A wavelet-based Gaussian method for energy dispersive X-ray fluorescence spectrum.

PubMed

Liu, Pan; Deng, Xiaoyan; Tang, Xin; Shen, Shijian

2017-05-01

This paper presents a wavelet-based Gaussian method (WGM) for the peak intensity estimation of energy dispersive X-ray fluorescence (EDXRF). The relationship between the parameters of Gaussian curve and the wavelet coefficients of Gaussian peak point is firstly established based on the Mexican hat wavelet. It is found that the Gaussian parameters can be accurately calculated by any two wavelet coefficients at the peak point which has to be known. This fact leads to a local Gaussian estimation method for spectral peaks, which estimates the Gaussian parameters based on the detail wavelet coefficients of Gaussian peak point. The proposed method is tested via simulated and measured spectra from an energy X-ray spectrometer, and compared with some existing methods. The results prove that the proposed method can directly estimate the peak intensity of EDXRF free from the background information, and also effectively distinguish overlap peaks in EDXRF spectrum.

Nonparametric change point estimation for survival distributions with a partially constant hazard rate.

PubMed

Brazzale, Alessandra R; Küchenhoff, Helmut; Krügel, Stefanie; Schiergens, Tobias S; Trentzsch, Heiko; Hartl, Wolfgang

2018-04-05

We present a new method for estimating a change point in the hazard function of a survival distribution assuming a constant hazard rate after the change point and a decreasing hazard rate before the change point. Our method is based on fitting a stump regression to p values for testing hazard rates in small time intervals. We present three real data examples describing survival patterns of severely ill patients, whose excess mortality rates are known to persist far beyond hospital discharge. For designing survival studies in these patients and for the definition of hospital performance metrics (e.g. mortality), it is essential to define adequate and objective end points. The reliable estimation of a change point will help researchers to identify such end points. By precisely knowing this change point, clinicians can distinguish between the acute phase with high hazard (time elapsed after admission and before the change point was reached), and the chronic phase (time elapsed after the change point) in which hazard is fairly constant. We show in an extensive simulation study that maximum likelihood estimation is not robust in this setting, and we evaluate our new estimation strategy including bootstrap confidence intervals and finite sample bias correction.

A Simulation Study Comparison of Bayesian Estimation with Conventional Methods for Estimating Unknown Change Points

ERIC Educational Resources Information Center

Wang, Lijuan; McArdle, John J.

2008-01-01

The main purpose of this research is to evaluate the performance of a Bayesian approach for estimating unknown change points using Monte Carlo simulations. The univariate and bivariate unknown change point mixed models were presented and the basic idea of the Bayesian approach for estimating the models was discussed. The performance of Bayesian…

Lung motion estimation using dynamic point shifting: An innovative model based on a robust point matching algorithm.

