Enhancement of satellite VLBI tracking system with capability of correlator model parameters prediction

2009 ◽  
Author(s):  
Feng-chun Shu ◽  
Yun Yu ◽  
Wei-min Zheng ◽  
Xiu-zhong Zhang
Keyword(s):  
Tracking System ◽  
Model Parameters ◽  
Correlator Model

PO-1739 Optimal threshold of model parameters for the respiratory tracking system with helical tomotherapy

2021 ◽  
Vol 161 ◽  
pp. S1461-S1462
Author(s):  
W. Okada ◽  
M. Tanooka ◽  
H. Doi ◽  
K. Sano ◽  
M. Shibata ◽  
...  
Keyword(s):  
Helical Tomotherapy ◽  
Tracking System ◽  
Optimal Threshold ◽  
Model Parameters ◽  
Respiratory Tracking

scholarly journals Unsupervised Learning in RSS-Based DFLT Using an EM Algorithm

Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5549
Author(s):  
Ossi Kaltiokallio ◽  
Roland Hostettler ◽  
Hüseyin Yiğitler ◽  
Mikko Valkama
Keyword(s):  
Em Algorithm ◽  
Expectation Maximization ◽  
Tracking System ◽  
Model Parameters ◽  
Calibration Data ◽  
Tracking Accuracy ◽  
Time Period ◽  
The Em Algorithm ◽  
Device Free ◽  
Localization And Tracking

Received signal strength (RSS) changes of static wireless nodes can be used for device-free localization and tracking (DFLT). Most RSS-based DFLT systems require access to calibration data, either RSS measurements from a time period when the area was not occupied by people, or measurements while a person stands in known locations. Such calibration periods can be very expensive in terms of time and effort, making system deployment and maintenance challenging. This paper develops an Expectation-Maximization (EM) algorithm based on Gaussian smoothing for estimating the unknown RSS model parameters, liberating the system from supervised training and calibration periods. To fully use the EM algorithm’s potential, a novel localization-and-tracking system is presented to estimate a target’s arbitrary trajectory. To demonstrate the effectiveness of the proposed approach, it is shown that: (i) the system requires no calibration period; (ii) the EM algorithm improves the accuracy of existing DFLT methods; (iii) it is computationally very efficient; and (iv) the system outperforms a state-of-the-art adaptive DFLT system in terms of tracking accuracy.

scholarly journals A Spring–Dashpot System for Modelling Lung Tumour Motion in Radiotherapy

2010 ◽  
Vol 11 (1) ◽  
pp. 13-26 ◽  
Author(s):  
P. L. Wilson ◽  
J. Meyer
Keyword(s):  
Numerical Scheme ◽  
3D Model ◽  
Tracking System ◽  
Spatial Relationship ◽  
Single Equation ◽  
Lung Tumour ◽  
Model Parameters ◽  
Optimization Routine ◽  
Parameter Ranges ◽  
Differential Equations Models

A 3D system of springs and dashpots is presented to model the motion of a lung tumour during respiration. The main guiding factor in configuring the system is the spatial relationship between abdominal and lung tumour motion. A coupled, non-dimensional triple of ordinary differential equations models the tumour motion when driven by a 3D breathing signal. Asymptotic analysis is used to reduce the system to a single equation driven by a 3D signal, in the limit of small lateral and transverse tumour motions. A numerical scheme is introduced to solve this equation, and tested over wide parameter ranges. Real clinical data is used as input to the model, and the tumour motion output is in excellent agreement with that obtained by a prototype tumour tracking system, with model parameters obtained by optimization. The fully 3D model has the potential to accurately model the motion of any lung tumour given an abdominal signal as input, with model parameters obtained from an internal optimization routine.

DYPIC - Dynamic Positioning in Ice: First Phase of Model Testing

2012 ◽  
Author(s):  
Andrea Haase ◽  
Solange van der Werff ◽  
Peter Jochmann
Keyword(s):  
Tracking System ◽  
Development Project ◽  
Model Testing ◽  
Fine Tuning ◽  
Model Parameters ◽  
Second Phase ◽  
Dynamic Positioning ◽  
The European Union ◽  
Testing Procedures ◽  
Ice Conditions

DYPIC (Dynamic Positioning in Ice) is a research and development project within the MARTEC ERA-NET project of the European Union. Its objective is to contribute to the closure of the gap between DP in open water being an industry standard, and DP in ice which has some extra challenges to tackle. Two phases of model testing in ice form the back bone of the project and are facilitated by HSVA (Hamburg Ship Model Basin, Germany). The first test phase, which was executed from May to July 2011, involved two different model ships. Both were tested in free floating mode (where the model sailed solely by its own propulsion system) and fixed mode (where the model was connected to a carriage). In the free floating mode the controlling was performed by a prototype DP system scaled to model parameters. Four different managed ice fields with systematically varied ice concentration and ice floe size were prepared in the ice tank in order to investigate the influence of the relevant parameters. Tests were executed for several velocities and headings with respect to the approaching ice floes. In the free floating case ice loads on the hull were derived from the measured loads on the thrusters. The behavior of the model ship was captured by the position and heading tracking system Qualisys and several installed video cameras. The fixed mode tests serve well as a reference measurement. The results will be used to develop a model scale DP system for ice that is adjustable to different kinds of vessels and ice conditions and eventually to develop testing procedures for the assessment of the DP performance of a vessel in managed ice. A second phase of model testing for fine tuning and benchmarking the developed system will be carried out in August 2012. Within the scope of the paper is the description of the performed tests speaking of test setup and ice conditions. Analyses of results are not covered.

scholarly journals LMODEL: A Satellite Precipitation Methodology Using Cloud Development Modeling. Part II: Validation

2009 ◽  
Vol 10 (5) ◽  
pp. 1096-1108 ◽  
Author(s):  
Kuo-lin Hsu ◽  
Tim Bellerby ◽  
S. Sorooshian
Keyword(s):  
Tracking System ◽  
Lagrangian Model ◽  
Model Parameters ◽  
Generation Model ◽  
State Variables ◽  
Radar Rainfall ◽  
Spatial Coverage ◽  
Accumulated Rainfall ◽  
Cloud Development ◽  
Rainfall Estimates

Abstract A new satellite-based rainfall monitoring algorithm that integrates the strengths of both low Earth-orbiting (LEO) and geostationary Earth-orbiting (GEO) satellite information has been developed. The Lagrangian Model (LMODEL) algorithm combines a 2D cloud-advection tracking system and a GEO data–driven cloud development and rainfall generation model with procedures to update model parameters and state variables in near–real time. The details of the LMODEL algorithm were presented in Part I. This paper describes a comparative validation against ground radar rainfall measurements of 1- and 3-h LMODEL accumulated rainfall outputs. LMODEL rainfall estimates consistently outperform accumulated 3-h microwave (MW)-only rainfall estimates, even before the more restricted spatial coverage provided by the latter is taken into account. In addition, the performance of LMODEL products remains effective and consistent between MW overpasses. Case studies demonstrate that the LMODEL provides the potential to synergize available satellite data to generate useful precipitation measurements at an hourly scale.

scholarly journals A Method of Free-Space Point-of-Regard Estimation Based on 3D Eye Model and Stereo Vision

2018 ◽  
Vol 8 (10) ◽  
pp. 1769
Author(s):  
Zijing Wan ◽  
Xiangjun Wang ◽  
Lei Yin ◽  
Kai Zhou
Keyword(s):  
Tracking System ◽  
Estimation Method ◽  
Estimation Algorithm ◽  
Model Parameters ◽  
Gaze Tracking ◽  
Calibration Process ◽  
Eye Model ◽  
Stereo Cameras ◽  
Spatial Coordinates ◽  
Tracking Device

This paper proposes a 3D point-of-regard estimation method based on 3D eye model and a corresponding head-mounted gaze tracking device. Firstly, a head-mounted gaze tracking system is given. The gaze tracking device uses two pairs of stereo cameras to capture the left and right eye images, respectively, and then sets a pair of scene cameras to capture the scene images. Secondly, a 3D eye model and the calibration process are established. Common eye features are used to estimate the eye model parameters. Thirdly, a 3D point-of-regard estimation algorithm is proposed. Three main parts of this method are summarized as follows: (1) the spatial coordinates of the eye features are directly calculated by using stereo cameras; (2) the pupil center normal is used to the initial value for the estimation of optical axis; (3) a pair of scene cameras are used to solve the actual position of the objects being watched in the calibration process, and the calibration for the proposed eye model does not need the assistance of the light source. Experimental results show that the proposed method can output the coordinates of 3D point-of-regard more accurately.

scholarly journals Tracking with (Un)Certainty

2020 ◽  
Vol 8 (1) ◽  
pp. 10
Author(s):  
Abe D. Hofman ◽  
Matthieu J. S. Brinkhuis ◽  
Maria Bolsinova ◽  
Jonathan Klaiber ◽  
Gunter Maris ◽  
...  
Keyword(s):  
Adaptive Learning ◽  
Large Scale ◽  
Item Difficulty ◽  
Tracking System ◽  
Personalized Learning ◽  
Standard Errors ◽  
Model Parameters ◽  
Learning Effects ◽  
Elo Rating System ◽  
Statistical Issues

One of the highest ambitions in educational technology is the move towards personalized learning. To this end, computerized adaptive learning (CAL) systems are developed. A popular method to track the development of student ability and item difficulty, in CAL systems, is the Elo Rating System (ERS). The ERS allows for dynamic model parameters by updating key parameters after every response. However, drawbacks of the ERS are that it does not provide standard errors and that it results in rating variance inflation. We identify three statistical issues responsible for both of these drawbacks. To solve these issues we introduce a new tracking system based on urns, where every person and item is represented by an urn filled with a combination of green and red marbles. Urns are updated, by an exchange of marbles after each response, such that the proportions of green marbles represent estimates of person ability or item difficulty. A main advantage of this approach is that the standard errors are known, hence the method allows for statistical inference, such as testing for learning effects. We highlight features of the Urnings algorithm and compare it to the popular ERS in a simulation study and in an empirical data example from a large-scale CAL application.

scholarly journals Unifying account of visual motion and position perception

2015 ◽  
Vol 112 (26) ◽  
pp. 8142-8147 ◽  
Author(s):  
Oh-Sang Kwon ◽  
Duje Tadin ◽  
David C. Knill
Keyword(s):  
Object Tracking ◽  
Visual Experience ◽  
Visual Motion ◽  
Tracking System ◽  
Realistic Model ◽  
Model Parameters ◽  
Slow Speed ◽  
Object Position ◽  
System A ◽  
Tracking Model

Despite growing evidence for perceptual interactions between motion and position, no unifying framework exists to account for these two key features of our visual experience. We show that percepts of both object position and motion derive from a common object-tracking system—a system that optimally integrates sensory signals with a realistic model of motion dynamics, effectively inferring their generative causes. The object-tracking model provides an excellent fit to both position and motion judgments in simple stimuli. With no changes in model parameters, the same model also accounts for subjects’ novel illusory percepts in more complex moving stimuli. The resulting framework is characterized by a strong bidirectional coupling between position and motion estimates and provides a rational, unifying account of a number of motion and position phenomena that are currently thought to arise from independent mechanisms. This includes motion-induced shifts in perceived position, perceptual slow-speed biases, slowing of motions shown in visual periphery, and the well-known curveball illusion. These results reveal that motion perception cannot be isolated from position signals. Even in the simplest displays with no changes in object position, our perception is driven by the output of an object-tracking system that rationally infers different generative causes of motion signals. Taken together, we show that object tracking plays a fundamental role in perception of visual motion and position.

Instrumental and Ideological Union Commitment: Longitudinal Assessment of Construct Validity

2001 ◽  
Vol 17 (2) ◽  
pp. 98-111 ◽  
Author(s):  
Anders Sjöberg ◽  
Magnus Sverke
Keyword(s):  
Construct Validity ◽  
Temporal Stability ◽  
Strong Support ◽  
Internal Consistency Reliability ◽  
Measurement Model ◽  
Two Dimensions ◽  
Model Parameters ◽  
Longitudinal Assessment ◽  
Union Commitment ◽  
Union Participation

Summary: Previous research has identified instrumentality and ideology as important aspects of member attachment to labor unions. The present study evaluated the construct validity of a scale designed to reflect the two dimensions of instrumental and ideological union commitment using a sample of 1170 Swedish blue-collar union members. Longitudinal data were used to test seven propositions referring to the dimensionality, internal consistency reliability, and temporal stability of the scale as well as postulated group differences in union participation to which the scale should be sensitive. Support for the hypothesized factor structure of the scale and for adequate reliabilities of the dimensions was obtained and was also replicated 18 months later. Tests for equality of measurement model parameters and test-retest correlations indicated support for the temporal stability of the scale. In addition, the results were consistent with most of the predicted differences between groups characterized by different patterns of change/stability in union participation status. The study provides strong support for the construct validity of the scale and indicates that it can be used in future theory testing on instrumental and ideological union commitment.

An eye tracking system for analysis of pilots' scan paths.

1997 ◽  
Author(s):  
Paul A. Wetzel ◽  
Gretchen Krueger-Anderson ◽  
Christine Poprik ◽  
Peter Bascom
Keyword(s):  
Eye Tracking ◽  
Tracking System ◽  
Scan Paths
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