Tracking Procedure Research Articles

Linear Laser Scanning Measurement Method Tracking by a Binocular Vision

The 3D scanning of a freeform structure relies on the laser probe and the localization system. The localization system, determining the effect of the point cloud reconstruction, will generate positioning errors when the laser probe works in complex paths with a fast speed. To reduce the errors, in this paper, a linear laser scanning measurement method is proposed based on binocular vision calibration. A simple and effective eight-point positioning marker attached to the scanner is proposed to complete the positioning and tracking procedure. Based on this, the method of marked point detection based on image moment and the principle of global coordinate system calibration are introduced in detail. According to the invariance principle of space distance, the corresponding points matching method between different coordinate systems is designed. The experimental results show that the binocular vision system can complete localization under different light intensities and complex environments, and that the repeated translation error of the binocular vision system is less than 0.22 mm, while the rotation error is less than 0.15°. The repeated error of the measurement system is less than 0.36 mm, which can meet the requirements of the 3D shape measurement of the complex workpiece.

Tracking procedure outcomes using Epic SmartText and SmartData Elements following minor dermatologic procedures in the ambulatory setting

To the Editor: In 2017, the Department of Dermatology, Duke University, employed a template-generating electronic health record tool to collect variables related to surgical site infections (SSIs) following minor dermatologic procedures, including shave biopsies, punch biopsies, excisions, and electrodessication and curettages in the ambulatory setting. This system uses SmartText (a registered trademark of Epic Systems Corporation) with embedded SmartData Elements (SDEs) through Epic-based electronic health records. Our initiative aimed at improving the documentation of adverse outcomes, such as SSIs, wound bleeding, and wound dehiscence, reducing inconsistency in charting, and facilitating tracking in compliance with the Joint Commission on Accreditation of Healthcare Organizations, specifically regarding the Ongoing Professional Practice Evaluation and SSI tracking standards. 1 What are the key elements needed to meet the ongoing professional practice evaluation (OPPE) requirements? The Joint Commission. https://www.jointcommission.org/standards/standard-faqs/critical-access-hospital/medical-staff-ms/000001500/Date accessed: February 1, 2022 Google Scholar ,2 Surgical site infections (SSI): surveillance and resources. The Joint Commission. Posted September 25, 2017. Accessed February 1, 2022. https://www.jointcommission.org/standards/standard-faqs/critical-access-hospital/infection-prevention-and-control-ic/000002155/ Google Scholar Additionally, our SmartText simplifies documentation at postprocedural follow-up appointments and enables rapid, user-friendly data entry and analysis, offering a springboard for research projects while minimizing manual data extraction requirements.

TRamWAy: mapping physical properties of individual biomolecule random motion in large-scale single-particle tracking experiments.

Single-molecule localization microscopy allows studying the dynamics of biomolecules in cells and resolving the biophysical properties of the molecules and their environment underlying cellular function. With the continuously growing amount of data produced by individual experiments, the computational cost of quantifying these properties is increasingly becoming the bottleneck of single-molecule analysis. Mining these data requires an integrated and efficient analysis toolbox. We introduce TRamWAy, a modular Python library that features: (i) a conservative tracking procedure for localization data, (ii) a range of sampling techniques for meshing the spatio-temporal support of the data, (iii) computationally efficient solvers for inverse models, with the option of plugging in user-defined functions and (iv) a collection of analysis tools and a simple web-based interface. TRamWAy is a Python library and can be installed with pip and conda. The source code is available at https://github.com/DecBayComp/TRamWAy.

Efficient quantile tracking using an oracle

Concept drift is a well-known issue that arises when working with data streams. In this paper, we present a procedure that allows a quantile tracking procedure to cope with concept drift. We suggest using expected quantile loss, a popular loss function in quantile regression, to monitor the quantile tracking error, which, in turn, is used to efficiently adapt to concept drift. The suggested procedures adapt efficiently to concept drift, and the tracking performance is close to theoretically optimal. The procedures were further applied to three real-life streaming data sets related to Twitter event detection, activity recognition, and stock trading. The results show that the procedures are efficient at adapting to concept drift, thereby documenting the real-world applicability of the procedures. We further used asymptotic theory from statistics to show the appealing theoretical property that, if the data stream distribution is stationary over time, the procedures converge to the true quantile.

A Unified 3D Beam Training and Tracking Procedure for Terahertz Communication

Terahertz (THz) communication is considered as an attractive way to overcome the bandwidth bottleneck and satisfy the ever-increasing capacity demand in the future. Due to the high directivity and propagation loss of THz waves, a massive MIMO system using beamforming is envisioned as a promising technology in THz communication to realize high-gain and directional transmission. However, pilots, which are the fundamentals for many beamforming schemes, are challenging to be accurately detected in the THz band owing to the severe propagation loss. In this paper, a unified 3D beam training and tracking procedure is proposed to effectively realize the beamforming in THz communications, by considering the line-of-sight (LoS) propagation. In particular, a novel quadruple-uniform planar array (QUPA) architecture is analyzed to enlarge the signal coverage, increase the beam gain, and reduce the beam squint loss. Then, a new 3D grid-based (GB) beam training is developed with low complexity, including the design of the 3D codebook and training protocol. Finally, a simple yet effective grid-based hybrid (GBH) beam tracking is investigated to support THz beamforming in an efficient manner. The communication framework based on this procedure can dynamically trigger beam training/tracking depending on the real-time quality of service. Numerical results are presented to demonstrate the superiority of our proposed beam training and tracking over the benchmark methods.

Comparative Assessment between Five Control Techniques to Optimize the Maximum Power Point Tracking Procedure for PV Systems

Solar photovoltaic (PV) energy production is important in reducing global energy crises since it is transportable, scalable, and highly customizable dependent on the needs of the industry or end-user. In addition, compared to other renewable resources, photovoltaic systems can produce electricity without moving parts and have a long lifespan. Nevertheless, solar photovoltaic (PV) systems provide intermittent output electricity with a nonlinear output voltage. Due to this intermittent availability, PV installations are facing significant challenges. As a result, in PV power systems, a Maximum Power Point Tracker (MPPT), a power extraction mechanism, is required to assure maximum power delivery at any given moment. The main objective of this work is to study the MPPT method of extracting the maximum power from photovoltaic modules under different solar irradiation and temperatures. Several MPPT methods have been developed for photovoltaic systems to achieve MPP, depending on weather conditions and applications, ranging from simple to more complex methods. Among these methods, five techniques have been presented and compared that are P&O perturbation and observation method, INC incremental conductance method, the ANN neural network method, the open circuit voltage based neural network method FVCO, and the neural network method at the base of FCC (short circuit current).

"Anosmia" the mysterious collateral damage of COVID-19.

COVID-19 pandemic spreads worldwide, with more than 100 million positive cases and more than 2 million deaths. From the beginning of the COVID-19 pandemic, several otolaryngologists described many cases of a sudden loss of smell (anosmia) associated with the disease with or without additional symptoms. Anosmia is often the first and sometimes the only sign in the asymptomatic carriers of COVID-19. Still, this disorder is underestimated, and it is not life-threatening. However, it significantly decreases the quality of life. This olfactory dysfunction continues in several cases even after the nasopharyngeal swab was negative. The occurrence of anosmia can be used as a screening tool for COVID-19 patients and can be used to identify these patients to accomplish the isolation and tracking procedures. In this review, we highlighted the possible mechanisms of anosmia in COVID-19 patients, major pathologies and features of anosmia, implications of anosmia in early diagnosis of COVID-19, evaluation of the smell function during COVID-19, and management and treatment options of COVID-19 anosmia.

SAR Offset Tracking Based on Feature Points

The offset tracking approach has been widely used to measure large ground deformation as a complement to Interferometric Synthetic Aperture Radar (InSAR) when its coherence is poor and/or the deformation gradient is large. The standard offset tracking procedures estimate deformation of tie points, which are uniformly distributed over two SAR images, resulting in many unsatisfactory measurements. In this paper, we propose a feature point offset tracking (FPOT) procedure to overcome the limitation of the standard method. First, we identify feature points using the Speeded Up Robust Feature (SURF) algorithm. Improper feature points are masked using external land coverage information like water coverages. Then, we use the standard cross-correlation algorithm to find offsets of the remaining feature points between reference and secondary images. The offset outliers are removed using a quadtree filtering. Finally, the resultant deformation field is generated by removing systematic offsets estimated with far-field feature points. We assess the effectiveness of our proposed procedure using the 2016 Mw 7.8 Kaikōura earthquake in New Zealand. In far-field where deformation is expected to be negligible, histograms of offset distribution show that the root-mean-square error (RMSE) is decreased from 0.07 pixels to 0.02–0.03 pixels for regular points and feature points, respectively, after quadtree filtering. The RMSE between our FPOT-derived offsets and GPS measurements are 0.14 and 0.48 m for range and azimuth offsets, respectively. The results show that our proposed procedure can significantly improve the efficiency, accuracy, and reliability with respect to the standard regular point offset tracking (RPOT).

The NICA Complex and the MPD experiment at JINR: status and physics potential

The Multi-Purpose Detector is under construction at the Joint Institute for Nuclear Research in Dubna, as part of the NICA Accelerator Complex. The MPD Collaboration aims to study the phase diagram of QCD matter at maximum baryonic density, determine the nature of the phase transition between the deconfined and hadronic matter and search for the critical point. The combination of significant luminosity at NICA, collider geometry of the experiment and collision energies √SNN spanning the range of 4 to 11 GeV, where the transition from baryon to meson dominated matter is expected will allow MPD to provide unique insight into these questions. The status of the assembly of the detector in MPD Hall, as well as the progress in the production of MPD subdetectors will be reported on. The design physics performance of the detector will be discussed with the emphasis on the measurements in the strangeness sector. Tracking and particle identification procedures will enable precise determination of spectra of identified hadrons, including hyperons and hypernuclei, with the possibility of differential measurements and total yield extraction. The quality of directed and elliptic flow determination will be discussed, with comparison to model expectations. The sensitivity of event-by-event fluctuations to the nature of the phase transition and the presence of a critical point will be given. The femtoscopic analysis for charged pions and kaons has shown sensitivity to first order and cross-over phase transitions in EoS seen for the vHLLE model. All those studies will be put in context of addressing outstanding questions on the properties of the region of the QCD phase diagram probed by heavy-ion collisions in the NICA energy range.

Object Tracking-Based “Follow-Me” Unmanned Aerial Vehicle (UAV) System

The applications of information technology (IT) tools and techniques have, over the years, simplified complex problem solving procedures. But the power of automation is inhibited by the technicality in manning advanced equipment. To this end, tools deliberately combating this inhibition and advancing technological growth are the Unmanned Aerial Vehicles (UAVs). UAVs are rapidly taking over major industries such as logistics, security, and cinematography. Among others, this is a very efficient way of carrying out missions unconventional to humans. An application area of this technology is the local film industry which is not producing quality movies primarily due to the lack of technical know-how in utilizing these systems. This study therefore aim to devise an autonomous object tracking UAV system that would eliminate the complex procedure involved in stabilizing an aerial camera (aerial bot) midair and promote the creation of quality aerial video shooting. The study adopted Unified Modeling Language (UML) tools in modeling the system’s functionality. The traditional Server-Client model architecture was adopted. The OpenCV library employed proved highly efficient in aiding the tracking procedure. The system provided a usable web controller which provides easy interaction between the pilot and the drone. Conclusively, investments in UAVs would enhance creation of quality graphic contents.

Extendable Multiple Nodes Recurrent Tracking Framework With RTU+.

Recently, tracking-by-detection has become a popular paradigm in Multiple-object tracking (MOT) for its concise pipeline. Many current works first associate the detections to form track proposals and then score proposalns by manual functions to select the best. However, long-term tracking information is lost in this way due to detection failure or heavy occlusion. In this paper, the Extendable Multiple Nodes Tracking framework (EMNT) is introduced to model the association. Instead of detections, EMNT creates four basic types of nodes including correct, false, dummy and termination to generally model the tracking procedure. Further, we propose a General Recurrent Tracking Unit (RTU++) to score track proposals by capturing long-term information. In addition, we present an efficient generation method of simulated tracking data to overcome the dilemma of limited available data in MOT. The experiments show that our methods achieve state-of-the-art performance on MOT17, MOT20 and HiEve benchmarks. Meanwhile, RTU++ can be flexibly plugged into other trackers such as MHT, and bring significant improvements. The additional experiments on MOTS20 and CTMC-v1 also demonstrate the generalization ability of RTU++ trained by simulated data in various scenarios.

Detecting and Evaluating Dust‐Events in North China With Ground Air Quality Data

AbstractWe propose a dust‐event detection and tracking procedure based on air quality data from the ground monitoring network by detecting temporal and spatial change‐points in PM10 concentration. It supplements the existing remote sensing based approach with high temporal resolution and better weather adaptivity. Applications of the procedure on the labeled data showed its having high discriminating power for dust events, pollution events, and clean periods. Our study finds changing correlation patterns between PM10 and other air pollutants at the start of the dust events, which are utilized to enhance the discriminating power of the dust‐event detection procedure. The detection and tracking procedure allows the construction of transport networks of the dust‐events as well as the identification of the source regions and the transportation pattern, and assess the intensity and severity of the dust‐events in North China. Our analysis find the dust‐events contributed to 23.3%–34.6% for PM10 and 18.2–33.2% for PM2.5 in the source regions and 2.0%–7.3% and 0.8%–4.0%, respectively, in the down‐stream provinces in the spring season from 2015 to 2020.

Nutritional Risk Screening (NRS 2002) as a tool to predict clinical outcomes in hospitalized patients: a literature review

The presence of malnutrition in hospitalized patients is prevalent and studies show its association with a higher incidence of complications, mortality, length of stay, costs, and increased frequency of hospital readmission. Routine use of simple tracking procedures is recommended. Nutritional screening detects individuals who are malnourished or at risk of developing malnutrition, and who can receive specific nutritional support. Nutritional Risk Screening (NRS 2002) is a nutritional screening method recommended by the European Society for Clinical and Metabolism (ESPEN) and identifies the risk of developing malnutrition in hospitalized patients. The aim of this paper is to review the literature on the NRS screening method (2002) and its relationship with clinical outcomes in hospitalized patients.

Combination of Aerial, Satellite, and UAV Photogrammetry for Quantifying Rock Glacier Kinematics in the Dry Andes of Chile (30°S) Since the 1950s

The diachronic analysis of aerial and satellite imagery, uncrewed aerial vehicle (UAV) andin situsurveys obtained between 1956 and 2019 are employed to analyse landform surface kinematics for the Tapado site located in the Dry Andes of Chile. A feature tracking procedure was used between series of orthorectified and co-registered images to calculate surface velocities on several ice-debris landforms, including rock glaciers and debris-covered glaciers. For the active rock glaciers, the results exhibit typical viscous flow, though local destabilisation process seems to occur, increased velocities since 2000 (>1 m/yr) and terminus advance. Nevertheless, the debris-covered glaciers displays heterogeneous spatial patterns of surface velocities, together with collapse (downwasting) associated with the development of thermokarst depressions and supraglacial ponds. Our findings show that surface kinematics and multitemporal observations derived from different sensors are valuable tools for differentiating between glacial and periglacial features. The pluri-decadal time series since 1956 constitute a unique dataset for documenting the surface kinematics of creeping mountain permafrost in the Southern Hemisphere. The approach developed in this work offers a way forward to reconstruct the recent behaviour of glacial and periglacial features in the Andes, where archival aerial photographs are available but have not previously been processed rigorously to obtain an accurate assessment of landform kinematics.

UAV-Assisted Underwater Sensor Networks Using RF and Optical Wireless Links

Underwater sensor networks (UWSNs) are of interest to gather data from underwater sensor nodes (SNs) and deliver information to a terrestrial access point (AP) in the uplink transmission, and transfer data from the AP to the SNs in the downlink transmission. In this paper, we investigate a triple-hop UWSN in which autonomous underwater vehicle (AUV) and unmanned aerial vehicle (UAV) relays enable end-to-end communications between the SNs and the AP. It is assumed that the SN–AUV, AUV–UAV, and UAV–AP links are deployed by underwater optical communication (UWOC), free-space optic (FSO), and radio frequency (RF) technologies, respectively. Two scenarios are proposed for the FSO uplink and downlink transmissions between the AUV and the UAV, subject to water-to-air and air-to-water interface impacts; direct transmission scenario (DTS) and retro-reflection scenario (RRS). After providing the channel models and their statistics, the UWSN's outage probability and average bit error rate (BER) are computed. Besides, a tracking procedure is proposed to set up reliable and stable AUV– UAV FSO communications. Through numerical results, it is concluded that the RSS scheme outperforms the DTS one with about 200% (32%) and 80% (17%) better outage probability (average BER) in the uplink and downlink, respectively. It is also shown that the tracking procedure provides on average 480% and 170% improvements in the network's outage probability and average BER, respectively, compared to poorly aligned FSO conditions. The results are verified by applying Monte-Carlo simulations.

Solution Irregularity Remediation for Spatial Discretization Error Estimation for SN Transport Solutions

The discrete ordinates linear Boltzmann transport equation is typically solved in its spatially discretized form, incurring spatial discretization error. Quantification of this error for purposes such as adaptive mesh refinement or error analysis requires an a posteriori estimator, which utilizes the numerical solution to the spatially discretized equation to compute an estimate. Because the quality of the numerical solution informs the error estimate, irregularities, present in the true solution for any realistic problem configuration, tend to cause the largest deviation in the error estimate vis-a-vis the true error. In this paper, an analytical partial singular characteristic tracking (pSCT) procedure for reducing the estimator’s error is implemented within our novel residual source estimator for a zeroth-order discontinuous Galerkin scheme, at the additional cost of a single inner iteration. A metric-based evaluation of the pSCT scheme versus the standard residual source estimator is performed over the parameter range of a Method of Manufactured Solutions test suite. The pSCT scheme generates near-ideal accuracy in the estimate in problems where the dominant source of the estimator’s error is the solution irregularity, namely, problems where the true solution is discontinuous and problems where the true solution’s first derivative is discontinuous and the scattering ratio is low. In problems where the scattering ratio is high and the true solution is discontinuous in the first derivative, the error in the scattering source, which is not converged by the pSCT scheme, is greater than the error incurred due to the irregularity. Ultimately, a pSCT scheme is judged to be useful for error estimation in problems where the computational cost of the scheme is justified. In the presence of many irregularities, such a scheme may be intractable for general use, but in benchmarks, as an analytical tool, or in problems that have nondissipative discontinuities, the scheme may prove invaluable.

A Probabilistic Particle Tracking Framework for Guided and Brownian Motion Systems with High Particle Densities

This paper presents a new framework for particle tracking based on a Gaussian Mixture Model (GMM). It is an extension of the state-of-the-art iterative reconstruction of individual particles by a continuous modeling of the particle trajectories considering the position and velocity as coupled quantities. The proposed approach includes an initialization and a processing step. In the first step, the velocities at the initial points are determined after iterative reconstruction of individual particles of the first four images to be able to generate the tracks between these initial points. From there on, the tracks are extended in the processing step by searching for and including new points obtained from consecutive images based on continuous modeling of the particle trajectories with a Gaussian Mixture Model. The presented tracking procedure allows to extend existing trajectories interactively with low computing effort and to store them in a compact representation using little memory space. To demonstrate the performance and the functionality of this new particle tracking approach, it is successfully applied to a synthetic turbulent pipe flow, to the problem of observing particles corresponding to a Brownian motion (e.g., motion of cells), as well as to problems where the motion is guided by boundary forces, e.g., in the case of particle tracking velocimetry of turbulent Rayleigh–Bénard convection.

Computation of erosion in a hydro turbine

PurposeThis study aims to investigate the trajectories of sand particles and erosion wear in a hydraulic turbine model.Design/methodology/approachThe Lagrangian-based approach is used to track large numbers of sand particles and determine their impact through the hydro turbine components. The tracking procedure includes the stochastic eddy interaction model and the squeeze film effect. The number of particles, sizes and release positions are conformed to the particle concentration and size distribution. The impact locations, frequency and conditions of impacts are used to estimate the erosion rates and thereby the eroded mass from the distributor vane and the rotor blade and their deteriorated geometry.FindingsThe patterns of erosion in the stationary and rotating parts differ significantly and the effect of the initial position of the runner blade is elucidated. The distributor vane is characterized by a widespread of erosion over the pressure side. Typically, the surface beyond the throat and the root and tip junctions are the regions prone to erosion wear. The entry region of the runner blade is subject to a high number of impacts resulting in high erosion rates visible from the forepart of the blade pressure side.Practical implicationsThe erosion patterns and geometry deterioration may serve to evaluate the drop in the hydraulic performance and to select the appropriate surface coating to extend the lifetime of the turbomachinery parts and reduce the maintenance cost.Originality/valueErosion developments reveal a strong dependence on the blade position against the distributor vane and the particle size and concentration level.

Multi object tracking using gradient-based learning model in video-surveillance

On accomplishing an efficacious object tracking, the activity of an object concerned becomes notified in a forthright manner. An accurate form of object tracking task necessitates a robust object tracking procedures irrespective of hardware assistance. Such approaches inferred a vast computational complexity to track an object with high accuracy in a stipulated amount of processing time. On the other hand, the tracking gets affected owing to the existence of varied quality diminishing factors such as occlusion, illumination changes, shadows etc., In order to rectify all these inadequacies in tracking an object, a novel background normalization procedure articulated on the basis of a textural pattern is proposed in this paper. After preprocessing an acquired image, employment of an Environmental Succession Prediction algorithm for discriminating disparate background environment by background clustering approach have been accomplished. Afterward, abstract textural characterizations through utilization of a Probability based Gradient Pattern (PGP) approach for recognizing the similarity between patterns obtained so far. Comparison between standardized frame obtained in prior and those processed patterns detects the motion exposed by an object and the object concerned gets identified within a blob. Hence, the system is resistant towards illumination variations. These illumination variation was interpreted in object tracking residing within a dynamic background. Devised approach certainly outperforms other object tracking methodologies like Group Target Tracking (GTT), ViPER-GT, grabcut, snakes in terms of accuracy and average time. Proposed PGP-based pattern texture analysis is compared with Gamifying Video Object (GVO) approach and hence, it evidently outperforms in terms of precision, recall and F1 measure.

Detection and tracking for the awareness of surroundings of a ship based on deep learning

Abstract To prevent maritime accidents, it is crucial to be aware of the surrounding environment near ships. The images recorded by a camera mounted on a ship could be used for the awareness of other ships surrounding it. In this study, ship awareness was performed using three procedures: detection, localization, and tracking. Initially, ship detection was performed using the deep learning-based detection model, YOLO (You Only Look Once) v3, based on the camera image. A virtual image dataset was constructed using Unity to overcome the difficulty of obtaining camera images onboard with various sizes of ships, and to improve the detection performance. This was followed by the localization procedure in which the position of the horizon on the image was calculated using the orientation information from the ship. Subsequently, the position of the detected ship in the spatial coordinate system was calculated using the horizon information. Following this, the position, course over ground, and speed over ground of the target ships were tracked in the time domain using the extended Kalman filter. A deep learning model that determines the heading of the ship in the image was proposed to utilize abundant information of cameras, and it was used to set the initial value of the Kalman filter. Finally, the proposed method for the awareness of ships was validated using an actual video captured from a camera installed on an actual ship with various encountering scenarios. The tracking results were compared with actual automatic identification system data obtained from other ships. As a result, the entire detection, localization, and tracking procedures showed good performance, and it was estimated that the proposed method for the awareness of the surroundings of a ship, based on camera images, could be used in the future.