PubMed

Yi, Jianbing; Yang, Xuan; Chen, Guoliang; Li, Yan-Ran

2015-10-01

Image-guided radiotherapy is an advanced 4D radiotherapy technique that has been developed in recent years. However, respiratory motion causes significant uncertainties in image-guided radiotherapy procedures. To address these issues, an innovative lung motion estimation model based on a robust point matching is proposed in this paper. An innovative robust point matching algorithm using dynamic point shifting is proposed to estimate patient-specific lung motion during free breathing from 4D computed tomography data. The correspondence of the landmark points is determined from the Euclidean distance between the landmark points and the similarity between the local images that are centered at points at the same time. To ensure that the points in the source image correspond to the points in the target image during other phases, the virtual target points are first created and shifted based on the similarity between the local image centered at the source point and the local image centered at the virtual target point. Second, the target points are shifted by the constrained inverse function mapping the target points to the virtual target points. The source point set and shifted target point set are used to estimate the transformation function between the source image and target image. The performances of the authors' method are evaluated on two publicly available DIR-lab and POPI-model lung datasets. For computing target registration errors on 750 landmark points in six phases of the DIR-lab dataset and 37 landmark points in ten phases of the POPI-model dataset, the mean and standard deviation by the authors' method are 1.11 and 1.11 mm, but they are 2.33 and 2.32 mm without considering image intensity, and 1.17 and 1.19 mm with sliding conditions. For the two phases of maximum inhalation and maximum exhalation in the DIR-lab dataset with 300 landmark points of each case, the mean and standard deviation of target registration errors on the 3000 landmark points of ten cases by the authors' method are 1.21 and 1.04 mm. In the EMPIRE10 lung registration challenge, the authors' method ranks 24 of 39. According to the index of the maximum shear stretch, the authors' method is also efficient to describe the discontinuous motion at the lung boundaries. By establishing the correspondence of the landmark points in the source phase and the other target phases combining shape matching and image intensity matching together, the mismatching issue in the robust point matching algorithm is adequately addressed. The target registration errors are statistically reduced by shifting the virtual target points and target points. The authors' method with consideration of sliding conditions can effectively estimate the discontinuous motion, and the estimated motion is natural. The primary limitation of the proposed method is that the temporal constraints of the trajectories of voxels are not introduced into the motion model. However, the proposed method provides satisfactory motion information, which results in precise tumor coverage by the radiation dose during radiotherapy.

Heterogeneous Data Fusion Method to Estimate Travel Time Distributions in Congested Road Networks

PubMed Central

Lam, William H. K.; Li, Qingquan

2017-01-01

Travel times in congested urban road networks are highly stochastic. Provision of travel time distribution information, including both mean and variance, can be very useful for travelers to make reliable path choice decisions to ensure higher probability of on-time arrival. To this end, a heterogeneous data fusion method is proposed to estimate travel time distributions by fusing heterogeneous data from point and interval detectors. In the proposed method, link travel time distributions are first estimated from point detector observations. The travel time distributions of links without point detectors are imputed based on their spatial correlations with links that have point detectors. The estimated link travel time distributions are then fused with path travel time distributions obtained from the interval detectors using Dempster-Shafer evidence theory. Based on fused path travel time distribution, an optimization technique is further introduced to update link travel time distributions and their spatial correlations. A case study was performed using real-world data from Hong Kong and showed that the proposed method obtained accurate and robust estimations of link and path travel time distributions in congested road networks. PMID:29210978

Heterogeneous Data Fusion Method to Estimate Travel Time Distributions in Congested Road Networks.

PubMed

Shi, Chaoyang; Chen, Bi Yu; Lam, William H K; Li, Qingquan

2017-12-06

Travel times in congested urban road networks are highly stochastic. Provision of travel time distribution information, including both mean and variance, can be very useful for travelers to make reliable path choice decisions to ensure higher probability of on-time arrival. To this end, a heterogeneous data fusion method is proposed to estimate travel time distributions by fusing heterogeneous data from point and interval detectors. In the proposed method, link travel time distributions are first estimated from point detector observations. The travel time distributions of links without point detectors are imputed based on their spatial correlations with links that have point detectors. The estimated link travel time distributions are then fused with path travel time distributions obtained from the interval detectors using Dempster-Shafer evidence theory. Based on fused path travel time distribution, an optimization technique is further introduced to update link travel time distributions and their spatial correlations. A case study was performed using real-world data from Hong Kong and showed that the proposed method obtained accurate and robust estimations of link and path travel time distributions in congested road networks.

Comparison of dew point temperature estimation methods in Southwestern Georgia

Treesearch

Marcus D. Williams; Scott L. Goodrick; Andrew Grundstein; Marshall Shepherd

2015-01-01

Recent upward trends in acres irrigated have been linked to increasing near-surface moisture. Unfortunately, stations with dew point data for monitoring near-surface moisture are sparse. Thus, models that estimate dew points from more readily observed data sources are useful. Daily average dew temperatures were estimated and evaluated at 14 stations in...

Ocular and Densimeter Estimates of Understory Foliar Cover in Forests of Alabama

Treesearch

Thomas W. Popham; Roger L. Baker

1987-01-01

Foliar cover estimates of woody and herbaceous understory vegetation were done on twenty l-m2 plots for a variety of forest types in Alabama. The methods of estimation were ocular, loop-densimeter assisted ocular, and point frame. The point frame was used as the standard and the other two methods were compared using chi-square. Some ocular...

Estimation of the auto frequency response function at unexcited points using dummy masses

NASA Astrophysics Data System (ADS)

Hosoya, Naoki; Yaginuma, Shinji; Onodera, Hiroshi; Yoshimura, Takuya

2015-02-01

If structures with complex shapes have space limitations, vibration tests using an exciter or impact hammer for the excitation are difficult. Although measuring the auto frequency response function at an unexcited point may not be practical via a vibration test, it can be obtained by assuming that the inertia acting on a dummy mass is an external force on the target structure upon exciting a different excitation point. We propose a method to estimate the auto frequency response functions at unexcited points by attaching a small mass (dummy mass), which is comparable to the accelerometer mass. The validity of the proposed method is demonstrated by comparing the auto frequency response functions estimated at unexcited points in a beam structure to those obtained from numerical simulations. We also consider random measurement errors by finite element analysis and vibration tests, but not bias errors. Additionally, the applicability of the proposed method is demonstrated by applying it to estimate the auto frequency response function of the lower arm in a car suspension.

Objectivity and validity of EMG method in estimating anaerobic threshold.

PubMed

Kang, S-K; Kim, J; Kwon, M; Eom, H

2014-08-01

The purposes of this study were to verify and compare the performances of anaerobic threshold (AT) point estimates among different filtering intervals (9, 15, 20, 25, 30 s) and to investigate the interrelationships of AT point estimates obtained by ventilatory threshold (VT) and muscle fatigue thresholds using electromyographic (EMG) activity during incremental exercise on a cycle ergometer. 69 untrained male university students, yet pursuing regular exercise voluntarily participated in this study. The incremental exercise protocol was applied with a consistent stepwise increase in power output of 20 watts per minute until exhaustion. AT point was also estimated in the same manner using V-slope program with gas exchange parameters. In general, the estimated values of AT point-time computed by EMG method were more consistent across 5 filtering intervals and demonstrated higher correlations among themselves when compared with those values obtained by VT method. The results found in the present study suggest that the EMG signals could be used as an alternative or a new option in estimating AT point. Also the proposed computing procedure implemented in Matlab for the analysis of EMG signals appeared to be valid and reliable as it produced nearly identical values and high correlations with VT estimates. © Georg Thieme Verlag KG Stuttgart · New York.

A scientific and statistical analysis of accelerated aging for pharmaceuticals. Part 1: accuracy of fitting methods.

PubMed

Waterman, Kenneth C; Swanson, Jon T; Lippold, Blake L

2014-10-01

Three competing mathematical fitting models (a point-by-point estimation method, a linear fit method, and an isoconversion method) of chemical stability (related substance growth) when using high temperature data to predict room temperature shelf-life were employed in a detailed comparison. In each case, complex degradant formation behavior was analyzed by both exponential and linear forms of the Arrhenius equation. A hypothetical reaction was used where a drug (A) degrades to a primary degradant (B), which in turn degrades to a secondary degradation product (C). Calculated data with the fitting models were compared with the projected room-temperature shelf-lives of B and C, using one to four time points (in addition to the origin) for each of three accelerated temperatures. Isoconversion methods were found to provide more accurate estimates of shelf-life at ambient conditions. Of the methods for estimating isoconversion, bracketing the specification limit at each condition produced the best estimates and was considerably more accurate than when extrapolation was required. Good estimates of isoconversion produced similar shelf-life estimates fitting either linear or nonlinear forms of the Arrhenius equation, whereas poor isoconversion estimates favored one method or the other depending on which condition was most in error. © 2014 Wiley Periodicals, Inc. and the American Pharmacists Association.

A-posteriori error estimation for the finite point method with applications to compressible flow

NASA Astrophysics Data System (ADS)

Ortega, Enrique; Flores, Roberto; Oñate, Eugenio; Idelsohn, Sergio

2017-08-01

An a-posteriori error estimate with application to inviscid compressible flow problems is presented. The estimate is a surrogate measure of the discretization error, obtained from an approximation to the truncation terms of the governing equations. This approximation is calculated from the discrete nodal differential residuals using a reconstructed solution field on a modified stencil of points. Both the error estimation methodology and the flow solution scheme are implemented using the Finite Point Method, a meshless technique enabling higher-order approximations and reconstruction procedures on general unstructured discretizations. The performance of the proposed error indicator is studied and applications to adaptive grid refinement are presented.

Estimating monthly temperature using point based interpolation techniques

NASA Astrophysics Data System (ADS)

Saaban, Azizan; Mah Hashim, Noridayu; Murat, Rusdi Indra Zuhdi

2013-04-01

This paper discusses the use of point based interpolation to estimate the value of temperature at an unallocated meteorology stations in Peninsular Malaysia using data of year 2010 collected from the Malaysian Meteorology Department. Two point based interpolation methods which are Inverse Distance Weighted (IDW) and Radial Basis Function (RBF) are considered. The accuracy of the methods is evaluated using Root Mean Square Error (RMSE). The results show that RBF with thin plate spline model is suitable to be used as temperature estimator for the months of January and December, while RBF with multiquadric model is suitable to estimate the temperature for the rest of the months.

Unbiased estimation of the eyeball volume using the Cavalieri principle on computed tomography images.

PubMed

Acer, Niyazi; Sahin, Bunyamin; Ucar, Tolga; Usanmaz, Mustafa

2009-01-01

The size of the eyeball has been the subject of a few studies. None of them used stereological methods to estimate the volume. In the current study, we estimated the volume of eyeball in normal men and women using the stereological methods. Eyeball volume (EV) was estimated using the Cavalieri principle as a combination of point-counting and planimetry techniques. We used computed tomography scans taken from 36 participants (15 men and 21 women) to estimate the EV. The mean (SD) EV values obtained by planimetry method were 7.49 (0.79) and 7.06 (0.85) cm in men and women, respectively. By using point-counting method, the mean (SD) values were 7.48 (0.85) and 7.21 (0.84) cm in men and women, respectively. There was no statistically significant difference between the findings from the 2 methods (P > 0.05). A weak correlation was found between the axial length of eyeball and the EV estimated by point counting and planimetry (P < 0.05, r = 0.494 and r = 0.523, respectively). The findings of the current study using the stereological methods could provide data for the evaluation of normal and pathologic volumes of the eyeball.

Estimating continuous floodplain and major river bed topography mixing ordinal coutour lines and topographic points

NASA Astrophysics Data System (ADS)

Bailly, J. S.; Dartevelle, M.; Delenne, C.; Rousseau, A.

2017-12-01

Floodplain and major river bed topography govern many river biophysical processes during floods. Despite the grow of direct topographic measurements from LiDARS on riverine systems, it still room to develop methods for large (e.g. deltas) or very local (e.g. ponds) riverine systems that take advantage of information coming from simple SAR or optical image processing on floodplain, resulting from waterbodies delineation during flood up or down, and producing ordered coutour lines. The next challenge is thus to exploit such data in order to estimate continuous topography on the floodplain combining heterogeneous data: a topographic points dataset and a located but unknown and ordered contourline dataset. This article is comparing two methods designed to estimate continuous topography on the floodplain mixing ordinal coutour lines and continuous topographic points. For both methods a first estimation step is to value each contourline with elevation and a second step is next to estimate the continuous field from both topographic points and valued contourlines. The first proposed method is a stochastic method starting from multigaussian random-fields and conditional simualtion. The second is a deterministic method based on radial spline fonction for thin layers used for approximated bivariate surface construction. Results are first shown and discussed from a set of synoptic case studies presenting various topographic points density and topographic smoothness. Next, results are shown and discuss on an actual case study in the Montagua laguna, located in the north of Valparaiso, Chile.

Estimating continuous floodplain and major river bed topography mixing ordinal coutour lines and topographic points

NASA Astrophysics Data System (ADS)

Brown, T. G.; Lespez, L.; Sear, D. A.; Houben, P.; Klimek, K.

2016-12-01

Floodplain and major river bed topography govern many river biophysical processes during floods. Despite the grow of direct topographic measurements from LiDARS on riverine systems, it still room to develop methods for large (e.g. deltas) or very local (e.g. ponds) riverine systems that take advantage of information coming from simple SAR or optical image processing on floodplain, resulting from waterbodies delineation during flood up or down, and producing ordered coutour lines. The next challenge is thus to exploit such data in order to estimate continuous topography on the floodplain combining heterogeneous data: a topographic points dataset and a located but unknown and ordered contourline dataset. This article is comparing two methods designed to estimate continuous topography on the floodplain mixing ordinal coutour lines and continuous topographic points. For both methods a first estimation step is to value each contourline with elevation and a second step is next to estimate the continuous field from both topographic points and valued contourlines. The first proposed method is a stochastic method starting from multigaussian random-fields and conditional simualtion. The second is a deterministic method based on radial spline fonction for thin layers used for approximated bivariate surface construction. Results are first shown and discussed from a set of synoptic case studies presenting various topographic points density and topographic smoothness. Next, results are shown and discuss on an actual case study in the Montagua laguna, located in the north of Valparaiso, Chile.

Estimating the number of people in crowded scenes

NASA Astrophysics Data System (ADS)

Kim, Minjin; Kim, Wonjun; Kim, Changick

2011-01-01

This paper presents a method to estimate the number of people in crowded scenes without using explicit object segmentation or tracking. The proposed method consists of three steps as follows: (1) extracting space-time interest points using eigenvalues of the local spatio-temporal gradient matrix, (2) generating crowd regions based on space-time interest points, and (3) estimating the crowd density based on the multiple regression. In experimental results, the efficiency and robustness of our proposed method are demonstrated by using PETS 2009 dataset.

Bird biodiversity assessments in temperate forest: the value of point count versus acoustic monitoring protocols.

PubMed

Klingbeil, Brian T; Willig, Michael R

2015-01-01

Effective monitoring programs for biodiversity are needed to assess trends in biodiversity and evaluate the consequences of management. This is particularly true for birds and faunas that occupy interior forest and other areas of low human population density, as these are frequently under-sampled compared to other habitats. For birds, Autonomous Recording Units (ARUs) have been proposed as a supplement or alternative to point counts made by human observers to enhance monitoring efforts. We employed two strategies (i.e., simultaneous-collection and same-season) to compare point count and ARU methods for quantifying species richness and composition of birds in temperate interior forests. The simultaneous-collection strategy compares surveys by ARUs and point counts, with methods matched in time, location, and survey duration such that the person and machine simultaneously collect data. The same-season strategy compares surveys from ARUs and point counts conducted at the same locations throughout the breeding season, but methods differ in the number, duration, and frequency of surveys. This second strategy more closely follows the ways in which monitoring programs are likely to be implemented. Site-specific estimates of richness (but not species composition) differed between methods; however, the nature of the relationship was dependent on the assessment strategy. Estimates of richness from point counts were greater than estimates from ARUs in the simultaneous-collection strategy. Woodpeckers in particular, were less frequently identified from ARUs than point counts with this strategy. Conversely, estimates of richness were lower from point counts than ARUs in the same-season strategy. Moreover, in the same-season strategy, ARUs detected the occurrence of passerines at a higher frequency than did point counts. Differences between ARU and point count methods were only detected in site-level comparisons. Importantly, both methods provide similar estimates of species richness and composition for the region. Consequently, if single visits to sites or short-term monitoring are the goal, point counts will likely perform better than ARUs, especially if species are rare or vocalize infrequently. However, if seasonal or annual monitoring of sites is the goal, ARUs offer a viable alternative to standard point-count methods, especially in the context of large-scale or long-term monitoring of temperate forest birds.

Application of change-point problem to the detection of plant patches.

PubMed

López, I; Gámez, M; Garay, J; Standovár, T; Varga, Z

2010-03-01

In ecology, if the considered area or space is large, the spatial distribution of individuals of a given plant species is never homogeneous; plants form different patches. The homogeneity change in space or in time (in particular, the related change-point problem) is an important research subject in mathematical statistics. In the paper, for a given data system along a straight line, two areas are considered, where the data of each area come from different discrete distributions, with unknown parameters. In the paper a method is presented for the estimation of the distribution change-point between both areas and an estimate is given for the distributions separated by the obtained change-point. The solution of this problem will be based on the maximum likelihood method. Furthermore, based on an adaptation of the well-known bootstrap resampling, a method for the estimation of the so-called change-interval is also given. The latter approach is very general, since it not only applies in the case of the maximum-likelihood estimation of the change-point, but it can be also used starting from any other change-point estimation known in the ecological literature. The proposed model is validated against typical ecological situations, providing at the same time a verification of the applied algorithms.

Human Body 3D Posture Estimation Using Significant Points and Two Cameras

PubMed Central

Juang, Chia-Feng; Chen, Teng-Chang; Du, Wei-Chin

2014-01-01

This paper proposes a three-dimensional (3D) human posture estimation system that locates 3D significant body points based on 2D body contours extracted from two cameras without using any depth sensors. The 3D significant body points that are located by this system include the head, the center of the body, the tips of the feet, the tips of the hands, the elbows, and the knees. First, a linear support vector machine- (SVM-) based segmentation method is proposed to distinguish the human body from the background in red, green, and blue (RGB) color space. The SVM-based segmentation method uses not only normalized color differences but also included angle between pixels in the current frame and the background in order to reduce shadow influence. After segmentation, 2D significant points in each of the two extracted images are located. A significant point volume matching (SPVM) method is then proposed to reconstruct the 3D significant body point locations by using 2D posture estimation results. Experimental results show that the proposed SVM-based segmentation method shows better performance than other gray level- and RGB-based segmentation approaches. This paper also shows the effectiveness of the 3D posture estimation results in different postures. PMID:24883422

Vision System for Coarsely Estimating Motion Parameters for Unknown Fast Moving Objects in Space

PubMed Central

Chen, Min; Hashimoto, Koichi

2017-01-01

Motivated by biological interests in analyzing navigation behaviors of flying animals, we attempt to build a system measuring their motion states. To do this, in this paper, we build a vision system to detect unknown fast moving objects within a given space, calculating their motion parameters represented by positions and poses. We proposed a novel method to detect reliable interest points from images of moving objects, which can be hardly detected by general purpose interest point detectors. 3D points reconstructed using these interest points are then grouped and maintained for detected objects, according to a careful schedule, considering appearance and perspective changes. In the estimation step, a method is introduced to adapt the robust estimation procedure used for dense point set to the case for sparse set, reducing the potential risk of greatly biased estimation. Experiments are conducted against real scenes, showing the capability of the system of detecting multiple unknown moving objects and estimating their positions and poses. PMID:29206189

A Robust Method for Ego-Motion Estimation in Urban Environment Using Stereo Camera.

PubMed

Ci, Wenyan; Huang, Yingping

2016-10-17

Visual odometry estimates the ego-motion of an agent (e.g., vehicle and robot) using image information and is a key component for autonomous vehicles and robotics. This paper proposes a robust and precise method for estimating the 6-DoF ego-motion, using a stereo rig with optical flow analysis. An objective function fitted with a set of feature points is created by establishing the mathematical relationship between optical flow, depth and camera ego-motion parameters through the camera's 3-dimensional motion and planar imaging model. Accordingly, the six motion parameters are computed by minimizing the objective function, using the iterative Levenberg-Marquard method. One of key points for visual odometry is that the feature points selected for the computation should contain inliers as much as possible. In this work, the feature points and their optical flows are initially detected by using the Kanade-Lucas-Tomasi (KLT) algorithm. A circle matching is followed to remove the outliers caused by the mismatching of the KLT algorithm. A space position constraint is imposed to filter out the moving points from the point set detected by the KLT algorithm. The Random Sample Consensus (RANSAC) algorithm is employed to further refine the feature point set, i.e., to eliminate the effects of outliers. The remaining points are tracked to estimate the ego-motion parameters in the subsequent frames. The approach presented here is tested on real traffic videos and the results prove the robustness and precision of the method.

A Robust Method for Ego-Motion Estimation in Urban Environment Using Stereo Camera

PubMed Central

Ci, Wenyan; Huang, Yingping

2016-01-01

Visual odometry estimates the ego-motion of an agent (e.g., vehicle and robot) using image information and is a key component for autonomous vehicles and robotics. This paper proposes a robust and precise method for estimating the 6-DoF ego-motion, using a stereo rig with optical flow analysis. An objective function fitted with a set of feature points is created by establishing the mathematical relationship between optical flow, depth and camera ego-motion parameters through the camera’s 3-dimensional motion and planar imaging model. Accordingly, the six motion parameters are computed by minimizing the objective function, using the iterative Levenberg–Marquard method. One of key points for visual odometry is that the feature points selected for the computation should contain inliers as much as possible. In this work, the feature points and their optical flows are initially detected by using the Kanade–Lucas–Tomasi (KLT) algorithm. A circle matching is followed to remove the outliers caused by the mismatching of the KLT algorithm. A space position constraint is imposed to filter out the moving points from the point set detected by the KLT algorithm. The Random Sample Consensus (RANSAC) algorithm is employed to further refine the feature point set, i.e., to eliminate the effects of outliers. The remaining points are tracked to estimate the ego-motion parameters in the subsequent frames. The approach presented here is tested on real traffic videos and the results prove the robustness and precision of the method. PMID:27763508

Integrating SAS and GIS software to improve habitat-use estimates from radiotelemetry data

USGS Publications Warehouse

Kenow, K.P.; Wright, R.G.; Samuel, M.D.; Rasmussen, P.W.

2001-01-01

Radiotelemetry has been used commonly to remotely determine habitat use by a variety of wildlife species. However, habitat misclassification can occur because the true location of a radiomarked animal can only be estimated. Analytical methods that provide improved estimates of habitat use from radiotelemetry location data using a subsampling approach have been proposed previously. We developed software, based on these methods, to conduct improved habitat-use analyses. A Statistical Analysis System (SAS)-executable file generates a random subsample of points from the error distribution of an estimated animal location and formats the output into ARC/INFO-compatible coordinate and attribute files. An associated ARC/INFO Arc Macro Language (AML) creates a coverage of the random points, determines the habitat type at each random point from an existing habitat coverage, sums the number of subsample points by habitat type for each location, and outputs tile results in ASCII format. The proportion and precision of habitat types used is calculated from the subsample of points generated for each radiotelemetry location. We illustrate the method and software by analysis of radiotelemetry data for a female wild turkey (Meleagris gallopavo).

Estimation of optimal pivot point for remote center of motion alignment in surgery.

PubMed

Rosa, Benoît; Gruijthuijsen, Caspar; Van Cleynenbreugel, Ben; Sloten, Jos Vander; Reynaerts, Dominiek; Poorten, Emmanuel Vander

2015-02-01

The determination of an optimal pivot point ([Formula: see text]) is important for instrument manipulation in minimally invasive surgery. Such knowledge is of particular importance for robotic-assisted surgery where robots need to rotate precisely around a specific point in space in order to minimize trauma to the body wall while maintaining position control. Remote center of motion (RCM) mechanisms are commonly used, where the RCM point is manually and visually aligned. If not positioned appropriately, this misalignment might lead to intolerably high forces on the body wall with increased risk of postoperative complications or instrument damage. An automated method to align the RCM with the [Formula: see text] was developed and tested. Computer vision and a lightweight calibration procedure are used to estimate the optimal pivot point. One or two pre-calibrated cameras viewing the surgical scene are employed. The surgeon is asked to make short pivoting movements, applying as little torque as possible, with an instrument of choice passing through the insertion point while camera images are being recorded. The physical properties of an instrument rotating around a pivot point are exploited in a random sample consensus scheme to robustly estimate the ideal position of the RCM in the image planes. Triangulation is used to estimate the RCM position in 3D. Experiments were performed on a specially designed mockup to test the method. The position of the pivot point is estimated with an average error less than 1.85 mm using two webcams placed from approximately 30 cm to 1 m away from the scene. The entire procedure was completed in a few seconds. In automated method to estimate the ideal position of the RCM was shown to be reliable. The method can be implemented within a visual servoing approach to automatically place the RCM point, or the results can be displayed on a screen to provide guidance to the surgeon. Further work includes the development of an image-guided alignment method and validation with in vivo experiments.

The depth estimation of 3D face from single 2D picture based on manifold learning constraints

NASA Astrophysics Data System (ADS)

Li, Xia; Yang, Yang; Xiong, Hailiang; Liu, Yunxia

2018-04-01

The estimation of depth is virtual important in 3D face reconstruction. In this paper, we propose a t-SNE based on manifold learning constraints and introduce K-means method to divide the original database into several subset, and the selected optimal subset to reconstruct the 3D face depth information can greatly reduce the computational complexity. Firstly, we carry out the t-SNE operation to reduce the key feature points in each 3D face model from 1×249 to 1×2. Secondly, the K-means method is applied to divide the training 3D database into several subset. Thirdly, the Euclidean distance between the 83 feature points of the image to be estimated and the feature point information before the dimension reduction of each cluster center is calculated. The category of the image to be estimated is judged according to the minimum Euclidean distance. Finally, the method Kong D will be applied only in the optimal subset to estimate the depth value information of 83 feature points of 2D face images. Achieving the final depth estimation results, thus the computational complexity is greatly reduced. Compared with the traditional traversal search estimation method, although the proposed method error rate is reduced by 0.49, the number of searches decreases with the change of the category. In order to validate our approach, we use a public database to mimic the task of estimating the depth of face images from 2D images. The average number of searches decreased by 83.19%.

The method for homography estimation between two planes based on lines and points

NASA Astrophysics Data System (ADS)

Shemiakina, Julia; Zhukovsky, Alexander; Nikolaev, Dmitry

2018-04-01

The paper considers the problem of estimating a transform connecting two images of one plane object. The method based on RANSAC is proposed for calculating the parameters of projective transform which uses points and lines correspondences simultaneously. A series of experiments was performed on synthesized data. Presented results show that the algorithm convergence rate is significantly higher when actual lines are used instead of points of lines intersection. When using both lines and feature points it is shown that the convergence rate does not depend on the ratio between lines and feature points in the input dataset.

Using ROC Curves to Choose Minimally Important Change Thresholds when Sensitivity and Specificity Are Valued Equally: The Forgotten Lesson of Pythagoras. Theoretical Considerations and an Example Application of Change in Health Status

PubMed Central

Froud, Robert; Abel, Gary

2014-01-01

Background Receiver Operator Characteristic (ROC) curves are being used to identify Minimally Important Change (MIC) thresholds on scales that measure a change in health status. In quasi-continuous patient reported outcome measures, such as those that measure changes in chronic diseases with variable clinical trajectories, sensitivity and specificity are often valued equally. Notwithstanding methodologists agreeing that these should be valued equally, different approaches have been taken to estimating MIC thresholds using ROC curves. Aims and objectives We aimed to compare the different approaches used with a new approach, exploring the extent to which the methods choose different thresholds, and considering the effect of differences on conclusions in responder analyses. Methods Using graphical methods, hypothetical data, and data from a large randomised controlled trial of manual therapy for low back pain, we compared two existing approaches with a new approach that is based on the addition of the sums of squares of 1-sensitivity and 1-specificity. