images demonstrated the effectiveness of the tracking algorithm for visible tumor target. Compared with previous tracking methods, the authors’ algorithm has the potential to improve the tracking accuracy in radiation therapy. In addition, real-time tumor boundary information within the irradiation field will be potentially useful for further applications, such as adaptive beam delivery, dose evaluation.« less

Visualization of grid-generated turbulence in He II using PTV

NASA Astrophysics Data System (ADS)

Mastracci, B.; Guo, W.

2017-12-01

Due to its low viscosity, cryogenic He II has potential use for simulating large-scale, high Reynolds number turbulent flow in a compact and efficient apparatus. To realize this potential, the behavior of the fluid in the simplest cases, such as turbulence generated by flow past a mesh grid, must be well understood. We have designed, constructed, and commissioned an apparatus to visualize the evolution of turbulence in the wake of a mesh grid towed through He II. Visualization is accomplished using the particle tracking velocimetry (PTV) technique, where μm-sized tracer particles are introduced to the flow, illuminated with a planar laser sheet, and recorded by a scientific imaging camera; the particles move with the fluid, and tracking their motion with a computer algorithm results in a complete map of the turbulent velocity field in the imaging region. In our experiment, this region is inside a carefully designed He II filled cast acrylic channel measuring approximately 16 × 16 × 330 mm. One of three different grids, which have mesh numbers M = 3, 3.75, or 5 mm, can be attached to the pulling system which moves it through the channel with constant velocity up to 600 mm/s. The consequent motion of the solidified deuterium tracer particles is used to investigate the energy statistics, effective kinematic viscosity, and quantized vortex dynamics in turbulent He II.

Bounded fractional diffusion in geological media: Definition and Lagrangian approximation

NASA Astrophysics Data System (ADS)

Zhang, Yong; Green, Christopher T.; LaBolle, Eric M.; Neupauer, Roseanna M.; Sun, HongGuang

2016-11-01

Spatiotemporal fractional-derivative models (FDMs) have been increasingly used to simulate non-Fickian diffusion, but methods have not been available to define boundary conditions for FDMs in bounded domains. This study defines boundary conditions and then develops a Lagrangian solver to approximate bounded, one-dimensional fractional diffusion. Both the zero-value and nonzero-value Dirichlet, Neumann, and mixed Robin boundary conditions are defined, where the sign of Riemann-Liouville fractional derivative (capturing nonzero-value spatial-nonlocal boundary conditions with directional superdiffusion) remains consistent with the sign of the fractional-diffusive flux term in the FDMs. New Lagrangian schemes are then proposed to track solute particles moving in bounded domains, where the solutions are checked against analytical or Eulerian solutions available for simplified FDMs. Numerical experiments show that the particle-tracking algorithm for non-Fickian diffusion differs from Fickian diffusion in relocating the particle position around the reflective boundary, likely due to the nonlocal and nonsymmetric fractional diffusion. For a nonzero-value Neumann or Robin boundary, a source cell with a reflective face can be applied to define the release rate of random-walking particles at the specified flux boundary. Mathematical definitions of physically meaningful nonlocal boundaries combined with bounded Lagrangian solvers in this study may provide the only viable techniques at present to quantify the impact of boundaries on anomalous diffusion, expanding the applicability of FDMs from infinite domains to those with any size and boundary conditions.

PENGEOM-A general-purpose geometry package for Monte Carlo simulation of radiation transport in material systems defined by quadric surfaces

NASA Astrophysics Data System (ADS)

Almansa, Julio; Salvat-Pujol, Francesc; Díaz-Londoño, Gloria; Carnicer, Artur; Lallena, Antonio M.; Salvat, Francesc

2016-02-01

The Fortran subroutine package PENGEOM provides a complete set of tools to handle quadric geometries in Monte Carlo simulations of radiation transport. The material structure where radiation propagates is assumed to consist of homogeneous bodies limited by quadric surfaces. The PENGEOM subroutines (a subset of the PENELOPE code) track particles through the material structure, independently of the details of the physics models adopted to describe the interactions. Although these subroutines are designed for detailed simulations of photon and electron transport, where all individual interactions are simulated sequentially, they can also be used in mixed (class II) schemes for simulating the transport of high-energy charged particles, where the effect of soft interactions is described by the random-hinge method. The definition of the geometry and the details of the tracking algorithm are tailored to optimize simulation speed. The use of fuzzy quadric surfaces minimizes the impact of round-off errors. The provided software includes a Java graphical user interface for editing and debugging the geometry definition file and for visualizing the material structure. Images of the structure are generated by using the tracking subroutines and, hence, they describe the geometry actually passed to the simulation code.

Extracting three-dimensional orientation and tractography of myofibers using optical coherence tomography

PubMed Central

Gan, Yu; Fleming, Christine P.

2013-01-01

Abnormal changes in orientation of myofibers are associated with various cardiac diseases such as arrhythmia, irregular contraction, and cardiomyopathy. To extract fiber information, we present a method of quantifying fiber orientation and reconstructing three-dimensional tractography of myofibers using optical coherence tomography (OCT). A gradient based algorithm was developed to quantify fiber orientation in three dimensions and particle filtering technique was employed to track myofibers. Prior to image processing, three-dimensional image data set were acquired from all cardiac chambers and ventricular septum of swine hearts using OCT system without optical clearing. The algorithm was validated through rotation test and comparison with manual measurements. The experimental results demonstrate that we are able to visualize three-dimensional fiber tractography in myocardium tissues. PMID:24156071

Penalty dynamic programming algorithm for dim targets detection in sensor systems.

PubMed

Huang, Dayu; Xue, Anke; Guo, Yunfei

2012-01-01

In order to detect and track multiple maneuvering dim targets in sensor systems, an improved dynamic programming track-before-detect algorithm (DP-TBD) called penalty DP-TBD (PDP-TBD) is proposed. The performances of tracking techniques are used as a feedback to the detection part. The feedback is constructed by a penalty term in the merit function, and the penalty term is a function of the possible target state estimation, which can be obtained by the tracking methods. With this feedback, the algorithm combines traditional tracking techniques with DP-TBD and it can be applied to simultaneously detect and track maneuvering dim targets. Meanwhile, a reasonable constraint that a sensor measurement can originate from one target or clutter is proposed to minimize track separation. Thus, the algorithm can be used in the multi-target situation with unknown target numbers. The efficiency and advantages of PDP-TBD compared with two existing methods are demonstrated by several simulations.

The research and application of visual saliency and adaptive support vector machine in target tracking field.

PubMed

Chen, Yuantao; Xu, Weihong; Kuang, Fangjun; Gao, Shangbing

2013-01-01

The efficient target tracking algorithm researches have become current research focus of intelligent robots. The main problems of target tracking process in mobile robot face environmental uncertainty. They are very difficult to estimate the target states, illumination change, target shape changes, complex backgrounds, and other factors and all affect the occlusion in tracking robustness. To further improve the target tracking's accuracy and reliability, we present a novel target tracking algorithm to use visual saliency and adaptive support vector machine (ASVM). Furthermore, the paper's algorithm has been based on the mixture saliency of image features. These features include color, brightness, and sport feature. The execution process used visual saliency features and those common characteristics have been expressed as the target's saliency. Numerous experiments demonstrate the effectiveness and timeliness of the proposed target tracking algorithm in video sequences where the target objects undergo large changes in pose, scale, and illumination.

A Novel Multi-Sensor Environmental Perception Method Using Low-Rank Representation and a Particle Filter for Vehicle Reversing Safety

PubMed Central

Zhang, Zutao; Li, Yanjun; Wang, Fubing; Meng, Guanjun; Salman, Waleed; Saleem, Layth; Zhang, Xiaoliang; Wang, Chunbai; Hu, Guangdi; Liu, Yugang

2016-01-01

Environmental perception and information processing are two key steps of active safety for vehicle reversing. Single-sensor environmental perception cannot meet the need for vehicle reversing safety due to its low reliability. In this paper, we present a novel multi-sensor environmental perception method using low-rank representation and a particle filter for vehicle reversing safety. The proposed system consists of four main steps, namely multi-sensor environmental perception, information fusion, target recognition and tracking using low-rank representation and a particle filter, and vehicle reversing speed control modules. First of all, the multi-sensor environmental perception module, based on a binocular-camera system and ultrasonic range finders, obtains the distance data for obstacles behind the vehicle when the vehicle is reversing. Secondly, the information fusion algorithm using an adaptive Kalman filter is used to process the data obtained with the multi-sensor environmental perception module, which greatly improves the robustness of the sensors. Then the framework of a particle filter and low-rank representation is used to track the main obstacles. The low-rank representation is used to optimize an objective particle template that has the smallest L-1 norm. Finally, the electronic throttle opening and automatic braking is under control of the proposed vehicle reversing control strategy prior to any potential collisions, making the reversing control safer and more reliable. The final system simulation and practical testing results demonstrate the validity of the proposed multi-sensor environmental perception method using low-rank representation and a particle filter for vehicle reversing safety. PMID:27294931

A Novel Multi-Sensor Environmental Perception Method Using Low-Rank Representation and a Particle Filter for Vehicle Reversing Safety.

PubMed

Zhang, Zutao; Li, Yanjun; Wang, Fubing; Meng, Guanjun; Salman, Waleed; Saleem, Layth; Zhang, Xiaoliang; Wang, Chunbai; Hu, Guangdi; Liu, Yugang

2016-06-09

Environmental perception and information processing are two key steps of active safety for vehicle reversing. Single-sensor environmental perception cannot meet the need for vehicle reversing safety due to its low reliability. In this paper, we present a novel multi-sensor environmental perception method using low-rank representation and a particle filter for vehicle reversing safety. The proposed system consists of four main steps, namely multi-sensor environmental perception, information fusion, target recognition and tracking using low-rank representation and a particle filter, and vehicle reversing speed control modules. First of all, the multi-sensor environmental perception module, based on a binocular-camera system and ultrasonic range finders, obtains the distance data for obstacles behind the vehicle when the vehicle is reversing. Secondly, the information fusion algorithm using an adaptive Kalman filter is used to process the data obtained with the multi-sensor environmental perception module, which greatly improves the robustness of the sensors. Then the framework of a particle filter and low-rank representation is used to track the main obstacles. The low-rank representation is used to optimize an objective particle template that has the smallest L-1 norm. Finally, the electronic throttle opening and automatic braking is under control of the proposed vehicle reversing control strategy prior to any potential collisions, making the reversing control safer and more reliable. The final system simulation and practical testing results demonstrate the validity of the proposed multi-sensor environmental perception method using low-rank representation and a particle filter for vehicle reversing safety.

NASA Tech Briefs, July 2010

NASA Technical Reports Server (NTRS)

2010-01-01

Topics covered include: Wirelessly Interrogated Wear or Temperature Sensors; Processing Nanostructured Sensors Using Microfabrication Techniques; Optical Pointing Sensor; Radio-Frequency Tank Eigenmode Sensor for Propellant Quantity Gauging; High-Temperature Optical Sensor; Integral Battery Power Limiting Circuit for Intrinsically Safe Applications; Configurable Multi-Purpose Processor; Squeezing Alters Frequency Tuning of WGM Optical Resonator; Automated Computer Access Request System; Range Safety for an Autonomous Flight Safety System; Fast and Easy Searching of Files in Unisys 2200 Computers; Parachute Drag Model; Evolutionary Scheduler for the Deep Space Network; Modular Habitats Comprising Rigid and Inflatable Modules; More About N2O-Based Propulsion and Breathable-Gas Systems; Ultrasonic/Sonic Rotary-Hammer Drills; Miniature Piezoelectric Shaker for Distribution of Unconsolidated Samples to Instrument Cells; Lunar Soil Particle Separator; Advanced Aerobots for Scientific Exploration; Miniature Bioreactor System for Long-Term Cell Culture; Electrochemical Detection of Multiple Bioprocess Analytes; Fabrication and Modification of Nanoporous Silicon Particles; High-Altitude Hydration System; Photon Counting Using Edge-Detection Algorithm; Holographic Vortex Coronagraph; Optical Structural Health Monitoring Device; Fuel-Cell Power Source Based on Onboard Rocket Propellants; Polar Lunar Regions: Exploiting Natural and Augmented Thermal Environments; Simultaneous Spectral Temporal Adaptive Raman Spectrometer - SSTARS; Improved Speed and Functionality of a 580-GHz Imaging Radar; Bolometric Device Based on Fluxoid Quantization; Algorithms for Learning Preferences for Sets of Objects; Model for Simulating a Spiral Software-Development Process; Algorithm That Synthesizes Other Algorithms for Hashing; Algorithms for High-Speed Noninvasive Eye-Tracking System; and Adapting ASPEN for Orbital Express.

Integration of an On-Axis General Sun-Tracking Formula in the Algorithm of an Open-Loop Sun-Tracking System

PubMed Central

Chong, Kok-Keong; Wong, Chee-Woon; Siaw, Fei-Lu; Yew, Tiong-Keat; Ng, See-Seng; Liang, Meng-Suan; Lim, Yun-Seng; Lau, Sing-Liong

2009-01-01

A novel on-axis general sun-tracking formula has been integrated in the algorithm of an open-loop sun-tracking system in order to track the sun accurately and cost effectively. Sun-tracking errors due to installation defects of the 25 m2 prototype solar concentrator have been analyzed from recorded solar images with the use of a CCD camera. With the recorded data, misaligned angles from ideal azimuth-elevation axes have been determined and corrected by a straightforward changing of the parameters' values in the general formula of the tracking algorithm to improve the tracking accuracy to 2.99 mrad, which falls below the encoder resolution limit of 4.13 mrad. PMID:22408483

Game theory-based visual tracking approach focusing on color and texture features.

PubMed

Jin, Zefenfen; Hou, Zhiqiang; Yu, Wangsheng; Chen, Chuanhua; Wang, Xin

2017-07-20

It is difficult for a single-feature tracking algorithm to achieve strong robustness under a complex environment. To solve this problem, we proposed a multifeature fusion tracking algorithm that is based on game theory. By focusing on color and texture features as two gamers, this algorithm accomplishes tracking by using a mean shift iterative formula to search for the Nash equilibrium of the game. The contribution of different features is always keeping the state of optical balance, so that the algorithm can fully take advantage of feature fusion. According to the experiment results, this algorithm proves to possess good performance, especially under the condition of scene variation, target occlusion, and similar interference.

Binocular Vision-Based Position and Pose of Hand Detection and Tracking in Space

NASA Astrophysics Data System (ADS)

Jun, Chen; Wenjun, Hou; Qing, Sheng

After the study of image segmentation, CamShift target tracking algorithm and stereo vision model of space, an improved algorithm based of Frames Difference and a new space point positioning model were proposed, a binocular visual motion tracking system was constructed to verify the improved algorithm and the new model. The problem of the spatial location and pose of the hand detection and tracking have been solved.

Study of Computational Structures for Multiobject Tracking Algorithms

DTIC Science & Technology

1986-12-01

MULTIOBJECT TRACKING ALGORITHMS 12. PERSONAL AUTHOR(S) i Allen, Thomas G .; Kurien, Thomas; Washburn, Robert B. Jr. 13a. TYPE OF REPORT 13b. TIME COVERED 14...mentioned possible restructurings of the tracking algorithm that increase the amount of available parallelism ’ g ~. are investigated. This step is extremely...sufficient for our needs here. In the following section we will examine the structure and computational requirements of the track- g , oriented approach

Strong Tracking Spherical Simplex-Radial Cubature Kalman Filter for Maneuvering Target Tracking.

PubMed

Liu, Hua; Wu, Wen

2017-03-31

Conventional spherical simplex-radial cubature Kalman filter (SSRCKF) for maneuvering target tracking may decline in accuracy and even diverge when a target makes abrupt state changes. To overcome this problem, a novel algorithm named strong tracking spherical simplex-radial cubature Kalman filter (STSSRCKF) is proposed in this paper. The proposed algorithm uses the spherical simplex-radial (SSR) rule to obtain a higher accuracy than cubature Kalman filter (CKF) algorithm. Meanwhile, by introducing strong tracking filter (STF) into SSRCKF and modifying the predicted states' error covariance with a time-varying fading factor, the gain matrix is adjusted on line so that the robustness of the filter and the capability of dealing with uncertainty factors is improved. In this way, the proposed algorithm has the advantages of both STF's strong robustness and SSRCKF's high accuracy. Finally, a maneuvering target tracking problem with abrupt state changes is used to test the performance of the proposed filter. Simulation results show that the STSSRCKF algorithm can get better estimation accuracy and greater robustness for maneuvering target tracking.

Strong Tracking Spherical Simplex-Radial Cubature Kalman Filter for Maneuvering Target Tracking

PubMed Central

Liu, Hua; Wu, Wen

2017-01-01

Conventional spherical simplex-radial cubature Kalman filter (SSRCKF) for maneuvering target tracking may decline in accuracy and even diverge when a target makes abrupt state changes. To overcome this problem, a novel algorithm named strong tracking spherical simplex-radial cubature Kalman filter (STSSRCKF) is proposed in this paper. The proposed algorithm uses the spherical simplex-radial (SSR) rule to obtain a higher accuracy than cubature Kalman filter (CKF) algorithm. Meanwhile, by introducing strong tracking filter (STF) into SSRCKF and modifying the predicted states’ error covariance with a time-varying fading factor, the gain matrix is adjusted on line so that the robustness of the filter and the capability of dealing with uncertainty factors is improved. In this way, the proposed algorithm has the advantages of both STF’s strong robustness and SSRCKF’s high accuracy. Finally, a maneuvering target tracking problem with abrupt state changes is used to test the performance of the proposed filter. Simulation results show that the STSSRCKF algorithm can get better estimation accuracy and greater robustness for maneuvering target tracking. PMID:28362347

Decontaminate feature for tracking: adaptive tracking via evolutionary feature subset

NASA Astrophysics Data System (ADS)

Liu, Qiaoyuan; Wang, Yuru; Yin, Minghao; Ren, Jinchang; Li, Ruizhi

2017-11-01

Although various visual tracking algorithms have been proposed in the last 2-3 decades, it remains a challenging problem for effective tracking with fast motion, deformation, occlusion, etc. Under complex tracking conditions, most tracking models are not discriminative and adaptive enough. When the combined feature vectors are inputted to the visual models, this may lead to redundancy causing low efficiency and ambiguity causing poor performance. An effective tracking algorithm is proposed to decontaminate features for each video sequence adaptively, where the visual modeling is treated as an optimization problem from the perspective of evolution. Every feature vector is compared to a biological individual and then decontaminated via classical evolutionary algorithms. With the optimized subsets of features, the "curse of dimensionality" has been avoided while the accuracy of the visual model has been improved. The proposed algorithm has been tested on several publicly available datasets with various tracking challenges and benchmarked with a number of state-of-the-art approaches. The comprehensive experiments have demonstrated the efficacy of the proposed methodology.

Three-Dimensional Visualization of Particle Tracks.

ERIC Educational Resources Information Center

Julian, Glenn M.

1993-01-01

Suggests ways to bring home to the introductory physics student some of the excitement of recent discoveries in particle physics. Describes particle detectors and encourages the use of the Standard Model along with real images of particle tracks to determine three-dimensional views of tracks. (MVL)

Data fusion for target tracking and classification with wireless sensor network

NASA Astrophysics Data System (ADS)

Pannetier, Benjamin; Doumerc, Robin; Moras, Julien; Dezert, Jean; Canevet, Loic

2016-10-01

In this paper, we address the problem of multiple ground target tracking and classification with information obtained from a unattended wireless sensor network. A multiple target tracking (MTT) algorithm, taking into account road and vegetation information, is proposed based on a centralized architecture. One of the key issue is how to adapt classical MTT approach to satisfy embedded processing. Based on track statistics, the classification algorithm uses estimated location, velocity and acceleration to help to classify targets. The algorithms enables tracking human and vehicles driving both on and off road. We integrate road or trail width and vegetation cover, as constraints in target motion models to improve performance of tracking under constraint with classification fusion. Our algorithm also presents different dynamic models, to palliate the maneuvers of targets. The tracking and classification algorithms are integrated into an operational platform (the fusion node). In order to handle realistic ground target tracking scenarios, we use an autonomous smart computer deposited in the surveillance area. After the calibration step of the heterogeneous sensor network, our system is able to handle real data from a wireless ground sensor network. The performance of system is evaluated in a real exercise for intelligence operation ("hunter hunt" scenario).

Photovoltaic Cells Mppt Algorithm and Design of Controller Monitoring System

NASA Astrophysics Data System (ADS)

Meng, X. Z.; Feng, H. B.

2017-10-01

This paper combined the advantages of each maximum power point tracking (MPPT) algorithm, put forward a kind of algorithm with higher speed and higher precision, based on this algorithm designed a maximum power point tracking controller with ARM. The controller, communication technology and PC software formed a control system. Results of the simulation and experiment showed that the process of maximum power tracking was effective, and the system was stable.

An Improved Interacting Multiple Model Filtering Algorithm Based on the Cubature Kalman Filter for Maneuvering Target Tracking.

PubMed

Zhu, Wei; Wang, Wei; Yuan, Gannan

2016-06-01

In order to improve the tracking accuracy, model estimation accuracy and quick response of multiple model maneuvering target tracking, the interacting multiple models five degree cubature Kalman filter (IMM5CKF) is proposed in this paper. In the proposed algorithm, the interacting multiple models (IMM) algorithm processes all the models through a Markov Chain to simultaneously enhance the model tracking accuracy of target tracking. Then a five degree cubature Kalman filter (5CKF) evaluates the surface integral by a higher but deterministic odd ordered spherical cubature rule to improve the tracking accuracy and the model switch sensitivity of the IMM algorithm. Finally, the simulation results demonstrate that the proposed algorithm exhibits quick and smooth switching when disposing different maneuver models, and it also performs better than the interacting multiple models cubature Kalman filter (IMMCKF), interacting multiple models unscented Kalman filter (IMMUKF), 5CKF and the optimal mode transition matrix IMM (OMTM-IMM).

A novel Gravity-FREAK feature extraction and Gravity-KLT tracking registration algorithm based on iPhone MEMS mobile sensor in mobile environment

PubMed Central

Lin, Fan; Xiao, Bin

2017-01-01

Based on the traditional Fast Retina Keypoint (FREAK) feature description algorithm, this paper proposed a Gravity-FREAK feature description algorithm based on Micro-electromechanical Systems (MEMS) sensor to overcome the limited computing performance and memory resources of mobile devices and further improve the reality interaction experience of clients through digital information added to the real world by augmented reality technology. The algorithm takes the gravity projection vector corresponding to the feature point as its feature orientation, which saved the time of calculating the neighborhood gray gradient of each feature point, reduced the cost of calculation and improved the accuracy of feature extraction. In the case of registration method of matching and tracking natural features, the adaptive and generic corner detection based on the Gravity-FREAK matching purification algorithm was used to eliminate abnormal matches, and Gravity Kaneda-Lucas Tracking (KLT) algorithm based on MEMS sensor can be used for the tracking registration of the targets and robustness improvement of tracking registration algorithm under mobile environment. PMID:29088228

A novel Gravity-FREAK feature extraction and Gravity-KLT tracking registration algorithm based on iPhone MEMS mobile sensor in mobile environment.

PubMed

Hong, Zhiling; Lin, Fan; Xiao, Bin

2017-01-01

Based on the traditional Fast Retina Keypoint (FREAK) feature description algorithm, this paper proposed a Gravity-FREAK feature description algorithm based on Micro-electromechanical Systems (MEMS) sensor to overcome the limited computing performance and memory resources of mobile devices and further improve the reality interaction experience of clients through digital information added to the real world by augmented reality technology. The algorithm takes the gravity projection vector corresponding to the feature point as its feature orientation, which saved the time of calculating the neighborhood gray gradient of each feature point, reduced the cost of calculation and improved the accuracy of feature extraction. In the case of registration method of matching and tracking natural features, the adaptive and generic corner detection based on the Gravity-FREAK matching purification algorithm was used to eliminate abnormal matches, and Gravity Kaneda-Lucas Tracking (KLT) algorithm based on MEMS sensor can be used for the tracking registration of the targets and robustness improvement of tracking registration algorithm under mobile environment.

Multiple object tracking using the shortest path faster association algorithm.

PubMed

Xi, Zhenghao; Liu, Heping; Liu, Huaping; Yang, Bin

2014-01-01

To solve the persistently multiple object tracking in cluttered environments, this paper presents a novel tracking association approach based on the shortest path faster algorithm. First, the multiple object tracking is formulated as an integer programming problem of the flow network. Then we relax the integer programming to a standard linear programming problem. Therefore, the global optimum can be quickly obtained using the shortest path faster algorithm. The proposed method avoids the difficulties of integer programming, and it has a lower worst-case complexity than competing methods but better robustness and tracking accuracy in complex environments. Simulation results show that the proposed algorithm takes less time than other state-of-the-art methods and can operate in real time.

Multiple Object Tracking Using the Shortest Path Faster Association Algorithm

PubMed Central

Liu, Heping; Liu, Huaping; Yang, Bin

2014-01-01

To solve the persistently multiple object tracking in cluttered environments, this paper presents a novel tracking association approach based on the shortest path faster algorithm. First, the multiple object tracking is formulated as an integer programming problem of the flow network. Then we relax the integer programming to a standard linear programming problem. Therefore, the global optimum can be quickly obtained using the shortest path faster algorithm. The proposed method avoids the difficulties of integer programming, and it has a lower worst-case complexity than competing methods but better robustness and tracking accuracy in complex environments. Simulation results show that the proposed algorithm takes less time than other state-of-the-art methods and can operate in real time. PMID:25215322

V-ONSET: Introducing turbulent multiphase flow facility focusing on Lagrangian interfacial transfer dynamics

NASA Astrophysics Data System (ADS)

Salibindla, Ashwanth; Masuk, Ashik Ullah Mohammad; Ni, Rui

2017-11-01

We have designed and constructed a new vertical water tunnel, V-ONSET, to investigate interfacial mass, momentum and energy transfer between two phases in a Lagrangian frame. This system features an independent control of mean flow and turbulence level. The mean flow opposes the rising/falling velocity of the second phase, ``suspending'' the particles and increasing tracking time in the view area. Strong turbulence is generated by shooting 88 digitally-controlled water jets into the test section. The second phase, either bubbles or oil droplets, can be introduced into the test section through a capillary island. In addition to this flow control system, V-ONSET comes with a 3D two-phase visualization system, consisting of high-speed cameras, two-colored LED system, and in-house Lagrangian particle tracking algorithm. This enables us to acquire the Lagrangian evolution of both phases and the interfacial transfer dynamics in between, paving the way for new closure models for two-phase simulations. Financial support for this project was provided by National Science Foundation under Grant Number: 1653389 and 1705246.

FastSim: A Fast Simulation for the SuperB Detector

NASA Astrophysics Data System (ADS)

Andreassen, R.; Arnaud, N.; Brown, D. N.; Burmistrov, L.; Carlson, J.; Cheng, C.-h.; Di Simone, A.; Gaponenko, I.; Manoni, E.; Perez, A.; Rama, M.; Roberts, D.; Rotondo, M.; Simi, G.; Sokoloff, M.; Suzuki, A.; Walsh, J.

2011-12-01

We have developed a parameterized (fast) simulation for detector optimization and physics reach studies of the proposed SuperB Flavor Factory in Italy. Detector components are modeled as thin sections of planes, cylinders, disks or cones. Particle-material interactions are modeled using simplified cross-sections and formulas. Active detectors are modeled using parameterized response functions. Geometry and response parameters are configured using xml files with a custom-designed schema. Reconstruction algorithms adapted from BaBar are used to build tracks and clusters. Multiple sources of background signals can be merged with primary signals. Pattern recognition errors are modeled statistically by randomly misassigning nearby tracking hits. Standard BaBar analysis tuples are used as an event output. Hadronic B meson pair events can be simulated at roughly 10Hz.

Prediction-based Dynamic Energy Management in Wireless Sensor Networks

PubMed Central

Wang, Xue; Ma, Jun-Jie; Wang, Sheng; Bi, Dao-Wei

2007-01-01

Energy consumption is a critical constraint in wireless sensor networks. Focusing on the energy efficiency problem of wireless sensor networks, this paper proposes a method of prediction-based dynamic energy management. A particle filter was introduced to predict a target state, which was adopted to awaken wireless sensor nodes so that their sleep time was prolonged. With the distributed computing capability of nodes, an optimization approach of distributed genetic algorithm and simulated annealing was proposed to minimize the energy consumption of measurement. Considering the application of target tracking, we implemented target position prediction, node sleep scheduling and optimal sensing node selection. Moreover, a routing scheme of forwarding nodes was presented to achieve extra energy conservation. Experimental results of target tracking verified that energy-efficiency is enhanced by prediction-based dynamic energy management.

Active contour-based visual tracking by integrating colors, shapes, and motions.

PubMed

Hu, Weiming; Zhou, Xue; Li, Wei; Luo, Wenhan; Zhang, Xiaoqin; Maybank, Stephen

2013-05-01

In this paper, we present a framework for active contour-based visual tracking using level sets. The main components of our framework include contour-based tracking initialization, color-based contour evolution, adaptive shape-based contour evolution for non-periodic motions, dynamic shape-based contour evolution for periodic motions, and the handling of abrupt motions. For the initialization of contour-based tracking, we develop an optical flow-based algorithm for automatically initializing contours at the first frame. For the color-based contour evolution, Markov random field theory is used to measure correlations between values of neighboring pixels for posterior probability estimation. For adaptive shape-based contour evolution, the global shape information and the local color information are combined to hierarchically evolve the contour, and a flexible shape updating model is constructed. For the dynamic shape-based contour evolution, a shape mode transition matrix is learnt to characterize the temporal correlations of object shapes. For the handling of abrupt motions, particle swarm optimization is adopted to capture the global motion which is applied to the contour in the current frame to produce an initial contour in the next frame.

Image Restoration and Analysis of Influenza Virions Binding to Membrane Receptors Reveal Adhesion-Strengthening Kinetics

PubMed Central

Lee, Donald W.; Hsu, Hung-Lun; Bacon, Kaitlyn B.; Daniel, Susan

2016-01-01

With the development of single-particle tracking (SPT) microscopy and host membrane mimics called supported lipid bilayers (SLBs), stochastic virus-membrane binding interactions can be studied in depth while maintaining control over host receptor type and concentration. However, several experimental design challenges and quantitative image analysis limitations prevent the widespread use of this approach. One main challenge of SPT studies is the low signal-to-noise ratio of SPT videos, which is sometimes inevitable due to small particle sizes, low quantum yield of fluorescent dyes, and photobleaching. These situations could render current particle tracking software to yield biased binding kinetic data caused by intermittent tracking error. Hence, we developed an effective image restoration algorithm for SPT applications called STAWASP that reveals particles with a signal-to-noise ratio of 2.2 while preserving particle features. We tested our improvements to the SPT binding assay experiment and imaging procedures by monitoring X31 influenza virus binding to α2,3 sialic acid glycolipids. Our interests lie in how slight changes to the peripheral oligosaccharide structures can affect the binding rate and residence times of viruses. We were able to detect viruses binding weakly to a glycolipid called GM3, which was undetected via assays such as surface plasmon resonance. The binding rate was around 28 folds higher when the virus bound to a different glycolipid called GD1a, which has a sialic acid group extending further away from the bilayer surface than GM3. The improved imaging allowed us to obtain binding residence time distributions that reflect an adhesion-strengthening mechanism via multivalent bonds. We empirically fitted these distributions using a time-dependent unbinding rate parameter, koff, which diverges from standard treatment of koff as a constant. We further explain how to convert these models to fit ensemble-averaged binding data obtained by assays such as surface plasmon resonance. PMID:27695072

Developing the fuzzy c-means clustering algorithm based on maximum entropy for multitarget tracking in a cluttered environment

NASA Astrophysics Data System (ADS)

Chen, Xiao; Li, Yaan; Yu, Jing; Li, Yuxing

2018-01-01

For fast and more effective implementation of tracking multiple targets in a cluttered environment, we propose a multiple targets tracking (MTT) algorithm called maximum entropy fuzzy c-means clustering joint probabilistic data association that combines fuzzy c-means clustering and the joint probabilistic data association (PDA) algorithm. The algorithm uses the membership value to express the probability of the target originating from measurement. The membership value is obtained through fuzzy c-means clustering objective function optimized by the maximum entropy principle. When considering the effect of the public measurement, we use a correction factor to adjust the association probability matrix to estimate the state of the target. As this algorithm avoids confirmation matrix splitting, it can solve the high computational load problem of the joint PDA algorithm. The results of simulations and analysis conducted for tracking neighbor parallel targets and cross targets in a different density cluttered environment show that the proposed algorithm can realize MTT quickly and efficiently in a cluttered environment. Further, the performance of the proposed algorithm remains constant with increasing process noise variance. The proposed algorithm has the advantages of efficiency and low computational load, which can ensure optimum performance when tracking multiple targets in a dense cluttered environment.

Tracking Small Artists

NASA Astrophysics Data System (ADS)

Russell, James C.; Klette, Reinhard; Chen, Chia-Yen

Tracks of small animals are important in environmental surveillance, where pattern recognition algorithms allow species identification of the individuals creating tracks. These individuals can also be seen as artists, presented in their natural environments with a canvas upon which they can make prints. We present tracks of small mammals and reptiles which have been collected for identification purposes, and re-interpret them from an esthetic point of view. We re-classify these tracks not by their geometric qualities as pattern recognition algorithms would, but through interpreting the 'artist', their brush strokes and intensity. We describe the algorithms used to enhance and present the work of the 'artists'.

Interacting with target tracking algorithms in a gaze-enhanced motion video analysis system

NASA Astrophysics Data System (ADS)

Hild, Jutta; Krüger, Wolfgang; Heinze, Norbert; Peinsipp-Byma, Elisabeth; Beyerer, Jürgen

2016-05-01

Motion video analysis is a challenging task, particularly if real-time analysis is required. It is therefore an important issue how to provide suitable assistance for the human operator. Given that the use of customized video analysis systems is more and more established, one supporting measure is to provide system functions which perform subtasks of the analysis. Recent progress in the development of automated image exploitation algorithms allow, e.g., real-time moving target tracking. Another supporting measure is to provide a user interface which strives to reduce the perceptual, cognitive and motor load of the human operator for example by incorporating the operator's visual focus of attention. A gaze-enhanced user interface is able to help here. This work extends prior work on automated target recognition, segmentation, and tracking algorithms as well as about the benefits of a gaze-enhanced user interface for interaction with moving targets. We also propose a prototypical system design aiming to combine both the qualities of the human observer's perception and the automated algorithms in order to improve the overall performance of a real-time video analysis system. In this contribution, we address two novel issues analyzing gaze-based interaction with target tracking algorithms. The first issue extends the gaze-based triggering of a target tracking process, e.g., investigating how to best relaunch in the case of track loss. The second issue addresses the initialization of tracking algorithms without motion segmentation where the operator has to provide the system with the object's image region in order to start the tracking algorithm.

Charged-particle multiplicities in proton-proton collisions at √{s} = 0.9 to 8 TeV

NASA Astrophysics Data System (ADS)

Adam, J.; Adamová, D.; Aggarwal, M. M.; Rinella, G. Aglieri; Agnello, M.; Agrawal, N.; Ahammed, Z.; Ahmed, I.; Ahn, S. U.; Aiola, S.; Akindinov, A.; Alam, S. N.; Aleksandrov, D.; Alessandro, B.; Alexandre, D.; Molina, R. Alfaro; Alici, A.; Alkin, A.; Almaraz, J. R. M.; Alme, J.; Alt, T.; Altinpinar, S.; Altsybeev, I.; Prado, C. Alves Garcia; Andrei, C.; Andronic, A.; Anguelov, V.; Anielski, J.; Antičić, T.; Antinori, F.; Antonioli, P.; Aphecetche, L.; Appelshäuser, H.; Arcelli, S.; Arnaldi, R.; Arnold, O. W.; Arsene, I. C.; Arslandok, M.; Audurier, B.; Augustinus, A.; Averbeck, R.; Azmi, M. D.; Badalà, A.; Baek, Y. W.; Bagnasco, S.; Bailhache, R.; Bala, R.; Baldisseri, A.; Baral, R. C.; Barbano, A. M.; Barbera, R.; Barile, F.; Barnaföldi, G. G.; Barnby, L. S.; Barret, V.; Bartalini, P.; Barth, K.; Bartke, J.; Bartsch, E.; Basile, M.; Bastid, N.; Basu, S.; Bathen, B.; Batigne, G.; Camejo, A. Batista; Batyunya, B.; Batzing, P. C.; Bearden, I. G.; Beck, H.; Bedda, C.; Behera, N. K.; Belikov, I.; Bellini, F.; Martinez, H. Bello; Bellwied, R.; Belmont, R.; Belmont-Moreno, E.; Belyaev, V.; Bencedi, G.; Beole, S.; Berceanu, I.; Bercuci, A.; Berdnikov, Y.; Berenyi, D.; Bertens, R. A.; Berzano, D.; Betev, L.; Bhasin, A.; Bhat, I. R.; Bhati, A. K.; Bhattacharjee, B.; Bhom, J.; Bianchi, L.; Bianchi, N.; Bianchin, C.; Bielčík, J.; Bielčíková, J.; Bilandzic, A.; Biswas, R.; Biswas, S.; Bjelogrlic, S.; Blair, J. T.; Blau, D.; Blume, C.; Bock, F.; Bogdanov, A.; Bøggild, H.; Boldizsár, L.; Bombara, M.; Book, J.; Borel, H.; Borissov, A.; Borri, M.; Bossú, F.; Botta, E.; Böttger, S.; Bourjau, C.; Braun-Munzinger, P.; Bregant, M.; Breitner, T.; Broker, T. A.; Browning, T. A.; Broz, M.; Brucken, E. J.; Bruna, E.; Bruno, G. E.; Budnikov, D.; Buesching, H.; Bufalino, S.; Buncic, P.; Busch, O.; Buthelezi, Z.; Butt, J. B.; Buxton, J. T.; Caffarri, D.; Cai, X.; Caines, H.; Diaz, L. Calero; Caliva, A.; Villar, E. Calvo; Camerini, P.; Carena, F.; Carena, W.; Carnesecchi, F.; Castellanos, J. Castillo; Castro, A. J.; Casula, E. A. R.; Sanchez, C. Ceballos; Cepila, J.; Cerello, P.; Cerkala, J.; Chang, B.; Chapeland, S.; Chartier, M.; Charvet, J. L.; Chattopadhyay, S.; Chattopadhyay, S.; Chelnokov, V.; Cherney, M.; Cheshkov, C.; Cheynis, B.; Barroso, V. Chibante; Chinellato, D. D.; Cho, S.; Chochula, P.; Choi, K.; Chojnacki, M.; Choudhury, S.; Christakoglou, P.; Christensen, C. H.; Christiansen, P.; Chujo, T.; Chung, S. U.; Cicalo, C.; Cifarelli, L.; Cindolo, F.; Cleymans, J.; Colamaria, F.; Colella, D.; Collu, A.; Colocci, M.; Balbastre, G. Conesa; Valle, Z. Conesa del; Connors, M. E.; Contreras, J. G.; Cormier, T. M.; Morales, Y. Corrales; Maldonado, I. Cortés; Cortese, P.; Cosentino, M. R.; Costa, F.; Crochet, P.; Albino, R. Cruz; Cuautle, E.; Cunqueiro, L.; Dahms, T.; Dainese, A.; Danu, A.; Das, D.; Das, I.; Das, S.; Dash, A.; Dash, S.; De, S.; De Caro, A.; de Cataldo, G.; de Conti, C.; de Cuveland, J.; De Falco, A.; De Gruttola, D.; De Marco, N.; De Pasquale, S.; Deisting, A.; Deloff, A.; Dénes, E.; Deplano, C.; Dhankher, P.; Di Bari, D.; Di Mauro, A.; Di Nezza, P.; Corchero, M. A. Diaz; Dietel, T.; Dillenseger, P.; Divià, R.; Djuvsland, Ø.; Dobrin, A.; Gimenez, D. Domenicis; Dönigus, B.; Dordic, O.; Drozhzhova, T.; Dubey, A. K.; Dubla, A.; Ducroux, L.; Dupieux, P.; Ehlers, R. J.; Elia, D.; Engel, H.; Epple, E.; Erazmus, B.; Erdemir, I.; Erhardt, F.; Espagnon, B.; Estienne, M.; Esumi, S.; Eum, J.; Evans, D.; Evdokimov, S.; Eyyubova, G.; Fabbietti, L.; Fabris, D.; Faivre, J.; Fantoni, A.; Fasel, M.; Feldkamp, L.; Feliciello, A.; Feofilov, G.; Ferencei, J.; Téllez, A. Fernández; Ferreiro, E. G.; Ferretti, A.; Festanti, A.; Feuillard, V. J. G.; Figiel, J.; Figueredo, M. A. S.; Filchagin, S.; Finogeev, D.; Fionda, F. M.; Fiore, E. M.; Fleck, M. G.; Floris, M.; Foertsch, S.; Foka, P.; Fokin, S.; Fragiacomo, E.; Francescon, A.; Frankenfeld, U.; Fuchs, U.; Furget, C.; Furs, A.; Girard, M. Fusco; Gaardhøje, J. J.; Gagliardi, M.; Gago, A. M.; Gallio, M.; Gangadharan, D. R.; Ganoti, P.; Gao, C.; Garabatos, C.; Garcia-Solis, E.; Gargiulo, C.; Gasik, P.; Gauger, E. F.; Germain, M.; Gheata, A.; Gheata, M.; Ghosh, P.; Ghosh, S. K.; Gianotti, P.; Giubellino, P.; Giubilato, P.; Gladysz-Dziadus, E.; Glässel, P.; Coral, D. M. Goméz; Ramirez, A. Gomez; Gonzalez, V.; González-Zamora, P.; Gorbunov, S.; Görlich, L.; Gotovac, S.; Grabski, V.; Grachov, O. A.; Graczykowski, L. K.; Graham, K. L.; Grelli, A.; Grigoras, A.; Grigoras, C.; Grigoriev, V.; Grigoryan, A.; Grigoryan, S.; Grinyov, B.; Grion, N.; Gronefeld, J. M.; Grosse-Oetringhaus, J. F.; Grossiord, J.-Y.; Grosso, R.; Guber, F.; Guernane, R.; Guerzoni, B.; Gulbrandsen, K.; Gunji, T.; Gupta, A.; Gupta, R.; Haake, R.; Haaland, Ø.; Hadjidakis, C.; Haiduc, M.; Hamagaki, H.; Hamar, G.; Harris, J. W.; Harton, A.; Hatzifotiadou, D.; Hayashi, S.; Heckel, S. T.; Heide, M.; Helstrup, H.; Herghelegiu, A.; Corral, G. Herrera; Hess, B. A.; Hetland, K. F.; Hillemanns, H.; Hippolyte, B.; Hosokawa, R.; Hristov, P.; Huang, M.; Humanic, T. J.; Hussain, N.; Hussain, T.; Hutter, D.; Hwang, D. S.; Ilkaev, R.; Inaba, M.; Ippolitov, M.; Irfan, M.; Ivanov, M.; Ivanov, V.; Izucheev, V.; Jachołkowski, A.; Jacobs, P. M.; Jadhav, M. B.; Jadlovska, S.; Jadlovsky, J.; Jahnke, C.; Jakubowska, M. J.; Jang, H. J.; Janik, M. A.; Jayarathna, P. H. S. Y.; Jena, C.; Jena, S.; Bustamante, R. T. Jimenez; Jones, P. G.; Jung, H.; Jusko, A.; Kalinak, P.; Kalweit, A.; Kamin, J.; Kang, J. H.; Kaplin, V.; Kar, S.; Uysal, A. Karasu; Karavichev, O.; Karavicheva, T.; Karayan, L.; Karpechev, E.; Kebschull, U.; Keidel, R.; Keijdener, D. L. D.; Keil, M.; Khan, M. Mohisin; Khan, P.; Khan, S. A.; Khanzadeev, A.; Kharlov, Y.; Kileng, B.; Kim, B.; Kim, D. W.; Kim, D. J.; Kim, D.; Kim, H.; Kim, J. S.; Kim, M.; Kim, M.; Kim, S.; Kim, T.; Kirsch, S.; Kisel, I.; Kiselev, S.; Kisiel, A.; Kiss, G.; Klay, J. L.; Klein, C.; Klein, J.; Klein-Bösing, C.; Klewin, S.; Kluge, A.; Knichel, M. L.; Knospe, A. G.; Kobayashi, T.; Kobdaj, C.; Kofarago, M.; Kollegger, T.; Kolojvari, A.; Kondratiev, V.; Kondratyeva, N.; Kondratyuk, E.; Konevskikh, A.; Kopcik, M.; Kour, M.; Kouzinopoulos, C.; Kovalenko, O.; Kovalenko, V.; Kowalski, M.; Meethaleveedu, G. Koyithatta; Králik, I.; Kravčáková, A.; Kretz, M.; Krivda, M.; Krizek, F.; Kryshen, E.; Krzewicki, M.; Kubera, A. M.; Kučera, V.; Kuhn, C.; Kuijer, P. G.; Kumar, A.; Kumar, J.; Kumar, L.; Kumar, S.; Kurashvili, P.; Kurepin, A.; Kurepin, A. B.; Kuryakin, A.; Kweon, M. J.; Kwon, Y.; Pointe, S. L. La; Rocca, P. La; de Guevara, P. Ladron; Fernandes, C. Lagana; Lakomov, I.; Langoy, R.; Lara, C.; Lardeux, A.; Lattuca, A.; Laudi, E.; Lea, R.; Leardini, L.; Lee, G. R.; Lee, S.; Lehas, F.; Lemmon, R. C.; Lenti, V.; Leogrande, E.; Monzón, I. León; Vargas, H. León; Leoncino, M.; Lévai, P.; Li, S.; Li, X.; Lien, J.; Lietava, R.; Lindal, S.; Lindenstruth, V.; Lippmann, C.; Lisa, M. A.; Ljunggren, H. M.; Lodato, D. F.; Loenne, P. I.; Loginov, V.; Loizides, C.; Lopez, X.; Torres, E. López; Lowe, A.; Luettig, P.; Lunardon, M.; Luparello, G.; Maevskaya, A.; Mager, M.; Mahajan, S.; Mahmood, S. M.; Maire, A.; Majka, R. D.; Malaev, M.; Cervantes, I. Maldonado; Malinina, L.; Mal'Kevich, D.; Malzacher, P.; Mamonov, A.; Manko, V.; Manso, F.; Manzari, V.; Marchisone, M.; Mareš, J.; Margagliotti, G. V.; Margotti, A.; Margutti, J.; Marín, A.; Markert, C.; Marquard, M.; Martin, N. A.; Blanco, J. Martin; Martinengo, P.; Martínez, M. I.; García, G. Martínez; Pedreira, M. Martinez; Mas, A.; Masciocchi, S.; Masera, M.; Masoni, A.; Massacrier, L.; Mastroserio, A.; Matyja, A.; Mayer, C.; Mazer, J.; Mazzoni, M. A.; Mcdonald, D.; Meddi, F.; Melikyan, Y.; Menchaca-Rocha, A.; Meninno, E.; Pérez, J. Mercado; Meres, M.; Miake, Y.; Mieskolainen, M. M.; Mikhaylov, K.; Milano, L.; Milosevic, J.; Minervini, L. M.; Mischke, A.; Mishra, A. N.; Miśkowiec, D.; Mitra, J.; Mitu, C. M.; Mohammadi, N.; Mohanty, B.; Molnar, L.; Zetina, L. Montaño; Montes, E.; De Godoy, D. A. Moreira; Moreno, L. A. P.; Moretto, S.; Morreale, A.; Morsch, A.; Muccifora, V.; Mudnic, E.; Mühlheim, D.; Muhuri, S.; Mukherjee, M.; Mulligan, J. D.; Munhoz, M. G.; Munzer, R. H.; Murray, S.; Musa, L.; Musinsky, J.; Naik, B.; Nair, R.; Nandi, B. K.; Nania, R.; Nappi, E.; Naru, M. U.; da Luz, H. Natal; Nattrass, C.; Nayak, K.; Nayak, T. K.; Nazarenko, S.; Nedosekin, A.; Nellen, L.; Ng, F.; Nicassio, M.; Niculescu, M.; Niedziela, J.; Nielsen, B. S.; Nikolaev, S.; Nikulin, S.; Nikulin, V.; Noferini, F.; Nomokonov, P.; Nooren, G.; Noris, J. C. C.; Norman, J.; Nyanin, A.; Nystrand, J.; Oeschler, H.; Oh, S.; Oh, S. K.; Ohlson, A.; Okatan, A.; Okubo, T.; Olah, L.; Oleniacz, J.; Silva, A. C. Oliveira Da; Oliver, M. H.; Onderwaater, J.; Oppedisano, C.; Orava, R.; Velasquez, A. Ortiz; Oskarsson, A.; Otwinowski, J.; Oyama, K.; Ozdemir, M.; Pachmayer, Y.; Pagano, P.; Paić, G.; Pal, S. K.; Pan, J.; Pandey, A. K.; Papcun, P.; Papikyan, V.; Pappalardo, G. S.; Pareek, P.; Park, W. J.; Parmar, S.; Passfeld, A.; Paticchio, V.; Patra, R. N.; Paul, B.; Peitzmann, T.; Costa, H. Pereira Da; Filho, E. Pereira De Oliveira; Peresunko, D.; Lara, C. E. Pérez; Lezama, E. Perez; Peskov, V.; Pestov, Y.; Petráček, V.; Petrov, V.; Petrovici, M.; Petta, C.; Piano, S.; Pikna, M.; Pillot, P.; Pinazza, O.; Pinsky, L.; Piyarathna, D. B.; oskoń, M. Pł; Planinic, M.; Pluta, J.; Pochybova, S.; Podesta-Lerma, P. L. M.; Poghosyan, M. G.; Polichtchouk, B.; Poljak, N.; Poonsawat, W.; Pop, A.; Porteboeuf-Houssais, S.; Porter, J.; Pospisil, J.; Prasad, S. K.; Preghenella, R.; Prino, F.; Pruneau, C. A.; Pshenichnov, I.; Puccio, M.; Puddu, G.; Pujahari, P.; Punin, V.; Putschke, J.; Qvigstad, H.; Rachevski, A.; Raha, S.; Rajput, S.; Rak, J.; Rakotozafindrabe, A.; Ramello, L.; Rami, F.; Raniwala, R.; Raniwala, S.; Räsänen, S. S.; Rascanu, B. T.; Rathee, D.; Read, K. F.; Redlich, K.; Reed, R. J.; Rehman, A.; Reichelt, P.; Reidt, F.; Ren, X.; Renfordt, R.; Reolon, A. R.; Reshetin, A.; Revol, J.-P.; Reygers, K.; Riabov, V.; Ricci, R. A.; Richert, T.; Richter, M.; Riedler, P.; Riegler, W.; Riggi, F.; Ristea, C.; Rocco, E.; Cahuantzi, M. Rodríguez; Manso, A. Rodriguez; Røed, K.; Rogochaya, E.; Rohr, D.; Röhrich, D.; Romita, R.; Ronchetti, F.; Ronflette, L.; Rosnet, P.; Rossi, A.; Roukoutakis, F.; Roy, A.; Roy, C.; Roy, P.; Montero, A. J. Rubio; Rui, R.; Russo, R.; Ryabinkin, E.; Ryabov, Y.; Rybicki, A.; Sadovsky, S.; Šafařík, K.; Sahlmuller, B.; Sahoo, P.; Sahoo, R.; Sahoo, S.; Sahu, P. K.; Saini, J.; Sakai, S.; Saleh, M. A.; Salzwedel, J.; Sambyal, S.; Samsonov, V.; Šándor, L.; Sandoval, A.; Sano, M.; Sarkar, D.; Scapparone, E.; Scarlassara, F.; Schiaua, C.; Schicker, R.; Schmidt, C.; Schmidt, H. R.; Schuchmann, S.; Schukraft, J.; Schulc, M.; Schuster, T.; Schutz, Y.; Schwarz, K.; Schweda, K.; Scioli, G.; Scomparin, E.; Scott, R.; Šefčík, M.; Seger, J. E.; Sekiguchi, Y.; Sekihata, D.; Selyuzhenkov, I.; Senosi, K.; Senyukov, S.; Serradilla, E.; Sevcenco, A.; Shabanov, A.; Shabetai, A.; Shadura, O.; Shahoyan, R.; Shangaraev, A.; Sharma, A.; Sharma, M.; Sharma, M.; Sharma, N.; Shigaki, K.; Shtejer, K.; Sibiriak, Y.; Siddhanta, S.; Sielewicz, K. M.; Siemiarczuk, T.; Silvermyr, D.; Silvestre, C.; Simatovic, G.; Simonetti, G.; Singaraju, R.; Singh, R.; Singha, S.; Singhal, V.; Sinha, B. C.; Sinha, T.; Sitar, B.; Sitta, M.; Skaali, T. B.; Slupecki, M.; Smirnov, N.; Snellings, R. J. M.; Snellman, T. W.; Søgaard, C.; Song, J.; Song, M.; Song, Z.; Soramel, F.; Sorensen, S.; Sozzi, F.; Spacek, M.; Spiriti, E.; Sputowska, I.; Spyropoulou-Stassinaki, M.; Stachel, J.; Stan, I.; Stefanek, G.; Stenlund, E.; Steyn, G.; Stiller, J. H.; Stocco, D.; Strmen, P.; Suaide, A. A. P.; Sugitate, T.; Suire, C.; Suleymanov, M.; Suljic, M.; Sultanov, R.; Šumbera, M.; Szabo, A.; de Toledo, A. Szanto; Szarka, I.; Szczepankiewicz, A.; Szymanski, M.; Tabassam, U.; Takahashi, J.; Tambave, G. J.; Tanaka, N.; Tangaro, M. A.; Tarhini, M.; Tariq, M.; Tarzila, M. G.; Tauro, A.; Muñoz, G. Tejeda; Telesca, A.; Terasaki, K.; Terrevoli, C.; Teyssier, B.; Thäder, J.; Thomas, D.; Tieulent, R.; Timmins, A. R.; Toia, A.; Trogolo, S.; Trombetta, G.; Trubnikov, V.; Trzaska, W. H.; Tsuji, T.; Tumkin, A.; Turrisi, R.; Tveter, T. S.; Ullaland, K.; Uras, A.; Usai, G. L.; Utrobicic, A.; Vajzer, M.; Vala, M.; Palomo, L. Valencia; Vallero, S.; Van Der Maarel, J.; Van Hoorne, J. W.; van Leeuwen, M.; Vanat, T.; Vyvre, P. Vande; Varga, D.; Vargas, A.; Vargyas, M.; Varma, R.; Vasileiou, M.; Vasiliev, A.; Vauthier, A.; Vechernin, V.; Veen, A. M.; Veldhoen, M.; Velure, A.; Venaruzzo, M.; Vercellin, E.; Limón, S. Vergara; Vernet, R.; Verweij, M.; Vickovic, L.; Viesti, G.; Viinikainen, J.; Vilakazi, Z.; Baillie, O. Villalobos; Tello, A. Villatoro; Vinogradov, A.; Vinogradov, L.; Vinogradov, Y.; Virgili, T.; Vislavicius, V.; Viyogi, Y. P.; Vodopyanov, A.; Völkl, M. A.; Voloshin, K.; Voloshin, S. A.; Volpe, G.; von Haller, B.; Vorobyev, I.; Vranic, D.; Vrláková, J.; Vulpescu, B.; Vyushin, A.; Wagner, B.; Wagner, J.; Wang, H.; Wang, M.; Watanabe, D.; Watanabe, Y.; Weber, M.; Weber, S. G.; Weiser, D. F.; Wessels, J. P.; Westerhoff, U.; Whitehead, A. M.; Wiechula, J.; Wikne, J.; Wilde, M.; Wilk, G.; Wilkinson, J.; Williams, M. C. S.; Windelband, B.; Winn, M.; Yaldo, C. G.; Yang, H.; Yang, P.; Yano, S.; Yasar, C.; Yin, Z.; Yokoyama, H.; Yoo, I.-K.; Yoon, J. H.; Yurchenko, V.; Yushmanov, I.; Zaborowska, A.; Zaccolo, V.; Zaman, A.; Zampolli, C.; Zanoli, H. J. C.; Zaporozhets, S.; Zardoshti, N.; Zarochentsev, A.; Závada, P.; Zaviyalov, N.; Zbroszczyk, H.; Zgura, I. S.; Zhalov, M.; Zhang, H.; Zhang, X.; Zhang, Y.; Zhang, C.; Zhang, Z.; Zhao, C.; Zhigareva, N.; Zhou, D.; Zhou, Y.; Zhou, Z.; Zhu, H.; Zhu, J.; Zichichi, A.; Zimmermann, A.; Zimmermann, M. B.; Zinovjev, G.; Zyzak, M.

2017-01-01

A detailed study of pseudorapidity densities and multiplicity distributions of primary charged particles produced in proton-proton collisions, at √{s} = 0.9, 2.36, 2.76, 7 and 8 TeV, in the pseudorapidity range |η |<2, was carried out using the ALICE detector. Measurements were obtained for three event classes: inelastic, non-single diffractive and events with at least one charged particle in the pseudorapidity interval |η |<1. The use of an improved track-counting algorithm combined with ALICE's measurements of diffractive processes allows a higher precision compared to our previous publications. A KNO scaling study was performed in the pseudorapidity intervals |η |< 0.5, 1.0 and 1.5. The data are compared to other experimental results and to models as implemented in Monte Carlo event generators PHOJET and recent tunes of PYTHIA6, PYTHIA8 and EPOS.

Charged-particle multiplicities in proton–proton collisions at $$\\sqrt{s} = 0.9$$ s = 0.9 to 8 TeV

DOE PAGES

Adam, J.; Adamová, D.; Aggarwal, M. M.; ...

2017-01-17

A detailed study of pseudorapidity densities and multiplicity distributions of primary charged particles produced in proton–proton collisions, at s= 0.9, 2.36, 2.76, 7 and 8 TeV, in the pseudorapidity range | η| < 2 , was carried out using the ALICE detector. Measurements were obtained for three event classes: inelastic, non-single diffractive and events with at least one charged particle in the pseudorapidity interval | η| < 1. The use of an improved track-counting algorithm combined with ALICE’s measurements of diffractive processes allows a higher precision compared to our previous publications. A KNO scaling study was performed in the pseudorapiditymore » intervals | η| < 0.5, 1.0 and 1.5. The data are compared to other experimental results and to models as implemented in Monte Carlo event generators PHOJET and recent tunes of PYTHIA6, PYTHIA8 and EPOS.« less

SU-E-T-764: Track Repeating Algorithm for Proton Therapy Applied to Intensity Modulated Proton Therapy for Head-And-Neck Patients

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yepes, P; Mirkovic, D; Mohan, R

Purpose: To determine the suitability of fast Monte Carlo techniques for dose calculation in particle therapy based on track-repeating algorithm for Intensity Modulated Proton Therapy, IMPT. The application of this technique will make possible detailed retrospective studies of large cohort of patients, which may lead to a better determination of Relative Biological Effects from the analysis of patient data. Methods: A cohort of six head-and-neck patients treated at the University of Texas MD Anderson Cancer Center with IMPT were utilized. The dose distributions were calculated with the standard Treatment Plan System, TPS, MCNPX, GEANT4 and FDC, a fast track-repeating algorithmmore » for proton therapy for the verification and the patient plans. FDC is based on a GEANT4 database of trajectories of protons in a water. The obtained dose distributions were compared to each other utilizing the g-index criteria for 3mm-3% and 2mm-2%, for the maximum spatial and dose differences. The γ-index was calculated for voxels with a dose at least 10% of the maximum delivered dose. Dose Volume Histograms are also calculated for the various dose distributions. Results: Good agreement between GEANT4 and FDC is found with less than 1% of the voxels with a γ-index larger than 1 for 2 mm-2%. The agreement between MCNPX with FDC is within the requirements of clinical standards, even though it is slightly worse than the comparison with GEANT4.The comparison with TPS yielded larger differences, what is also to be expected because pencil beam algorithm do not always performed well in highly inhomogeneous areas like head-and-neck. Conclusion: The good agreement between a track-repeating algorithm and a full Monte Carlo for a large cohort of patients and a challenging, site like head-and-neck, opens the path to systematic and detailed studies of large cohorts, which may yield better understanding of biological effects.« less

Particle track identification: application of a new technique to apollo helmets.

PubMed

Fleischer, R L; Hart, H R; Giard, W R

1970-12-11

The Apollo helmets are being used to record the dose of heavy particles to which astronauts are exposed on space missions. An improved method for examining and identifying the etched tracks of heavy charged particles consists of replicating tracks and measuring the etching rate as a function of position along the track. Tracks have been observed in Apollo helmets that correspond to ionized atoms heavier than iron.

Analysis of wind-blown sand movement over transverse dunes.

PubMed

Jiang, Hong; Huang, Ning; Zhu, Yuanjian

2014-12-01

Wind-blown sand movement often occurs in a very complicated desert environment where sand dunes and ripples are the basic forms. However, most current studies on the theoretic and numerical models of wind-blown sand movement only consider ideal conditions such as steady wind velocity, flat sand surface, etc. In fact, the windward slope gradient plays a great role in the lift-off and sand particle saltation. In this paper, we propose a numerical model for the coupling effect between wind flow and saltating sand particles to simulate wind-blown sand movement over the slope surface and use the SIMPLE algorithm to calculate wind flow and simulate sands transport by tracking sand particle trajectories. We furthermore compare the result of numerical simulation with wind tunnel experiments. These results prove that sand particles have obvious effect on wind flow, especially that over the leeward slope. This study is a preliminary study on windblown sand movement in a complex terrain, and is of significance in the control of dust storms and land desertification.

Analysis of Wind-blown Sand Movement over Transverse Dunes

PubMed Central

Jiang, Hong; Huang, Ning; Zhu, Yuanjian

2014-01-01

Wind-blown sand movement often occurs in a very complicated desert environment where sand dunes and ripples are the basic forms. However, most current studies on the theoretic and numerical models of wind-blown sand movement only consider ideal conditions such as steady wind velocity, flat sand surface, etc. In fact, the windward slope gradient plays a great role in the lift-off and sand particle saltation. In this paper, we propose a numerical model for the coupling effect between wind flow and saltating sand particles to simulate wind-blown sand movement over the slope surface and use the SIMPLE algorithm to calculate wind flow and simulate sands transport by tracking sand particle trajectories. We furthermore compare the result of numerical simulation with wind tunnel experiments. These results prove that sand particles have obvious effect on wind flow, especially that over the leeward slope. This study is a preliminary study on windblown sand movement in a complex terrain, and is of significance in the control of dust storms and land desertification. PMID:25434372

Simultaneous acquisition of trajectory and fluorescence lifetime of moving single particles

NASA Astrophysics Data System (ADS)

Wu, Qianqian; Qi, Jing; Lin, Danying; Yan, Wei; Hu, Rui; Peng, Xiao; Qu, Junle

2017-02-01

Fluorescence lifetime imaging (FLIM) has been a powerful tool in life science because it can reveal the interactions of an excited fluorescent molecule and its environment. The combination with two-photon excitation (TPE) and timecorrelated single photon counting (TCSPC) provides it the ability of optical sectioning, high time resolution and detection efficiency. In previous work, we have introduced a two-dimensional acousto-optic deflector (AOD) into TCSPC-based FLIM to achieve fast and flexible FLIM. In this work, we combined the AOD-FLIM system with a single particle tracking (SPT) setup and algorithm and developed an SPT-FLIM system. Using the system, we acquired the trajectory and fluorescence lifetime of a moving particle simultaneously and reconstructed a life-time-marked pseudocolored trajectory, which might reflect dynamic interaction between the moving particle and its local environment along its motion trail. The results indicated the potential of the technique for studying the interaction between specific moving biological macromolecules and the ambient micro-environment in live cells.

Random-subset fitting of digital holograms for fast three-dimensional particle tracking [invited].

PubMed

Dimiduk, Thomas G; Perry, Rebecca W; Fung, Jerome; Manoharan, Vinothan N

2014-09-20

Fitting scattering solutions to time series of digital holograms is a precise way to measure three-dimensional dynamics of microscale objects such as colloidal particles. However, this inverse-problem approach is computationally expensive. We show that the computational time can be reduced by an order of magnitude or more by fitting to a random subset of the pixels in a hologram. We demonstrate our algorithm on experimentally measured holograms of micrometer-scale colloidal particles, and we show that 20-fold increases in speed, relative to fitting full frames, can be attained while introducing errors in the particle positions of 10 nm or less. The method is straightforward to implement and works for any scattering model. It also enables a parallelization strategy wherein random-subset fitting is used to quickly determine initial guesses that are subsequently used to fit full frames in parallel. This approach may prove particularly useful for studying rare events, such as nucleation, that can only be captured with high frame rates over long times.

A fast hybrid algorithm combining regularized motion tracking and predictive search for reducing the occurrence of large displacement errors.

PubMed

Jiang, Jingfeng; Hall, Timothy J

2011-04-01

A hybrid approach that inherits both the robustness of the regularized motion tracking approach and the efficiency of the predictive search approach is reported. The basic idea is to use regularized speckle tracking to obtain high-quality seeds in an explorative search that can be used in the subsequent intelligent predictive search. The performance of the hybrid speckle-tracking algorithm was compared with three published speckle-tracking methods using in vivo breast lesion data. We found that the hybrid algorithm provided higher displacement quality metric values, lower root mean squared errors compared with a locally smoothed displacement field, and higher improvement ratios compared with the classic block-matching algorithm. On the basis of these comparisons, we concluded that the hybrid method can further enhance the accuracy of speckle tracking compared with its real-time counterparts, at the expense of slightly higher computational demands. © 2011 IEEE

A parallel electrostatic Particle-in-Cell method on unstructured tetrahedral grids for large-scale bounded collisionless plasma simulations

NASA Astrophysics Data System (ADS)

Averkin, Sergey N.; Gatsonis, Nikolaos A.

2018-06-01

An unstructured electrostatic Particle-In-Cell (EUPIC) method is developed on arbitrary tetrahedral grids for simulation of plasmas bounded by arbitrary geometries. The electric potential in EUPIC is obtained on cell vertices from a finite volume Multi-Point Flux Approximation of Gauss' law using the indirect dual cell with Dirichlet, Neumann and external circuit boundary conditions. The resulting matrix equation for the nodal potential is solved with a restarted generalized minimal residual method (GMRES) and an ILU(0) preconditioner algorithm, parallelized using a combination of node coloring and level scheduling approaches. The electric field on vertices is obtained using the gradient theorem applied to the indirect dual cell. The algorithms for injection, particle loading, particle motion, and particle tracking are parallelized for unstructured tetrahedral grids. The algorithms for the potential solver, electric field evaluation, loading, scatter-gather algorithms are verified using analytic solutions for test cases subject to Laplace and Poisson equations. Grid sensitivity analysis examines the L2 and L∞ norms of the relative error in potential, field, and charge density as a function of edge-averaged and volume-averaged cell size. Analysis shows second order of convergence for the potential and first order of convergence for the electric field and charge density. Temporal sensitivity analysis is performed and the momentum and energy conservation properties of the particle integrators in EUPIC are examined. The effects of cell size and timestep on heating, slowing-down and the deflection times are quantified. The heating, slowing-down and the deflection times are found to be almost linearly dependent on number of particles per cell. EUPIC simulations of current collection by cylindrical Langmuir probes in collisionless plasmas show good comparison with previous experimentally validated numerical results. These simulations were also used in a parallelization efficiency investigation. Results show that the EUPIC has efficiency of more than 80% when the simulation is performed on a single CPU from a non-uniform memory access node and the efficiency is decreasing as the number of threads further increases. The EUPIC is applied to the simulation of the multi-species plasma flow over a geometrically complex CubeSat in Low Earth Orbit. The EUPIC potential and flowfield distribution around the CubeSat exhibit features that are consistent with previous simulations over simpler geometrical bodies.

Dual-color multiple-particle tracking at 50-nm localization and over 100-µm range in 3D with temporal focusing two-photon microscopy

PubMed Central

Ding, Yu; Li, Chunqiang

2016-01-01

Nanoscale particle tracking in three dimensions is crucial to directly observe dynamics of molecules and nanoparticles in living cells. Here we present a three-dimensional particle tracking method based on temporally focused two-photon excitation. Multiple particles are imaged at 30 frames/s in volume up to 180 × 180 × 100 µm3. The spatial localization precision can reach 50 nm. We demonstrate its capability of tracking fast swimming microbes at speed of ~200 µm/s. Two-photon dual-color tracking is achieved by simultaneously exciting two kinds of fluorescent beads at 800 nm to demonstrate its potential in molecular interaction studies. Our method provides a simple wide-field fluorescence imaging approach for deep multiple-particle tracking. PMID:27867724

Penalty Dynamic Programming Algorithm for Dim Targets Detection in Sensor Systems

PubMed Central

Huang, Dayu; Xue, Anke; Guo, Yunfei

2012-01-01

In order to detect and track multiple maneuvering dim targets in sensor systems, an improved dynamic programming track-before-detect algorithm (DP-TBD) called penalty DP-TBD (PDP-TBD) is proposed. The performances of tracking techniques are used as a feedback to the detection part. The feedback is constructed by a penalty term in the merit function, and the penalty term is a function of the possible target state estimation, which can be obtained by the tracking methods. With this feedback, the algorithm combines traditional tracking techniques with DP-TBD and it can be applied to simultaneously detect and track maneuvering dim targets. Meanwhile, a reasonable constraint that a sensor measurement can originate from one target or clutter is proposed to minimize track separation. Thus, the algorithm can be used in the multi-target situation with unknown target numbers. The efficiency and advantages of PDP-TBD compared with two existing methods are demonstrated by several simulations. PMID:22666074

Trajectory Control of Rendezvous with Maneuver Target Spacecraft

NASA Technical Reports Server (NTRS)

Zhou, Zhinqiang

2012-01-01

In this paper, a nonlinear trajectory control algorithm of rendezvous with maneuvering target spacecraft is presented. The disturbance forces on the chaser and target spacecraft and the thrust forces on the chaser spacecraft are considered in the analysis. The control algorithm developed in this paper uses the relative distance and relative velocity between the target and chaser spacecraft as the inputs. A general formula of reference relative trajectory of the chaser spacecraft to the target spacecraft is developed and applied to four different proximity maneuvers, which are in-track circling, cross-track circling, in-track spiral rendezvous and cross-track spiral rendezvous. The closed-loop differential equations of the proximity relative motion with the control algorithm are derived. It is proven in the paper that the tracking errors between the commanded relative trajectory and the actual relative trajectory are bounded within a constant region determined by the control gains. The prediction of the tracking errors is obtained. Design examples are provided to show the implementation of the control algorithm. The simulation results show that the actual relative trajectory tracks the commanded relative trajectory tightly. The predicted tracking errors match those calculated in the simulation results. The control algorithm developed in this paper can also be applied to interception of maneuver target spacecraft and relative trajectory control of spacecraft formation flying.

Nonstationary EO/IR Clutter Suppression and Dim Object Tracking

NASA Astrophysics Data System (ADS)

Tartakovsky, A.; Brown, A.; Brown, J.

2010-09-01

We develop and evaluate the performance of advanced algorithms which provide significantly improved capabilities for automated detection and tracking of ballistic and flying dim objects in the presence of highly structured intense clutter. Applications include ballistic missile early warning, midcourse tracking, trajectory prediction, and resident space object detection and tracking. The set of algorithms include, in particular, adaptive spatiotemporal clutter estimation-suppression and nonlinear filtering-based multiple-object track-before-detect. These algorithms are suitable for integration into geostationary, highly elliptical, or low earth orbit scanning or staring sensor suites, and are based on data-driven processing that adapts to real-world clutter backgrounds, including celestial, earth limb, or terrestrial clutter. In many scenarios of interest, e.g., for highly elliptic and, especially, low earth orbits, the resulting clutter is highly nonstationary, providing a significant challenge for clutter suppression to or below sensor noise levels, which is essential for dim object detection and tracking. We demonstrate the success of the developed algorithms using semi-synthetic and real data. In particular, our algorithms are shown to be capable of detecting and tracking point objects with signal-to-clutter levels down to 1/1000 and signal-to-noise levels down to 1/4.

Estimation for general birth-death processes.

PubMed

Crawford, Forrest W; Minin, Vladimir N; Suchard, Marc A

2014-04-01

Birth-death processes (BDPs) are continuous-time Markov chains that track the number of "particles" in a system over time. While widely used in population biology, genetics and ecology, statistical inference of the instantaneous particle birth and death rates remains largely limited to restrictive linear BDPs in which per-particle birth and death rates are constant. Researchers often observe the number of particles at discrete times, necessitating data augmentation procedures such as expectation-maximization (EM) to find maximum likelihood estimates. For BDPs on finite state-spaces, there are powerful matrix methods for computing the conditional expectations needed for the E-step of the EM algorithm. For BDPs on infinite state-spaces, closed-form solutions for the E-step are available for some linear models, but most previous work has resorted to time-consuming simulation. Remarkably, we show that the E-step conditional expectations can be expressed as convolutions of computable transition probabilities for any general BDP with arbitrary rates. This important observation, along with a convenient continued fraction representation of the Laplace transforms of the transition probabilities, allows for novel and efficient computation of the conditional expectations for all BDPs, eliminating the need for truncation of the state-space or costly simulation. We use this insight to derive EM algorithms that yield maximum likelihood estimation for general BDPs characterized by various rate models, including generalized linear models. We show that our Laplace convolution technique outperforms competing methods when they are available and demonstrate a technique to accelerate EM algorithm convergence. We validate our approach using synthetic data and then apply our methods to cancer cell growth and estimation of mutation parameters in microsatellite evolution.

Method and system for detecting polygon boundaries of structures in images as particle tracks through fields of corners and pixel gradients

DOEpatents

Paglieroni, David W [Pleasanton, CA; Manay, Siddharth [Livermore, CA

2011-12-20

A stochastic method and system for detecting polygon structures in images, by detecting a set of best matching corners of predetermined acuteness .alpha. of a polygon model from a set of similarity scores based on GDM features of corners, and tracking polygon boundaries as particle tracks using a sequential Monte Carlo approach. The tracking involves initializing polygon boundary tracking by selecting pairs of corners from the set of best matching corners to define a first side of a corresponding polygon boundary; tracking all intermediate sides of the polygon boundaries using a particle filter, and terminating polygon boundary tracking by determining the last side of the tracked polygon boundaries to close the polygon boundaries. The particle tracks are then blended to determine polygon matches, which may be made available, such as to a user, for ranking and inspection.

Determination of time zero from a charged particle detector

DOEpatents

Green, Jesse Andrew [Los Alamos, NM

2011-03-15

A method, system and computer program is used to determine a linear track having a good fit to a most likely or expected path of charged particle passing through a charged particle detector having a plurality of drift cells. Hit signals from the charged particle detector are associated with a particular charged particle track. An initial estimate of time zero is made from these hit signals and linear tracks are then fit to drift radii for each particular time-zero estimate. The linear track having the best fit is then searched and selected and errors in fit and tracking parameters computed. The use of large and expensive fast detectors needed to time zero in the charged particle detectors can be avoided by adopting this method and system.

Determining the bias and variance of a deterministic finger-tracking algorithm.

PubMed

Morash, Valerie S; van der Velden, Bas H M

2016-06-01

Finger tracking has the potential to expand haptic research and applications, as eye tracking has done in vision research. In research applications, it is desirable to know the bias and variance associated with a finger-tracking method. However, assessing the bias and variance of a deterministic method is not straightforward. Multiple measurements of the same finger position data will not produce different results, implying zero variance. Here, we present a method of assessing deterministic finger-tracking variance and bias through comparison to a non-deterministic measure. A proof-of-concept is presented using a video-based finger-tracking algorithm developed for the specific purpose of tracking participant fingers during a psychological research study. The algorithm uses ridge detection on videos of the participant's hand, and estimates the location of the right index fingertip. The algorithm was evaluated using data from four participants, who explored tactile maps using only their right index finger and all right-hand fingers. The algorithm identified the index fingertip in 99.78 % of one-finger video frames and 97.55 % of five-finger video frames. Although the algorithm produced slightly biased and more dispersed estimates relative to a human coder, these differences (x=0.08 cm, y=0.04 cm) and standard deviations (σ x =0.16 cm, σ y =0.21 cm) were small compared to the size of a fingertip (1.5-2.0 cm). Some example finger-tracking results are provided where corrections are made using the bias and variance estimates.

Vehicle tracking using fuzzy-based vehicle detection window with adaptive parameters

NASA Astrophysics Data System (ADS)

Chitsobhuk, Orachat; Kasemsiri, Watjanapong; Glomglome, Sorayut; Lapamonpinyo, Pipatphon

2018-04-01

In this paper, fuzzy-based vehicle tracking system is proposed. The proposed system consists of two main processes: vehicle detection and vehicle tracking. In the first process, the Gradient-based Adaptive Threshold Estimation (GATE) algorithm is adopted to provide the suitable threshold value for the sobel edge detection. The estimated threshold can be adapted to the changes of diverse illumination conditions throughout the day. This leads to greater vehicle detection performance compared to a fixed user's defined threshold. In the second process, this paper proposes the novel vehicle tracking algorithms namely Fuzzy-based Vehicle Analysis (FBA) in order to reduce the false estimation of the vehicle tracking caused by uneven edges of the large vehicles and vehicle changing lanes. The proposed FBA algorithm employs the average edge density and the Horizontal Moving Edge Detection (HMED) algorithm to alleviate those problems by adopting fuzzy rule-based algorithms to rectify the vehicle tracking. The experimental results demonstrate that the proposed system provides the high accuracy of vehicle detection about 98.22%. In addition, it also offers the low false detection rates about 3.92%.

On charged particle tracks in cellulose nitrate and Lexan

NASA Technical Reports Server (NTRS)

Benton, E. V.; Henke, R. P.

1972-01-01

Investigations were performed aimed at developing plastic nuclear track detectors into quantitative tools for recording and measuring multicharged, heavy particles. Accurate track etch rate measurements as a function of LET were performed for cellulose nitrate and Lexan plastic detectors. This was done using a variety of incident charged particle types and energies. The effect of aging of latent tracks in Lexan in different gaseous atmospheres was investigated. Range distributions of high energy N-14 particle bevatron beams in nuclear emulsion were measured. Investigation of charge resolution and Bragg peak measurements were carried out using plastic nuclear track detectors.

Shape classification of wear particles by image boundary analysis using machine learning algorithms

NASA Astrophysics Data System (ADS)

Yuan, Wei; Chin, K. S.; Hua, Meng; Dong, Guangneng; Wang, Chunhui

2016-05-01

The shape features of wear particles generated from wear track usually contain plenty of information about the wear states of a machinery operational condition. Techniques to quickly identify types of wear particles quickly to respond to the machine operation and prolong the machine's life appear to be lacking and are yet to be established. To bridge rapid off-line feature recognition with on-line wear mode identification, this paper presents a new radial concave deviation (RCD) method that mainly involves the use of the particle boundary signal to analyze wear particle features. Signal output from the RCDs subsequently facilitates the determination of several other feature parameters, typically relevant to the shape and size of the wear particle. Debris feature and type are identified through the use of various classification methods, such as linear discriminant analysis, quadratic discriminant analysis, naïve Bayesian method, and classification and regression tree method (CART). The average errors of the training and test via ten-fold cross validation suggest CART is a highly suitable approach for classifying and analyzing particle features. Furthermore, the results of the wear debris analysis enable the maintenance team to diagnose faults appropriately.

Lagrangian Particle Tracking in a Discontinuous Galerkin Method for Hypersonic Reentry Flows in Dusty Environments

NASA Astrophysics Data System (ADS)

Ching, Eric; Lv, Yu; Ihme, Matthias

2017-11-01

Recent interest in human-scale missions to Mars has sparked active research into high-fidelity simulations of reentry flows. A key feature of the Mars atmosphere is the high levels of suspended dust particles, which can not only enhance erosion of thermal protection systems but also transfer energy and momentum to the shock layer, increasing surface heat fluxes. Second-order finite-volume schemes are typically employed for hypersonic flow simulations, but such schemes suffer from a number of limitations. An attractive alternative is discontinuous Galerkin methods, which benefit from arbitrarily high spatial order of accuracy, geometric flexibility, and other advantages. As such, a Lagrangian particle method is developed in a discontinuous Galerkin framework to enable the computation of particle-laden hypersonic flows. Two-way coupling between the carrier and disperse phases is considered, and an efficient particle search algorithm compatible with unstructured curved meshes is proposed. In addition, variable thermodynamic properties are considered to accommodate high-temperature gases. The performance of the particle method is demonstrated in several test cases, with focus on the accurate prediction of particle trajectories and heating augmentation. Financial support from a Stanford Graduate Fellowship and the NASA Early Career Faculty program are gratefully acknowledged.

A GPU-Accelerated 3-D Coupled Subsample Estimation Algorithm for Volumetric Breast Strain Elastography.

PubMed

Peng, Bo; Wang, Yuqi; Hall, Timothy J; Jiang, Jingfeng

2017-04-01

Our primary objective of this paper was to extend a previously published 2-D coupled subsample tracking algorithm for 3-D speckle tracking in the framework of ultrasound breast strain elastography. In order to overcome heavy computational cost, we investigated the use of a graphic processing unit (GPU) to accelerate the 3-D coupled subsample speckle tracking method. The performance of the proposed GPU implementation was tested using a tissue-mimicking phantom and in vivo breast ultrasound data. The performance of this 3-D subsample tracking algorithm was compared with the conventional 3-D quadratic subsample estimation algorithm. On the basis of these evaluations, we concluded that the GPU implementation of this 3-D subsample estimation algorithm can provide high-quality strain data (i.e., high correlation between the predeformation and the motion-compensated postdeformation radio frequency echo data and high contrast-to-noise ratio strain images), as compared with the conventional 3-D quadratic subsample algorithm. Using the GPU implementation of the 3-D speckle tracking algorithm, volumetric strain data can be achieved relatively fast (approximately 20 s per volume [2.5 cm ×2.5 cm ×2.5 cm]).

Particle Tracking Facilitates Real Time Capable Motion Correction in 2D or 3D Two-Photon Imaging of Neuronal Activity.

PubMed

Aghayee, Samira; Winkowski, Daniel E; Bowen, Zachary; Marshall, Erin E; Harrington, Matt J; Kanold, Patrick O; Losert, Wolfgang

2017-01-01

The application of 2-photon laser scanning microscopy (TPLSM) techniques to measure the dynamics of cellular calcium signals in populations of neurons is an extremely powerful technique for characterizing neural activity within the central nervous system. The use of TPLSM on awake and behaving subjects promises new insights into how neural circuit elements cooperatively interact to form sensory perceptions and generate behavior. A major challenge in imaging such preparations is unavoidable animal and tissue movement, which leads to shifts in the imaging location (jitter). The presence of image motion can lead to artifacts, especially since quantification of TPLSM images involves analysis of fluctuations in fluorescence intensities for each neuron, determined from small regions of interest (ROIs). Here, we validate a new motion correction approach to compensate for motion of TPLSM images in the superficial layers of auditory cortex of awake mice. We use a nominally uniform fluorescent signal as a secondary signal to complement the dynamic signals from genetically encoded calcium indicators. We tested motion correction for single plane time lapse imaging as well as multiplane (i.e., volume) time lapse imaging of cortical tissue. Our procedure of motion correction relies on locating the brightest neurons and tracking their positions over time using established techniques of particle finding and tracking. We show that our tracking based approach provides subpixel resolution without compromising speed. Unlike most established methods, our algorithm also captures deformations of the field of view and thus can compensate e.g., for rotations. Object tracking based motion correction thus offers an alternative approach for motion correction, one that is well suited for real time spike inference analysis and feedback control, and for correcting for tissue distortions.

Particle Tracking Facilitates Real Time Capable Motion Correction in 2D or 3D Two-Photon Imaging of Neuronal Activity

PubMed Central

Aghayee, Samira; Winkowski, Daniel E.; Bowen, Zachary; Marshall, Erin E.; Harrington, Matt J.; Kanold, Patrick O.; Losert, Wolfgang

2017-01-01

The application of 2-photon laser scanning microscopy (TPLSM) techniques to measure the dynamics of cellular calcium signals in populations of neurons is an extremely powerful technique for characterizing neural activity within the central nervous system. The use of TPLSM on awake and behaving subjects promises new insights into how neural circuit elements cooperatively interact to form sensory perceptions and generate behavior. A major challenge in imaging such preparations is unavoidable animal and tissue movement, which leads to shifts in the imaging location (jitter). The presence of image motion can lead to artifacts, especially since quantification of TPLSM images involves analysis of fluctuations in fluorescence intensities for each neuron, determined from small regions of interest (ROIs). Here, we validate a new motion correction approach to compensate for motion of TPLSM images in the superficial layers of auditory cortex of awake mice. We use a nominally uniform fluorescent signal as a secondary signal to complement the dynamic signals from genetically encoded calcium indicators. We tested motion correction for single plane time lapse imaging as well as multiplane (i.e., volume) time lapse imaging of cortical tissue. Our procedure of motion correction relies on locating the brightest neurons and tracking their positions over time using established techniques of particle finding and tracking. We show that our tracking based approach provides subpixel resolution without compromising speed. Unlike most established methods, our algorithm also captures deformations of the field of view and thus can compensate e.g., for rotations. Object tracking based motion correction thus offers an alternative approach for motion correction, one that is well suited for real time spike inference analysis and feedback control, and for correcting for tissue distortions. PMID:28860973

Etracker: A Mobile Gaze-Tracking System with Near-Eye Display Based on a Combined Gaze-Tracking Algorithm.

PubMed

Li, Bin; Fu, Hong; Wen, Desheng; Lo, WaiLun

2018-05-19

Eye tracking technology has become increasingly important for psychological analysis, medical diagnosis, driver assistance systems, and many other applications. Various gaze-tracking models have been established by previous researchers. However, there is currently no near-eye display system with accurate gaze-tracking performance and a convenient user experience. In this paper, we constructed a complete prototype of the mobile gaze-tracking system ' Etracker ' with a near-eye viewing device for human gaze tracking. We proposed a combined gaze-tracking algorithm. In this algorithm, the convolutional neural network is used to remove blinking images and predict coarse gaze position, and then a geometric model is defined for accurate human gaze tracking. Moreover, we proposed using the mean value of gazes to resolve pupil center changes caused by nystagmus in calibration algorithms, so that an individual user only needs to calibrate it the first time, which makes our system more convenient. The experiments on gaze data from 26 participants show that the eye center detection accuracy is 98% and Etracker can provide an average gaze accuracy of 0.53° at a rate of 30⁻60 Hz.

Three-dimensional spatiotemporal tracking of fluorine-18 radiolabeled yeast cells via positron emission particle tracking

DOE PAGES

Langford, Seth T.; Wiggins, Cody S.; Santos, Roque; ...

2017-07-06

A method for Positron Emission Particle Tracking (PEPT) based on optical feature point identification techniques is demonstrated for use in low activity tracking experiments. Furthermore, a population of yeast cells of approximately 125,000 members is activated to roughly 55 Bq/cell by 18F uptake. An in vitro particle tracking experiment is performed with nearly 20 of these cells after decay to 32 Bq/cell. These cells are successfully identified and tracked simultaneously in this experiment. Our work extends the applicability of PEPT as a cell tracking method by allowing a number of cells to be tracked together, and demonstrating tracking for verymore » low activity tracers.« less

Three-dimensional spatiotemporal tracking of fluorine-18 radiolabeled yeast cells via positron emission particle tracking

DOE Office of Scientific and Technical Information (OSTI.GOV)

Langford, Seth T.; Wiggins, Cody S.; Santos, Roque

A method for Positron Emission Particle Tracking (PEPT) based on optical feature point identification techniques is demonstrated for use in low activity tracking experiments. Furthermore, a population of yeast cells of approximately 125,000 members is activated to roughly 55 Bq/cell by 18F uptake. An in vitro particle tracking experiment is performed with nearly 20 of these cells after decay to 32 Bq/cell. These cells are successfully identified and tracked simultaneously in this experiment. Our work extends the applicability of PEPT as a cell tracking method by allowing a number of cells to be tracked together, and demonstrating tracking for verymore » low activity tracers.« less

Tri-linear interpolation-based cerebral white matter fiber imaging

PubMed Central

Jiang, Shan; Zhang, Pengfei; Han, Tong; Liu, Weihua; Liu, Meixia

2013-01-01

Diffusion tensor imaging is a unique method to visualize white matter fibers three-dimensionally, non-invasively and in vivo, and therefore it is an important tool for observing and researching neural regeneration. Different diffusion tensor imaging-based fiber tracking methods have been already investigated, but making the computing faster, fiber tracking longer and smoother and the details shown clearer are needed to be improved for clinical applications. This study proposed a new fiber tracking strategy based on tri-linear interpolation. We selected a patient with acute infarction of the right basal ganglia and designed experiments based on either the tri-linear interpolation algorithm or tensorline algorithm. Fiber tracking in the same regions of interest (genu of the corpus callosum) was performed separately. The validity of the tri-linear interpolation algorithm was verified by quantitative analysis, and its feasibility in clinical diagnosis was confirmed by the contrast between tracking results and the disease condition of the patient as well as the actual brain anatomy. Statistical results showed that the maximum length and average length of the white matter fibers tracked by the tri-linear interpolation algorithm were significantly longer. The tracking images of the fibers indicated that this method can obtain smoother tracked fibers, more obvious orientation and clearer details. Tracking fiber abnormalities are in good agreement with the actual condition of patients, and tracking displayed fibers that passed though the corpus callosum, which was consistent with the anatomical structures of the brain. Therefore, the tri-linear interpolation algorithm can achieve a clear, anatomically correct and reliable tracking result. PMID:25206524

NASA Tech Briefs, August 2007

NASA Technical Reports Server (NTRS)

2007-01-01

Topics include: Program Merges SAR Data on Terrain and Vegetation Heights; Using G(exp 4)FETs as a Data Router for In-Plane Crossing of Signal Paths; Two Algorithms for Processing Electronic Nose Data; Radiation-Tolerant Dual Data Bus; General-Purpose Front End for Real-Time Data Processing; Nanocomposite Photoelectrochemical Cells; Ultracapacitor-Powered Cordless Drill, Cumulative Timers for Microprocessors; Photocatalytic/Magnetic Composite Particles; Separation and Sealing of a Sample Container Using Brazing; Automated Aerial Refueling Hitches a Ride on AFF; Cobra Probes Containing Replaceable Thermocouples; High-Speed Noninvasive Eye-Tracking System; Detergent-Specific Membrane Protein Crystallization Screens; Evaporation-Cooled Protective Suits for Firefighters; Plasmonic Antenna Coupling for QWIPs; Electronic Tongue Containing Redox and Conductivity Sensors; Improved Heat-Stress Algorithm; A Method of Partly Automated Testing of Software; Rover Wheel-Actuated Tool Interface; and Second-Generation Electronic Nose.

Multitarget mixture reduction algorithm with incorporated target existence recursions

NASA Astrophysics Data System (ADS)

Ristic, Branko; Arulampalam, Sanjeev

2000-07-01

The paper derives a deferred logic data association algorithm based on the mixture reduction approach originally due to Salmond [SPIE vol.1305, 1990]. The novelty of the proposed algorithm provides the recursive formulae for both data association and target existence (confidence) estimation, thus allowing automatic track initiation and termination. T he track initiation performance of the proposed filter is investigated by computer simulations. It is observed that at moderately high levels of clutter density the proposed filter initiates tracks more reliably than its corresponding PDA filter. An extension of the proposed filter to the multi-target case is also presented. In addition, the paper compares the track maintenance performance of the MR algorithm with an MHT implementation.

Enhancement of tracking performance in electro-optical system based on servo control algorithm

NASA Astrophysics Data System (ADS)

Choi, WooJin; Kim, SungSu; Jung, DaeYoon; Seo, HyoungKyu

2017-10-01

Modern electro-optical surveillance and reconnaissance systems require tracking capability to get exact images of target or to accurately direct the line of sight to target which is moving or still. This leads to the tracking system composed of image based tracking algorithm and servo control algorithm. In this study, we focus on the servo control function to minimize the overshoot in the tracking motion and do not miss the target. The scheme is to limit acceleration and velocity parameters in the tracking controller, depending on the target state information in the image. We implement the proposed techniques by creating a system model of DIRCM and simulate the same environment, validate the performance on the actual equipment.

Bounded fractional diffusion in geological media: Definition and Lagrangian approximation

USGS Publications Warehouse

Zhang, Yong; Green, Christopher T.; LaBolle, Eric M.; Neupauer, Roseanna M.; Sun, HongGuang

2016-01-01

Spatiotemporal Fractional-Derivative Models (FDMs) have been increasingly used to simulate non-Fickian diffusion, but methods have not been available to define boundary conditions for FDMs in bounded domains. This study defines boundary conditions and then develops a Lagrangian solver to approximate bounded, one-dimensional fractional diffusion. Both the zero-value and non-zero-value Dirichlet, Neumann, and mixed Robin boundary conditions are defined, where the sign of Riemann-Liouville fractional derivative (capturing non-zero-value spatial-nonlocal boundary conditions with directional super-diffusion) remains consistent with the sign of the fractional-diffusive flux term in the FDMs. New Lagrangian schemes are then proposed to track solute particles moving in bounded domains, where the solutions are checked against analytical or Eularian solutions available for simplified FDMs. Numerical experiments show that the particle-tracking algorithm for non-Fickian diffusion differs from Fickian diffusion in relocating the particle position around the reflective boundary, likely due to the non-local and non-symmetric fractional diffusion. For a non-zero-value Neumann or Robin boundary, a source cell with a reflective face can be applied to define the release rate of random-walking particles at the specified flux boundary. Mathematical definitions of physically meaningful nonlocal boundaries combined with bounded Lagrangian solvers in this study may provide the only viable techniques at present to quantify the impact of boundaries on anomalous diffusion, expanding the applicability of FDMs from infinite do mains to those with any size and boundary conditions.

UWB Tracking System Design with TDOA Algorithm

NASA Technical Reports Server (NTRS)

Ni, Jianjun; Arndt, Dickey; Ngo, Phong; Phan, Chau; Gross, Julia; Dusl, John; Schwing, Alan

2006-01-01

This presentation discusses an ultra-wideband (UWB) tracking system design effort using a tracking algorithm TDOA (Time Difference of Arrival). UWB technology is exploited to implement the tracking system due to its properties, such as high data rate, fine time resolution, and low power spectral density. A system design using commercially available UWB products is proposed. A two-stage weighted least square method is chosen to solve the TDOA non-linear equations. Matlab simulations in both two-dimensional space and three-dimensional space show that the tracking algorithm can achieve fine tracking resolution with low noise TDOA data. The error analysis reveals various ways to improve the tracking resolution. Lab experiments demonstrate the UWBTDOA tracking capability with fine resolution. This research effort is motivated by a prototype development project Mini-AERCam (Autonomous Extra-vehicular Robotic Camera), a free-flying video camera system under development at NASA Johnson Space Center for aid in surveillance around the International Space Station (ISS).

Development of a Sunspot Tracking System

NASA Technical Reports Server (NTRS)

Taylor, Jaime R.

1998-01-01

Large solar flares produce a significant amount of energetic particles which pose a hazard for human activity in space. In the hope of understanding flare mechanisms and thus better predicting solar flares, NASA's Marshall Space Flight Center (MSFC) developed an experimental vector magnetograph (EXVM) polarimeter to measure the Sun's magnetic field. The EXVM will be used to perform ground-based solar observations and will provide a proof of concept for the design of a similar instrument for the Japanese Solar-B space mission. The EXVM typically operates for a period of several minutes. During this time there is image motion due to atmospheric fluctuation and telescope wind loading. To optimize the EXVM performance an image motion compensation device (sunspot tracker) is needed. The sunspot tracker consists of two parts, an image motion determination system and an image deflection system. For image motion determination a CCD or CID camera is used to digitize an image, than an algorithm is applied to determine the motion. This motion or error signal is sent to the image deflection system which moves the image back to its original location. Both of these systems are under development. Two algorithms are available for sunspot tracking which require the use of only one row and one column of image data. To implement these algorithms, two identical independent systems are being developed, one system for each axis of motion. Two CID cameras have been purchased; the data from each camera will be used to determine image motion for each direction. The error signal generated by the tracking algorithm will be sent to an image deflection system consisting of an actuator and a mirror constrained to move about one axis. Magnetostrictive actuators were chosen to move the mirror over piezoelectrics due to their larger driving force and larger range of motion. The actuator and mirror mounts are currently under development.

An improved multi-domain convolution tracking algorithm

NASA Astrophysics Data System (ADS)

Sun, Xin; Wang, Haiying; Zeng, Yingsen

2018-04-01

Along with the wide application of the Deep Learning in the field of Computer vision, Deep learning has become a mainstream direction in the field of object tracking. The tracking algorithm in this paper is based on the improved multidomain convolution neural network, and the VOT video set is pre-trained on the network by multi-domain training strategy. In the process of online tracking, the network evaluates candidate targets sampled from vicinity of the prediction target in the previous with Gaussian distribution, and the candidate target with the highest score is recognized as the prediction target of this frame. The Bounding Box Regression model is introduced to make the prediction target closer to the ground-truths target box of the test set. Grouping-update strategy is involved to extract and select useful update samples in each frame, which can effectively prevent over fitting. And adapt to changes in both target and environment. To improve the speed of the algorithm while maintaining the performance, the number of candidate target succeed in adjusting dynamically with the help of Self-adaption parameter Strategy. Finally, the algorithm is tested by OTB set, compared with other high-performance tracking algorithms, and the plot of success rate and the accuracy are drawn. which illustrates outstanding performance of the tracking algorithm in this paper.

Vision-based measurement for rotational speed by improving Lucas-Kanade template tracking algorithm.

PubMed

Guo, Jie; Zhu, Chang'an; Lu, Siliang; Zhang, Dashan; Zhang, Chunyu

2016-09-01

Rotational angle and speed are important parameters for condition monitoring and fault diagnosis of rotating machineries, and their measurement is useful in precision machining and early warning of faults. In this study, a novel vision-based measurement algorithm is proposed to complete this task. A high-speed camera is first used to capture the video of the rotational object. To extract the rotational angle, the template-based Lucas-Kanade algorithm is introduced to complete motion tracking by aligning the template image in the video sequence. Given the special case of nonplanar surface of the cylinder object, a nonlinear transformation is designed for modeling the rotation tracking. In spite of the unconventional and complex form, the transformation can realize angle extraction concisely with only one parameter. A simulation is then conducted to verify the tracking effect, and a practical tracking strategy is further proposed to track consecutively the video sequence. Based on the proposed algorithm, instantaneous rotational speed (IRS) can be measured accurately and efficiently. Finally, the effectiveness of the proposed algorithm is verified on a brushless direct current motor test rig through the comparison with results obtained by the microphone. Experimental results demonstrate that the proposed algorithm can extract accurately rotational angles and can measure IRS with the advantage of noncontact and effectiveness.

An open source framework for tracking and state estimation ('Stone Soup')

NASA Astrophysics Data System (ADS)

Thomas, Paul A.; Barr, Jordi; Balaji, Bhashyam; White, Kruger

2017-05-01

The ability to detect and unambiguously follow all moving entities in a state-space is important in multiple domains both in defence (e.g. air surveillance, maritime situational awareness, ground moving target indication) and the civil sphere (e.g. astronomy, biology, epidemiology, dispersion modelling). However, tracking and state estimation researchers and practitioners have difficulties recreating state-of-the-art algorithms in order to benchmark their own work. Furthermore, system developers need to assess which algorithms meet operational requirements objectively and exhaustively rather than intuitively or driven by personal favourites. We have therefore commenced the development of a collaborative initiative to create an open source framework for production, demonstration and evaluation of Tracking and State Estimation algorithms. The initiative will develop a (MIT-licensed) software platform for researchers and practitioners to test, verify and benchmark a variety of multi-sensor and multi-object state estimation algorithms. The initiative is supported by four defence laboratories, who will contribute to the development effort for the framework. The tracking and state estimation community will derive significant benefits from this work, including: access to repositories of verified and validated tracking and state estimation algorithms, a framework for the evaluation of multiple algorithms, standardisation of interfaces and access to challenging data sets. Keywords: Tracking,

Tracking and people counting using Particle Filter Method

NASA Astrophysics Data System (ADS)

Sulistyaningrum, D. R.; Setiyono, B.; Rizky, M. S.

2018-03-01

In recent years, technology has developed quite rapidly, especially in the field of object tracking. Moreover, if the object under study is a person and the number of people a lot. The purpose of this research is to apply Particle Filter method for tracking and counting people in certain area. Tracking people will be rather difficult if there are some obstacles, one of which is occlusion. The stages of tracking and people counting scheme in this study include pre-processing, segmentation using Gaussian Mixture Model (GMM), tracking using particle filter, and counting based on centroid. The Particle Filter method uses the estimated motion included in the model used. The test results show that the tracking and people counting can be done well with an average accuracy of 89.33% and 77.33% respectively from six videos test data. In the process of tracking people, the results are good if there is partial occlusion and no occlusion

A micro-fluidic treadmill for observing suspended plankton in the lab

NASA Astrophysics Data System (ADS)

Jaffe, J. S.; Laxton, B.; Garwood, J. C.; Franks, P. J. S.; Roberts, P. L.

2016-02-01

A significant obstacle to laboratory studies of interactions between small organisms ( mm) and their fluid environment is our ability to obtain high-resolution images while allowing freedom of motion. This is because as the organisms sink, they will often move out of the field of view of the observation system. One solution to this problem is to impose a water circulation pattern that preserves their location relative to the camera system while imaging the organisms away from the glass walls. To accomplish this we have designed and created a plankton treadmill. Our computer-controlled system consists of a digital video camera attached to a macro or microscope and a micro-fluidic pump whose flow is regulated to maintain a suspended organism's position relative to the field of view. Organisms are detected and tracked in real time in the video frames, allowing a control algorithm to compensate for any vertical movement by adjusting the flow. The flow control can be manually adjusted using on-screen controls, semi-automatically adjusted to allow the user to select a particular organism to be tracked or fully automatic through the use of classification and tracking algorithms. Experiments with a simple cm-sized cuvette and a number of organisms that are both positively and negatively buoyant have demonstrated the success of the system in permitting longer observation times than would be possible in the absence of a controlled-flow environment. The subjects were observed using a new dual-view, holographic imaging system that provides 3-dimensional microscopic observations with relatively isotropic resolution. We will present the system design, construction, the control algorithm, and some images obtained with the holographic system, demonstrating its effectiveness. Small particles seeded into the flow clearly show the 3D flow fields around the subjects as they freely sink or swim.

Particle sizing of pharmaceutical aerosols via direct imaging of particle settling velocities.

PubMed

Fishler, Rami; Verhoeven, Frank; de Kruijf, Wilbur; Sznitman, Josué

2018-02-15

We present a novel method for characterizing in near real-time the aerodynamic particle size distributions from pharmaceutical inhalers. The proposed method is based on direct imaging of airborne particles followed by a particle-by-particle measurement of settling velocities using image analysis and particle tracking algorithms. Due to the simplicity of the principle of operation, this method has the potential of circumventing potential biases of current real-time particle analyzers (e.g. Time of Flight analysis), while offering a cost effective solution. The simple device can also be constructed in laboratory settings from off-the-shelf materials for research purposes. To demonstrate the feasibility and robustness of the measurement technique, we have conducted benchmark experiments whereby aerodynamic particle size distributions are obtained from several commercially-available dry powder inhalers (DPIs). Our measurements yield size distributions (i.e. MMAD and GSD) that are closely in line with those obtained from Time of Flight analysis and cascade impactors suggesting that our imaging-based method may embody an attractive methodology for rapid inhaler testing and characterization. In a final step, we discuss some of the ongoing limitations of the current prototype and conceivable routes for improving the technique. Copyright © 2017 Elsevier B.V. All rights reserved.

Ghost hunting—an assessment of ghost particle detection and removal methods for tomographic-PIV

NASA Astrophysics Data System (ADS)

Elsinga, G. E.; Tokgoz, S.

2014-08-01

This paper discusses and compares several methods, which aim to remove spurious peaks, i.e. ghost particles, from the volume intensity reconstruction in tomographic-PIV. The assessment is based on numerical simulations of time-resolved tomographic-PIV experiments in linear shear flows. Within the reconstructed volumes, intensity peaks are detected and tracked over time. These peaks are associated with particles (either ghosts or actual particles) and are characterized by their peak intensity, size and track length. Peak intensity and track length are found to be effective in discriminating between most ghosts and the actual particles, although not all ghosts can be detected using only a single threshold. The size of the reconstructed particles does not reveal an important difference between ghosts and actual particles. The joint distribution of peak intensity and track length however does, under certain conditions, allow a complete separation of ghosts and actual particles. The ghosts can have either a high intensity or a long track length, but not both combined, like all the actual particles. Removing the detected ghosts from the reconstructed volume and performing additional MART iterations can decrease the particle position error at low to moderate seeding densities, but increases the position error, velocity error and tracking errors at higher densities. The observed trends in the joint distribution of peak intensity and track length are confirmed by results from a real experiment in laminar Taylor-Couette flow. This diagnostic plot allows an estimate of the number of ghosts that are indistinguishable from the actual particles.

Uninformative Prior Multiple Target Tracking Using Evidential Particle Filters

NASA Astrophysics Data System (ADS)

Worthy, J. L., III; Holzinger, M. J.

Space situational awareness requires the ability to initialize state estimation from short measurements and the reliable association of observations to support the characterization of the space environment. The electro-optical systems used to observe space objects cannot fully characterize the state of an object given a short, unobservable sequence of measurements. Further, it is difficult to associate these short-arc measurements if many such measurements are generated through the observation of a cluster of satellites, debris from a satellite break-up, or from spurious detections of an object. An optimization based, probabilistic short-arc observation association approach coupled with a Dempster-Shafer based evidential particle filter in a multiple target tracking framework is developed and proposed to address these problems. The optimization based approach is shown in literature to be computationally efficient and can produce probabilities of association, state estimates, and covariances while accounting for systemic errors. Rigorous application of Dempster-Shafer theory is shown to be effective at enabling ignorance to be properly accounted for in estimation by augmenting probability with belief and plausibility. The proposed multiple hypothesis framework will use a non-exclusive hypothesis formulation of Dempster-Shafer theory to assign belief mass to candidate association pairs and generate tracks based on the belief to plausibility ratio. The proposed algorithm is demonstrated using simulated observations of a GEO satellite breakup scenario.

Matched filter based detection of floating mines in IR spacetime

NASA Astrophysics Data System (ADS)

Borghgraef, Alexander; Lapierre, Fabian; Philips, Wilfried; Acheroy, Marc

2009-09-01

Ship-based automatic detection of small floating objects on an agitated sea surface remains a hard problem. Our main concern is the detection of floating mines, which proved a real threat to shipping in confined waterways during the first Gulf War, but applications include salvaging,search-and-rescue and perimeter or harbour defense. IR video was chosen for its day-and-night imaging capability, and its availability on military vessels. Detection is difficult because a rough sea is seen as a dynamic background of moving objects with size order, shape and temperature similar to those of the floating mine. We do find a determinant characteristic in the target's periodic motion, which differs from that of the propagating surface waves composing the background. The classical detection and tracking approaches give bad results when applied to this problem. While background detection algorithms assume a quasi-static background, the sea surface is actually very dynamic, causing this category of algorithms to fail. Kalman or particle filter algorithms on the other hand, which stress temporal coherence, suffer from tracking loss due to occlusions and the great noise level of the image. We propose an innovative approach. This approach uses the periodicity of the objects movement and thus its temporal coherence. The principle is to consider the video data as a spacetime volume similar to a hyperspectral data cube by replacing the spectral axis with a temporal axis. We can then apply algorithms developed for hyperspectral detection problems to the detection of small floating objects. We treat the detection problem using multilinear algebra, designing a number of finite impulse response filters (FIR) maximizing the target response. The algorithm was applied to test footage of practice mines in the infrared.

CUDA-Accelerated Geodesic Ray-Tracing for Fiber Tracking

PubMed Central

van Aart, Evert; Sepasian, Neda; Jalba, Andrei; Vilanova, Anna

2011-01-01

Diffusion Tensor Imaging (DTI) allows to noninvasively measure the diffusion of water in fibrous tissue. By reconstructing the fibers from DTI data using a fiber-tracking algorithm, we can deduce the structure of the tissue. In this paper, we outline an approach to accelerating such a fiber-tracking algorithm using a Graphics Processing Unit (GPU). This algorithm, which is based on the calculation of geodesics, has shown promising results for both synthetic and real data, but is limited in its applicability by its high computational requirements. We present a solution which uses the parallelism offered by modern GPUs, in combination with the CUDA platform by NVIDIA, to significantly reduce the execution time of the fiber-tracking algorithm. Compared to a multithreaded CPU implementation of the same algorithm, our GPU mapping achieves a speedup factor of up to 40 times. PMID:21941525

Adaptive particle filter for robust visual tracking

NASA Astrophysics Data System (ADS)

Dai, Jianghua; Yu, Shengsheng; Sun, Weiping; Chen, Xiaoping; Xiang, Jinhai

2009-10-01

Object tracking plays a key role in the field of computer vision. Particle filter has been widely used for visual tracking under nonlinear and/or non-Gaussian circumstances. In particle filter, the state transition model for predicting the next location of tracked object assumes the object motion is invariable, which cannot well approximate the varying dynamics of the motion changes. In addition, the state estimate calculated by the mean of all the weighted particles is coarse or inaccurate due to various noise disturbances. Both these two factors may degrade tracking performance greatly. In this work, an adaptive particle filter (APF) with a velocity-updating based transition model (VTM) and an adaptive state estimate approach (ASEA) is proposed to improve object tracking. In APF, the motion velocity embedded into the state transition model is updated continuously by a recursive equation, and the state estimate is obtained adaptively according to the state posterior distribution. The experiment results show that the APF can increase the tracking accuracy and efficiency in complex environments.

A novel vehicle tracking algorithm based on mean shift and active contour model in complex environment

NASA Astrophysics Data System (ADS)

Cai, Lei; Wang, Lin; Li, Bo; Zhang, Libao; Lv, Wen

2017-06-01

Vehicle tracking technology is currently one of the most active research topics in machine vision. It is an important part of intelligent transportation system. However, in theory and technology, it still faces many challenges including real-time and robustness. In video surveillance, the targets need to be detected in real-time and to be calculated accurate position for judging the motives. The contents of video sequence images and the target motion are complex, so the objects can't be expressed by a unified mathematical model. Object-tracking is defined as locating the interest moving target in each frame of a piece of video. The current tracking technology can achieve reliable results in simple environment over the target with easy identified characteristics. However, in more complex environment, it is easy to lose the target because of the mismatch between the target appearance and its dynamic model. Moreover, the target usually has a complex shape, but the tradition target tracking algorithm usually represents the tracking results by simple geometric such as rectangle or circle, so it cannot provide accurate information for the subsequent upper application. This paper combines a traditional object-tracking technology, Mean-Shift algorithm, with a kind of image segmentation algorithm, Active-Contour model, to get the outlines of objects while the tracking process and automatically handle topology changes. Meanwhile, the outline information is used to aid tracking algorithm to improve it.

Context-specific selection of algorithms for recursive feature tracking in endoscopic image using a new methodology.

PubMed

Selka, F; Nicolau, S; Agnus, V; Bessaid, A; Marescaux, J; Soler, L

2015-03-01

In minimally invasive surgery, the tracking of deformable tissue is a critical component for image-guided applications. Deformation of the tissue can be recovered by tracking features using tissue surface information (texture, color,...). Recent work in this field has shown success in acquiring tissue motion. However, the performance evaluation of detection and tracking algorithms on such images are still difficult and are not standardized. This is mainly due to the lack of ground truth data on real data. Moreover, in order to avoid supplementary techniques to remove outliers, no quantitative work has been undertaken to evaluate the benefit of a pre-process based on image filtering, which can improve feature tracking robustness. In this paper, we propose a methodology to validate detection and feature tracking algorithms, using a trick based on forward-backward tracking that provides an artificial ground truth data. We describe a clear and complete methodology to evaluate and compare different detection and tracking algorithms. In addition, we extend our framework to propose a strategy to identify the best combinations from a set of detector, tracker and pre-process algorithms, according to the live intra-operative data. Experimental results have been performed on in vivo datasets and show that pre-process can have a strong influence on tracking performance and that our strategy to find the best combinations is relevant for a reasonable computation cost. Copyright © 2014 Elsevier Ltd. All rights reserved.

Optical tracking of nanoscale particles in microscale environments

NASA Astrophysics Data System (ADS)

Mathai, P. P.; Liddle, J. A.; Stavis, S. M.

2016-03-01

The trajectories of nanoscale particles through microscale environments record useful information about both the particles and the environments. Optical microscopes provide efficient access to this information through measurements of light in the far field from nanoparticles. Such measurements necessarily involve trade-offs in tracking capabilities. This article presents a measurement framework, based on information theory, that facilitates a more systematic understanding of such trade-offs to rationally design tracking systems for diverse applications. This framework includes the degrees of freedom of optical microscopes, which determine the limitations of tracking measurements in theory. In the laboratory, tracking systems are assemblies of sources and sensors, optics and stages, and nanoparticle emitters. The combined characteristics of such systems determine the limitations of tracking measurements in practice. This article reviews this tracking hardware with a focus on the essential functions of nanoparticles as optical emitters and microenvironmental probes. Within these theoretical and practical limitations, experimentalists have implemented a variety of tracking systems with different capabilities. This article reviews a selection of apparatuses and techniques for tracking multiple and single particles by tuning illumination and detection, and by using feedback and confinement to improve the measurements. Prior information is also useful in many tracking systems and measurements, which apply across a broad spectrum of science and technology. In the context of the framework and review of apparatuses and techniques, this article reviews a selection of applications, with particle diffusion serving as a prelude to tracking measurements in biological, fluid, and material systems, fabrication and assembly processes, and engineered devices. In so doing, this review identifies trends and gaps in particle tracking that might influence future research.

A FPGA-based Cluster Finder for CMOS Monolithic Active Pixel Sensors of the MIMOSA-26 Family

NASA Astrophysics Data System (ADS)

Li, Qiyan; Amar-Youcef, S.; Doering, D.; Deveaux, M.; Fröhlich, I.; Koziel, M.; Krebs, E.; Linnik, B.; Michel, J.; Milanovic, B.; Müntz, C.; Stroth, J.; Tischler, T.

2014-06-01

CMOS Monolithic Active Pixel Sensors (MAPS) demonstrated excellent performances in the field of charged particle tracking. Among their strong points are an single point resolution few μm, a light material budget of 0.05% X0 in combination with a good radiation tolerance and high rate capability. Those features make the sensors a valuable technology for vertex detectors of various experiments in heavy ion and particle physics. To reduce the load on the event builders and future mass storage systems, we have developed algorithms suited for preprocessing and reducing the data streams generated by the MAPS. This real-time processing employs remaining free resources of the FPGAs of the readout controllers of the detector and complements the on-chip data reduction circuits of the MAPS.

Coupled particle-in-cell and Monte Carlo transport modeling of intense radiographic sources

NASA Astrophysics Data System (ADS)

Rose, D. V.; Welch, D. R.; Oliver, B. V.; Clark, R. E.; Johnson, D. L.; Maenchen, J. E.; Menge, P. R.; Olson, C. L.; Rovang, D. C.

2002-03-01

Dose-rate calculations for intense electron-beam diodes using particle-in-cell (PIC) simulations along with Monte Carlo electron/photon transport calculations are presented. The electromagnetic PIC simulations are used to model the dynamic operation of the rod-pinch and immersed-B diodes. These simulations include algorithms for tracking electron scattering and energy loss in dense materials. The positions and momenta of photons created in these materials are recorded and separate Monte Carlo calculations are used to transport the photons to determine the dose in far-field detectors. These combined calculations are used to determine radiographer equations (dose scaling as a function of diode current and voltage) that are compared directly with measured dose rates obtained on the SABRE generator at Sandia National Laboratories.

MALBEC: a new CUDA-C ray-tracer in general relativity

NASA Astrophysics Data System (ADS)

Quiroga, G. D.

2018-06-01

A new CUDA-C code for tracing orbits around non-charged black holes is presented. This code, named MALBEC, take advantage of the graphic processing units and the CUDA platform for tracking null and timelike test particles in Schwarzschild and Kerr. Also, a new general set of equations that describe the closed circular orbits of any timelike test particle in the equatorial plane is derived. These equations are extremely important in order to compare the analytical behavior of the orbits with the numerical results and verify the correct implementation of the Runge-Kutta algorithm in MALBEC. Finally, other numerical tests are performed, demonstrating that MALBEC is able to reproduce some well-known results in these metrics in a faster and more efficient way than a conventional CPU implementation.

An extended Kalman filter for mouse tracking.

PubMed

Choi, Hongjun; Kim, Mingi; Lee, Onseok

2018-05-19

Animal tracking is an important tool for observing behavior, which is useful in various research areas. Animal specimens can be tracked using dynamic models and observation models that require several types of data. Tracking mouse has several barriers due to the physical characteristics of the mouse, their unpredictable movement, and cluttered environments. Therefore, we propose a reliable method that uses a detection stage and a tracking stage to successfully track mouse. The detection stage detects the surface area of the mouse skin, and the tracking stage implements an extended Kalman filter to estimate the state variables of a nonlinear model. The changes in the overall shape of the mouse are tracked using an oval-shaped tracking model to estimate the parameters for the ellipse. An experiment is conducted to demonstrate the performance of the proposed tracking algorithm using six video images showing various types of movement, and the ground truth values for synthetic images are compared to the values generated by the tracking algorithm. A conventional manual tracking method is also applied to compare across eight experimenters. Furthermore, the effectiveness of the proposed tracking method is also demonstrated by applying the tracking algorithm with actual images of mouse. Graphical abstract.

Experimental investigation of a moving averaging algorithm for motion perpendicular to the leaf travel direction in dynamic MLC target tracking.

PubMed

Yoon, Jai-Woong; Sawant, Amit; Suh, Yelin; Cho, Byung-Chul; Suh, Tae-Suk; Keall, Paul

2011-07-01

In dynamic multileaf collimator (MLC) motion tracking with complex intensity-modulated radiation therapy (IMRT) fields, target motion perpendicular to the MLC leaf travel direction can cause beam holds, which increase beam delivery time by up to a factor of 4. As a means to balance delivery efficiency and accuracy, a moving average algorithm was incorporated into a dynamic MLC motion tracking system (i.e., moving average tracking) to account for target motion perpendicular to the MLC leaf travel direction. The experimental investigation of the moving average algorithm compared with real-time tracking and no compensation beam delivery is described. The properties of the moving average algorithm were measured and compared with those of real-time tracking (dynamic MLC motion tracking accounting for both target motion parallel and perpendicular to the leaf travel direction) and no compensation beam delivery. The algorithm was investigated using a synthetic motion trace with a baseline drift and four patient-measured 3D tumor motion traces representing regular and irregular motions with varying baseline drifts. Each motion trace was reproduced by a moving platform. The delivery efficiency, geometric accuracy, and dosimetric accuracy were evaluated for conformal, step-and-shoot IMRT, and dynamic sliding window IMRT treatment plans using the synthetic and patient motion traces. The dosimetric accuracy was quantified via a tgamma-test with a 3%/3 mm criterion. The delivery efficiency ranged from 89 to 100% for moving average tracking, 26%-100% for real-time tracking, and 100% (by definition) for no compensation. The root-mean-square geometric error ranged from 3.2 to 4.0 mm for moving average tracking, 0.7-1.1 mm for real-time tracking, and 3.7-7.2 mm for no compensation. The percentage of dosimetric points failing the gamma-test ranged from 4 to 30% for moving average tracking, 0%-23% for real-time tracking, and 10%-47% for no compensation. The delivery efficiency of moving average tracking was up to four times higher than that of real-time tracking and approached the efficiency of no compensation for all cases. The geometric accuracy and dosimetric accuracy of the moving average algorithm was between real-time tracking and no compensation, approximately half the percentage of dosimetric points failing the gamma-test compared with no compensation.

Detection and Tracking of Dynamic Objects by Using a Multirobot System: Application to Critical Infrastructures Surveillance

PubMed Central

Rodríguez-Canosa, Gonzalo; Giner, Jaime del Cerro; Barrientos, Antonio

2014-01-01

The detection and tracking of mobile objects (DATMO) is progressively gaining importance for security and surveillance applications. This article proposes a set of new algorithms and procedures for detecting and tracking mobile objects by robots that work collaboratively as part of a multirobot system. These surveillance algorithms are conceived of to work with data provided by long distance range sensors and are intended for highly reliable object detection in wide outdoor environments. Contrary to most common approaches, in which detection and tracking are done by an integrated procedure, the approach proposed here relies on a modular structure, in which detection and tracking are carried out independently, and the latter might accept input data from different detection algorithms. Two movement detection algorithms have been developed for the detection of dynamic objects by using both static and/or mobile robots. The solution to the overall problem is based on the use of a Kalman filter to predict the next state of each tracked object. Additionally, new tracking algorithms capable of combining dynamic objects lists coming from either one or various sources complete the solution. The complementary performance of the separated modular structure for detection and identification is evaluated and, finally, a selection of test examples discussed. PMID:24526305

Evaluation of Real-Time Hand Motion Tracking Using a Range Camera and the Mean-Shift Algorithm

NASA Astrophysics Data System (ADS)

Lahamy, H.; Lichti, D.

2011-09-01

Several sensors have been tested for improving the interaction between humans and machines including traditional web cameras, special gloves, haptic devices, cameras providing stereo pairs of images and range cameras. Meanwhile, several methods are described in the literature for tracking hand motion: the Kalman filter, the mean-shift algorithm and the condensation algorithm. In this research, the combination of a range camera and the simple version of the mean-shift algorithm has been evaluated for its capability for hand motion tracking. The evaluation was assessed in terms of position accuracy of the tracking trajectory in x, y and z directions in the camera space and the time difference between image acquisition and image display. Three parameters have been analyzed regarding their influence on the tracking process: the speed of the hand movement, the distance between the camera and the hand and finally the integration time of the camera. Prior to the evaluation, the required warm-up time of the camera has been measured. This study has demonstrated the suitability of the range camera used in combination with the mean-shift algorithm for real-time hand motion tracking but for very high speed hand movement in the traverse plane with respect to the camera, the tracking accuracy is low and requires improvement.

Enhanced compressed sensing for visual target tracking in wireless visual sensor networks

NASA Astrophysics Data System (ADS)

Qiang, Guo

2017-11-01

Moving object tracking in wireless sensor networks (WSNs) has been widely applied in various fields. Designing low-power WSNs for the limited resources of the sensor, such as energy limitation, energy restriction, and bandwidth constraints, is of high priority. However, most existing works focus on only single conflicting optimization criteria. An efficient compressive sensing technique based on a customized memory gradient pursuit algorithm with early termination in WSNs is presented, which strikes compelling trade-offs among energy dissipation for wireless transmission, certain types of bandwidth, and minimum storage. Then, the proposed approach adopts an unscented particle filter to predict the location of the target. The experimental results with a theoretical analysis demonstrate the substantially superior effectiveness of the proposed model and framework in regard to the energy and speed under the resource limitation of a visual sensor node.

Performance analysis of visual tracking algorithms for motion-based user interfaces on mobile devices

NASA Astrophysics Data System (ADS)

Winkler, Stefan; Rangaswamy, Karthik; Tedjokusumo, Jefry; Zhou, ZhiYing

2008-02-01

Determining the self-motion of a camera is useful for many applications. A number of visual motion-tracking algorithms have been developed till date, each with their own advantages and restrictions. Some of them have also made their foray into the mobile world, powering augmented reality-based applications on phones with inbuilt cameras. In this paper, we compare the performances of three feature or landmark-guided motion tracking algorithms, namely marker-based tracking with MXRToolkit, face tracking based on CamShift, and MonoSLAM. We analyze and compare the complexity, accuracy, sensitivity, robustness and restrictions of each of the above methods. Our performance tests are conducted over two stages: The first stage of testing uses video sequences created with simulated camera movements along the six degrees of freedom in order to compare accuracy in tracking, while the second stage analyzes the robustness of the algorithms by testing for manipulative factors like image scaling and frame-skipping.

Multiple objects tracking in fluorescence microscopy.

PubMed

Kalaidzidis, Yannis

2009-01-01

Many processes in cell biology are connected to the movement of compact entities: intracellular vesicles and even single molecules. The tracking of individual objects is important for understanding cellular dynamics. Here we describe the tracking algorithms which have been developed in the non-biological fields and successfully applied to object detection and tracking in biological applications. The characteristics features of the different algorithms are compared.

Eye-Tracking Verification of the Strategy Used to Analyse Algorithms Expressed in a Flowchart and Pseudocode

ERIC Educational Resources Information Center

Andrzejewska, Magdalena; Stolinska, Anna; Blasiak, Wladyslaw; Peczkowski, Pawel; Rosiek, Roman; Rozek, Bozena; Sajka, Miroslawa; Wcislo, Dariusz

2016-01-01

The results of qualitative and quantitative investigations conducted with individuals who learned algorithms in school are presented in this article. In these investigations, eye-tracking technology was used to follow the process of solving algorithmic problems. The algorithmic problems were presented in two comparable variants: in a pseudocode…

Instrumentation, Techniques, and Evaluation of ePTV for Particle Manipulation Studies Using Micro-Scale Oscillators

NASA Astrophysics Data System (ADS)

Kafashi, Sajad

A need for dynamic micro-particle manipulation is the ability to position fragile particles without damaging them, for instance biological particles like blood cells, stem cells, neurons, pancreatic ? cells, DNA, chromosomes, for repeated measurement without altering their behavior. An oscillating fiber will induce vortices in a slurry of particles, subsequently the vortex force created by this oscillation attracts and traps the particles located at steady streaming micro-eddies. If multiple oscillatory fibers are placed inside the slurry, depending on frequency and timing of oscillation this method can be used for contact-free particle shepherding and sorting and for transporting particles from one location to another. Due to the complicated dynamics of particles traveling in the fluid and the presence of noise, and significant number of particles, attempts to use commercial PIV softwares to track individual particle paths could not discriminate real particles from noise interference. To enhance identification and tracking of individual particles a novel encoded-particle tracking velocimetry (ePTV) technique is developed in this dissertation work and used in the experiments to track the particle trajectories. An analytic model is developed to determine the number of lost particles due to the finite image size based on a calculation of the probability that imaged particles of a specific mean velocity or having a uniform velocity distribution and encoding pattern will exit the field of view. The encoded pulse technique has been implemented in experiments for which images containing 100-200 objects including encoded trajectories have been measured. Using the developed ePTV algorithm approximately 30 % of the identified objects were classified as an encoded particle trajectory. Two types of oscillation mechanism are used in the experimental component of this study, a PZT flexure-based macro-probe driven at frequencies around 250 Hz and higher frequency dynamic-absorber, quartz-based, micro-probes driven at frequencies around 32 kHz. Two models for predicting the frequency response of micro-scale oscillatory probes are developed in this dissertation. In these studies, the attached fibers were either 75 mum diameter tungsten or 7 mum diameter carbon with lengths ranging from around 1 to 15 mm. The oscillators used in these experiments were commercial 32.768 kHz quartz tuning forks. Theoretical predictions of the values of the natural frequencies for different vibration modes show an asymptotic relationship with the length and a linear relationship with the diameter of the attached fiber. Similar results are observed from experiment, one with a tungsten probe having an initial fiber length of 14.11 mm incrementally etched down to 0.83 mm, and another tungsten probe of length 8.16 mm incrementally etched in diameter, in both cases using chronocoulometry to determine incremental volumetric material removal. Of particular relevance is that, when a 'zero' is observed in the response of the tine, one mode of the fiber is matched to the tine frequency and is acting as an absorber. This represents an optimal condition for contact sensing and for transferring energy to the fiber for fluid mixing, touch sensing and surface modification applications. Consequently the parametric models developed in this dissertation can be utilized for designing probes of arbitrary sizes thereby eliminating the empirical trial and error previously used.

Micro-heterogeneity of corn hulls cellulosic fiber biopolymer studied by multiple-particle tracking (MPT)

USDA-ARS?s Scientific Manuscript database

A novel technique named multiple-particle tracking (MPT) was used to investigate the micro-structural heterogeneities of Z-trim, a zero calorie cellulosic fiber biopolymer produced from corn hulls. The Multiple-Particle Tracking (MPT) method was used in this study, which was originally described by ...

Interacting Multiple Model (IMM) Fifth-Degree Spherical Simplex-Radial Cubature Kalman Filter for Maneuvering Target Tracking

PubMed Central

Liu, Hua; Wu, Wen

2017-01-01

For improving the tracking accuracy and model switching speed of maneuvering target tracking in nonlinear systems, a new algorithm named the interacting multiple model fifth-degree spherical simplex-radial cubature Kalman filter (IMM5thSSRCKF) is proposed in this paper. The new algorithm is a combination of the interacting multiple model (IMM) filter and the fifth-degree spherical simplex-radial cubature Kalman filter (5thSSRCKF). The proposed algorithm makes use of Markov process to describe the switching probability among the models, and uses 5thSSRCKF to deal with the state estimation of each model. The 5thSSRCKF is an improved filter algorithm, which utilizes the fifth-degree spherical simplex-radial rule to improve the filtering accuracy. Finally, the tracking performance of the IMM5thSSRCKF is evaluated by simulation in a typical maneuvering target tracking scenario. Simulation results show that the proposed algorithm has better tracking performance and quicker model switching speed when disposing maneuver models compared with the interacting multiple model unscented Kalman filter (IMMUKF), the interacting multiple model cubature Kalman filter (IMMCKF) and the interacting multiple model fifth-degree cubature Kalman filter (IMM5thCKF). PMID:28608843

Interacting Multiple Model (IMM) Fifth-Degree Spherical Simplex-Radial Cubature Kalman Filter for Maneuvering Target Tracking.

PubMed

Liu, Hua; Wu, Wen

2017-06-13

For improving the tracking accuracy and model switching speed of maneuvering target tracking in nonlinear systems, a new algorithm named the interacting multiple model fifth-degree spherical simplex-radial cubature Kalman filter (IMM5thSSRCKF) is proposed in this paper. The new algorithm is a combination of the interacting multiple model (IMM) filter and the fifth-degree spherical simplex-radial cubature Kalman filter (5thSSRCKF). The proposed algorithm makes use of Markov process to describe the switching probability among the models, and uses 5thSSRCKF to deal with the state estimation of each model. The 5thSSRCKF is an improved filter algorithm, which utilizes the fifth-degree spherical simplex-radial rule to improve the filtering accuracy. Finally, the tracking performance of the IMM5thSSRCKF is evaluated by simulation in a typical maneuvering target tracking scenario. Simulation results show that the proposed algorithm has better tracking performance and quicker model switching speed when disposing maneuver models compared with the interacting multiple model unscented Kalman filter (IMMUKF), the interacting multiple model cubature Kalman filter (IMMCKF) and the interacting multiple model fifth-degree cubature Kalman filter (IMM5thCKF).

A GPU-accelerated 3D Coupled Sub-sample Estimation Algorithm for Volumetric Breast Strain Elastography

PubMed Central

Peng, Bo; Wang, Yuqi; Hall, Timothy J; Jiang, Jingfeng

2017-01-01

Our primary objective of this work was to extend a previously published 2D coupled sub-sample tracking algorithm for 3D speckle tracking in the framework of ultrasound breast strain elastography. In order to overcome heavy computational cost, we investigated the use of a graphic processing unit (GPU) to accelerate the 3D coupled sub-sample speckle tracking method. The performance of the proposed GPU implementation was tested using a tissue-mimicking (TM) phantom and in vivo breast ultrasound data. The performance of this 3D sub-sample tracking algorithm was compared with the conventional 3D quadratic sub-sample estimation algorithm. On the basis of these evaluations, we concluded that the GPU implementation of this 3D sub-sample estimation algorithm can provide high-quality strain data (i.e. high correlation between the pre- and the motion-compensated post-deformation RF echo data and high contrast-to-noise ratio strain images), as compared to the conventional 3D quadratic sub-sample algorithm. Using the GPU implementation of the 3D speckle tracking algorithm, volumetric strain data can be achieved relatively fast (approximately 20 seconds per volume [2.5 cm × 2.5 cm × 2.5 cm]). PMID:28166493

Implementation Strategies for Large-Scale Transport Simulations Using Time Domain Particle Tracking

NASA Astrophysics Data System (ADS)

Painter, S.; Cvetkovic, V.; Mancillas, J.; Selroos, J.

2008-12-01

Time domain particle tracking is an emerging alternative to the conventional random walk particle tracking algorithm. With time domain particle tracking, particles are moved from node to node on one-dimensional pathways defined by streamlines of the groundwater flow field or by discrete subsurface features. The time to complete each deterministic segment is sampled from residence time distributions that include the effects of advection, longitudinal dispersion, a variety of kinetically controlled retention (sorption) processes, linear transformation, and temporal changes in groundwater velocities and sorption parameters. The simulation results in a set of arrival times at a monitoring location that can be post-processed with a kernel method to construct mass discharge (breakthrough) versus time. Implementation strategies differ for discrete flow (fractured media) systems and continuous porous media systems. The implementation strategy also depends on the scale at which hydraulic property heterogeneity is represented in the supporting flow model. For flow models that explicitly represent discrete features (e.g., discrete fracture networks), the sampling of residence times along segments is conceptually straightforward. For continuous porous media, such sampling needs to be related to the Lagrangian velocity field. Analytical or semi-analytical methods may be used to approximate the Lagrangian segment velocity distributions in aquifers with low-to-moderate variability, thereby capturing transport effects of subgrid velocity variability. If variability in hydraulic properties is large, however, Lagrangian velocity distributions are difficult to characterize and numerical simulations are required; in particular, numerical simulations are likely to be required for estimating the velocity integral scale as a basis for advective segment distributions. Aquifers with evolving heterogeneity scales present additional challenges. Large-scale simulations of radionuclide transport at two potential repository sites for high-level radioactive waste will be used to demonstrate the potential of the method. The simulations considered approximately 1000 source locations, multiple radionuclides with contrasting sorption properties, and abrupt changes in groundwater velocity associated with future glacial scenarios. Transport pathways linking the source locations to the accessible environment were extracted from discrete feature flow models that include detailed representations of the repository construction (tunnels, shafts, and emplacement boreholes) embedded in stochastically generated fracture networks. Acknowledgment The authors are grateful to SwRI Advisory Committee for Research, the Swedish Nuclear Fuel and Waste Management Company, and Posiva Oy for financial support.

An Objective Comparison of Cell Tracking Algorithms

PubMed Central

Ulman, Vladimír; Maška, Martin; Magnusson, Klas E. G.; Ronneberger, Olaf; Haubold, Carsten; Harder, Nathalie; Matula, Pavel; Matula, Petr; Svoboda, David; Radojevic, Miroslav; Smal, Ihor; Rohr, Karl; Jaldén, Joakim; Blau, Helen M.; Dzyubachyk, Oleh; Lelieveldt, Boudewijn; Xiao, Pengdong; Li, Yuexiang; Cho, Siu-Yeung; Dufour, Alexandre C.; Olivo-Marin, Jean-Christophe; Reyes-Aldasoro, Constantino C.; Solis-Lemus, Jose A.; Bensch, Robert; Brox, Thomas; Stegmaier, Johannes; Mikut, Ralf; Wolf, Steffen; Hamprecht, Fred. A.; Esteves, Tiago; Quelhas, Pedro; Demirel, Ömer; Malmström, Lars; Jug, Florian; Tomancak, Pavel; Meijering, Erik; Muñoz-Barrutia, Arrate; Kozubek, Michal; Ortiz-de-Solorzano, Carlos

2017-01-01

We present a combined report on the results of three editions of the Cell Tracking Challenge, an ongoing initiative aimed at promoting the development and objective evaluation of cell tracking algorithms. With twenty-one participating algorithms and a data repository consisting of thirteen datasets of various microscopy modalities, the challenge displays today’s state of the art in the field. We analyze the results using performance measures for segmentation and tracking that rank all participating methods. We also analyze the performance of all algorithms in terms of biological measures and their practical usability. Even though some methods score high in all technical aspects, not a single one obtains fully correct solutions. We show that methods that either take prior information into account using learning strategies or analyze cells in a global spatio-temporal video context perform better than other methods under the segmentation and tracking scenarios included in the challenge. PMID:29083403

An objective comparison of cell-tracking algorithms.

PubMed

Ulman, Vladimír; Maška, Martin; Magnusson, Klas E G; Ronneberger, Olaf; Haubold, Carsten; Harder, Nathalie; Matula, Pavel; Matula, Petr; Svoboda, David; Radojevic, Miroslav; Smal, Ihor; Rohr, Karl; Jaldén, Joakim; Blau, Helen M; Dzyubachyk, Oleh; Lelieveldt, Boudewijn; Xiao, Pengdong; Li, Yuexiang; Cho, Siu-Yeung; Dufour, Alexandre C; Olivo-Marin, Jean-Christophe; Reyes-Aldasoro, Constantino C; Solis-Lemus, Jose A; Bensch, Robert; Brox, Thomas; Stegmaier, Johannes; Mikut, Ralf; Wolf, Steffen; Hamprecht, Fred A; Esteves, Tiago; Quelhas, Pedro; Demirel, Ömer; Malmström, Lars; Jug, Florian; Tomancak, Pavel; Meijering, Erik; Muñoz-Barrutia, Arrate; Kozubek, Michal; Ortiz-de-Solorzano, Carlos

2017-12-01

We present a combined report on the results of three editions of the Cell Tracking Challenge, an ongoing initiative aimed at promoting the development and objective evaluation of cell segmentation and tracking algorithms. With 21 participating algorithms and a data repository consisting of 13 data sets from various microscopy modalities, the challenge displays today's state-of-the-art methodology in the field. We analyzed the challenge results using performance measures for segmentation and tracking that rank all participating methods. We also analyzed the performance of all of the algorithms in terms of biological measures and practical usability. Although some methods scored high in all technical aspects, none obtained fully correct solutions. We found that methods that either take prior information into account using learning strategies or analyze cells in a global spatiotemporal video context performed better than other methods under the segmentation and tracking scenarios included in the challenge.

Target-type probability combining algorithms for multisensor tracking

NASA Astrophysics Data System (ADS)

Wigren, Torbjorn

2001-08-01

Algorithms for the handing of target type information in an operational multi-sensor tracking system are presented. The paper discusses recursive target type estimation, computation of crosses from passive data (strobe track triangulation), as well as the computation of the quality of the crosses for deghosting purposes. The focus is on Bayesian algorithms that operate in the discrete target type probability space, and on the approximations introduced for computational complexity reduction. The centralized algorithms are able to fuse discrete data from a variety of sensors and information sources, including IFF equipment, ESM's, IRST's as well as flight envelopes estimated from track data. All algorithms are asynchronous and can be tuned to handle clutter, erroneous associations as well as missed and erroneous detections. A key to obtain this ability is the inclusion of data forgetting by a procedure for propagation of target type probability states between measurement time instances. Other important properties of the algorithms are their abilities to handle ambiguous data and scenarios. The above aspects are illustrated in a simulations study. The simulation setup includes 46 air targets of 6 different types that are tracked by 5 airborne sensor platforms using ESM's and IRST's as data sources.

Fuzzy Neural Network-Based Interacting Multiple Model for Multi-Node Target Tracking Algorithm

PubMed Central

Sun, Baoliang; Jiang, Chunlan; Li, Ming

2016-01-01

An interacting multiple model for multi-node target tracking algorithm was proposed based on a fuzzy neural network (FNN) to solve the multi-node target tracking problem of wireless sensor networks (WSNs). Measured error variance was adaptively adjusted during the multiple model interacting output stage using the difference between the theoretical and estimated values of the measured error covariance matrix. The FNN fusion system was established during multi-node fusion to integrate with the target state estimated data from different nodes and consequently obtain network target state estimation. The feasibility of the algorithm was verified based on a network of nine detection nodes. Experimental results indicated that the proposed algorithm could trace the maneuvering target effectively under sensor failure and unknown system measurement errors. The proposed algorithm exhibited great practicability in the multi-node target tracking of WSNs. PMID:27809271

A joint tracking method for NSCC based on WLS algorithm

NASA Astrophysics Data System (ADS)

Luo, Ruidan; Xu, Ying; Yuan, Hong

2017-12-01

Navigation signal based on compound carrier (NSCC), has the flexible multi-carrier scheme and various scheme parameters configuration, which enables it to possess significant efficiency of navigation augmentation in terms of spectral efficiency, tracking accuracy, multipath mitigation capability and anti-jamming reduction compared with legacy navigation signals. Meanwhile, the typical scheme characteristics can provide auxiliary information for signal synchronism algorithm design. This paper, based on the characteristics of NSCC, proposed a kind of joint tracking method utilizing Weighted Least Square (WLS) algorithm. In this method, the LS algorithm is employed to jointly estimate each sub-carrier frequency shift with the frequency-Doppler linear relationship, by utilizing the known sub-carrier frequency. Besides, the weighting matrix is set adaptively according to the sub-carrier power to ensure the estimation accuracy. Both the theory analysis and simulation results illustrate that the tracking accuracy and sensitivity of this method outperforms the single-carrier algorithm with lower SNR.

Novel algorithm and MATLAB-based program for automated power law analysis of single particle, time-dependent mean-square displacement

NASA Astrophysics Data System (ADS)

Umansky, Moti; Weihs, Daphne

2012-08-01

In many physical and biophysical studies, single-particle tracking is utilized to reveal interactions, diffusion coefficients, active modes of driving motion, dynamic local structure, micromechanics, and microrheology. The basic analysis applied to those data is to determine the time-dependent mean-square displacement (MSD) of particle trajectories and perform time- and ensemble-averaging of similar motions. The motion of particles typically exhibits time-dependent power-law scaling, and only trajectories with qualitatively and quantitatively comparable MSD should be ensembled. Ensemble averaging trajectories that arise from different mechanisms, e.g., actively driven and diffusive, is incorrect and can result inaccurate correlations between structure, mechanics, and activity. We have developed an algorithm to automatically and accurately determine power-law scaling of experimentally measured single-particle MSD. Trajectories can then categorized and grouped according to user defined cutoffs of time, amplitudes, scaling exponent values, or combinations. Power-law fits are then provided for each trajectory alongside categorized groups of trajectories, histograms of power laws, and the ensemble-averaged MSD of each group. The codes are designed to be easily incorporated into existing user codes. We expect that this algorithm and program will be invaluable to anyone performing single-particle tracking, be it in physical or biophysical systems. Catalogue identifier: AEMD_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEMD_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 25 892 No. of bytes in distributed program, including test data, etc.: 5 572 780 Distribution format: tar.gz Programming language: MATLAB (MathWorks Inc.) version 7.11 (2010b) or higher, program should also be backwards compatible. Symbolic Math Toolboxes (5.5) is required. The Curve Fitting Toolbox (3.0) is recommended. Computer: Tested on Windows only, yet should work on any computer running MATLAB. In Windows 7, should be used as administrator, if the user is not the administrator the program may not be able to save outputs and temporary outputs to all locations. Operating system: Any supporting MATLAB (MathWorks Inc.) v7.11 / 2010b or higher. Supplementary material: Sample output files (approx. 30 MBytes) are available. Classification: 12 External routines: Several MATLAB subfunctions (m-files), freely available on the web, were used as part of and included in, this code: count, NaN suite, parseArgs, roundsd, subaxis, wcov, wmean, and the executable pdfTK.exe. Nature of problem: In many physical and biophysical areas employing single-particle tracking, having the time-dependent power-laws governing the time-averaged meansquare displacement (MSD) of a single particle is crucial. Those power laws determine the mode-of-motion and hint at the underlying mechanisms driving motion. Accurate determination of the power laws that describe each trajectory will allow categorization into groups for further analysis of single trajectories or ensemble analysis, e.g. ensemble and time-averaged MSD. Solution method: The algorithm in the provided program automatically analyzes and fits time-dependent power laws to single particle trajectories, then group particles according to user defined cutoffs. It accepts time-dependent trajectories of several particles, each trajectory is run through the program, its time-averaged MSD is calculated, and power laws are determined in regions where the MSD is linear on a log-log scale. Our algorithm searches for high-curvature points in experimental data, here time-dependent MSD. Those serve as anchor points for determining the ranges of the power-law fits. Power-law scaling is then accurately determined and error estimations of the parameters and quality of fit are provided. After all single trajectory time-averaged MSDs are fit, we obtain cutoffs from the user to categorize and segment the power laws into groups; cutoff are either in exponents of the power laws, time of appearance of the fits, or both together. The trajectories are sorted according to the cutoffs and the time- and ensemble-averaged MSD of each group is provided, with histograms of the distributions of the exponents in each group. The program then allows the user to generate new trajectory files with trajectories segmented according to the determined groups, for any further required analysis. Additional comments: README file giving the names and a brief description of all the files that make-up the package and clear instructions on the installation and execution of the program is included in the distribution package. Running time: On an i5 Windows 7 machine with 4 GB RAM the automated parts of the run (excluding data loading and user input) take less than 45 minutes to analyze and save all stages for an 844 trajectory file, including optional PDF save. Trajectory length did not affect run time (tested up to 3600 frames/trajectory), which was on average 3.2±0.4 seconds per trajectory.

Track structure in radiation biology: theory and applications.

PubMed

Nikjoo, H; Uehara, S; Wilson, W E; Hoshi, M; Goodhead, D T

1998-04-01

A brief review is presented of the basic concepts in track structure and the relative merit of various theoretical approaches adopted in Monte-Carlo track-structure codes are examined. In the second part of the paper, a formal cluster analysis is introduced to calculate cluster-distance distributions. Total experimental ionization cross-sections were least-square fitted and compared with the calculation by various theoretical methods. Monte-Carlo track-structure code Kurbuc was used to examine and compare the spectrum of the secondary electrons generated by using functions given by Born-Bethe, Jain-Khare, Gryzinsky, Kim-Rudd, Mott and Vriens' theories. The cluster analysis in track structure was carried out using the k-means method and Hartigan algorithm. Data are presented on experimental and calculated total ionization cross-sections: inverse mean free path (IMFP) as a function of electron energy used in Monte-Carlo track-structure codes; the spectrum of secondary electrons generated by different functions for 500 eV primary electrons; cluster analysis for 4 MeV and 20 MeV alpha-particles in terms of the frequency of total cluster energy to the root-mean-square (rms) radius of the cluster and differential distance distributions for a pair of clusters; and finally relative frequency distribution for energy deposited in DNA, single-strand break and double-strand breaks for 10MeV/u protons, alpha-particles and carbon ions. There are a number of Monte-Carlo track-structure codes that have been developed independently and the bench-marking presented in this paper allows a better choice of the theoretical method adopted in a track-structure code to be made. A systematic bench-marking of cross-sections and spectra of the secondary electrons shows differences between the codes at atomic level, but such differences are not significant in biophysical modelling at the macromolecular level. Clustered-damage evaluation shows: that a substantial proportion of dose ( 30%) is deposited by low-energy electrons; the majority of DNA damage lesions are of simple type; the complexity of damage increases with increased LET, while the total yield of strand breaks remains constant; and at high LET values nearly 70% of all double-strand breaks are of complex type.

Research of maneuvering target prediction and tracking technology based on IMM algorithm

NASA Astrophysics Data System (ADS)

Cao, Zheng; Mao, Yao; Deng, Chao; Liu, Qiong; Chen, Jing

2016-09-01

Maneuvering target prediction and tracking technology is widely used in both military and civilian applications, the study of those technologies is all along the hotspot and difficulty. In the Electro-Optical acquisition-tracking-pointing system (ATP), the primary traditional maneuvering targets are ballistic target, large aircraft and other big targets. Those targets have the features of fast velocity and a strong regular trajectory and Kalman Filtering and polynomial fitting have good effects when they are used to track those targets. In recent years, the small unmanned aerial vehicles developed rapidly for they are small, nimble and simple operation. The small unmanned aerial vehicles have strong maneuverability in the observation system of ATP although they are close-in, slow and small targets. Moreover, those vehicles are under the manual operation, therefore, the acceleration of them changes greatly and they move erratically. So the prediction and tracking precision is low when traditional algorithms are used to track the maneuvering fly of those targets, such as speeding up, turning, climbing and so on. The interacting multiple model algorithm (IMM) use multiple models to match target real movement trajectory, there are interactions between each model. The IMM algorithm can switch model based on a Markov chain to adapt to the change of target movement trajectory, so it is suitable to solve the prediction and tracking problems of the small unmanned aerial vehicles because of the better adaptability of irregular movement. This paper has set up model set of constant velocity model (CV), constant acceleration model (CA), constant turning model (CT) and current statistical model. And the results of simulating and analyzing the real movement trajectory data of the small unmanned aerial vehicles show that the prediction and tracking technology based on the interacting multiple model algorithm can get relatively lower tracking error and improve tracking precision comparing with traditional algorithms.

Decorrelation correction for nanoparticle tracking analysis of dilute polydisperse suspensions in bulk flow

NASA Astrophysics Data System (ADS)

Hartman, John; Kirby, Brian

2017-03-01

Nanoparticle tracking analysis, a multiprobe single particle tracking technique, is a widely used method to quickly determine the concentration and size distribution of colloidal particle suspensions. Many popular tools remove non-Brownian components of particle motion by subtracting the ensemble-average displacement at each time step, which is termed dedrifting. Though critical for accurate size measurements, dedrifting is shown here to introduce significant biasing error and can fundamentally limit the dynamic range of particle size that can be measured for dilute heterogeneous suspensions such as biological extracellular vesicles. We report a more accurate estimate of particle mean-square displacement, which we call decorrelation analysis, that accounts for correlations between individual and ensemble particle motion, which are spuriously introduced by dedrifting. Particle tracking simulation and experimental results show that this approach more accurately determines particle diameters for low-concentration polydisperse suspensions when compared with standard dedrifting techniques.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Qin, SB; Cady, ST; Dominguez-Garcia, AD

This paper presents the theory and implementation of a distributed algorithm for controlling differential power processing converters in photovoltaic (PV) applications. This distributed algorithm achieves true maximum power point tracking of series-connected PV submodules by relying only on local voltage measurements and neighbor-to-neighbor communication between the differential power converters. Compared to previous solutions, the proposed algorithm achieves reduced number of perturbations at each step and potentially faster tracking without adding extra hardware; all these features make this algorithm well-suited for long submodule strings. The formulation of the algorithm, discussion of its properties, as well as three case studies are presented.more » The performance of the distributed tracking algorithm has been verified via experiments, which yielded quantifiable improvements over other techniques that have been implemented in practice. Both simulations and hardware experiments have confirmed the effectiveness of the proposed distributed algorithm.« less

Sequential Monte Carlo tracking of the marginal artery by multiple cue fusion and random forest regression.

PubMed

Cherry, Kevin M; Peplinski, Brandon; Kim, Lauren; Wang, Shijun; Lu, Le; Zhang, Weidong; Liu, Jianfei; Wei, Zhuoshi; Summers, Ronald M

2015-01-01

Given the potential importance of marginal artery localization in automated registration in computed tomography colonography (CTC), we have devised a semi-automated method of marginal vessel detection employing sequential Monte Carlo tracking (also known as particle filtering tracking) by multiple cue fusion based on intensity, vesselness, organ detection, and minimum spanning tree information for poorly enhanced vessel segments. We then employed a random forest algorithm for intelligent cue fusion and decision making which achieved high sensitivity and robustness. After applying a vessel pruning procedure to the tracking results, we achieved statistically significantly improved precision compared to a baseline Hessian detection method (2.7% versus 75.2%, p<0.001). This method also showed statistically significantly improved recall rate compared to a 2-cue baseline method using fewer vessel cues (30.7% versus 67.7%, p<0.001). These results demonstrate that marginal artery localization on CTC is feasible by combining a discriminative classifier (i.e., random forest) with a sequential Monte Carlo tracking mechanism. In so doing, we present the effective application of an anatomical probability map to vessel pruning as well as a supplementary spatial coordinate system for colonic segmentation and registration when this task has been confounded by colon lumen collapse. Published by Elsevier B.V.

Nonstationary EO/IR Clutter Suppression and Dim Object Tracking

DTIC Science & Technology

2010-01-01

Brown, A., and Brown, J., Enhanced Algorithms for EO /IR Electronic Stabilization, Clutter Suppression, and Track - Before - Detect for Multiple Low...estimation-suppression and nonlinear filtering-based multiple-object track - before - detect . These algorithms are suitable for integration into...In such cases, it is imperative to develop efficient real or near-real time tracking before detection methods. This paper continues the work started

Navigation of autonomous vehicles for oil spill cleaning in dynamic and uncertain environments

NASA Astrophysics Data System (ADS)

Jin, Xin; Ray, Asok

2014-04-01

In the context of oil spill cleaning by autonomous vehicles in dynamic and uncertain environments, this paper presents a multi-resolution algorithm that seamlessly integrates the concepts of local navigation and global navigation based on the sensory information; the objective here is to enable adaptive decision making and online replanning of vehicle paths. The proposed algorithm provides a complete coverage of the search area for clean-up of the oil spills and does not suffer from the problem of having local minima, which is commonly encountered in potential-field-based methods. The efficacy of the algorithm is tested on a high-fidelity player/stage simulator for oil spill cleaning in a harbour, where the underlying oil weathering process is modelled as 2D random-walk particle tracking. A preliminary version of this paper was presented by X. Jin and A. Ray as 'Coverage Control of Autonomous Vehicles for Oil Spill Cleaning in Dynamic and Uncertain Environments', Proceedings of the American Control Conference, Washington, DC, June 2013, pp. 2600-2605.

Electrons and photons at High Level Trigger in CMS for Run II

NASA Astrophysics Data System (ADS)

Anuar, Afiq A.

2015-12-01

The CMS experiment has been designed with a 2-level trigger system. The first level is implemented using custom-designed electronics. The second level is the so-called High Level Trigger (HLT), a streamlined version of the CMS offline reconstruction software running on a computer farm. For Run II of the Large Hadron Collider, the increase in center-of-mass energy and luminosity will raise the event rate to a level challenging for the HLT algorithms. New approaches have been studied to keep the HLT output rate manageable while maintaining thresholds low enough to cover physics analyses. The strategy mainly relies on porting online the ingredients that have been successfully applied in the offline reconstruction, thus allowing to move HLT selection closer to offline cuts. Improvements in HLT electron and photon definitions will be presented, focusing in particular on: updated clustering algorithm and the energy calibration procedure, new Particle-Flow-based isolation approach and pileup mitigation techniques, and the electron-dedicated track fitting algorithm based on Gaussian Sum Filter.

Different types of maximum power point tracking techniques for renewable energy systems: A survey

NASA Astrophysics Data System (ADS)

Khan, Mohammad Junaid; Shukla, Praveen; Mustafa, Rashid; Chatterji, S.; Mathew, Lini

2016-03-01

Global demand for electricity is increasing while production of energy from fossil fuels is declining and therefore the obvious choice of the clean energy source that is abundant and could provide security for development future is energy from the sun. In this paper, the characteristic of the supply voltage of the photovoltaic generator is nonlinear and exhibits multiple peaks, including many local peaks and a global peak in non-uniform irradiance. To keep global peak, MPPT is the important component of photovoltaic systems. Although many review articles discussed conventional techniques such as P & O, incremental conductance, the correlation ripple control and very few attempts have been made with intelligent MPPT techniques. This document also discusses different algorithms based on fuzzy logic, Ant Colony Optimization, Genetic Algorithm, artificial neural networks, Particle Swarm Optimization Algorithm Firefly, Extremum seeking control method and hybrid methods applied to the monitoring of maximum value of power at point in systems of photovoltaic under changing conditions of irradiance.

Edge-following algorithm for tracking geological features

NASA Technical Reports Server (NTRS)

Tietz, J. C.

1977-01-01

Sequential edge-tracking algorithm employs circular scanning to point permit effective real-time tracking of coastlines and rivers from earth resources satellites. Technique eliminates expensive high-resolution cameras. System might also be adaptable for application in monitoring automated assembly lines, inspecting conveyor belts, or analyzing thermographs, or x ray images.

Optical tracking of nanoscale particles in microscale environments

PubMed Central

Mathai, P. P.; Liddle, J. A.; Stavis, S. M.

2016-01-01

The trajectories of nanoscale particles through microscale environments record useful information about both the particles and the environments. Optical microscopes provide efficient access to this information through measurements of light in the far field from nanoparticles. Such measurements necessarily involve trade-offs in tracking capabilities. This article presents a measurement framework, based on information theory, that facilitates a more systematic understanding of such trade-offs to rationally design tracking systems for diverse applications. This framework includes the degrees of freedom of optical microscopes, which determine the limitations of tracking measurements in theory. In the laboratory, tracking systems are assemblies of sources and sensors, optics and stages, and nanoparticle emitters. The combined characteristics of such systems determine the limitations of tracking measurements in practice. This article reviews this tracking hardware with a focus on the essential functions of nanoparticles as optical emitters and microenvironmental probes. Within these theoretical and practical limitations, experimentalists have implemented a variety of tracking systems with different capabilities. This article reviews a selection of apparatuses and techniques for tracking multiple and single particles by tuning illumination and detection, and by using feedback and confinement to improve the measurements. Prior information is also useful in many tracking systems and measurements, which apply across a broad spectrum of science and technology. In the context of the framework and review of apparatuses and techniques, this article reviews a selection of applications, with particle diffusion serving as a prelude to tracking measurements in biological, fluid, and material systems, fabrication and assembly processes, and engineered devices. In so doing, this review identifies trends and gaps in particle tracking that might influence future research. PMID:27213022

Model of ballistic targets' dynamics used for trajectory tracking algorithms

NASA Astrophysics Data System (ADS)

Okoń-FÄ fara, Marta; Kawalec, Adam; Witczak, Andrzej

2017-04-01

There are known only few ballistic object tracking algorithms. To develop such algorithms and to its further testing, it is necessary to implement possibly simple and reliable objects' dynamics model. The article presents the dynamics' model of a tactical ballistic missile (TBM) including the three stages of flight: the boost stage and two passive stages - the ascending one and the descending one. Additionally, the procedure of transformation from the local coordinate system to the polar-radar oriented and the global is presented. The prepared theoretical data may be used to determine the tracking algorithm parameters and to its further verification.

Autonomous subpixel satellite track end point determination for space-based images.

PubMed

Simms, Lance M

2011-08-01

An algorithm for determining satellite track end points with subpixel resolution in spaced-based images is presented. The algorithm allows for significant curvature in the imaged track due to rotation of the spacecraft capturing the image. The motivation behind the subpixel end point determination is first presented, followed by a description of the methodology used. Results from running the algorithm on real ground-based and simulated spaced-based images are shown to highlight its effectiveness.

Magnetic particle tracking for nonspherical particles in a cylindrical fluidized bed.

PubMed

Buist, Kay A; Jayaprakash, Pavithra; Kuipers, J A M; Deen, Niels G; Padding, Johan T

2017-12-01

In granular flow operations, often particles are nonspherical. This has inspired a vast amount of research in understanding the behavior of these particles. Various models are being developed to study the hydrodynamics involving nonspherical particles. Experiments however are often limited to obtain data on the translational motion only. This paper focusses on the unique capability of Magnetic Particle Tracking to track the orientation of a marker in a full 3-D cylindrical fluidized bed. Stainless steel particles with the same volume and different aspect ratios are fluidized at a range of superficial gas velocities. Spherical and rod-like particles show distinctly different fluidization behavior. Also, the distribution of angles for rod-like particles changes with position in the fluidized bed as well as with the superficial velocity. Magnetic Particle Tracking shows its unique capability to study both spatial distribution and orientation of the particles allowing more in-depth validation of Discrete Particle Models. © 2017 The Authors AIChE Journal published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers , 63: 5335-5342, 2017.

The performance analysis of three-dimensional track-before-detect algorithm based on Fisher-Tippett-Gnedenko theorem

NASA Astrophysics Data System (ADS)

Cho, Hoonkyung; Chun, Joohwan; Song, Sungchan

2016-09-01

The dim moving target tracking from the infrared image sequence in the presence of high clutter and noise has been recently under intensive investigation. The track-before-detect (TBD) algorithm processing the image sequence over a number of frames before decisions on the target track and existence is known to be especially attractive in very low SNR environments (⩽ 3 dB). In this paper, we shortly present a three-dimensional (3-D) TBD with dynamic programming (TBD-DP) algorithm using multiple IR image sensors. Since traditional two-dimensional TBD algorithm cannot track and detect the along the viewing direction, we use 3-D TBD with multiple sensors and also strictly analyze the detection performance (false alarm and detection probabilities) based on Fisher-Tippett-Gnedenko theorem. The 3-D TBD-DP algorithm which does not require a separate image registration step uses the pixel intensity values jointly read off from multiple image frames to compute the merit function required in the DP process. Therefore, we also establish the relationship between the pixel coordinates of image frame and the reference coordinates.

Relationship between axenic growth of Dictyostelium discoideum strains and their track morphology on substrates coated with gold particles

PubMed Central

1983-01-01

Amoebae of Dictyostelium discoideum produce tracks with two distinct morphologies on gold-coated coverslips. The wild-type strain and other strains that feed only by phagocytosis produced indistinct, fuzzy tracks, whereas mutants capable of axenic growth produced clear, sharp tracks. The sharp track morphology was found to be a recessive phenotype that segregates with axenicity and probably requires a previously unidentified axenic mutation. Axenic and nonaxenic strains also differed in their ability to pinocytose. When the two types of cells were shifted from bacterial growth plates to nutrient media, within 24 h the axenic strain established a rapid rate of pinocytosis, approximately 100-fold higher than the low rate detectable for the nonaxenic strain. However, track formation did not appear to be directly related to endocytosis. Electron microscopic examination of cells during track formation showed that both axenic and nonaxenic strains accumulated gold particles on their surfaces, but neither strain internalized the gold to any significant degree. Observation of living cells revealed that axenic strains collected all particles that they contacted, whereas wild-type strains left many particles undisturbed. The size of the gold particle clusters discarded by the cells also contributed to track morphology. PMID:6619183

Probabilistic Multi-Sensor Fusion Based Indoor Positioning System on a Mobile Device

PubMed Central

He, Xiang; Aloi, Daniel N.; Li, Jia

2015-01-01

Nowadays, smart mobile devices include more and more sensors on board, such as motion sensors (accelerometer, gyroscope, magnetometer), wireless signal strength indicators (WiFi, Bluetooth, Zigbee), and visual sensors (LiDAR, camera). People have developed various indoor positioning techniques based on these sensors. In this paper, the probabilistic fusion of multiple sensors is investigated in a hidden Markov model (HMM) framework for mobile-device user-positioning. We propose a graph structure to store the model constructed by multiple sensors during the offline training phase, and a multimodal particle filter to seamlessly fuse the information during the online tracking phase. Based on our algorithm, we develop an indoor positioning system on the iOS platform. The experiments carried out in a typical indoor environment have shown promising results for our proposed algorithm and system design. PMID:26694387

Probabilistic Multi-Sensor Fusion Based Indoor Positioning System on a Mobile Device.

PubMed

He, Xiang; Aloi, Daniel N; Li, Jia

2015-12-14

Nowadays, smart mobile devices include more and more sensors on board, such as motion sensors (accelerometer, gyroscope, magnetometer), wireless signal strength indicators (WiFi, Bluetooth, Zigbee), and visual sensors (LiDAR, camera). People have developed various indoor positioning techniques based on these sensors. In this paper, the probabilistic fusion of multiple sensors is investigated in a hidden Markov model (HMM) framework for mobile-device user-positioning. We propose a graph structure to store the model constructed by multiple sensors during the offline training phase, and a multimodal particle filter to seamlessly fuse the information during the online tracking phase. Based on our algorithm, we develop an indoor positioning system on the iOS platform. The experiments carried out in a typical indoor environment have shown promising results for our proposed algorithm and system design.

A mathematical model for computer image tracking.

PubMed

Legters, G R; Young, T Y

1982-06-01

A mathematical model using an operator formulation for a moving object in a sequence of images is presented. Time-varying translation and rotation operators are derived to describe the motion. A variational estimation algorithm is developed to track the dynamic parameters of the operators. The occlusion problem is alleviated by using a predictive Kalman filter to keep the tracking on course during severe occlusion. The tracking algorithm (variational estimation in conjunction with Kalman filter) is implemented to track moving objects with occasional occlusion in computer-simulated binary images.

Study of Track Irregularity Time Series Calibration and Variation Pattern at Unit Section

PubMed Central

Jia, Chaolong; Wei, Lili; Wang, Hanning; Yang, Jiulin

2014-01-01

Focusing on problems existing in track irregularity time series data quality, this paper first presents abnormal data identification, data offset correction algorithm, local outlier data identification, and noise cancellation algorithms. And then proposes track irregularity time series decomposition and reconstruction through the wavelet decomposition and reconstruction approach. Finally, the patterns and features of track irregularity standard deviation data sequence in unit sections are studied, and the changing trend of track irregularity time series is discovered and described. PMID:25435869

A Coulomb collision algorithm for weighted particle simulations

NASA Technical Reports Server (NTRS)

Miller, Ronald H.; Combi, Michael R.

1994-01-01

A binary Coulomb collision algorithm is developed for weighted particle simulations employing Monte Carlo techniques. Charged particles within a given spatial grid cell are pair-wise scattered, explicitly conserving momentum and implicitly conserving energy. A similar algorithm developed by Takizuka and Abe (1977) conserves momentum and energy provided the particles are unweighted (each particle representing equal fractions of the total particle density). If applied as is to simulations incorporating weighted particles, the plasma temperatures equilibrate to an incorrect temperature, as compared to theory. Using the appropriate pairing statistics, a Coulomb collision algorithm is developed for weighted particles. The algorithm conserves energy and momentum and produces the appropriate relaxation time scales as compared to theoretical predictions. Such an algorithm is necessary for future work studying self-consistent multi-species kinetic transport.

WE-AB-303-08: Direct Lung Tumor Tracking Using Short Imaging Arcs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shieh, C; Huang, C; Keall, P

2015-06-15

Purpose: Most current tumor tracking technologies rely on implanted markers, which suffer from potential toxicity of marker placement and mis-targeting due to marker migration. Several markerless tracking methods have been proposed: these are either indirect methods or have difficulties tracking lung tumors in most clinical cases due to overlapping anatomies in 2D projection images. We propose a direct lung tumor tracking algorithm robust to overlapping anatomies using short imaging arcs. Methods: The proposed algorithm tracks the tumor based on kV projections acquired within the latest six-degree imaging arc. To account for respiratory motion, an external motion surrogate is used tomore » select projections of the same phase within the latest arc. For each arc, the pre-treatment 4D cone-beam CT (CBCT) with tumor contours are used to estimate and remove the contribution to the integral attenuation from surrounding anatomies. The position of the tumor model extracted from 4D CBCT of the same phase is then optimized to match the processed projections using the conjugate gradient method. The algorithm was retrospectively validated on two kV scans of a lung cancer patient with implanted fiducial markers. This patient was selected as the tumor is attached to the mediastinum, representing a challenging case for markerless tracking methods. The tracking results were converted to expected marker positions and compared with marker trajectories obtained via direct marker segmentation (ground truth). Results: The root-mean-squared-errors of tracking were 0.8 mm and 0.9 mm in the superior-inferior direction for the two scans. Tracking error was found to be below 2 and 3 mm for 90% and 98% of the time, respectively. Conclusions: A direct lung tumor tracking algorithm robust to overlapping anatomies was proposed and validated on two scans of a lung cancer patient. Sub-millimeter tracking accuracy was observed, indicating the potential of this algorithm for real-time guidance applications.« less

Tracking and recognition face in videos with incremental local sparse representation model

NASA Astrophysics Data System (ADS)

Wang, Chao; Wang, Yunhong; Zhang, Zhaoxiang

2013-10-01

This paper addresses the problem of tracking and recognizing faces via incremental local sparse representation. First a robust face tracking algorithm is proposed via employing local sparse appearance and covariance pooling method. In the following face recognition stage, with the employment of a novel template update strategy, which combines incremental subspace learning, our recognition algorithm adapts the template to appearance changes and reduces the influence of occlusion and illumination variation. This leads to a robust video-based face tracking and recognition with desirable performance. In the experiments, we test the quality of face recognition in real-world noisy videos on YouTube database, which includes 47 celebrities. Our proposed method produces a high face recognition rate at 95% of all videos. The proposed face tracking and recognition algorithms are also tested on a set of noisy videos under heavy occlusion and illumination variation. The tracking results on challenging benchmark videos demonstrate that the proposed tracking algorithm performs favorably against several state-of-the-art methods. In the case of the challenging dataset in which faces undergo occlusion and illumination variation, and tracking and recognition experiments under significant pose variation on the University of California, San Diego (Honda/UCSD) database, our proposed method also consistently demonstrates a high recognition rate.

Neural network fusion capabilities for efficient implementation of tracking algorithms

NASA Astrophysics Data System (ADS)

Sundareshan, Malur K.; Amoozegar, Farid

1996-05-01

The ability to efficiently fuse information of different forms for facilitating intelligent decision-making is one of the major capabilities of trained multilayer neural networks that is being recognized int eh recent times. While development of innovative adaptive control algorithms for nonlinear dynamical plants which attempt to exploit these capabilities seems to be more popular, a corresponding development of nonlinear estimation algorithms using these approaches, particularly for application in target surveillance and guidance operations, has not received similar attention. In this paper we describe the capabilities and functionality of neural network algorithms for data fusion and implementation of nonlinear tracking filters. For a discussion of details and for serving as a vehicle for quantitative performance evaluations, the illustrative case of estimating the position and velocity of surveillance targets is considered. Efficient target tracking algorithms that can utilize data from a host of sensing modalities and are capable of reliably tracking even uncooperative targets executing fast and complex maneuvers are of interest in a number of applications. The primary motivation for employing neural networks in these applications comes form the efficiency with which more features extracted from different sensor measurements can be utilized as inputs for estimating target maneuvers. Such an approach results in an overall nonlinear tracking filter which has several advantages over the popular efforts at designing nonlinear estimation algorithms for tracking applications, the principle one being the reduction of mathematical and computational complexities. A system architecture that efficiently integrates the processing capabilities of a trained multilayer neural net with the tracking performance of a Kalman filter is described in this paper.

Determination of feature generation methods for PTZ camera object tracking

NASA Astrophysics Data System (ADS)

Doyle, Daniel D.; Black, Jonathan T.

2012-06-01

Object detection and tracking using computer vision (CV) techniques have been widely applied to sensor fusion applications. Many papers continue to be written that speed up performance and increase learning of artificially intelligent systems through improved algorithms, workload distribution, and information fusion. Military application of real-time tracking systems is becoming more and more complex with an ever increasing need of fusion and CV techniques to actively track and control dynamic systems. Examples include the use of metrology systems for tracking and measuring micro air vehicles (MAVs) and autonomous navigation systems for controlling MAVs. This paper seeks to contribute to the determination of select tracking algorithms that best track a moving object using a pan/tilt/zoom (PTZ) camera applicable to both of the examples presented. The select feature generation algorithms compared in this paper are the trained Scale-Invariant Feature Transform (SIFT) and Speeded Up Robust Features (SURF), the Mixture of Gaussians (MoG) background subtraction method, the Lucas- Kanade optical flow method (2000) and the Farneback optical flow method (2003). The matching algorithm used in this paper for the trained feature generation algorithms is the Fast Library for Approximate Nearest Neighbors (FLANN). The BSD licensed OpenCV library is used extensively to demonstrate the viability of each algorithm and its performance. Initial testing is performed on a sequence of images using a stationary camera. Further testing is performed on a sequence of images such that the PTZ camera is moving in order to capture the moving object. Comparisons are made based upon accuracy, speed and memory.

Calorimetry at the International Linear Collider

NASA Astrophysics Data System (ADS)

Repond, José

2007-03-01

The physics potential of the International Linear Collider depends critically on the jet energy resolution of its detector. Detector concepts are being developed which optimize the jet energy resolution, with the aim of achieving σjet=30%/√{Ejet}. Under the assumption that Particle Flow Algorithms (PFAs), which combine tracking and calorimeter information to reconstruct the energy of hadronic jets, can provide this unprecedented jet energy resolution, calorimeters with very fine granularity are being developed. After a brief introduction outlining the principles of PFAs, the current status of various calorimeter prototype construction projects and their plans for the next few years will be reviewed.

Model of mobile agents for sexual interactions networks

NASA Astrophysics Data System (ADS)

González, M. C.; Lind, P. G.; Herrmann, H. J.

2006-02-01

We present a novel model to simulate real social networks of complex interactions, based in a system of colliding particles (agents). The network is build by keeping track of the collisions and evolves in time with correlations which emerge due to the mobility of the agents. Therefore, statistical features are a consequence only of local collisions among its individual agents. Agent dynamics is realized by an event-driven algorithm of collisions where energy is gained as opposed to physical systems which have dissipation. The model reproduces empirical data from networks of sexual interactions, not previously obtained with other approaches.

Evaluation of beam tracking strategies for the THOR-CSW solar wind instrument

NASA Astrophysics Data System (ADS)

De Keyser, Johan; Lavraud, Benoit; Prech, Lubomir; Neefs, Eddy; Berkenbosch, Sophie; Beeckman, Bram; Maggiolo, Romain; Fedorov, Andrei; Baruah, Rituparna; Wong, King-Wah; Amoros, Carine; Mathon, Romain; Génot, Vincent

2017-04-01

We compare different beam tracking strategies for the Cold Solar Wind (CSW) plasma spectrometer on the ESA M4 THOR mission candidate. The goal is to intelligently select the energy and angular windows the instrument is sampling and to adapt these windows as the solar wind properties evolve, with the aim to maximize the velocity distribution acquisition rate while maintaining excellent energy and angular resolution. Using synthetic data constructed using high-cadence measurements by the Faraday cup instrument on the Spektr-R mission (30 ms resolution), we test the performance of energy beam tracking with or without angular beam tracking. The algorithm can be fed both by data acquired by the plasma spectrometer during the previous measurement cycle, or by data from another instrument, in casu the Faraday Cup (FAR) instrument foreseen on THOR. We verify how these beam tracking algorithms behave for different sizes of the energy and angular windows, and for different data integration times, in order to assess the limitations of the algorithm and to avoid situations in which the algorithm loses track of the beam.

UWB Tracking Software Development

NASA Technical Reports Server (NTRS)

Gross, Julia; Arndt, Dickey; Ngo, Phong; Phan, Chau; Dusl, John; Ni, Jianjun; Rafford, Melinda

2006-01-01

An Ultra-Wideband (UWB) two-cluster Angle of Arrival (AOA) tracking prototype system is currently being developed and tested at NASA Johnson Space Center for space exploration applications. This talk discusses the software development efforts for this UWB two-cluster AOA tracking system. The role the software plays in this system is to take waveform data from two UWB radio receivers as an input, feed this input into an AOA tracking algorithm, and generate the target position as an output. The architecture of the software (Input/Output Interface and Algorithm Core) will be introduced in this talk. The development of this software has three phases. In Phase I, the software is mostly Matlab driven and calls C++ socket functions to provide the communication links to the radios. This is beneficial in the early stage when it is necessary to frequently test changes in the algorithm. Phase II of the development is to have the software mostly C++ driven and call a Matlab function for the AOA tracking algorithm. This is beneficial in order to send the tracking results to other systems and also to improve the tracking update rate of the system. The third phase is part of future work and is to have the software completely C++ driven with a graphics user interface. This software design enables the fine resolution tracking of the UWB two-cluster AOA tracking system.

Robust visual tracking based on deep convolutional neural networks and kernelized correlation filters

NASA Astrophysics Data System (ADS)

Yang, Hua; Zhong, Donghong; Liu, Chenyi; Song, Kaiyou; Yin, Zhouping

2018-03-01

Object tracking is still a challenging problem in computer vision, as it entails learning an effective model to account for appearance changes caused by occlusion, out of view, plane rotation, scale change, and background clutter. This paper proposes a robust visual tracking algorithm called deep convolutional neural network (DCNNCT) to simultaneously address these challenges. The proposed DCNNCT algorithm utilizes a DCNN to extract the image feature of a tracked target, and the full range of information regarding each convolutional layer is used to express the image feature. Subsequently, the kernelized correlation filters (CF) in each convolutional layer are adaptively learned, the correlation response maps of that are combined to estimate the location of the tracked target. To avoid the case of tracking failure, an online random ferns classifier is employed to redetect the tracked target, and a dual-threshold scheme is used to obtain the final target location by comparing the tracking result with the detection result. Finally, the change in scale of the target is determined by building scale pyramids and training a CF. Extensive experiments demonstrate that the proposed algorithm is effective at tracking, especially when evaluated using an index called the overlap rate. The DCNNCT algorithm is also highly competitive in terms of robustness with respect to state-of-the-art trackers in various challenging scenarios.

An adaptive tracker for ShipIR/NTCS

NASA Astrophysics Data System (ADS)

Ramaswamy, Srinivasan; Vaitekunas, David A.

2015-05-01

A key component in any image-based tracking system is the adaptive tracking algorithm used to segment the image into potential targets, rank-and-select the best candidate target, and the gating of the selected target to further improve tracker performance. This paper will describe a new adaptive tracker algorithm added to the naval threat countermeasure simulator (NTCS) of the NATO-standard ship signature model (ShipIR). The new adaptive tracking algorithm is an optional feature used with any of the existing internal NTCS or user-defined seeker algorithms (e.g., binary centroid, intensity centroid, and threshold intensity centroid). The algorithm segments the detected pixels into clusters, and the smallest set of clusters that meet the detection criterion is obtained by using a knapsack algorithm to identify the set of clusters that should not be used. The rectangular area containing the chosen clusters defines an inner boundary, from which a weighted centroid is calculated as the aim-point. A track-gate is then positioned around the clusters, taking into account the rate of change of the bounding area and compensating for any gimbal displacement. A sequence of scenarios is used to test the new tracking algorithm on a generic unclassified DDG ShipIR model, with and without flares, and demonstrate how some of the key seeker signals are impacted by both the ship and flare intrinsic signatures.

Fuzzy logic particle tracking velocimetry

NASA Technical Reports Server (NTRS)

Wernet, Mark P.

1993-01-01

Fuzzy logic has proven to be a simple and robust method for process control. Instead of requiring a complex model of the system, a user defined rule base is used to control the process. In this paper the principles of fuzzy logic control are applied to Particle Tracking Velocimetry (PTV). Two frames of digitally recorded, single exposure particle imagery are used as input. The fuzzy processor uses the local particle displacement information to determine the correct particle tracks. Fuzzy PTV is an improvement over traditional PTV techniques which typically require a sequence (greater than 2) of image frames for accurately tracking particles. The fuzzy processor executes in software on a PC without the use of specialized array or fuzzy logic processors. A pair of sample input images with roughly 300 particle images each, results in more than 200 velocity vectors in under 8 seconds of processing time.

Cosmic ray particle dosimetry and trajectory tracing. [cosmic ray track analysis for Apollo 17 BIOCORE

NASA Technical Reports Server (NTRS)

Cruty, M. R.; Benton, E. V.; Turnbill, C. E.; Philpott, D. E.

1975-01-01

Five pocket mice (Perognathus longimembris) were flown on Apollo XVII, each with a solid-state (plastic) nuclear track detector implanted beneath its scalp. The subscalp detectors were sensitive to HZE cosmic ray particles with a LET greater than or approximately equal to 0.15 million electron volts per micrometer (MeV/micron). A critical aspect of the dosimetry of the experiment involved tracing individual particle trajectories through each mouse head from particle tracks registered in the individual subscalp detectors, thereby establishing a one-to-one correspondence between a trajectory location in the tissue and the presence or absence of a lesion. The other major aspect was the identification of each registered particle. An average of 16 particles with Z greater than or equal to 6 and 2.2 particles with Z greater than or equal to 20 were found per detector. The track density, 29 tracks/sq cm, when adjusted for detection volume, was in agreement with the photographic emulsion data from an area dosimeter located next to the flight package.

A three-dimensional electrostatic particle-in-cell methodology on unstructured Delaunay-Voronoi grids

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gatsonis, Nikolaos A.; Spirkin, Anton

2009-06-01

The mathematical formulation and computational implementation of a three-dimensional particle-in-cell methodology on unstructured Delaunay-Voronoi tetrahedral grids is presented. The method allows simulation of plasmas in complex domains and incorporates the duality of the Delaunay-Voronoi in all aspects of the particle-in-cell cycle. Charge assignment and field interpolation weighting schemes of zero- and first-order are formulated based on the theory of long-range constraints. Electric potential and fields are derived from a finite-volume formulation of Gauss' law using the Voronoi-Delaunay dual. Boundary conditions and the algorithms for injection, particle loading, particle motion, and particle tracking are implemented for unstructured Delaunay grids. Error andmore » sensitivity analysis examines the effects of particles/cell, grid scaling, and timestep on the numerical heating, the slowing-down time, and the deflection times. The problem of current collection by cylindrical Langmuir probes in collisionless plasmas is used for validation. Numerical results compare favorably with previous numerical and analytical solutions for a wide range of probe radius to Debye length ratios, probe potentials, and electron to ion temperature ratios. The versatility of the methodology is demonstrated with the simulation of a complex plasma microsensor, a directional micro-retarding potential analyzer that includes a low transparency micro-grid.« less

Measurement of the centrality dependence of the charged particle pseudorapidity distribution in lead-lead collisions at √{sNN} = 2.76 TeV with the ATLAS detector

NASA Astrophysics Data System (ADS)

Aad, G.; Abbott, B.; Abdallah, J.; Abdelalim, A. A.; Abdesselam, A.; Abdinov, O.; Abi, B.; Abolins, M.; Abramowicz, H.; Abreu, H.; Acerbi, E.; Acharya, B. S.; Adams, D. L.; Addy, T. N.; Adelman, J.; Aderholz, M.; Adomeit, S.; Adragna, P.; Adye, T.; Aefsky, S.; Aguilar-Saavedra, J. A.; Aharrouche, M.; Ahlen, S. P.; Ahles, F.; Ahmad, A.; Ahsan, M.; Aielli, G.; Akdogan, T.; Åkesson, T. P. A.; Akimoto, G.; Akimov, A. V.; Akiyama, A.; Alam, M. S.; Alam, M. A.; Albert, J.; Albrand, S.; Aleksa, M.; Aleksandrov, I. N.; Alessandria, F.; Alexa, C.; Alexander, G.; Alexandre, G.; Alexopoulos, T.; Alhroob, M.; Aliev, M.; Alimonti, G.; Alison, J.; Aliyev, M.; Allport, P. P.; Allwood-Spiers, S. E.; Almond, J.; Aloisio, A.; Alon, R.; Alonso, A.; Alviggi, M. G.; Amako, K.; Amaral, P.; Amelung, C.; Ammosov, V. V.; Amorim, A.; Amorós, G.; Amram, N.; Anastopoulos, C.; Andari, N.; Andeen, T.; Anders, C. F.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Andrieux, M.-L.; Anduaga, X. S.; Angerami, A.; Anghinolfi, F.; Anjos, N.; Annovi, A.; Antonaki, A.; Antonelli, M.; Antonov, A.; Antos, J.; Anulli, F.; Aoun, S.; Aperio Bella, L.; Apolle, R.; Arabidze, G.; Aracena, I.; Arai, Y.; Arce, A. T. H.; Archambault, J. P.; Arfaoui, S.; Arguin, J.-F.; Arik, E.; Arik, M.; Armbruster, A. J.; Arnaez, O.; Arnault, C.; Artamonov, A.; Artoni, G.; Arutinov, D.; Asai, S.; Asfandiyarov, R.; Ask, S.; Åsman, B.; Asquith, L.; Assamagan, K.; Astbury, A.; Astvatsatourov, A.; Atoian, G.; Aubert, B.; Auerbach, B.; Auge, E.; Augsten, K.; Aurousseau, M.; Austin, N.; Avolio, G.; Avramidou, R.; Axen, D.; Ay, C.; Azuelos, G.; Azuma, Y.; Baak, M. A.; Baccaglioni, G.; Bacci, C.; Bach, A. M.; Bachacou, H.; Bachas, K.; Bachy, G.; Backes, M.; Backhaus, M.; Badescu, E.; Bagnaia, P.; Bahinipati, S.; Bai, Y.; Bailey, D. C.; Bain, T.; Baines, J. T.; Baker, O. K.; Baker, M. D.; Baker, S.; Baltasar Dos Santos Pedrosa, F.; Banas, E.; Banerjee, P.; Banerjee, Sw.; Banfi, D.; Bangert, A.; Bansal, V.; Bansil, H. S.; Barak, L.; Baranov, S. P.; Barashkou, A.; Barbaro Galtieri, A.; Barber, T.; Barberio, E. L.; Barberis, D.; Barbero, M.; Bardin, D. Y.; Barillari, T.; Barisonzi, M.; Barklow, T.; Barlow, N.; Barnett, B. M.; Barnett, R. M.; Baroncelli, A.; Barone, G.; Barr, A. J.; Barreiro, F.; Barreiro Guimarães da Costa, J.; Barrillon, P.; Bartoldus, R.; Barton, A. E.; Bartsch, D.; Bartsch, V.; Bates, R. L.; Batkova, L.; Batley, J. R.; Battaglia, A.; Battistin, M.; Battistoni, G.; Bauer, F.; Bawa, H. S.; Beare, B.; Beau, T.; Beauchemin, P. H.; Beccherle, R.; Bechtle, P.; Beck, H. P.; Beckingham, M.; Becks, K. H.; Beddall, A. J.; Beddall, A.; Bedikian, S.; Bednyakov, V. A.; Bee, C. P.; Begel, M.; Behar Harpaz, S.; Behera, P. K.; Beimforde, M.; Belanger-Champagne, C.; Bell, P. J.; Bell, W. H.; Bella, G.; Bellagamba, L.; Bellina, F.; Bellomo, M.; Belloni, A.; Beloborodova, O.; Belotskiy, K.; Beltramello, O.; Ben Ami, S.; Benary, O.; Benchekroun, D.; Benchouk, C.; Bendel, M.; Benedict, B. H.; Benekos, N.; Benhammou, Y.; Benjamin, D. P.; Benoit, M.; Bensinger, J. R.; Benslama, K.; Bentvelsen, S.; Berge, D.; Bergeaas Kuutmann, E.; Berger, N.; Berghaus, F.; Berglund, E.; Beringer, J.; Bernardet, K.; Bernat, P.; Bernhard, R.; Bernius, C.; Berry, T.; Bertin, A.; Bertinelli, F.; Bertolucci, F.; Besana, M. I.; Besson, N.; Bethke, S.; Bhimji, W.; Bianchi, R. M.; Bianco, M.; Biebel, O.; Bieniek, S. P.; Biesiada, J.; Biglietti, M.; Bilokon, H.; Bindi, M.; Binet, S.; Bingul, A.; Bini, C.; Biscarat, C.; Bitenc, U.; Black, K. M.; Blair, R. E.; Blanchard, J.-B.; Blanchot, G.; Blazek, T.; Blocker, C.; Blocki, J.; Blondel, A.; Blum, W.; Blumenschein, U.; Bobbink, G. J.; Bobrovnikov, V. B.; Bocchetta, S. S.; Bocci, A.; Boddy, C. R.; Boehler, M.; Boek, J.; Boelaert, N.; Böser, S.; Bogaerts, J. A.; Bogdanchikov, A.; Bogouch, A.; Bohm, C.; Boisvert, V.; Bold, T.; Boldea, V.; Bolnet, N. M.; Bona, M.; Bondarenko, V. G.; Boonekamp, M.; Boorman, G.; Booth, C. N.; Bordoni, S.; Borer, C.; Borisov, A.; Borissov, G.; Borjanovic, I.; Borroni, S.; Bos, K.; Boscherini, D.; Bosman, M.; Boterenbrood, H.; Botterill, D.; Bouchami, J.; Boudreau, J.; Bouhova-Thacker, E. V.; Boulahouache, C.; Bourdarios, C.; Bousson, N.; Boveia, A.; Boyd, J.; Boyko, I. R.; Bozhko, N. I.; Bozovic-Jelisavcic, I.; Bracinik, J.; Braem, A.; Branchini, P.; Brandenburg, G. W.; Brandt, A.; Brandt, G.; Brandt, O.; Bratzler, U.; Brau, B.; Brau, J. E.; Braun, H. M.; Brelier, B.; Bremer, J.; Brenner, R.; Bressler, S.; Breton, D.; Britton, D.; Brochu, F. M.; Brock, I.; Brock, R.; Brodbeck, T. J.; Brodet, E.; Broggi, F.; Bromberg, C.; Brooijmans, G.; Brooks, W. K.; Brown, G.; Brown, H.; Bruckman de Renstrom, P. A.; Bruncko, D.; Bruneliere, R.; Brunet, S.; Bruni, A.; Bruni, G.; Bruschi, M.; Buanes, T.; Bucci, F.; Buchanan, J.; Buchanan, N. J.; Buchholz, P.; Buckingham, R. M.; Buckley, A. G.; Buda, S. I.; Budagov, I. A.; Budick, B.; Büscher, V.; Bugge, L.; Buira-Clark, D.; Bulekov, O.; Bunse, M.; Buran, T.; Burckhart, H.; Burdin, S.; Burgess, T.; Burke, S.; Busato, E.; Bussey, P.; Buszello, C. P.; Butin, F.; Butler, B.; Butler, J. M.; Buttar, C. M.; Butterworth, J. M.; Buttinger, W.; Byatt, T.; Cabrera Urbán, S.; Caforio, D.; Cakir, O.; Calafiura, P.; Calderini, G.; Calfayan, P.; Calkins, R.; Caloba, L. P.; Caloi, R.; Calvet, D.; Calvet, S.; Camacho Toro, R.; Camarri, P.; Cambiaghi, M.; Cameron, D.; Campana, S.; Campanelli, M.; Canale, V.; Canelli, F.; Canepa, A.; Cantero, J.; Capasso, L.; Capeans Garrido, M. D. M.; Caprini, I.; Caprini, M.; Capriotti, D.; Capua, M.; Caputo, R.; Cardarelli, R.; Carli, T.; Carlino, G.; Carminati, L.; Caron, B.; Caron, S.; Carrillo Montoya, G. D.; Carter, A. A.; Carter, J. R.; Carvalho, J.; Casadei, D.; Casado, M. P.; Cascella, M.; Caso, C.; Castaneda Hernandez, A. M.; Castaneda-Miranda, E.; Castillo Gimenez, V.; Castro, N. F.; Cataldi, G.; Cataneo, F.; Catinaccio, A.; Catmore, J. R.; Cattai, A.; Cattani, G.; Caughron, S.; Cauz, D.; Cavalleri, P.; Cavalli, D.; Cavalli-Sforza, M.; Cavasinni, V.; Ceradini, F.; Cerqueira, A. S.; Cerri, A.; Cerrito, L.; Cerutti, F.; Cetin, S. A.; Cevenini, F.; Chafaq, A.; Chakraborty, D.; Chan, K.; Chapleau, B.; Chapman, J. D.; Chapman, J. W.; Chareyre, E.; Charlton, D. G.; Chavda, V.; Chavez Barajas, C. A.; Cheatham, S.; Chekanov, S.; Chekulaev, S. V.; Chelkov, G. A.; Chelstowska, M. A.; Chen, C.; Chen, H.; Chen, S.; Chen, T.; Chen, X.; Chen, Y.; Cheng, S.; Cheplakov, A.; Chepurnov, V. F.; Cherkaoui El Moursli, R.; Chernyatin, V.; Cheu, E.; Cheung, S. L.; Chevalier, L.; Chiefari, G.; Chikovani, L.; Childers, J. T.; Chilingarov, A.; Chiodini, G.; Chizhov, M. V.; Choudalakis, G.; Chouridou, S.; Christidi, I. A.; Christov, A.; Chromek-Burckhart, D.; Chu, M. L.; Chudoba, J.; Ciapetti, G.; Ciba, K.; Ciftci, A. K.; Ciftci, R.; Cinca, D.; Cindro, V.; Ciobotaru, M. D.; Ciocca, C.; Ciocio, A.; Cirilli, M.; Ciubancan, M.; Clark, A.; Clark, P. J.; Cleland, W.; Clemens, J. C.; Clement, B.; Clement, C.; Clifft, R. W.; Coadou, Y.; Cobal, M.; Coccaro, A.; Cochran, J.; Coe, P.; Cogan, J. G.; Coggeshall, J.; Cogneras, E.; Cojocaru, C. D.; Colas, J.; Colijn, A. P.; Collard, C.; Collins, N. J.; Collins-Tooth, C.; Collot, J.; Colon, G.; Conde Muiño, P.; Coniavitis, E.; Conidi, M. C.; Consonni, M.; Consorti, V.; Constantinescu, S.; Conta, C.; Conventi, F.; Cook, J.; Cooke, M.; Cooper, B. D.; Cooper-Sarkar, A. M.; Cooper-Smith, N. J.; Copic, K.; Cornelissen, T.; Corradi, M.; Corriveau, F.; Cortes-Gonzalez, A.; Cortiana, G.; Costa, G.; Costa, M. J.; Costanzo, D.; Costin, T.; Côté, D.; Coura Torres, R.; Courneyea, L.; Cowan, G.; Cowden, C.; Cox, B. E.; Cranmer, K.; Crescioli, F.; Cristinziani, M.; Crosetti, G.; Crupi, R.; Crépé-Renaudin, S.; Cuciuc, C.-M.; Cuenca Almenar, C.; Cuhadar Donszelmann, T.; Cuneo, S.; Curatolo, M.; Curtis, C. J.; Cwetanski, P.; Czirr, H.; Czyczula, Z.; D'Auria, S.; D'Onofrio, M.; D'Orazio, A.; da Silva, P. V. M.; da Via, C.; Dabrowski, W.; Dai, T.; Dallapiccola, C.; Dam, M.; Dameri, M.; Damiani, D. S.; Danielsson, H. O.; Dannheim, D.; Dao, V.; Darbo, G.; Darlea, G. L.; Daum, C.; Dauvergne, J. P.; Davey, W.; Davidek, T.; Davidson, N.; Davidson, R.; Davies, E.; Davies, M.; Davison, A. R.; Davygora, Y.; Dawe, E.; Dawson, I.; Dawson, J. W.; Daya, R. K.; de, K.; de Asmundis, R.; de Castro, S.; de Castro Faria Salgado, P. E.; de Cecco, S.; de Graat, J.; de Groot, N.; de Jong, P.; de La Taille, C.; de la Torre, H.; de Lotto, B.; de Mora, L.; de Nooij, L.; de Oliveira Branco, M.; de Pedis, D.; de Saintignon, P.; de Salvo, A.; de Sanctis, U.; de Santo, A.; de Vivie de Regie, J. B.; Dean, S.; Debbe, R.; Dedovich, D. V.; Degenhardt, J.; Dehchar, M.; Deile, M.; Del Papa, C.; Del Peso, J.; Del Prete, T.; Deliyergiyev, M.; Dell'Acqua, A.; Dell'Asta, L.; Della Pietra, M.; Della Volpe, D.; Delmastro, M.; Delpierre, P.; Delruelle, N.; Delsart, P. A.; Deluca, C.; Demers, S.; Demichev, M.; Demirkoz, B.; Deng, J.; Denisov, S. P.; Derendarz, D.; Derkaoui, J. E.; Derue, F.; Dervan, P.; Desch, K.; Devetak, E.; Deviveiros, P. O.; Dewhurst, A.; Dewilde, B.; Dhaliwal, S.; Dhullipudi, R.; di Ciaccio, A.; di Ciaccio, L.; di Girolamo, A.; di Girolamo, B.; di Luise, S.; di Mattia, A.; di Micco, B.; di Nardo, R.; di Simone, A.; di Sipio, R.; Diaz, M. A.; Diblen, F.; Diehl, E. B.; Dietrich, J.; Dietzsch, T. A.; Diglio, S.; Dindar Yagci, K.; Dingfelder, J.; Dionisi, C.; Dita, P.; Dita, S.; Dittus, F.; Djama, F.; Djobava, T.; Do Vale, M. A. B.; Do Valle Wemans, A.; Doan, T. K. O.; Dobbs, M.; Dobinson, R.; Dobos, D.; Dobson, E.; Dobson, M.; Dodd, J.; Doglioni, C.; Doherty, T.; Doi, Y.; Dolejsi, J.; Dolenc, I.; Dolezal, Z.; Dolgoshein, B. A.; Dohmae, T.; Donadelli, M.; Donega, M.; Donini, J.; Dopke, J.; Doria, A.; Dos Anjos, A.; Dosil, M.; Dotti, A.; Dova, M. T.; Dowell, J. D.; Doxiadis, A. D.; Doyle, A. T.; Drasal, Z.; Drees, J.; Dressnandt, N.; Drevermann, H.; Driouichi, C.; Dris, M.; Dubbert, J.; Dubbs, T.; Dube, S.; Duchovni, E.; Duckeck, G.; Dudarev, A.; Dudziak, F.; Dührssen, M.; Duerdoth, I. P.; Duflot, L.; Dufour, M.-A.; Dunford, M.; Duran Yildiz, H.; Duxfield, R.; Dwuznik, M.; Dydak, F.; Dzahini, D.; Düren, M.; Ebenstein, W. L.; Ebke, J.; Eckert, S.; Eckweiler, S.; Edmonds, K.; Edwards, C. A.; Edwards, N. C.; Ehrenfeld, W.; Ehrich, T.; Eifert, T.; Eigen, G.; Einsweiler, K.; Eisenhandler, E.; Ekelof, T.; El Kacimi, M.; Ellert, M.; Elles, S.; Ellinghaus, F.; Ellis, K.; Ellis, N.; Elmsheuser, J.; Elsing, M.; Ely, R.; Emeliyanov, D.; Engelmann, R.; Engl, A.; Epp, B.; Eppig, A.; Erdmann, J.; Ereditato, A.; Eriksson, D.; Ernst, J.; Ernst, M.; Ernwein, J.; Errede, D.; Errede, S.; Ertel, E.; Escalier, M.; Escobar, C.; Espinal Curull, X.; Esposito, B.; Etienne, F.; Etienvre, A. I.; Etzion, E.; Evangelakou, D.; Evans, H.; Fabbri, L.; Fabre, C.; Fakhrutdinov, R. M.; Falciano, S.; Fang, Y.; Fanti, M.; Farbin, A.; Farilla, A.; Farley, J.; Farooque, T.; Farrington, S. M.; Farthouat, P.; Fassnacht, P.; Fassouliotis, D.; Fatholahzadeh, B.; Favareto, A.; Fayard, L.; Fazio, S.; Febbraro, R.; Federic, P.; Fedin, O. L.; Fedorko, W.; Fehling-Kaschek, M.; Feligioni, L.; Fellmann, D.; Felzmann, C. U.; Feng, C.; Feng, E. J.; Fenyuk, A. 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F.; Mora Herrera, C.; Moraes, A.; Morais, A.; Morange, N.; Morel, J.; Morello, G.; Moreno, D.; Moreno Llácer, M.; Morettini, P.; Morii, M.; Morin, J.; Morita, Y.; Morley, A. K.; Mornacchi, G.; Morone, M.-C.; Morozov, S. V.; Morris, J. D.; Morvaj, L.; Moser, H. G.; Mosidze, M.; Moss, J.; Mount, R.; Mountricha, E.; Mouraviev, S. V.; Moyse, E. J. W.; Mudrinic, M.; Mueller, F.; Mueller, J.; Mueller, K.; Müller, T. A.; Muenstermann, D.; Muijs, A.; Muir, A.; Munwes, Y.; Murakami, K.; Murray, W. J.; Mussche, I.; Musto, E.; Myagkov, A. G.; Myska, M.; Nadal, J.; Nagai, K.; Nagano, K.; Nagasaka, Y.; Nairz, A. M.; Nakahama, Y.; Nakamura, K.; Nakano, I.; Nanava, G.; Napier, A.; Nash, M.; Nation, N. R.; Nattermann, T.; Naumann, T.; Navarro, G.; Neal, H. A.; Nebot, E.; Nechaeva, P. Yu.; Negri, A.; Negri, G.; Nektarijevic, S.; Nelson, A.; Nelson, S.; Nelson, T. K.; Nemecek, S.; Nemethy, P.; Nepomuceno, A. A.; Nessi, M.; Nesterov, S. Y.; Neubauer, M. S.; Neusiedl, A.; Neves, R. M.; Nevski, P.; Newman, P. R.; Nguyen Thi Hong, V.; Nickerson, R. B.; Nicolaidou, R.; Nicolas, L.; Nicquevert, B.; Niedercorn, F.; Nielsen, J.; Niinikoski, T.; Nikiforov, A.; Nikolaenko, V.; Nikolaev, K.; Nikolic-Audit, I.; Nikolics, K.; Nikolopoulos, K.; Nilsen, H.; Nilsson, P.; Ninomiya, Y.; Nisati, A.; Nishiyama, T.; Nisius, R.; Nodulman, L.; Nomachi, M.; Nomidis, I.; Nordberg, M.; Nordkvist, B.; Norton, P. R.; Novakova, J.; Nozaki, M.; Nožička, M.; Nozka, L.; Nugent, I. M.; Nuncio-Quiroz, A.-E.; Nunes Hanninger, G.; Nunnemann, T.; Nurse, E.; Nyman, T.; O'Brien, B. J.; O'Neale, S. W.; O'Neil, D. C.; O'Shea, V.; Oakham, F. G.; Oberlack, H.; Ocariz, J.; Ochi, A.; Oda, S.; Odaka, S.; Odier, J.; Ogren, H.; Oh, A.; Oh, S. H.; Ohm, C. C.; Ohshima, T.; Ohshita, H.; Ohska, T. K.; Ohsugi, T.; Okada, S.; Okawa, H.; Okumura, Y.; Okuyama, T.; Olcese, M.; Olchevski, A. G.; Oliveira, M.; Oliveira Damazio, D.; Oliver Garcia, E.; Olivito, D.; Olszewski, A.; Olszowska, J.; Omachi, C.; Onofre, A.; Onyisi, P. U. E.; Oram, C. J.; Oreglia, M. J.; Oren, Y.; Orestano, D.; Orlov, I.; Oropeza Barrera, C.; Orr, R. S.; Osculati, B.; Ospanov, R.; Osuna, C.; Otero Y Garzon, G.; Ottersbach, J. P.; Ouchrif, M.; Ould-Saada, F.; Ouraou, A.; Ouyang, Q.; Owen, M.; Owen, S.; Øye, O. K.; Ozcan, V. E.; Ozturk, N.; Pacheco Pages, A.; Padilla Aranda, C.; Pagan Griso, S.; Paganis, E.; Paige, F.; Pajchel, K.; Palestini, S.; Pallin, D.; Palma, A.; Palmer, J. D.; Pan, Y. B.; Panagiotopoulou, E.; Panes, B.; Panikashvili, N.; Panitkin, S.; Pantea, D.; Panuskova, M.; Paolone, V.; Papadelis, A.; Papadopoulou, Th. D.; Paramonov, A.; Park, W.; Parker, M. A.; Parodi, F.; Parsons, J. A.; Parzefall, U.; Pasqualucci, E.; Passeri, A.; Pastore, F.; Pastore, Fr.; Pásztor, G.; Pataraia, S.; Patel, N.; Pater, J. R.; Patricelli, S.; Pauly, T.; Pecsy, M.; Pedraza Morales, M. I.; Peleganchuk, S. V.; Peng, H.; Pengo, R.; Penson, A.; Penwell, J.; Perantoni, M.; Perez, K.; Perez Cavalcanti, T.; Perez Codina, E.; Pérez García-Estañ, M. T.; Perez Reale, V.; Perini, L.; Pernegger, H.; Perrino, R.; Perrodo, P.; Persembe, S.; Peshekhonov, V. D.; Peters, O.; Petersen, B. A.; Petersen, J.; Petersen, T. C.; Petit, E.; Petridis, A.; Petridou, C.; Petrolo, E.; Petrucci, F.; Petschull, D.; Petteni, M.; Pezoa, R.; Phan, A.; Phillips, A. W.; Phillips, P. W.; Piacquadio, G.; Piccaro, E.; Piccinini, M.; Pickford, A.; Piec, S. M.; Piegaia, R.; Pilcher, J. E.; Pilkington, A. D.; Pina, J.; Pinamonti, M.; Pinder, A.; Pinfold, J. L.; Ping, J.; Pinto, B.; Pirotte, O.; Pizio, C.; Placakyte, R.; Plamondon, M.; Plano, W. G.; Pleier, M.-A.; Pleskach, A. V.; Poblaguev, A.; Poddar, S.; Podlyski, F.; Poggioli, L.; Poghosyan, T.; Pohl, M.; Polci, F.; Polesello, G.; Policicchio, A.; Polini, A.; Poll, J.; Polychronakos, V.; Pomarede, D. M.; Pomeroy, D.; Pommès, K.; Pontecorvo, L.; Pope, B. G.; Popeneciu, G. A.; Popovic, D. S.; Poppleton, A.; Portell Bueso, X.; Porter, R.; Posch, C.; Pospelov, G. E.; Pospisil, S.; Potrap, I. N.; Potter, C. J.; Potter, C. T.; Poulard, G.; Poveda, J.; Prabhu, R.; Pralavorio, P.; Prasad, S.; Pravahan, R.; Prell, S.; Pretzl, K.; Pribyl, L.; Price, D.; Price, L. E.; Price, M. J.; Prichard, P. M.; Prieur, D.; Primavera, M.; Prokofiev, K.; Prokoshin, F.; Protopopescu, S.; Proudfoot, J.; Prudent, X.; Przysiezniak, H.; Psoroulas, S.; Ptacek, E.; Purdham, J.; Purohit, M.; Puzo, P.; Pylypchenko, Y.; Qian, J.; Qian, Z.; Qin, Z.; Quadt, A.; Quarrie, D. R.; Quayle, W. B.; Quinonez, F.; Raas, M.; Radescu, V.; Radics, B.; Rador, T.; Ragusa, F.; Rahal, G.; Rahimi, A. M.; Rahm, D.; Rajagopalan, S.; Rammensee, M.; Rammes, M.; Ramstedt, M.; Randrianarivony, K.; Ratoff, P. N.; Rauscher, F.; Rauter, E.; Raymond, M.; Read, A. L.; Rebuzzi, D. M.; Redelbach, A.; Redlinger, G.; Reece, R.; Reeves, K.; Reichold, A.; Reinherz-Aronis, E.; Reinsch, A.; Reisinger, I.; Reljic, D.; Rembser, C.; Ren, Z. L.; Renaud, A.; Renkel, P.; Rescigno, M.; Resconi, S.; Resende, B.; Reznicek, P.; Rezvani, R.; Richards, A.; Richter, R.; Richter-Was, E.; Ridel, M.; Rieke, S.; Rijpstra, M.; Rijssenbeek, M.; Rimoldi, A.; Rinaldi, L.; Rios, R. R.; Riu, I.; Rivoltella, G.; Rizatdinova, F.; Rizvi, E.; Robertson, S. H.; Robichaud-Veronneau, A.; Robinson, D.; Robinson, J. E. M.; Robinson, M.; Robson, A.; Rocha de Lima, J. G.; Roda, C.; Roda Dos Santos, D.; Rodier, S.; Rodriguez, D.; Roe, A.; Roe, S.; Røhne, O.; Rojo, V.; Rolli, S.; Romaniouk, A.; Romanov, V. M.; Romeo, G.; Romero Maltrana, D.; Roos, L.; Ros, E.; Rosati, S.; Rosbach, K.; Rose, M.; Rosenbaum, G. A.; Rosenberg, E. I.; Rosendahl, P. L.; Rosselet, L.; Rossetti, V.; Rossi, E.; Rossi, L. P.; Rossi, L.; Rotaru, M.; Roth, I.; Rothberg, J.; Rousseau, D.; Royon, C. R.; Rozanov, A.; Rozen, Y.; Ruan, X.; Rubinskiy, I.; Ruckert, B.; Ruckstuhl, N.; Rud, V. I.; Rudolph, C.; Rudolph, G.; Rühr, F.; Ruggieri, F.; Ruiz-Martinez, A.; Rulikowska-Zarebska, E.; Rumiantsev, V.; Rumyantsev, L.; Runge, K.; Runolfsson, O.; Rurikova, Z.; Rusakovich, N. A.; Rust, D. R.; Rutherfoord, J. P.; Ruwiedel, C.; Ruzicka, P.; Ryabov, Y. F.; Ryadovikov, V.; Ryan, P.; Rybar, M.; Rybkin, G.; Ryder, N. C.; Rzaeva, S.; Saavedra, A. F.; Sadeh, I.; Sadrozinski, H. F.-W.; Sadykov, R.; Safai Tehrani, F.; Sakamoto, H.; Salamanna, G.; Salamon, A.; Saleem, M.; Salihagic, D.; Salnikov, A.; Salt, J.; Salvachua Ferrando, B. M.; Salvatore, D.; Salvatore, F.; Salvucci, A.; Salzburger, A.; Sampsonidis, D.; Samset, B. H.; Sanchez, A.; Sandaker, H.; Sander, H. G.; Sanders, M. P.; Sandhoff, M.; Sandoval, T.; Sandstroem, R.; Sandvoss, S.; Sankey, D. P. C.; Sansoni, A.; Santamarina Rios, C.; Santoni, C.; Santonico, R.; Santos, H.; Saraiva, J. G.; Sarangi, T.; Sarkisyan-Grinbaum, E.; Sarri, F.; Sartisohn, G.; Sasaki, O.; Sasaki, T.; Sasao, N.; Satsounkevitch, I.; Sauvage, G.; Sauvan, E.; Sauvan, J. B.; Savard, P.; Savinov, V.; Savu, D. O.; Savva, P.; Sawyer, L.; Saxon, D. H.; Says, L. P.; Sbarra, C.; Sbrizzi, A.; Scallon, O.; Scannicchio, D. A.; Schaarschmidt, J.; Schacht, P.; Schäfer, U.; Schaepe, S.; Schaetzel, S.; Schaffer, A. C.; Schaile, D.; Schamberger, R. D.; Schamov, A. G.; Scharf, V.; Schegelsky, V. A.; Scheirich, D.; Schernau, M.; Scherzer, M. I.; Schiavi, C.; Schieck, J.; Schioppa, M.; Schlenker, S.; Schlereth, J. L.; Schmidt, E.; Schmieden, K.; Schmitt, C.; Schmitt, S.; Schmitz, M.; Schöning, A.; Schott, M.; Schouten, D.; Schovancova, J.; Schram, M.; Schroeder, C.; Schroer, N.; Schuh, S.; Schuler, G.; Schultes, J.; Schultz-Coulon, H.-C.; Schulz, H.; Schumacher, J. W.; Schumacher, M.; Schumm, B. A.; Schune, Ph.; Schwanenberger, C.; Schwartzman, A.; Schwemling, Ph.; Schwienhorst, R.; Schwierz, R.; Schwindling, J.; Scott, W. G.; Searcy, J.; Sedykh, E.; Segura, E.; Seidel, S. C.; Seiden, A.; Seifert, F.; Seixas, J. M.; Sekhniaidze, G.; Seliverstov, D. M.; Sellden, B.; Sellers, G.; Seman, M.; Semprini-Cesari, N.; Serfon, C.; Serin, L.; Seuster, R.; Severini, H.; Sevior, M. E.; Sfyrla, A.; Shabalina, E.; Shamim, M.; Shan, L. Y.; Shank, J. T.; Shao, Q. T.; Shapiro, M.; Shatalov, P. B.; Shaver, L.; Shaw, C.; Shaw, K.; Sherman, D.; Sherwood, P.; Shibata, A.; Shichi, H.; Shimizu, S.; Shimojima, M.; Shin, T.; Shmeleva, A.; Shochet, M. J.; Short, D.; Shupe, M. A.; Sicho, P.; Sidoti, A.; Siebel, A.; Siegert, F.; Siegrist, J.; Sijacki, Dj.; Silbert, O.; Silva, J.; Silver, Y.; Silverstein, D.; Silverstein, S. B.; Simak, V.; Simard, O.; Simic, Lj.; Simion, S.; Simmons, B.; Simonyan, M.; Sinervo, P.; Sinev, N. B.; Sipica, V.; Siragusa, G.; Sisakyan, A. N.; Sivoklokov, S. Yu.; Sjölin, J.; Sjursen, T. B.; Skinnari, L. A.; Skovpen, K.; Skubic, P.; Skvorodnev, N.; Slater, M.; Slavicek, T.; Sliwa, K.; Sloan, T. J.; Sloper, J.; Smakhtin, V.; Smirnov, S. Yu.; Smirnova, L. N.; Smirnova, O.; Smith, B. C.; Smith, D.; Smith, K. M.; Smizanska, M.; Smolek, K.; Snesarev, A. A.; Snow, S. W.; Snow, J.; Snuverink, J.; Snyder, S.; Soares, M.; Sobie, R.; Sodomka, J.; Soffer, A.; Solans, C. A.; Solar, M.; Solc, J.; Soldatov, E.; Soldevila, U.; Solfaroli Camillocci, E.; Solodkov, A. A.; Solovyanov, O. V.; Sondericker, J.; Soni, N.; Sopko, V.; Sopko, B.; Sorbi, M.; Sosebee, M.; Soukharev, A.; Spagnolo, S.; Spanò, F.; Spighi, R.; Spigo, G.; Spila, F.; Spiriti, E.; Spiwoks, R.; Spousta, M.; Spreitzer, T.; Spurlock, B.; St. Denis, R. D.; Stahl, T.; Stahlman, J.; Stamen, R.; Stanecka, E.; Stanek, R. W.; Stanescu, C.; Stapnes, S.; Starchenko, E. A.; Stark, J.; Staroba, P.; Starovoitov, P.; Staude, A.; Stavina, P.; Stavropoulos, G.; Steele, G.; Steinbach, P.; Steinberg, P.; Stekl, I.; Stelzer, B.; Stelzer, H. J.; Stelzer-Chilton, O.; Stenzel, H.; Stevenson, K.; Stewart, G. A.; Stillings, J. A.; Stockmanns, T.; Stockton, M. C.; Stoerig, K.; Stoicea, G.; Stonjek, S.; Strachota, P.; Stradling, A. R.; Straessner, A.; Strandberg, J.; Strandberg, S.; Strandlie, A.; Strang, M.; Strauss, E.; Strauss, M.; Strizenec, P.; Ströhmer, R.; Strom, D. M.; Strong, J. A.; Stroynowski, R.; Strube, J.; Stugu, B.; Stumer, I.; Stupak, J.; Sturm, P.; Soh, D. A.; Su, D.; Subramania, Hs.; Succurro, A.; Sugaya, Y.; Sugimoto, T.; Suhr, C.; Suita, K.; Suk, M.; Sulin, V. V.; Sultansoy, S.; Sumida, T.; Sun, X.; Sundermann, J. E.; Suruliz, K.; Sushkov, S.; Susinno, G.; Sutton, M. R.; Suzuki, Y.; Svatos, M.; Sviridov, Yu. M.; Swedish, S.; Sykora, I.; Sykora, T.; Szeless, B.; Sánchez, J.; Ta, D.; Tackmann, K.; Taffard, A.; Tafirout, R.; Taga, A.; Taiblum, N.; Takahashi, Y.; Takai, H.; Takashima, R.; Takeda, H.; Takeshita, T.; Talby, M.; Talyshev, A.; Tamsett, M. C.; Tanaka, J.; Tanaka, R.; Tanaka, S.; Tanaka, S.; Tanaka, Y.; Tani, K.; Tannoury, N.; Tappern, G. P.; Tapprogge, S.; Tardif, D.; Tarem, S.; Tarrade, F.; Tartarelli, G. F.; Tas, P.; Tasevsky, M.; Tassi, E.; Tatarkhanov, M.; Tayalati, Y.; Taylor, C.; Taylor, F. E.; Taylor, G. N.; Taylor, W.; Teixeira Dias Castanheira, M.; Teixeira-Dias, P.; Temming, K. K.; Ten Kate, H.; Teng, P. K.; Terada, S.; Terashi, K.; Terron, J.; Terwort, M.; Testa, M.; Teuscher, R. J.; Thadome, J.; Therhaag, J.; Theveneaux-Pelzer, T.; Thioye, M.; Thoma, S.; Thomas, J. P.; Thompson, E. N.; Thompson, P. D.; Thompson, P. D.; Thompson, A. S.; Thomson, E.; Thomson, M.; Thun, R. P.; Tic, T.; Tikhomirov, V. O.; Tikhonov, Y. A.; Timmermans, C. J. W. P.; Tipton, P.; Tique Aires Viegas, F. J.; Tisserant, S.; Tobias, J.; Toczek, B.; Todorov, T.; Todorova-Nova, S.; Toggerson, B.; Tojo, J.; Tokár, S.; Tokunaga, K.; Tokushuku, K.; Tollefson, K.; Tomoto, M.; Tompkins, L.; Toms, K.; Tong, G.; Tonoyan, A.; Topfel, C.; Topilin, N. D.; Torchiani, I.; Torrence, E.; Torres, H.; Torró Pastor, E.; Toth, J.; Touchard, F.; Tovey, D. R.; Traynor, D.; Trefzger, T.; Tremblet, L.; Tricoli, A.; Trigger, I. M.; Trincaz-Duvoid, S.; Trinh, T. N.; Tripiana, M. F.; Trischuk, W.; Trivedi, A.; Trocmé, B.; Troncon, C.; Trottier-McDonald, M.; Trzupek, A.; Tsarouchas, C.; Tseng, J. C.-L.; Tsiakiris, M.; Tsiareshka, P. V.; Tsionou, D.; Tsipolitis, G.; Tsiskaridze, V.; Tskhadadze, E. G.; Tsukerman, I. I.; Tsulaia, V.; Tsung, J.-W.; Tsuno, S.; Tsybychev, D.; Tua, A.; Tuggle, J. M.; Turala, M.; Turecek, D.; Turk Cakir, I.; Turlay, E.; Turra, R.; Tuts, P. M.; Tykhonov, A.; Tylmad, M.; Tyndel, M.; Tyrvainen, H.; Tzanakos, G.; Uchida, K.; Ueda, I.; Ueno, R.; Ugland, M.; Uhlenbrock, M.; Uhrmacher, M.; Ukegawa, F.; Unal, G.; Underwood, D. G.; Undrus, A.; Unel, G.; Unno, Y.; Urbaniec, D.; Urkovsky, E.; Urrejola, P.; Usai, G.; Uslenghi, M.; Vacavant, L.; Vacek, V.; Vachon, B.; Vahsen, S.; Valenta, J.; Valente, P.; Valentinetti, S.; Valkar, S.; Valladolid Gallego, E.; Vallecorsa, S.; Valls Ferrer, J. A.; van der Graaf, H.; van der Kraaij, E.; van der Leeuw, R.; van der Poel, E.; van der Ster, D.; van Eijk, B.; van Eldik, N.; van Gemmeren, P.; van Kesteren, Z.; van Vulpen, I.; Vandelli, W.; Vandoni, G.; Vaniachine, A.; Vankov, P.; Vannucci, F.; Varela Rodriguez, F.; Vari, R.; Varnes, E. W.; Varouchas, D.; Vartapetian, A.; Varvell, K. E.; Vassilakopoulos, V. I.; Vazeille, F.; Vegni, G.; Veillet, J. J.; Vellidis, C.; Veloso, F.; Veness, R.; Veneziano, S.; Ventura, A.; Ventura, D.; Venturi, M.; Venturi, N.; Vercesi, V.; Verducci, M.; Verkerke, W.; Vermeulen, J. C.; Vest, A.; Vetterli, M. C.; Vichou, I.; Vickey, T.; Viehhauser, G. H. A.; Viel, S.; Villa, M.; Villaplana Perez, M.; Vilucchi, E.; Vincter, M. G.; Vinek, E.; Vinogradov, V. B.; Virchaux, M.; Virzi, J.; Vitells, O.; Viti, M.; Vivarelli, I.; Vives Vaque, F.; Vlachos, S.; Vlasak, M.; Vlasov, N.; Vogel, A.; Vokac, P.; Volpi, G.; Volpi, M.; Volpini, G.; von der Schmitt, H.; von Loeben, J.; von Radziewski, H.; von Toerne, E.; Vorobel, V.; Vorobiev, A. P.; Vorwerk, V.; Vos, M.; Voss, R.; Voss, T. T.; Vossebeld, J. H.; Vranjes, N.; Vranjes Milosavljevic, M.; Vrba, V.; Vreeswijk, M.; Vu Anh, T.; Vuillermet, R.; Vukotic, I.; Wagner, W.; Wagner, P.; Wahlen, H.; Wakabayashi, J.; Walbersloh, J.; Walch, S.; Walder, J.; Walker, R.; Walkowiak, W.; Wall, R.; Waller, P.; Wang, C.; Wang, H.; Wang, H.; Wang, J.; Wang, J.; Wang, J. C.; Wang, R.; Wang, S. M.; Warburton, A.; Ward, C. P.; Warsinsky, M.; Watkins, P. M.; Watson, A. T.; Watson, M. F.; Watts, G.; Watts, S.; Waugh, A. T.; Waugh, B. M.; Weber, J.; Weber, M.; Weber, M. S.; Weber, P.; Weidberg, A. R.; Weigell, P.; Weingarten, J.; Weiser, C.; Wellenstein, H.; Wells, P. S.; Wen, M.; Wenaus, T.; Wendler, S.; Weng, Z.; Wengler, T.; Wenig, S.; Wermes, N.; Werner, M.; Werner, P.; Werth, M.; Wessels, M.; Weydert, C.; Whalen, K.; Wheeler-Ellis, S. J.; Whitaker, S. P.; White, A.; White, M. J.; White, S.; Whitehead, S. R.; Whiteson, D.; Whittington, D.; Wicek, F.; Wicke, D.; Wickens, F. J.; Wiedenmann, W.; Wielers, M.; Wienemann, P.; Wiglesworth, C.; Wiik, L. A. M.; Wijeratne, P. A.; Wildauer, A.; Wildt, M. A.; Wilhelm, I.; Wilkens, H. G.; Will, J. Z.; Williams, E.; Williams, H. H.; Willis, W.; Willocq, S.; Wilson, J. A.; Wilson, M. G.; Wilson, A.; Wingerter-Seez, I.; Winkelmann, S.; Winklmeier, F.; Wittgen, M.; Wolter, M. W.; Wolters, H.; Wooden, G.; Wosiek, B. K.; Wotschack, J.; Woudstra, M. J.; Wraight, K.; Wright, C.; Wrona, B.; Wu, S. L.; Wu, X.; Wu, Y.; Wulf, E.; Wunstorf, R.; Wynne, B. M.; Xaplanteris, L.; Xella, S.; Xie, S.; Xie, Y.; Xu, C.; Xu, D.; Xu, G.; Yabsley, B.; Yamada, M.; Yamamoto, A.; Yamamoto, K.; Yamamoto, S.; Yamamura, T.; Yamaoka, J.; Yamazaki, T.; Yamazaki, Y.; Yan, Z.; Yang, H.; Yang, U. K.; Yang, Y.; Yang, Y.; Yang, Z.; Yanush, S.; Yao, W.-M.; Yao, Y.; Yasu, Y.; Ybeles Smit, G. V.; Ye, J.; Ye, S.; Yilmaz, M.; Yoosoofmiya, R.; Yorita, K.; Yoshida, R.; Young, C.; Youssef, S.; Yu, D.; Yu, J.; Yu, J.; Yuan, L.; Yurkewicz, A.; Zaets, V. G.; Zaidan, R.; Zaitsev, A. M.; Zajacova, Z.; Zalite, Yo. K.; Zanello, L.; Zarzhitsky, P.; Zaytsev, A.; Zeitnitz, C.; Zeller, M.; Zemla, A.; Zendler, C.; Zenin, A. V.; Zenin, O.; Ženiš, T.; Zenonos, Z.; Zenz, S.; Zerwas, D.; Zevi Della Porta, G.; Zhan, Z.; Zhang, D.; Zhang, H.; Zhang, J.; Zhang, X.; Zhang, Z.; Zhao, L.; Zhao, T.; Zhao, Z.; Zhemchugov, A.; Zheng, S.; Zhong, J.; Zhou, B.; Zhou, N.; Zhou, Y.; Zhu, C. G.; Zhu, H.; Zhu, J.; Zhu, Y.; Zhuang, X.; Zhuravlov, V.; Zieminska, D.; Zimmermann, R.; Zimmermann, S.; Zimmermann, S.; Ziolkowski, M.; Zitoun, R.; Živković, L.; Zmouchko, V. V.; Zobernig, G.; Zoccoli, A.; Zolnierowski, Y.; Zsenei, A.; Zur Nedden, M.; Zutshi, V.; Zwalinski, L.; Atlas Collaboration

2012-04-01

The ATLAS experiment at the LHC has measured the centrality dependence of charged particle pseudorapidity distributions over | η | < 2 in lead-lead collisions at a nucleon-nucleon centre-of-mass energy of √{sNN} = 2.76 TeV. In order to include particles with transverse momentum as low as 30 MeV, the data were recorded with the central solenoid magnet off. Charged particles were reconstructed with two algorithms (2-point "tracklets" and full tracks) using information from the pixel detector only. The lead-lead collision centrality was characterized by the total transverse energy in the forward calorimeter in the range 3.2 < | η | < 4.9. Measurements are presented of the per-event charged particle pseudorapidity distribution, dNch / dη, and the average charged particle multiplicity in the pseudorapidity interval | η | < 0.5 in several intervals of collision centrality. The results are compared to previous mid-rapidity measurements at the LHC and RHIC. The variation of the mid-rapidity charged particle yield per colliding nucleon pair with the number of participants is consistent with lower √{sNN} results. The shape of the dNch / dη distribution is found to be independent of centrality within the systematic uncertainties of the measurement.

Implementation of a flexible and scalable particle-in-cell method for massively parallel computations in the mantle convection code ASPECT

NASA Astrophysics Data System (ADS)

Gassmöller, Rene; Bangerth, Wolfgang

2016-04-01

Particle-in-cell methods have a long history and many applications in geodynamic modelling of mantle convection, lithospheric deformation and crustal dynamics. They are primarily used to track material information, the strain a material has undergone, the pressure-temperature history a certain material region has experienced, or the amount of volatiles or partial melt present in a region. However, their efficient parallel implementation - in particular combined with adaptive finite-element meshes - is complicated due to the complex communication patterns and frequent reassignment of particles to cells. Consequently, many current scientific software packages accomplish this efficient implementation by specifically designing particle methods for a single purpose, like the advection of scalar material properties that do not evolve over time (e.g., for chemical heterogeneities). Design choices for particle integration, data storage, and parallel communication are then optimized for this single purpose, making the code relatively rigid to changing requirements. Here, we present the implementation of a flexible, scalable and efficient particle-in-cell method for massively parallel finite-element codes with adaptively changing meshes. Using a modular plugin structure, we allow maximum flexibility of the generation of particles, the carried tracer properties, the advection and output algorithms, and the projection of properties to the finite-element mesh. We present scaling tests ranging up to tens of thousands of cores and tens of billions of particles. Additionally, we discuss efficient load-balancing strategies for particles in adaptive meshes with their strengths and weaknesses, local particle-transfer between parallel subdomains utilizing existing communication patterns from the finite element mesh, and the use of established parallel output algorithms like the HDF5 library. Finally, we show some relevant particle application cases, compare our implementation to a modern advection-field approach, and demonstrate under which conditions which method is more efficient. We implemented the presented methods in ASPECT (aspect.dealii.org), a freely available open-source community code for geodynamic simulations. The structure of the particle code is highly modular, and segregated from the PDE solver, and can thus be easily transferred to other programs, or adapted for various application cases.

Chemistry and particle track studies of Apollo 14 glasses.

NASA Technical Reports Server (NTRS)

Glass, B. P.; Storzer, D.; Wagner, G. A.

1972-01-01

The abundance and the composition of Apollo 14 glasses have been studied. Glass particles were analyzed for Si, Ti, Al, Fe, Mn, Mg, Na, and K by electron microprobe analysis. The refractive indices of 26 particles were determined by the oil immersion method. Track analyses have been carried out in order to determine the uranium content and the radiation history of glass particles. The proper identification of galactic and solar flare nuclei tracks makes it possible to estimated residence times of the glass particles in the top layer of the lunar soil.

Multitarget tracking in cluttered environment for a multistatic passive radar system under the DAB/DVB network

NASA Astrophysics Data System (ADS)

Shi, Yi Fang; Park, Seung Hyo; Song, Taek Lyul

2017-12-01

The target tracking using multistatic passive radar in a digital audio/video broadcast (DAB/DVB) network with illuminators of opportunity faces two main challenges: the first challenge is that one has to solve the measurement-to-illuminator association ambiguity in addition to the conventional association ambiguity between the measurements and targets, which introduces a significantly complex three-dimensional (3-D) data association problem among the target-measurement illuminator, this is because all the illuminators transmit the same carrier frequency signals and signals transmitted by different illuminators but reflected via the same target become indistinguishable; the other challenge is that only the bistatic range and range-rate measurements are available while the angle information is unavailable or of very poor quality. In this paper, the authors propose a new target tracking algorithm directly in three-dimensional (3-D) Cartesian coordinates with the capability of track management using the probability of target existence as a track quality measure. The proposed algorithm is termed sequential processing-joint integrated probabilistic data association (SP-JIPDA), which applies the modified sequential processing technique to resolve the additional association ambiguity between measurements and illuminators. The SP-JIPDA algorithm sequentially operates the JIPDA tracker to update each track for each illuminator with all the measurements in the common measurement set at each time. For reasons of fair comparison, the existing modified joint probabilistic data association (MJPDA) algorithm that addresses the 3-D data association problem via "supertargets" using gate grouping and provides tracks directly in 3-D Cartesian coordinates, is enhanced by incorporating the probability of target existence as an effective track quality measure for track management. Both algorithms deal with nonlinear observations using the extended Kalman filtering. A simulation study is performed to verify the superiority of the proposed SP-JIPDA algorithm over the MJIPDA in this multistatic passive radar system.

A physics-enabled flow restoration algorithm for sparse PIV and PTV measurements

NASA Astrophysics Data System (ADS)

Vlasenko, Andrey; Steele, Edward C. C.; Nimmo-Smith, W. Alex M.

2015-06-01

The gaps and noise present in particle image velocimetry (PIV) and particle tracking velocimetry (PTV) measurements affect the accuracy of the data collected. Existing algorithms developed for the restoration of such data are only applicable to experimental measurements collected under well-prepared laboratory conditions (i.e. where the pattern of the velocity flow field is known), and the distribution, size and type of gaps and noise may be controlled by the laboratory set-up. However, in many cases, such as PIV and PTV measurements of arbitrarily turbid coastal waters, the arrangement of such conditions is not possible. When the size of gaps or the level of noise in these experimental measurements become too large, their successful restoration with existing algorithms becomes questionable. Here, we outline a new physics-enabled flow restoration algorithm (PEFRA), specially designed for the restoration of such velocity data. Implemented as a ‘black box’ algorithm, where no user-background in fluid dynamics is necessary, the physical structure of the flow in gappy or noisy data is able to be restored in accordance with its hydrodynamical basis. The use of this is not dependent on types of flow, types of gaps or noise in measurements. The algorithm will operate on any data time-series containing a sequence of velocity flow fields recorded by PIV or PTV. Tests with numerical flow fields established that this method is able to successfully restore corrupted PIV and PTV measurements with different levels of sparsity and noise. This assessment of the algorithm performance is extended with an example application to in situ submersible 3D-PTV measurements collected in the bottom boundary layer of the coastal ocean, where the naturally-occurring plankton and suspended sediments used as tracers causes an increase in the noise level that, without such denoising, will contaminate the measurements.

Detection and Tracking of Moving Objects with Real-Time Onboard Vision System

NASA Astrophysics Data System (ADS)

Erokhin, D. Y.; Feldman, A. B.; Korepanov, S. E.

2017-05-01

Detection of moving objects in video sequence received from moving video sensor is a one of the most important problem in computer vision. The main purpose of this work is developing set of algorithms, which can detect and track moving objects in real time computer vision system. This set includes three main parts: the algorithm for estimation and compensation of geometric transformations of images, an algorithm for detection of moving objects, an algorithm to tracking of the detected objects and prediction their position. The results can be claimed to create onboard vision systems of aircraft, including those relating to small and unmanned aircraft.

Four-dimensional guidance algorithms for aircraft in an air traffic control environment

NASA Technical Reports Server (NTRS)

Pecsvaradi, T.

1975-01-01

Theoretical development and computer implementation of three guidance algorithms are presented. From a small set of input parameters the algorithms generate the ground track, altitude profile, and speed profile required to implement an experimental 4-D guidance system. Given a sequence of waypoints that define a nominal flight path, the first algorithm generates a realistic, flyable ground track consisting of a sequence of straight line segments and circular arcs. Each circular turn is constrained by the minimum turning radius of the aircraft. The ground track and the specified waypoint altitudes are used as inputs to the second algorithm which generates the altitude profile. The altitude profile consists of piecewise constant flight path angle segments, each segment lying within specified upper and lower bounds. The third algorithm generates a feasible speed profile subject to constraints on the rate of change in speed, permissible speed ranges, and effects of wind. Flight path parameters are then combined into a chronological sequence to form the 4-D guidance vectors. These vectors can be used to drive the autopilot/autothrottle of the aircraft so that a 4-D flight path could be tracked completely automatically; or these vectors may be used to drive the flight director and other cockpit displays, thereby enabling the pilot to track a 4-D flight path manually.

Modeling the solute transport by particle-tracing method with variable weights

NASA Astrophysics Data System (ADS)

Jiang, J.

2016-12-01

Particle-tracing method is usually used to simulate the solute transport in fracture media. In this method, the concentration at one point is proportional to number of particles visiting this point. However, this method is rather inefficient at the points with small concentration. Few particles visit these points, which leads to violent oscillation or gives zero value of concentration. In this paper, we proposed a particle-tracing method with variable weights. The concentration at one point is proportional to the sum of the weights of the particles visiting it. It adjusts the weight factors during simulations according to the estimated probabilities of corresponding walks. If the weight W of a tracking particle is larger than the relative concentration C at the corresponding site, the tracking particle will be splitted into Int(W/C) copies and each copy will be simulated independently with the weight W/Int(W/C) . If the weight W of a tracking particle is less than the relative concentration C at the corresponding site, the tracking particle will be continually tracked with a probability W/C and the weight will be adjusted to be C. By adjusting weights, the number of visiting particles distributes evenly in the whole range. Through this variable weights scheme, we can eliminate the violent oscillation and increase the accuracy of orders of magnitudes.

MEASURING PROJECTOR

DOEpatents

Franck, J.V.; Broadhead, P.S.; Skiff, E.W.

1959-07-14

A semiautomatic measuring projector particularly adapted for measurement of the coordinates of photographic images of particle tracks as prcduced in a bubble or cloud chamber is presented. A viewing screen aids the operator in selecting a particle track for measurement. After approximate manual alignment, an image scanning system coupled to a servo control provides automatic exact alignment of a track image with a reference point. The apparatus can follow along a track with a continuous motion while recording coordinate data at various selected points along the track. The coordinate data is recorded on punched cards for subsequent computer calculation of particle trajectory, momentum, etc.

Analysis of the track- and dose-averaged LET and LET spectra in proton therapy using the geant4 Monte Carlo code

PubMed Central

Guan, Fada; Peeler, Christopher; Bronk, Lawrence; Geng, Changran; Taleei, Reza; Randeniya, Sharmalee; Ge, Shuaiping; Mirkovic, Dragan; Grosshans, David; Mohan, Radhe; Titt, Uwe

2015-01-01

Purpose: The motivation of this study was to find and eliminate the cause of errors in dose-averaged linear energy transfer (LET) calculations from therapeutic protons in small targets, such as biological cell layers, calculated using the geant 4 Monte Carlo code. Furthermore, the purpose was also to provide a recommendation to select an appropriate LET quantity from geant 4 simulations to correlate with biological effectiveness of therapeutic protons. Methods: The authors developed a particle tracking step based strategy to calculate the average LET quantities (track-averaged LET, LETt and dose-averaged LET, LETd) using geant 4 for different tracking step size limits. A step size limit refers to the maximally allowable tracking step length. The authors investigated how the tracking step size limit influenced the calculated LETt and LETd of protons with six different step limits ranging from 1 to 500 μm in a water phantom irradiated by a 79.7-MeV clinical proton beam. In addition, the authors analyzed the detailed stochastic energy deposition information including fluence spectra and dose spectra of the energy-deposition-per-step of protons. As a reference, the authors also calculated the averaged LET and analyzed the LET spectra combining the Monte Carlo method and the deterministic method. Relative biological effectiveness (RBE) calculations were performed to illustrate the impact of different LET calculation methods on the RBE-weighted dose. Results: Simulation results showed that the step limit effect was small for LETt but significant for LETd. This resulted from differences in the energy-deposition-per-step between the fluence spectra and dose spectra at different depths in the phantom. Using the Monte Carlo particle tracking method in geant 4 can result in incorrect LETd calculation results in the dose plateau region for small step limits. The erroneous LETd results can be attributed to the algorithm to determine fluctuations in energy deposition along the tracking step in geant 4. The incorrect LETd values lead to substantial differences in the calculated RBE. Conclusions: When the geant 4 particle tracking method is used to calculate the average LET values within targets with a small step limit, such as smaller than 500 μm, the authors recommend the use of LETt in the dose plateau region and LETd around the Bragg peak. For a large step limit, i.e., 500 μm, LETd is recommended along the whole Bragg curve. The transition point depends on beam parameters and can be found by determining the location where the gradient of the ratio of LETd and LETt becomes positive. PMID:26520716

Visualization and mechanisms of splashing erosion of electrodes in a DC air arc

NASA Astrophysics Data System (ADS)

Wu, Yi; Cui, Yufei; Rong, Mingzhe; Murphy, Anthony B.; Yang, Fei; Sun, Hao; Niu, Chunping; Fan, Shaodi

2017-11-01

The splashing erosion of electrodes in a DC atmospheric-pressure air arc has been investigated by visualization of the electrode surface and the sputtered droplets, and tracking of the droplet trajectories, using image processing techniques. A particle tracking velocimetry algorithm has been introduced to measure the sputtering velocity distribution. Erosion of both tungsten-copper and tungsten-ceria electrodes is studied; in both cases electrode erosion is found to be dominated by droplet splashing rather than metal evaporation. Erosion is directly influenced by both melting and the formation of plasma jets, and can be reduced by the tuning of the plasma jet and electrode material. The results provide an understanding of the mechanisms that lead to the long lifetime of tungsten-copper electrodes, and may provide a path for the design of the electrode system subjected to electric arc to minimize erosion.

B-spline based image tracking by detection

NASA Astrophysics Data System (ADS)

Balaji, Bhashyam; Sithiravel, Rajiv; Damini, Anthony; Kirubarajan, Thiagalingam; Rajan, Sreeraman

2016-05-01

Visual image tracking involves the estimation of the motion of any desired targets in a surveillance region using a sequence of images. A standard method of isolating moving targets in image tracking uses background subtraction. The standard background subtraction method is often impacted by irrelevant information in the images, which can lead to poor performance in image-based target tracking. In this paper, a B-Spline based image tracking is implemented. The novel method models the background and foreground using the B-Spline method followed by a tracking-by-detection algorithm. The effectiveness of the proposed algorithm is demonstrated.

A real-time dynamic-MLC control algorithm for delivering IMRT to targets undergoing 2D rigid motion in the beam's eye view.

PubMed

McMahon, Ryan; Berbeco, Ross; Nishioka, Seiko; Ishikawa, Masayori; Papiez, Lech

2008-09-01

An MLC control algorithm for delivering intensity modulated radiation therapy (IMRT) to targets that are undergoing two-dimensional (2D) rigid motion in the beam's eye view (BEV) is presented. The goal of this method is to deliver 3D-derived fluence maps over a moving patient anatomy. Target motion measured prior to delivery is first used to design a set of planned dynamic-MLC (DMLC) sliding-window leaf trajectories. During actual delivery, the algorithm relies on real-time feedback to compensate for target motion that does not agree with the motion measured during planning. The methodology is based on an existing one-dimensional (ID) algorithm that uses on-the-fly intensity calculations to appropriately adjust the DMLC leaf trajectories in real-time during exposure delivery [McMahon et al., Med. Phys. 34, 3211-3223 (2007)]. To extend the 1D algorithm's application to 2D target motion, a real-time leaf-pair shifting mechanism has been developed. Target motion that is orthogonal to leaf travel is tracked by appropriately shifting the positions of all MLC leaves. The performance of the tracking algorithm was tested for a single beam of a fractionated IMRT treatment, using a clinically derived intensity profile and a 2D target trajectory based on measured patient data. Comparisons were made between 2D tracking, 1D tracking, and no tracking. The impact of the tracking lag time and the frequency of real-time imaging were investigated. A study of the dependence of the algorithm's performance on the level of agreement between the motion measured during planning and delivery was also included. Results demonstrated that tracking both components of the 2D motion (i.e., parallel and orthogonal to leaf travel) results in delivered fluence profiles that are superior to those that track the component of motion that is parallel to leaf travel alone. Tracking lag time effects may lead to relatively large intensity delivery errors compared to the other sources of error investigated. However, the algorithm presented is robust in the sense that it does not rely on a high level of agreement between the target motion measured during treatment planning and delivery.

Single and Multiple Object Tracking Using a Multi-Feature Joint Sparse Representation.

PubMed

Hu, Weiming; Li, Wei; Zhang, Xiaoqin; Maybank, Stephen

2015-04-01

In this paper, we propose a tracking algorithm based on a multi-feature joint sparse representation. The templates for the sparse representation can include pixel values, textures, and edges. In the multi-feature joint optimization, noise or occlusion is dealt with using a set of trivial templates. A sparse weight constraint is introduced to dynamically select the relevant templates from the full set of templates. A variance ratio measure is adopted to adaptively adjust the weights of different features. The multi-feature template set is updated adaptively. We further propose an algorithm for tracking multi-objects with occlusion handling based on the multi-feature joint sparse reconstruction. The observation model based on sparse reconstruction automatically focuses on the visible parts of an occluded object by using the information in the trivial templates. The multi-object tracking is simplified into a joint Bayesian inference. The experimental results show the superiority of our algorithm over several state-of-the-art tracking algorithms.

Real-time depth camera tracking with geometrically stable weight algorithm

NASA Astrophysics Data System (ADS)

Fu, Xingyin; Zhu, Feng; Qi, Feng; Wang, Mingming

2017-03-01

We present an approach for real-time camera tracking with depth stream. Existing methods are prone to drift in sceneries without sufficient geometric information. First, we propose a new weight method for an iterative closest point algorithm commonly used in real-time dense mapping and tracking systems. By detecting uncertainty in pose and increasing weight of points that constrain unstable transformations, our system achieves accurate and robust trajectory estimation results. Our pipeline can be fully parallelized with GPU and incorporated into the current real-time depth camera tracking system seamlessly. Second, we compare the state-of-the-art weight algorithms and propose a weight degradation algorithm according to the measurement characteristics of a consumer depth camera. Third, we use Nvidia Kepler Shuffle instructions during warp and block reduction to improve the efficiency of our system. Results on the public TUM RGB-D database benchmark demonstrate that our camera tracking system achieves state-of-the-art results both in accuracy and efficiency.

Optimal configuration of power grid sources based on optimal particle swarm algorithm

NASA Astrophysics Data System (ADS)

Wen, Yuanhua

2018-04-01

In order to optimize the distribution problem of power grid sources, an optimized particle swarm optimization algorithm is proposed. First, the concept of multi-objective optimization and the Pareto solution set are enumerated. Then, the performance of the classical genetic algorithm, the classical particle swarm optimization algorithm and the improved particle swarm optimization algorithm are analyzed. The three algorithms are simulated respectively. Compared with the test results of each algorithm, the superiority of the algorithm in convergence and optimization performance is proved, which lays the foundation for subsequent micro-grid power optimization configuration solution.

Performance Analysis of the Probabilistic Multi-Hypothesis Tracking Algorithm on the SEABAR Data Sets

DTIC Science & Technology

2009-07-01

Performance Analysis of the Probabilistic Multi- Hypothesis Tracking Algorithm On the SEABAR Data Sets Dr. Christian G . Hempel Naval...Hypothesis Tracking,” NUWC-NPT Technical Report 10,428, Naval Undersea Warfare Center Division, Newport, RI, 15 February 1995. [2] G . McLachlan, T...the 9th International Conference on Information Fusion, Florence Italy, July, 2006. [8] C. Hempel, “Track Initialization for Multi-Static Active Sonay

Multilevel Monte Carlo and improved timestepping methods in atmospheric dispersion modelling

NASA Astrophysics Data System (ADS)

Katsiolides, Grigoris; Müller, Eike H.; Scheichl, Robert; Shardlow, Tony; Giles, Michael B.; Thomson, David J.

2018-02-01

A common way to simulate the transport and spread of pollutants in the atmosphere is via stochastic Lagrangian dispersion models. Mathematically, these models describe turbulent transport processes with stochastic differential equations (SDEs). The computational bottleneck is the Monte Carlo algorithm, which simulates the motion of a large number of model particles in a turbulent velocity field; for each particle, a trajectory is calculated with a numerical timestepping method. Choosing an efficient numerical method is particularly important in operational emergency-response applications, such as tracking radioactive clouds from nuclear accidents or predicting the impact of volcanic ash clouds on international aviation, where accurate and timely predictions are essential. In this paper, we investigate the application of the Multilevel Monte Carlo (MLMC) method to simulate the propagation of particles in a representative one-dimensional dispersion scenario in the atmospheric boundary layer. MLMC can be shown to result in asymptotically superior computational complexity and reduced computational cost when compared to the Standard Monte Carlo (StMC) method, which is currently used in atmospheric dispersion modelling. To reduce the absolute cost of the method also in the non-asymptotic regime, it is equally important to choose the best possible numerical timestepping method on each level. To investigate this, we also compare the standard symplectic Euler method, which is used in many operational models, with two improved timestepping algorithms based on SDE splitting methods.

Three dimensional indoor positioning based on visible light with Gaussian mixture sigma-point particle filter technique

NASA Astrophysics Data System (ADS)

Gu, Wenjun; Zhang, Weizhi; Wang, Jin; Amini Kashani, M. R.; Kavehrad, Mohsen

2015-01-01

Over the past decade, location based services (LBS) have found their wide applications in indoor environments, such as large shopping malls, hospitals, warehouses, airports, etc. Current technologies provide wide choices of available solutions, which include Radio-frequency identification (RFID), Ultra wideband (UWB), wireless local area network (WLAN) and Bluetooth. With the rapid development of light-emitting-diodes (LED) technology, visible light communications (VLC) also bring a practical approach to LBS. As visible light has a better immunity against multipath effect than radio waves, higher positioning accuracy is achieved. LEDs are utilized both for illumination and positioning purpose to realize relatively lower infrastructure cost. In this paper, an indoor positioning system using VLC is proposed, with LEDs as transmitters and photo diodes as receivers. The algorithm for estimation is based on received-signalstrength (RSS) information collected from photo diodes and trilateration technique. By appropriately making use of the characteristics of receiver movements and the property of trilateration, estimation on three-dimensional (3-D) coordinates is attained. Filtering technique is applied to enable tracking capability of the algorithm, and a higher accuracy is reached compare to raw estimates. Gaussian mixture Sigma-point particle filter (GM-SPPF) is proposed for this 3-D system, which introduces the notion of Gaussian Mixture Model (GMM). The number of particles in the filter is reduced by approximating the probability distribution with Gaussian components.

A parallelization scheme of the periodic signals tracking algorithm for isochronous mass spectrometry on GPUs

NASA Astrophysics Data System (ADS)

Chen, R. J.; Wang, M.; Yan, X. L.; Yang, Q.; Lam, Y. H.; Yang, L.; Zhang, Y. H.

2017-12-01

The periodic signals tracking algorithm has been used to determine the revolution times of ions stored in storage rings in isochronous mass spectrometry (IMS) experiments. It has been a challenge to perform real-time data analysis by using the periodic signals tracking algorithm in the IMS experiments. In this paper, a parallelization scheme of the periodic signals tracking algorithm is introduced and a new program is developed. The computing time of data analysis can be reduced by a factor of ∼71 and of ∼346 by using our new program on Tesla C1060 GPU and Tesla K20c GPU, compared to using old program on Xeon E5540 CPU. We succeed in performing real-time data analysis for the IMS experiments by using the new program on Tesla K20c GPU.

Development of a real-time internal and external marker tracking system for particle therapy: a phantom study using patient tumor trajectory data

PubMed Central

Cho, Junsang; Cheon, Wonjoong; Ahn, Sanghee; Jung, Hyunuk; Sheen, Heesoon; Park, Hee Chul

2017-01-01

Abstract Target motion–induced uncertainty in particle therapy is more complicated than that in X-ray therapy, requiring more accurate motion management. Therefore, a hybrid motion-tracking system that can track internal tumor motion and as well as an external surrogate of tumor motion was developed. Recently, many correlation tests between internal and external markers in X-ray therapy have been developed; however, the accuracy of such internal/external marker tracking systems, especially in particle therapy, has not yet been sufficiently tested. In this article, the process of installing an in-house hybrid internal/external motion-tracking system is described and the accuracy level of tracking system was acquired. Our results demonstrated that the developed in-house external/internal combined tracking system has submillimeter accuracy, and can be clinically used as a particle therapy system as well as a simulation system for moving tumor treatment. PMID:28201522

Multi-Target Angle Tracking Algorithm for Bistatic MIMO Radar Based on the Elements of the Covariance Matrix

PubMed Central

Zhang, Zhengyan; Zhang, Jianyun; Zhou, Qingsong; Li, Xiaobo

2018-01-01

In this paper, we consider the problem of tracking the direction of arrivals (DOA) and the direction of departure (DOD) of multiple targets for bistatic multiple-input multiple-output (MIMO) radar. A high-precision tracking algorithm for target angle is proposed. First, the linear relationship between the covariance matrix difference and the angle difference of the adjacent moment was obtained through three approximate relations. Then, the proposed algorithm obtained the relationship between the elements in the covariance matrix difference. On this basis, the performance of the algorithm was improved by averaging the covariance matrix element. Finally, the least square method was used to estimate the DOD and DOA. The algorithm realized the automatic correlation of the angle and provided better performance when compared with the adaptive asymmetric joint diagonalization (AAJD) algorithm. The simulation results demonstrated the effectiveness of the proposed algorithm. The algorithm provides the technical support for the practical application of MIMO radar. PMID:29518957

Multi-Target Angle Tracking Algorithm for Bistatic Multiple-Input Multiple-Output (MIMO) Radar Based on the Elements of the Covariance Matrix.

PubMed

Zhang, Zhengyan; Zhang, Jianyun; Zhou, Qingsong; Li, Xiaobo

2018-03-07

In this paper, we consider the problem of tracking the direction of arrivals (DOA) and the direction of departure (DOD) of multiple targets for bistatic multiple-input multiple-output (MIMO) radar. A high-precision tracking algorithm for target angle is proposed. First, the linear relationship between the covariance matrix difference and the angle difference of the adjacent moment was obtained through three approximate relations. Then, the proposed algorithm obtained the relationship between the elements in the covariance matrix difference. On this basis, the performance of the algorithm was improved by averaging the covariance matrix element. Finally, the least square method was used to estimate the DOD and DOA. The algorithm realized the automatic correlation of the angle and provided better performance when compared with the adaptive asymmetric joint diagonalization (AAJD) algorithm. The simulation results demonstrated the effectiveness of the proposed algorithm. The algorithm provides the technical support for the practical application of MIMO radar.

Scalable Domain Decomposed Monte Carlo Particle Transport

NASA Astrophysics Data System (ADS)

O'Brien, Matthew Joseph

In this dissertation, we present the parallel algorithms necessary to run domain decomposed Monte Carlo particle transport on large numbers of processors (millions of processors). Previous algorithms were not scalable, and the parallel overhead became more computationally costly than the numerical simulation. The main algorithms we consider are: • Domain decomposition of constructive solid geometry: enables extremely large calculations in which the background geometry is too large to fit in the memory of a single computational node. • Load Balancing: keeps the workload per processor as even as possible so the calculation runs efficiently. • Global Particle Find: if particles are on the wrong processor, globally resolve their locations to the correct processor based on particle coordinate and background domain. • Visualizing constructive solid geometry, sourcing particles, deciding that particle streaming communication is completed and spatial redecomposition. These algorithms are some of the most important parallel algorithms required for domain decomposed Monte Carlo particle transport. We demonstrate that our previous algorithms were not scalable, prove that our new algorithms are scalable, and run some of the algorithms up to 2 million MPI processes on the Sequoia supercomputer.

An Improved Perturb and Observe Algorithm for Photovoltaic Motion Carriers

NASA Astrophysics Data System (ADS)

Peng, Lele; Xu, Wei; Li, Liming; Zheng, Shubin

2018-03-01

An improved perturbation and observation algorithm for photovoltaic motion carriers is proposed in this paper. The model of the proposed algorithm is given by using Lambert W function and tangent error method. Moreover, by using matlab and experiment of photovoltaic system, the tracking performance of the proposed algorithm is tested. And the results demonstrate that the improved algorithm has fast tracking speed and high efficiency. Furthermore, the energy conversion efficiency by the improved method has increased by nearly 8.2%.

An improved KCF tracking algorithm based on multi-feature and multi-scale

NASA Astrophysics Data System (ADS)

Wu, Wei; Wang, Ding; Luo, Xin; Su, Yang; Tian, Weiye

2018-02-01

The purpose of visual tracking is to associate the target object in a continuous video frame. In recent years, the method based on the kernel correlation filter has become the research hotspot. However, the algorithm still has some problems such as video capture equipment fast jitter, tracking scale transformation. In order to improve the ability of scale transformation and feature description, this paper has carried an innovative algorithm based on the multi feature fusion and multi-scale transform. The experimental results show that our method solves the problem that the target model update when is blocked or its scale transforms. The accuracy of the evaluation (OPE) is 77.0%, 75.4% and the success rate is 69.7%, 66.4% on the VOT and OTB datasets. Compared with the optimal one of the existing target-based tracking algorithms, the accuracy of the algorithm is improved by 6.7% and 6.3% respectively. The success rates are improved by 13.7% and 14.2% respectively.

Stardust Interstellar Preliminary Examination V: XRF Analyses of Interstellar Dust Candidates at ESRF ID13

NASA Technical Reports Server (NTRS)

Brenker, Frank E.; Westphal, Andrew J.; Simionovici, Alexandre S.; Flynn, George J.; Gainsforth, Zack; Allen, Carlton C.; Sanford, Scott; Zolensky, Michael E.; Bastien, Ron K.; Frank, David R.

2014-01-01

Here, we report analyses by synchrotron X-ray fluorescence microscopy of the elemental composition of eight candidate impact features extracted from the Stardust Interstellar Dust Collector (SIDC). Six of the features were unambiguous tracks, and two were crater-like features. Five of the tracks are so-called midnight tracks that is, they had trajectories consistent with an origin either in the interstellar dust stream or as secondaries from impacts on the Sample Return Capsule (SRC). In a companion paper reporting synchrotron X-ray diffraction analyses of ISPE candidates, we show that two of these particles contain natural crystalline materials: the terminal particle of track 30contains olivine and spinel, and the terminal particle of track 34 contains olivine. Here, we show that the terminal particle of track 30, Orion, shows elemental abundances, normalized to Fe, that are close to CI values, and a complex, fine-grained structure. The terminal particle of track 34, Hylabrook, shows abundances that deviate strongly from CI, but shows little fine structure and is nearly homogenous. The terminal particles of other midnight tracks, 29 and 37, had heavy element abundances below detection threshold. A third, track28, showed a composition inconsistent with an extraterrestrial origin, but also inconsistent with known spacecraft materials. A sixth track, with a trajectory consistent with secondary ejecta from an impact on one of the spacecraft solar panels, contains abundant Ce and Zn. This is consistent with the known composition of the glass covering the solar panel. Neither crater-like feature is likely to be associated with extraterrestrial materials. We also analyzed blank aerogel samples to characterize background and variability between aerogel tiles. We found significant differences in contamination levels and compositions, emphasizing the need for local background subtraction for accurate quantification.

Fast Compressive Tracking.

PubMed

Zhang, Kaihua; Zhang, Lei; Yang, Ming-Hsuan

2014-10-01

It is a challenging task to develop effective and efficient appearance models for robust object tracking due to factors such as pose variation, illumination change, occlusion, and motion blur. Existing online tracking algorithms often update models with samples from observations in recent frames. Despite much success has been demonstrated, numerous issues remain to be addressed. First, while these adaptive appearance models are data-dependent, there does not exist sufficient amount of data for online algorithms to learn at the outset. Second, online tracking algorithms often encounter the drift problems. As a result of self-taught learning, misaligned samples are likely to be added and degrade the appearance models. In this paper, we propose a simple yet effective and efficient tracking algorithm with an appearance model based on features extracted from a multiscale image feature space with data-independent basis. The proposed appearance model employs non-adaptive random projections that preserve the structure of the image feature space of objects. A very sparse measurement matrix is constructed to efficiently extract the features for the appearance model. We compress sample images of the foreground target and the background using the same sparse measurement matrix. The tracking task is formulated as a binary classification via a naive Bayes classifier with online update in the compressed domain. A coarse-to-fine search strategy is adopted to further reduce the computational complexity in the detection procedure. The proposed compressive tracking algorithm runs in real-time and performs favorably against state-of-the-art methods on challenging sequences in terms of efficiency, accuracy and robustness.

Using Image Attributes to Assure Accurate Particle Size and Count Using Nanoparticle Tracking Analysis.

PubMed

Defante, Adrian P; Vreeland, Wyatt N; Benkstein, Kurt D; Ripple, Dean C

2018-05-01

Nanoparticle tracking analysis (NTA) obtains particle size by analysis of particle diffusion through a time series of micrographs and particle count by a count of imaged particles. The number of observed particles imaged is controlled by the scattering cross-section of the particles and by camera settings such as sensitivity and shutter speed. Appropriate camera settings are defined as those that image, track, and analyze a sufficient number of particles for statistical repeatability. Here, we test if image attributes, features captured within the image itself, can provide measurable guidelines to assess the accuracy for particle size and count measurements using NTA. The results show that particle sizing is a robust process independent of image attributes for model systems. However, particle count is sensitive to camera settings. Using open-source software analysis, it was found that a median pixel area, 4 pixels 2 , results in a particle concentration within 20% of the expected value. The distribution of these illuminated pixel areas can also provide clues about the polydispersity of particle solutions prior to using a particle tracking analysis. Using the median pixel area serves as an operator-independent means to assess the quality of the NTA measurement for count. Published by Elsevier Inc.

Modeling and optimization of a time-resolved proton radiographic imaging system for proton cancer treatment

NASA Astrophysics Data System (ADS)

Han, Bin

This dissertation describes a research project to test the clinical utility of a time-resolved proton radiographic (TRPR) imaging system by performing comprehensive Monte Carlo simulations of a physical device coupled with realistic lung cancer patient anatomy defined by 4DCT for proton therapy. A time-resolved proton radiographic imaging system was modeled through Monte Carlo simulations. A particle-tracking feature was employed to evaluate the performance of the proton imaging system, especially in its ability to visualize and quantify proton range variations during respiration. The Most Likely Path (MLP) algorithm was developed to approximate the multiple Coulomb scattering paths of protons for the purpose of image reconstruction. Spatial resolution of ˜ 1 mm and range resolution of 1.3% of the total range were achieved using the MLP algorithm. Time-resolved proton radiographs of five patient cases were reconstructed to track tumor motion and to calculate water equivalent length variations. By comparing with direct 4DCT measurement, the accuracy of tumor tracking was found to be better than 2 mm in five patient cases. Utilizing tumor tracking information to reduce margins to the planning target volume, a gated treatment plan was compared with un-gated treatment plan. The equivalent uniform dose (EUD) and the normal tissue complication probability (NTCP) were used to quantify the gain in the quality of treatments. The EUD of the OARs was found to be reduced up to 11% and the corresponding NTCP of organs at risk (OARs) was found to be reduced up to 16.5%. These results suggest that, with image guidance by proton radiography, dose to OARs can be reduced and the corresponding NTCPs can be significantly reduced. The study concludes that the proton imaging system can accurately track the motion of the tumor and detect the WEL variations, leading to potential gains in using image-guided proton radiography for lung cancer treatments.

Measurement of charm meson production in Au+Au collisions at √S NN =200 GEV

NASA Astrophysics Data System (ADS)

Quintero, Amilkar

The study and characterization of nuclear matter under extreme conditions of temperature and pressure, and a full understanding of deconfined partonic matter, the Quark Gluon Plasma (QGP), are major goals of modern high-energy nuclear physics. Heavy quarks (charm and bottom) are formed mainly in the early stages of the collision. Open heavy flavor measurements, e.g. D0, D+/-, DS, are excellent tools to probe and study the hot and dense medium formed in heavy ion collisions. Details of their interaction with the surrounding medium can be studied through energy loss and elliptic flow measurements thus providing valuable information about the nature of the medium and its degree of thermalization. Initial indirect reconstruction studies of heavy quark particles using the electrons from heavy flavor decays, showed a large magnitude of energy loss that was inconsistent with model predictions and assumptions, at the time. Precise measurements of fully reconstructed heavy mesons would provide better understanding of the energy loss mechanisms and the properties of the formed medium. In relativistic heavy ion collisions, the relatively low abundance of heavy quarks and their short lifetimes makes them difficult to distinguish from the event vertex and the combinatorial background; therefore the need for a high precision vertex detector to reconstruct their decay particles. In 2014 a new micro vertex detector was installed in the STAR experiment at Brookhaven National Lab. The Heavy Flavor Tracker (HFT) was designed to perform direct topological reconstruction of the weak decays of heavy flavor particles. The HFT improves STAR track pointing resolution from a few millimeters to ˜30 microns for 1 GeV/c pions, allowing direct reconstruction of short lifetime particles. Although the results of the open charm meson reconstruction using the HFT improved dramatically there is still a lot of room for optimization, especially for reconstructed particles with low transverse momentum (< 1 GeV/c). The standard reconstruction algorithm in the STAR experiment is based on a helix swimming of the reconstructed tracks. This method consists of finding the distance of closest approach between the two helices and defining the midpoint as the decay particle's vertex position. In this work we are using an algorithm based on the Kalman filter to perform full vertex reconstruction. Although the Kalman filter is the most common fitting and filtering method used in tracking, it is not commonly used for particle reconstruction. By using the Kalman filter, the full error matrix for each track is taken into account in the calculations, performing a more complete approach to vertex reconstruction of the charm mesons by providing error estimates on all reconstructed quantities. Also in the traditional analyses, rectangular cuts are made to the reconstructed parameters of the candidate particle decay in order to improve the signal to background ratio and get the cleanest signal possible. In this analysis we use multivariate techniques (i.e. machine learning) to maximize the efficiency of the acquired signal. Machine learning techniques are widely used in many data analysis problems and are also in wide use in high-energy physics experiments. Different optimization methods are tested like Likelihood, Neural Networks. The one with the better performance for reconstruction of D0 mesons was found to be the Binary Decision Trees (BDT). We have applied these analysis techniques on our Run-14 data sample (~1.2 billion Au+Au events at 200 GeV) and we present results for D0 meson pT spectra and nuclear modification factor (RAA) for different event centralities. We discuss the obtained results and compare with current theory models.

Markerless human motion tracking using hierarchical multi-swarm cooperative particle swarm optimization.

PubMed

Saini, Sanjay; Zakaria, Nordin; Rambli, Dayang Rohaya Awang; Sulaiman, Suziah

2015-01-01

The high-dimensional search space involved in markerless full-body articulated human motion tracking from multiple-views video sequences has led to a number of solutions based on metaheuristics, the most recent form of which is Particle Swarm Optimization (PSO). However, the classical PSO suffers from premature convergence and it is trapped easily into local optima, significantly affecting the tracking accuracy. To overcome these drawbacks, we have developed a method for the problem based on Hierarchical Multi-Swarm Cooperative Particle Swarm Optimization (H-MCPSO). The tracking problem is formulated as a non-linear 34-dimensional function optimization problem where the fitness function quantifies the difference between the observed image and a projection of the model configuration. Both the silhouette and edge likelihoods are used in the fitness function. Experiments using Brown and HumanEva-II dataset demonstrated that H-MCPSO performance is better than two leading alternative approaches-Annealed Particle Filter (APF) and Hierarchical Particle Swarm Optimization (HPSO). Further, the proposed tracking method is capable of automatic initialization and self-recovery from temporary tracking failures. Comprehensive experimental results are presented to support the claims.

Research on particle swarm optimization algorithm based on optimal movement probability

NASA Astrophysics Data System (ADS)

Ma, Jianhong; Zhang, Han; He, Baofeng

2017-01-01

The particle swarm optimization algorithm to improve the control precision, and has great application value training neural network and fuzzy system control fields etc.The traditional particle swarm algorithm is used for the training of feed forward neural networks,the search efficiency is low, and easy to fall into local convergence.An improved particle swarm optimization algorithm is proposed based on error back propagation gradient descent. Particle swarm optimization for Solving Least Squares Problems to meme group, the particles in the fitness ranking, optimization problem of the overall consideration, the error back propagation gradient descent training BP neural network, particle to update the velocity and position according to their individual optimal and global optimization, make the particles more to the social optimal learning and less to its optimal learning, it can avoid the particles fall into local optimum, by using gradient information can accelerate the PSO local search ability, improve the multi beam particle swarm depth zero less trajectory information search efficiency, the realization of improved particle swarm optimization algorithm. Simulation results show that the algorithm in the initial stage of rapid convergence to the global optimal solution can be near to the global optimal solution and keep close to the trend, the algorithm has faster convergence speed and search performance in the same running time, it can improve the convergence speed of the algorithm, especially the later search efficiency.

Lightning Jump Algorithm and Relation to Thunderstorm Cell Tracking, GLM Proxy and other Meteorological Measurements

NASA Technical Reports Server (NTRS)

Schultz, Christopher J.; Carey, Larry; Cecil, Dan; Bateman, Monte; Stano, Geoffrey; Goodman, Steve

2012-01-01

Objective of project is to refine, adapt and demonstrate the Lightning Jump Algorithm (LJA) for transition to GOES -R GLM (Geostationary Lightning Mapper) readiness and to establish a path to operations Ongoing work . reducing risk in GLM lightning proxy, cell tracking, LJA algorithm automation, and data fusion (e.g., radar + lightning).

Nonlinear dynamics optimization with particle swarm and genetic algorithms for SPEAR3 emittance upgrade

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, Xiaobiao; Safranek, James

2014-09-01

Nonlinear dynamics optimization is carried out for a low emittance upgrade lattice of SPEAR3 in order to improve its dynamic aperture and Touschek lifetime. Two multi-objective optimization algorithms, a genetic algorithm and a particle swarm algorithm, are used for this study. The performance of the two algorithms are compared. The result shows that the particle swarm algorithm converges significantly faster to similar or better solutions than the genetic algorithm and it does not require seeding of good solutions in the initial population. These advantages of the particle swarm algorithm may make it more suitable for many accelerator optimization applications.

Extending Correlation Filter-Based Visual Tracking by Tree-Structured Ensemble and Spatial Windowing.

PubMed

Gundogdu, Erhan; Ozkan, Huseyin; Alatan, A Aydin

2017-11-01

Correlation filters have been successfully used in visual tracking due to their modeling power and computational efficiency. However, the state-of-the-art correlation filter-based (CFB) tracking algorithms tend to quickly discard the previous poses of the target, since they consider only a single filter in their models. On the contrary, our approach is to register multiple CFB trackers for previous poses and exploit the registered knowledge when an appearance change occurs. To this end, we propose a novel tracking algorithm [of complexity O(D) ] based on a large ensemble of CFB trackers. The ensemble [of size O(2 D ) ] is organized over a binary tree (depth D ), and learns the target appearance subspaces such that each constituent tracker becomes an expert of a certain appearance. During tracking, the proposed algorithm combines only the appearance-aware relevant experts to produce boosted tracking decisions. Additionally, we propose a versatile spatial windowing technique to enhance the individual expert trackers. For this purpose, spatial windows are learned for target objects as well as the correlation filters and then the windowed regions are processed for more robust correlations. In our extensive experiments on benchmark datasets, we achieve a substantial performance increase by using the proposed tracking algorithm together with the spatial windowing.

Textual and shape-based feature extraction and neuro-fuzzy classifier for nuclear track recognition

NASA Astrophysics Data System (ADS)

Khayat, Omid; Afarideh, Hossein

2013-04-01

Track counting algorithms as one of the fundamental principles of nuclear science have been emphasized in the recent years. Accurate measurement of nuclear tracks on solid-state nuclear track detectors is the aim of track counting systems. Commonly track counting systems comprise a hardware system for the task of imaging and software for analysing the track images. In this paper, a track recognition algorithm based on 12 defined textual and shape-based features and a neuro-fuzzy classifier is proposed. Features are defined so as to discern the tracks from the background and small objects. Then, according to the defined features, tracks are detected using a trained neuro-fuzzy system. Features and the classifier are finally validated via 100 Alpha track images and 40 training samples. It is shown that principle textual and shape-based features concomitantly yield a high rate of track detection compared with the single-feature based methods.

Particle Tracking Model (PTM) with Coastal Modeling System (CMS)

DTIC Science & Technology

2015-11-04

Coastal Inlets Research Program Particle Tracking Model (PTM) with Coastal Modeling System ( CMS ) The Particle Tracking Model (PTM) is a Lagrangian...currents and waves. The Coastal Inlets Research Program (CIRP) supports the PTM with the Coastal Modeling System ( CMS ), which provides coupled wave...and current forcing for PTM simulations. CMS -PTM is implemented in the Surface-water Modeling System, a GUI environment for input development

Enhanced object-based tracking algorithm for convective rain storms and cells

NASA Astrophysics Data System (ADS)

Muñoz, Carlos; Wang, Li-Pen; Willems, Patrick

2018-03-01

This paper proposes a new object-based storm tracking algorithm, based upon TITAN (Thunderstorm Identification, Tracking, Analysis and Nowcasting). TITAN is a widely-used convective storm tracking algorithm but has limitations in handling small-scale yet high-intensity storm entities due to its single-threshold identification approach. It also has difficulties to effectively track fast-moving storms because of the employed matching approach that largely relies on the overlapping areas between successive storm entities. To address these deficiencies, a number of modifications are proposed and tested in this paper. These include a two-stage multi-threshold storm identification, a new formulation for characterizing storm's physical features, and an enhanced matching technique in synergy with an optical-flow storm field tracker, as well as, according to these modifications, a more complex merging and splitting scheme. High-resolution (5-min and 529-m) radar reflectivity data for 18 storm events over Belgium are used to calibrate and evaluate the algorithm. The performance of the proposed algorithm is compared with that of the original TITAN. The results suggest that the proposed algorithm can better isolate and match convective rainfall entities, as well as to provide more reliable and detailed motion estimates. Furthermore, the improvement is found to be more significant for higher rainfall intensities. The new algorithm has the potential to serve as a basis for further applications, such as storm nowcasting and long-term stochastic spatial and temporal rainfall generation.

Alpha particle spectroscopy using FNTD and SIM super-resolution microscopy.

PubMed

Kouwenberg, J J M; Kremers, G J; Slotman, J A; Wolterbeek, H T; Houtsmuller, A B; Denkova, A G; Bos, A J J

2018-06-01

Structured illumination microscopy (SIM) for the imaging of alpha particle tracks in fluorescent nuclear track detectors (FNTD) was evaluated and compared to confocal laser scanning microscopy (CLSM). FNTDs were irradiated with an external alpha source and imaged using both methodologies. SIM imaging resulted in improved resolution, without increase in scan time. Alpha particle energy estimation based on the track length, direction and intensity produced results in good agreement with the expected alpha particle energy distribution. A pronounced difference was seen in the spatial scattering of alpha particles in the detectors, where SIM showed an almost 50% reduction compared to CLSM. The improved resolution of SIM allows for more detailed studies of the tracks induced by ionising particles. The combination of SIM and FNTDs for alpha radiation paves the way for affordable and fast alpha spectroscopy and dosimetry. © 2018 The Authors. Journal of Microscopy published by JohnWiley & Sons Ltd on behalf of Royal Microscopical Society.

Scintillator-fiber charged particle track-imaging detector

NASA Technical Reports Server (NTRS)

Binns, W. R.; Israel, M. H.; Klarmann, J.

1983-01-01

A scintillator-fiber charged-particle track-imaging detector was developed using a bundle of square cross section plastic scintillator fiber optics, proximity focused onto an image intensified charge injection device (CID) camera. The tracks of charged particle penetrating into the scintillator fiber bundle are projected onto the CID camera and the imaging information is read out in video format. The detector was exposed to beams of 15 MeV protons and relativistic Neon, Manganese, and Gold nuclei and images of their tracks were obtained. Details of the detector technique, properties of the tracks obtained, and preliminary range measurements of 15 MeV protons stopping in the fiber bundle are presented.

Maneuver Algorithm for Bearings-Only Target Tracking with Acceleration and Field of View Constraints

NASA Astrophysics Data System (ADS)

Roh, Heekun; Shim, Sang-Wook; Tahk, Min-Jea

2018-05-01

This paper proposes a maneuver algorithm for the agent performing target tracking with bearing angle information only. The goal of the agent is to estimate the target position and velocity based only on the bearing angle data. The methods of bearings-only target state estimation are outlined. The nature of bearings-only target tracking problem is then addressed. Based on the insight from above-mentioned properties, the maneuver algorithm for the agent is suggested. The proposed algorithm is composed of a nonlinear, hysteresis guidance law and the estimation accuracy assessment criteria based on the theory of Cramer-Rao bound. The proposed guidance law generates lateral acceleration command based on current field of view angle. The accuracy criteria supply the expected estimation variance, which acts as a terminal criterion for the proposed algorithm. The aforementioned algorithm is verified with a two-dimensional simulation.

Estimation for general birth-death processes

PubMed Central

Crawford, Forrest W.; Minin, Vladimir N.; Suchard, Marc A.

2013-01-01

Birth-death processes (BDPs) are continuous-time Markov chains that track the number of “particles” in a system over time. While widely used in population biology, genetics and ecology, statistical inference of the instantaneous particle birth and death rates remains largely limited to restrictive linear BDPs in which per-particle birth and death rates are constant. Researchers often observe the number of particles at discrete times, necessitating data augmentation procedures such as expectation-maximization (EM) to find maximum likelihood estimates. For BDPs on finite state-spaces, there are powerful matrix methods for computing the conditional expectations needed for the E-step of the EM algorithm. For BDPs on infinite state-spaces, closed-form solutions for the E-step are available for some linear models, but most previous work has resorted to time-consuming simulation. Remarkably, we show that the E-step conditional expectations can be expressed as convolutions of computable transition probabilities for any general BDP with arbitrary rates. This important observation, along with a convenient continued fraction representation of the Laplace transforms of the transition probabilities, allows for novel and efficient computation of the conditional expectations for all BDPs, eliminating the need for truncation of the state-space or costly simulation. We use this insight to derive EM algorithms that yield maximum likelihood estimation for general BDPs characterized by various rate models, including generalized linear models. We show that our Laplace convolution technique outperforms competing methods when they are available and demonstrate a technique to accelerate EM algorithm convergence. We validate our approach using synthetic data and then apply our methods to cancer cell growth and estimation of mutation parameters in microsatellite evolution. PMID:25328261

Measuring the lesion load of multiple sclerosis patients within the corticospinal tract

NASA Astrophysics Data System (ADS)

Klein, Jan; Hanken, Katrin; Koceva, Jasna; Hildebrandt, Helmut; Hahn, Horst K.

2015-03-01

In this paper we present a framework for reliable determination of the lesion load within the corticospinal tract (CST) of multiple sclerosis patients. The basis constitutes a probabilistic fiber tracking approach which checks possible parameter intervals on the fly using an anatomical brain atlas. By exploiting the range of those intervals, the algorithm is able to resolve fiber crossings and to determine the CST in its full entity although it can use a simple diffusion tensor model. Another advantage is its short running time, tracking the CST takes less than a minute. For segmenting the lesions we developed a semi-automatic approach. First, a trained classifier is applied to multimodal MRI data (T1/FLAIR) where the spectrum of lesions has been determined in advance by a clustering algorithm. This leads to an automatic detection of the lesions which can be manually corrected afterwards using a threshold-based approach. For evaluation we scanned 46 MS patients and 16 healthy controls. Fiber tracking has been performed using our novel fiber tracking and a standard defection based algorithm. Regression analysis of the old and new version of the algorithm showed a highly significant superiority of the new algorithm for disease duration. Additionally, a low correlation between old and new approach supports the observation that standard DTI fiber tracking is not always able to track and quantify the CST reliably.

Vision-Aided Inertial Navigation

NASA Technical Reports Server (NTRS)

Roumeliotis, Stergios I. (Inventor); Mourikis, Anastasios I. (Inventor)

2017-01-01

This document discloses, among other things, a system and method for implementing an algorithm to determine pose, velocity, acceleration or other navigation information using feature tracking data. The algorithm has computational complexity that is linear with the number of features tracked.

A Bayesian approach to tracking patients having changing pharmacokinetic parameters

NASA Technical Reports Server (NTRS)

Bayard, David S.; Jelliffe, Roger W.

2004-01-01

This paper considers the updating of Bayesian posterior densities for pharmacokinetic models associated with patients having changing parameter values. For estimation purposes it is proposed to use the Interacting Multiple Model (IMM) estimation algorithm, which is currently a popular algorithm in the aerospace community for tracking maneuvering targets. The IMM algorithm is described, and compared to the multiple model (MM) and Maximum A-Posteriori (MAP) Bayesian estimation methods, which are presently used for posterior updating when pharmacokinetic parameters do not change. Both the MM and MAP Bayesian estimation methods are used in their sequential forms, to facilitate tracking of changing parameters. Results indicate that the IMM algorithm is well suited for tracking time-varying pharmacokinetic parameters in acutely ill and unstable patients, incurring only about half of the integrated error compared to the sequential MM and MAP methods on the same example.

An Extended Kalman Filter-Based Attitude Tracking Algorithm for Star Sensors

PubMed Central

Li, Jian; Wei, Xinguo; Zhang, Guangjun

2017-01-01

Efficiency and reliability are key issues when a star sensor operates in tracking mode. In the case of high attitude dynamics, the performance of existing attitude tracking algorithms degenerates rapidly. In this paper an extended Kalman filtering-based attitude tracking algorithm is presented. The star sensor is modeled as a nonlinear stochastic system with the state estimate providing the three degree-of-freedom attitude quaternion and angular velocity. The star positions in the star image are predicted and measured to estimate the optimal attitude. Furthermore, all the cataloged stars observed in the sensor field-of-view according the predicted image motion are accessed using a catalog partition table to speed up the tracking, called star mapping. Software simulation and night-sky experiment are performed to validate the efficiency and reliability of the proposed method. PMID:28825684

An Extended Kalman Filter-Based Attitude Tracking Algorithm for Star Sensors.

PubMed

Li, Jian; Wei, Xinguo; Zhang, Guangjun

2017-08-21

Efficiency and reliability are key issues when a star sensor operates in tracking mode. In the case of high attitude dynamics, the performance of existing attitude tracking algorithms degenerates rapidly. In this paper an extended Kalman filtering-based attitude tracking algorithm is presented. The star sensor is modeled as a nonlinear stochastic system with the state estimate providing the three degree-of-freedom attitude quaternion and angular velocity. The star positions in the star image are predicted and measured to estimate the optimal attitude. Furthermore, all the cataloged stars observed in the sensor field-of-view according the predicted image motion are accessed using a catalog partition table to speed up the tracking, called star mapping. Software simulation and night-sky experiment are performed to validate the efficiency and reliability of the proposed method.

Recent numerical and algorithmic advances within the volume tracking framework for modeling interfacial flows

DOE PAGES

François, Marianne M.

2015-05-28

A review of recent advances made in numerical methods and algorithms within the volume tracking framework is presented. The volume tracking method, also known as the volume-of-fluid method has become an established numerical approach to model and simulate interfacial flows. Its advantage is its strict mass conservation. However, because the interface is not explicitly tracked but captured via the material volume fraction on a fixed mesh, accurate estimation of the interface position, its geometric properties and modeling of interfacial physics in the volume tracking framework remain difficult. Several improvements have been made over the last decade to address these challenges.more » In this study, the multimaterial interface reconstruction method via power diagram, curvature estimation via heights and mean values and the balanced-force algorithm for surface tension are highlighted.« less

Towards Automated Three-Dimensional Tracking of Nephrons through Stacked Histological Image Sets

PubMed Central

Bhikha, Charita; Andreasen, Arne; Christensen, Erik I.; Letts, Robyn F. R.; Pantanowitz, Adam; Rubin, David M.; Thomsen, Jesper S.; Zhai, Xiao-Yue

2015-01-01

An automated approach for tracking individual nephrons through three-dimensional histological image sets of mouse and rat kidneys is presented. In a previous study, the available images were tracked manually through the image sets in order to explore renal microarchitecture. The purpose of the current research is to reduce the time and effort required to manually trace nephrons by creating an automated, intelligent system as a standard tool for such datasets. The algorithm is robust enough to isolate closely packed nephrons and track their convoluted paths despite a number of nonideal, interfering conditions such as local image distortions, artefacts, and interstitial tissue interference. The system comprises image preprocessing, feature extraction, and a custom graph-based tracking algorithm, which is validated by a rule base and a machine learning algorithm. A study of a selection of automatically tracked nephrons, when compared with manual tracking, yields a 95% tracking accuracy for structures in the cortex, while those in the medulla have lower accuracy due to narrower diameter and higher density. Limited manual intervention is introduced to improve tracking, enabling full nephron paths to be obtained with an average of 17 manual corrections per mouse nephron and 58 manual corrections per rat nephron. PMID:26170896

Towards Automated Three-Dimensional Tracking of Nephrons through Stacked Histological Image Sets.

PubMed

Bhikha, Charita; Andreasen, Arne; Christensen, Erik I; Letts, Robyn F R; Pantanowitz, Adam; Rubin, David M; Thomsen, Jesper S; Zhai, Xiao-Yue

2015-01-01

An automated approach for tracking individual nephrons through three-dimensional histological image sets of mouse and rat kidneys is presented. In a previous study, the available images were tracked manually through the image sets in order to explore renal microarchitecture. The purpose of the current research is to reduce the time and effort required to manually trace nephrons by creating an automated, intelligent system as a standard tool for such datasets. The algorithm is robust enough to isolate closely packed nephrons and track their convoluted paths despite a number of nonideal, interfering conditions such as local image distortions, artefacts, and interstitial tissue interference. The system comprises image preprocessing, feature extraction, and a custom graph-based tracking algorithm, which is validated by a rule base and a machine learning algorithm. A study of a selection of automatically tracked nephrons, when compared with manual tracking, yields a 95% tracking accuracy for structures in the cortex, while those in the medulla have lower accuracy due to narrower diameter and higher density. Limited manual intervention is introduced to improve tracking, enabling full nephron paths to be obtained with an average of 17 manual corrections per mouse nephron and 58 manual corrections per rat nephron.

3D laser traking of a particle in 3DFM

NASA Astrophysics Data System (ADS)

Desai, Kalpit; Welch, Gregory; Bishop, Gary; Taylor, Russell; Superfine, Richard

2003-11-01

The principal goal of 3D tracking in our home-built 3D Magnetic Force Microscope is to monitor movement of the particle with respect to laser beam waist and keep the particle at the center of laser beam. The sensory element is a Quadrant Photo Diode (QPD) which captures scattering of light caused by particle motion with bandwidth up to 40 KHz. XYZ translation stage is the driver element which moves particle back in the center of the laser with accuracy of couple of nanometers and with bandwidth up to 300 Hz. Since our particles vary in size, composition and shape, instead of using a priori model we use standard system identification techniques to have optimal approximation to the relationship between particle motion and QPD response. We have developed position feedback control system software that is capable of 3-dimensional tracking of beads that are attached to cilia on living cells which are beating at up to 15Hz. We have also modeled the control system of instrument to simulate performance of 3D particle tracking for different experimental conditions. Given operational level of nanometers, noise poses a great challenge for the tracking system. We propose to use stochastic control theory approaches to increase robustness of tracking.

Infrared Spectroscopy of Wild 2 Particle Hypervelocity Tracks in Stardust Aerogel: Evidence for the presence of Volatile Organics in Comet Dust

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bajt, S; Sandford, S A; Flynn, G J

2007-08-28

Infrared spectroscopy maps of some tracks, made by cometary dust from 81P/Wild 2 impacting Stardust aerogel, reveal an interesting distribution of volatile organic material. Out of six examined tracks three show presence of volatile organic components possibly injected into the aerogel during particle impacts. When particle tracks contained excess volatile organic material, they were found to be -CH{sub 2}-rich. Off-normal particle tracks could indicate impacts by lower velocity particles that could have bounced off the Whipple shield, therefore carry off some contamination from it. However, this theory is not supported by data that show excess organic-rich material in normal andmore » off-normal particle tracks. It is clear that the population of cometary particles impacting the Stardust aerogel collectors also include grains that contained little or none of this volatile organic component. This observation is consistent with the highly heterogeneous nature of the collected grains, as seen by a multitude of other analytical techniques. We propose that at least some of the volatile organic material might be of cometary origin based on supporting data shown in this paper. However, we also acknowledge the presence of carbon (primarily as -CH{sub 3}) in the original aerogel, which complicates interpretation of these results.« less

Properties of jets measured from tracks in proton-proton collisions at center-of-mass energy s = 7 TeV with the ATLAS detector

DOE PAGES

Aad, G.; Abbott, B.; Abdallah, J.; ...

2011-09-20

Jets are identified and their properties studied in center-of-mass energy √s = 7 TeV proton-proton collisions at the Large Hadron Collider using charged particles measured by the ATLAS inner detector. Events are selected using a minimum bias trigger, allowing jets at very low transverse momentum to be observed and their characteristics in the transition to high-momentum fully perturbative jets to be studied. Jets are reconstructed using the anti-k t algorithm applied to charged particles with two radius parameter choices, 0.4 and 0.6. An inclusive charged jet transverse momentum cross section measurement from 4 GeV to 100 GeV is shown formore » four ranges in rapidity extending to 1.9 and corrected to charged particle-level truth jets. The transverse momenta and longitudinal momentum fractions of charged particles within jets are measured, along with the charged particle multiplicity and the particle density as a function of radial distance from the jet axis. Comparison of the data with the theoretical models implemented in existing tunings of Monte Carlo event generators indicates reasonable overall agreement between data and Monte Carlo. In conclusion, these comparisons are sensitive to Monte Carlo parton showering, hadronization, and soft physics models.« less

Vehicle active steering control research based on two-DOF robust internal model control

NASA Astrophysics Data System (ADS)

Wu, Jian; Liu, Yahui; Wang, Fengbo; Bao, Chunjiang; Sun, Qun; Zhao, Youqun

2016-07-01

Because of vehicle's external disturbances and model uncertainties, robust control algorithms have obtained popularity in vehicle stability control. The robust control usually gives up performance in order to guarantee the robustness of the control algorithm, therefore an improved robust internal model control(IMC) algorithm blending model tracking and internal model control is put forward for active steering system in order to reach high performance of yaw rate tracking with certain robustness. The proposed algorithm inherits the good model tracking ability of the IMC control and guarantees robustness to model uncertainties. In order to separate the design process of model tracking from the robustness design process, the improved 2 degree of freedom(DOF) robust internal model controller structure is given from the standard Youla parameterization. Simulations of double lane change maneuver and those of crosswind disturbances are conducted for evaluating the robust control algorithm, on the basis of a nonlinear vehicle simulation model with a magic tyre model. Results show that the established 2-DOF robust IMC method has better model tracking ability and a guaranteed level of robustness and robust performance, which can enhance the vehicle stability and handling, regardless of variations of the vehicle model parameters and the external crosswind interferences. Contradiction between performance and robustness of active steering control algorithm is solved and higher control performance with certain robustness to model uncertainties is obtained.

Data association approaches in bearings-only multi-target tracking

NASA Astrophysics Data System (ADS)

Xu, Benlian; Wang, Zhiquan

2008-03-01

According to requirements of time computation complexity and correctness of data association of the multi-target tracking, two algorithms are suggested in this paper. The proposed Algorithm 1 is developed from the modified version of dual Simplex method, and it has the advantage of direct and explicit form of the optimal solution. The Algorithm 2 is based on the idea of Algorithm 1 and rotational sort method, it combines not only advantages of Algorithm 1, but also reduces the computational burden, whose complexity is only 1/ N times that of Algorithm 1. Finally, numerical analyses are carried out to evaluate the performance of the two data association algorithms.

Primary cosmic ray particles with Z greater than 35 /VVH particles/. [Very Very Heavy particle track measurement by balloons

NASA Technical Reports Server (NTRS)

Blanford, G. E., Jr.; Friedlander, M. W.; Hoppe, M.; Klarmann, J.; Walker, R. M.; Wefel, J. P.

1974-01-01

Large areas of nuclear emulsions and plastic detectors were exposed to the primary cosmic radiation during high-altitude balloon flights. From an analysis of 141 particle tracks recorded during a total exposure of 13,000,000 sq m-ster-sec, a charge spectrum of the VVH particles has been derived.

A multipopulation PSO based memetic algorithm for permutation flow shop scheduling.

PubMed

Liu, Ruochen; Ma, Chenlin; Ma, Wenping; Li, Yangyang

2013-01-01

The permutation flow shop scheduling problem (PFSSP) is part of production scheduling, which belongs to the hardest combinatorial optimization problem. In this paper, a multipopulation particle swarm optimization (PSO) based memetic algorithm (MPSOMA) is proposed in this paper. In the proposed algorithm, the whole particle swarm population is divided into three subpopulations in which each particle evolves itself by the standard PSO and then updates each subpopulation by using different local search schemes such as variable neighborhood search (VNS) and individual improvement scheme (IIS). Then, the best particle of each subpopulation is selected to construct a probabilistic model by using estimation of distribution algorithm (EDA) and three particles are sampled from the probabilistic model to update the worst individual in each subpopulation. The best particle in the entire particle swarm is used to update the global optimal solution. The proposed MPSOMA is compared with two recently proposed algorithms, namely, PSO based memetic algorithm (PSOMA) and hybrid particle swarm optimization with estimation of distribution algorithm (PSOEDA), on 29 well-known PFFSPs taken from OR-library, and the experimental results show that it is an effective approach for the PFFSP.

Joint Transform Correlation for face tracking: elderly fall detection application

NASA Astrophysics Data System (ADS)

Katz, Philippe; Aron, Michael; Alfalou, Ayman

2013-03-01

In this paper, an iterative tracking algorithm based on a non-linear JTC (Joint Transform Correlator) architecture and enhanced by a digital image processing method is proposed and validated. This algorithm is based on the computation of a correlation plane where the reference image is updated at each frame. For that purpose, we use the JTC technique in real time to track a patient (target image) in a room fitted with a video camera. The correlation plane is used to localize the target image in the current video frame (frame i). Then, the reference image to be exploited in the next frame (frame i+1) is updated according to the previous one (frame i). In an effort to validate our algorithm, our work is divided into two parts: (i) a large study based on different sequences with several situations and different JTC parameters is achieved in order to quantify their effects on the tracking performances (decimation, non-linearity coefficient, size of the correlation plane, size of the region of interest...). (ii) the tracking algorithm is integrated into an application of elderly fall detection. The first reference image is a face detected by means of Haar descriptors, and then localized into the new video image thanks to our tracking method. In order to avoid a bad update of the reference frame, a method based on a comparison of image intensity histograms is proposed and integrated in our algorithm. This step ensures a robust tracking of the reference frame. This article focuses on face tracking step optimisation and evalutation. A supplementary step of fall detection, based on vertical acceleration and position, will be added and studied in further work.

A Hybrid Maximum Power Point Tracking Method for Automobile Exhaust Thermoelectric Generator

NASA Astrophysics Data System (ADS)

Quan, Rui; Zhou, Wei; Yang, Guangyou; Quan, Shuhai

2017-05-01

To make full use of the maximum output power of automobile exhaust thermoelectric generator (AETEG) based on Bi2Te3 thermoelectric modules (TEMs), taking into account the advantages and disadvantages of existing maximum power point tracking methods, and according to the output characteristics of TEMs, a hybrid maximum power point tracking method combining perturb and observe (P&O) algorithm, quadratic interpolation and constant voltage tracking method was put forward in this paper. Firstly, it searched the maximum power point with P&O algorithms and a quadratic interpolation method, then, it forced the AETEG to work at its maximum power point with constant voltage tracking. A synchronous buck converter and controller were implemented in the electric bus of the AETEG applied in a military sports utility vehicle, and the whole system was modeled and simulated with a MATLAB/Simulink environment. Simulation results demonstrate that the maximum output power of the AETEG based on the proposed hybrid method is increased by about 3.0% and 3.7% compared with that using only the P&O algorithm and the quadratic interpolation method, respectively. The shorter tracking time is only 1.4 s, which is reduced by half compared with that of the P&O algorithm and quadratic interpolation method, respectively. The experimental results demonstrate that the tracked maximum power is approximately equal to the real value using the proposed hybrid method,and it can preferentially deal with the voltage fluctuation of the AETEG with only P&O algorithm, and resolve the issue that its working point can barely be adjusted only with constant voltage tracking when the operation conditions change.

Radar tracking with an interacting multiple model and probabilistic data association filter for civil aviation applications.

PubMed

Jan, Shau-Shiun; Kao, Yu-Chun

2013-05-17

The current trend of the civil aviation technology is to modernize the legacy air traffic control (ATC) system that is mainly supported by many ground based navigation aids to be the new air traffic management (ATM) system that is enabled by global positioning system (GPS) technology. Due to the low receiving power of GPS signal, it is a major concern to aviation authorities that the operation of the ATM system might experience service interruption when the GPS signal is jammed by either intentional or unintentional radio-frequency interference. To maintain the normal operation of the ATM system during the period of GPS outage, the use of the current radar system is proposed in this paper. However, the tracking performance of the current radar system could not meet the required performance of the ATM system, and an enhanced tracking algorithm, the interacting multiple model and probabilistic data association filter (IMMPDAF), is therefore developed to support the navigation and surveillance services of the ATM system. The conventional radar tracking algorithm, the nearest neighbor Kalman filter (NNKF), is used as the baseline to evaluate the proposed radar tracking algorithm, and the real flight data is used to validate the IMMPDAF algorithm. As shown in the results, the proposed IMMPDAF algorithm could enhance the tracking performance of the current aviation radar system and meets the required performance of the new ATM system. Thus, the current radar system with the IMMPDAF algorithm could be used as an alternative system to continue aviation navigation and surveillance services of the ATM system during GPS outage periods.

Radar Tracking with an Interacting Multiple Model and Probabilistic Data Association Filter for Civil Aviation Applications

PubMed Central

Jan, Shau-Shiun; Kao, Yu-Chun

2013-01-01

The current trend of the civil aviation technology is to modernize the legacy air traffic control (ATC) system that is mainly supported by many ground based navigation aids to be the new air traffic management (ATM) system that is enabled by global positioning system (GPS) technology. Due to the low receiving power of GPS signal, it is a major concern to aviation authorities that the operation of the ATM system might experience service interruption when the GPS signal is jammed by either intentional or unintentional radio-frequency interference. To maintain the normal operation of the ATM system during the period of GPS outage, the use of the current radar system is proposed in this paper. However, the tracking performance of the current radar system could not meet the required performance of the ATM system, and an enhanced tracking algorithm, the interacting multiple model and probabilistic data association filter (IMMPDAF), is therefore developed to support the navigation and surveillance services of the ATM system. The conventional radar tracking algorithm, the nearest neighbor Kalman filter (NNKF), is used as the baseline to evaluate the proposed radar tracking algorithm, and the real flight data is used to validate the IMMPDAF algorithm. As shown in the results, the proposed IMMPDAF algorithm could enhance the tracking performance of the current aviation radar system and meets the required performance of the new ATM system. Thus, the current radar system with the IMMPDAF algorithm could be used as an alternative system to continue aviation navigation and surveillance services of the ATM system during GPS outage periods. PMID:23686142

A Novel Particle Swarm Optimization Algorithm for Global Optimization

PubMed Central

Wang, Chun-Feng; Liu, Kui

2016-01-01

Particle Swarm Optimization (PSO) is a recently developed optimization method, which has attracted interest of researchers in various areas due to its simplicity and effectiveness, and many variants have been proposed. In this paper, a novel Particle Swarm Optimization algorithm is presented, in which the information of the best neighbor of each particle and the best particle of the entire population in the current iteration is considered. Meanwhile, to avoid premature, an abandoned mechanism is used. Furthermore, for improving the global convergence speed of our algorithm, a chaotic search is adopted in the best solution of the current iteration. To verify the performance of our algorithm, standard test functions have been employed. The experimental results show that the algorithm is much more robust and efficient than some existing Particle Swarm Optimization algorithms. PMID:26955387

Lightning Jump Algorithm and Relation to Thunderstorm Cell Tracking, GLM Proxy and Other Meteorological Measurements

NASA Technical Reports Server (NTRS)

Schultz, Christopher J.; Carey, Lawrence D.; Cecil, Daniel J.; Bateman, Monte

2012-01-01

The lightning jump algorithm has a robust history in correlating upward trends in lightning to severe and hazardous weather occurrence. The algorithm uses the correlation between the physical principles that govern an updraft's ability to produce microphysical and kinematic conditions conducive for electrification and its role in the development of severe weather conditions. Recent work has demonstrated that the lightning jump algorithm concept holds significant promise in the operational realm, aiding in the identification of thunderstorms that have potential to produce severe or hazardous weather. However, a large amount of work still needs to be completed in spite of these positive results. The total lightning jump algorithm is not a stand-alone concept that can be used independent of other meteorological measurements, parameters, and techniques. For example, the algorithm is highly dependent upon thunderstorm tracking to build lightning histories on convective cells. Current tracking methods show that thunderstorm cell tracking is most reliable and cell histories are most accurate when radar information is incorporated with lightning data. In the absence of radar data, the cell tracking is a bit less reliable but the value added by the lightning information is much greater. For optimal application, the algorithm should be integrated with other measurements that assess storm scale properties (e.g., satellite, radar). Therefore, the recent focus of this research effort has been assessing the lightning jump's relation to thunderstorm tracking, meteorological parameters, and its potential uses in operational meteorology. Furthermore, the algorithm must be tailored for the optically-based GOES-R Geostationary Lightning Mapper (GLM), as what has been observed using Very High Frequency Lightning Mapping Array (VHF LMA) measurements will not exactly translate to what will be observed by GLM due to resolution and other instrument differences. Herein, we present some of the promising aspects and challenges encountered in utilizing objective tracking and GLM proxy data, as well as recent results that demonstrate the value added information gained by combining the lightning jump concept with traditional meteorological measurements.

An Integrated Centroid Finding and Particle Overlap Decomposition Algorithm for Stereo Imaging Velocimetry

NASA Technical Reports Server (NTRS)

McDowell, Mark

2004-01-01

An integrated algorithm for decomposing overlapping particle images (multi-particle objects) along with determining each object s constituent particle centroid(s) has been developed using image analysis techniques. The centroid finding algorithm uses a modified eight-direction search method for finding the perimeter of any enclosed object. The centroid is calculated using the intensity-weighted center of mass of the object. The overlap decomposition algorithm further analyzes the object data and breaks it down into its constituent particle centroid(s). This is accomplished with an artificial neural network, feature based technique and provides an efficient way of decomposing overlapping particles. Combining the centroid finding and overlap decomposition routines into a single algorithm allows us to accurately predict the error associated with finding the centroid(s) of particles in our experiments. This algorithm has been tested using real, simulated, and synthetic data and the results are presented and discussed.

Accelerated simulation of stochastic particle removal processes in particle-resolved aerosol models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Curtis, J.H.; Michelotti, M.D.; Riemer, N.

2016-10-01

Stochastic particle-resolved methods have proven useful for simulating multi-dimensional systems such as composition-resolved aerosol size distributions. While particle-resolved methods have substantial benefits for highly detailed simulations, these techniques suffer from high computational cost, motivating efforts to improve their algorithmic efficiency. Here we formulate an algorithm for accelerating particle removal processes by aggregating particles of similar size into bins. We present the Binned Algorithm for particle removal processes and analyze its performance with application to the atmospherically relevant process of aerosol dry deposition. We show that the Binned Algorithm can dramatically improve the efficiency of particle removals, particularly for low removalmore » rates, and that computational cost is reduced without introducing additional error. In simulations of aerosol particle removal by dry deposition in atmospherically relevant conditions, we demonstrate about 50-times increase in algorithm efficiency.« less

Development of a real-time internal and external marker tracking system for particle therapy: a phantom study using patient tumor trajectory data.

PubMed

Cho, Junsang; Cheon, Wonjoong; Ahn, Sanghee; Jung, Hyunuk; Sheen, Heesoon; Park, Hee Chul; Han, Youngyih

2017-09-01

Target motion-induced uncertainty in particle therapy is more complicated than that in X-ray therapy, requiring more accurate motion management. Therefore, a hybrid motion-tracking system that can track internal tumor motion and as well as an external surrogate of tumor motion was developed. Recently, many correlation tests between internal and external markers in X-ray therapy have been developed; however, the accuracy of such internal/external marker tracking systems, especially in particle therapy, has not yet been sufficiently tested. In this article, the process of installing an in-house hybrid internal/external motion-tracking system is described and the accuracy level of tracking system was acquired. Our results demonstrated that the developed in-house external/internal combined tracking system has submillimeter accuracy, and can be clinically used as a particle therapy system as well as a simulation system for moving tumor treatment. © The Author 2017. Published by Oxford University Press on behalf of The Japan Radiation Research Society and Japanese Society for Radiation Oncology.

Hybrid three-dimensional and support vector machine approach for automatic vehicle tracking and classification using a single camera

NASA Astrophysics Data System (ADS)

Kachach, Redouane; Cañas, José María

2016-05-01

Using video in traffic monitoring is one of the most active research domains in the computer vision community. TrafficMonitor, a system that employs a hybrid approach for automatic vehicle tracking and classification on highways using a simple stationary calibrated camera, is presented. The proposed system consists of three modules: vehicle detection, vehicle tracking, and vehicle classification. Moving vehicles are detected by an enhanced Gaussian mixture model background estimation algorithm. The design includes a technique to resolve the occlusion problem by using a combination of two-dimensional proximity tracking algorithm and the Kanade-Lucas-Tomasi feature tracking algorithm. The last module classifies the shapes identified into five vehicle categories: motorcycle, car, van, bus, and truck by using three-dimensional templates and an algorithm based on histogram of oriented gradients and the support vector machine classifier. Several experiments have been performed using both real and simulated traffic in order to validate the system. The experiments were conducted on GRAM-RTM dataset and a proper real video dataset which is made publicly available as part of this work.

Accurately tracking single-cell movement trajectories in microfluidic cell sorting devices.

PubMed

Jeong, Jenny; Frohberg, Nicholas J; Zhou, Enlu; Sulchek, Todd; Qiu, Peng

2018-01-01

Microfluidics are routinely used to study cellular properties, including the efficient quantification of single-cell biomechanics and label-free cell sorting based on the biomechanical properties, such as elasticity, viscosity, stiffness, and adhesion. Both quantification and sorting applications require optimal design of the microfluidic devices and mathematical modeling of the interactions between cells, fluid, and the channel of the device. As a first step toward building such a mathematical model, we collected video recordings of cells moving through a ridged microfluidic channel designed to compress and redirect cells according to cell biomechanics. We developed an efficient algorithm that automatically and accurately tracked the cell trajectories in the recordings. We tested the algorithm on recordings of cells with different stiffness, and showed the correlation between cell stiffness and the tracked trajectories. Moreover, the tracking algorithm successfully picked up subtle differences of cell motion when passing through consecutive ridges. The algorithm for accurately tracking cell trajectories paves the way for future efforts of modeling the flow, forces, and dynamics of cell properties in microfluidics applications.

New robust algorithm for tracking cells in videos of Drosophila morphogenesis based on finding an ideal path in segmented spatio-temporal cellular structures.

PubMed

Bellaïche, Yohanns; Bosveld, Floris; Graner, François; Mikula, Karol; Remesíková, Mariana; Smísek, Michal

2011-01-01

In this paper, we present a novel algorithm for tracking cells in time lapse confocal microscopy movie of a Drosophila epithelial tissue during pupal morphogenesis. We consider a 2D + time video as a 3D static image, where frames are stacked atop each other, and using a spatio-temporal segmentation algorithm we obtain information about spatio-temporal 3D tubes representing evolutions of cells. The main idea for tracking is the usage of two distance functions--first one from the cells in the initial frame and second one from segmented boundaries. We track the cells backwards in time. The first distance function attracts the subsequently constructed cell trajectories to the cells in the initial frame and the second one forces them to be close to centerlines of the segmented tubular structures. This makes our tracking algorithm robust against noise and missing spatio-temporal boundaries. This approach can be generalized to a 3D + time video analysis, where spatio-temporal tubes are 4D objects.

Spacecraft Attitude Tracking and Maneuver Using Combined Magnetic Actuators

NASA Technical Reports Server (NTRS)

Zhou, Zhiqiang

2012-01-01

A paper describes attitude-control algorithms using the combination of magnetic actuators with reaction wheel assemblies (RWAs) or other types of actuators such as thrusters. The combination of magnetic actuators with one or two RWAs aligned with different body axis expands the two-dimensional control torque to three-dimensional. The algorithms can guarantee the spacecraft attitude and rates to track the commanded attitude precisely. A design example is presented for nadir-pointing, pitch, and yaw maneuvers. The results show that precise attitude tracking can be reached and the attitude- control accuracy is comparable with RWA-based attitude control. When there are only one or two workable RWAs due to RWA failures, the attitude-control system can switch to the control algorithms for the combined magnetic actuators with the RWAs without going to the safe mode, and the control accuracy can be maintained. The attitude-control algorithms of the combined actuators are derived, which can guarantee the spacecraft attitude and rates to track the commanded values precisely. Results show that precise attitude tracking can be reached, and the attitude-control accuracy is comparable with 3-axis wheel control.

Dense-HOG-based drift-reduced 3D face tracking for infant pain monitoring

NASA Astrophysics Data System (ADS)

Saeijs, Ronald W. J. J.; Tjon A Ten, Walther E.; de With, Peter H. N.

2017-03-01

This paper presents a new algorithm for 3D face tracking intended for clinical infant pain monitoring. The algorithm uses a cylinder head model and 3D head pose recovery by alignment of dynamically extracted templates based on dense-HOG features. The algorithm includes extensions for drift reduction, using re-registration in combination with multi-pose state estimation by means of a square-root unscented Kalman filter. The paper reports experimental results on videos of moving infants in hospital who are relaxed or in pain. Results show good tracking behavior for poses up to 50 degrees from upright-frontal. In terms of eye location error relative to inter-ocular distance, the mean tracking error is below 9%.

Assessment of the pseudo-tracking approach for the calculation of material acceleration and pressure fields from time-resolved PIV: part I. Error propagation

NASA Astrophysics Data System (ADS)

van Gent, P. L.; Schrijer, F. F. J.; van Oudheusden, B. W.

2018-04-01

Pseudo-tracking refers to the construction of imaginary particle paths from PIV velocity fields and the subsequent estimation of the particle (material) acceleration. In view of the variety of existing and possible alternative ways to perform the pseudo-tracking method, it is not straightforward to select a suitable combination of numerical procedures for its implementation. To address this situation, this paper extends the theoretical framework for the approach. The developed theory is verified by applying various implementations of pseudo-tracking to a simulated PIV experiment. The findings of the investigations allow us to formulate the following insights and practical recommendations: (1) the velocity errors along the imaginary particle track are primarily a function of velocity measurement errors and spatial velocity gradients; (2) the particle path may best be calculated with second-order accurate numerical procedures while ensuring that the CFL condition is met; (3) least-square fitting of a first-order polynomial is a suitable method to estimate the material acceleration from the track; and (4) a suitable track length may be selected on the basis of the variation in material acceleration with track length.

The effects of delta rays on the number of particle-track traversals per cell in laboratory and space exposures

NASA Technical Reports Server (NTRS)

Cucinotta, F. A.; Nikjoo, H.; Goodhead, D. T.; Wilson, J. W. (Principal Investigator)

1998-01-01

It is a common practice to estimate the number of particle-track traversals per cell or cell nucleus as the product of the ion's linear energy transfer (LET) and cell area. This practice ignores the effects of track width due to the lateral extension of delta rays. We make estimates of the number of particle-track traversals per cell, which includes the effects of delta rays using radial cutoffs in the ionization density about an ion's track of 1 mGy and 1 cGy. Calculations for laboratory and space radiation exposures are discussed, and show that the LET approximation provides a large underestimate of the actual number of particle-track traversals per cell from high-charge and energy (HZE) ions. In light of the current interest in the mechanisms of radiation action, including signal transduction and cytoplasmic damage, these results should be of interest for radiobiology studies with HZE ions.

Detection limit of a VCO based detection chain dedicated to particles recognition and tracking

NASA Astrophysics Data System (ADS)

Coulié, K.; Rahajandraibe, W.; Aziza, H.; Micolau, G.; Vauché, R.

2018-01-01

A particle detection chain based on CMOS-SOI VCO circuit is presented. The solution is used for the recognition and the tracking of a given particle at circuit level. TCAD simulation of the detector has been performed on a 3×3 matrix of diodes based detector for particles recognition and tracking. The current response of the detector has been used for a case study in order to determine the ability of the chain to recognize an alpha particle crossing a 3×3 detection cell. The detection limit of the proposed solution is investigated and discussed in this paper.

Target motion tracking in MRI-guided transrectal robotic prostate biopsy.

PubMed

Tadayyon, Hadi; Lasso, Andras; Kaushal, Aradhana; Guion, Peter; Fichtinger, Gabor

2011-11-01

MRI-guided prostate needle biopsy requires compensation for organ motion between target planning and needle placement. Two questions are studied and answered in this paper: 1) is rigid registration sufficient in tracking the targets with an error smaller than the clinically significant size of prostate cancer and 2) what is the effect of the number of intraoperative slices on registration accuracy and speed? we propose multislice-to-volume registration algorithms for tracking the biopsy targets within the prostate. Three orthogonal plus additional transverse intraoperative slices are acquired in the approximate center of the prostate and registered with a high-resolution target planning volume. Both rigid and deformable scenarios were implemented. Both simulated and clinical MRI-guided robotic prostate biopsy data were used to assess tracking accuracy. average registration errors in clinical patient data were 2.6 mm for the rigid algorithm and 2.1 mm for the deformable algorithm. rigid tracking appears to be promising. Three tracking slices yield significantly high registration speed with an affordable error.

Track-structure simulations for charged particles.

PubMed

Dingfelder, Michael

2012-11-01

Monte Carlo track-structure simulations provide a detailed and accurate picture of radiation transport of charged particles through condensed matter of biological interest. Liquid water serves as a surrogate for soft tissue and is used in most Monte Carlo track-structure codes. Basic theories of radiation transport and track-structure simulations are discussed and differences compared to condensed history codes highlighted. Interaction cross sections for electrons, protons, alpha particles, and light and heavy ions are required input data for track-structure simulations. Different calculation methods, including the plane-wave Born approximation, the dielectric theory, and semi-empirical approaches are presented using liquid water as a target. Low-energy electron transport and light ion transport are discussed as areas of special interest.

UWB Tracking System Design for Free-Flyers

NASA Technical Reports Server (NTRS)

Ni, Jianjun; Arndt, Dickey; Phan, Chan; Ngo, Phong; Gross, Julia; Dusl, John

2004-01-01

This paper discusses an ultra-wideband (UWB) tracking system design effort for Mini-AERCam (Autonomous Extra-vehicular Robotic Camera), a free-flying video camera system under development at NASA Johnson Space Center for aid in surveillance around the International Space Station (ISS). UWB technology is exploited to implement the tracking system due to its properties, such as high data rate, fine time resolution, and low power spectral density. A system design using commercially available UWB products is proposed. A tracking algorithm TDOA (Time Difference of Arrival) that operates cooperatively with the UWB system is developed in this research effort. Matlab simulations show that the tracking algorithm can achieve fine tracking resolution with low noise TDOA data. Lab experiments demonstrate the UWB tracking capability with fine resolution.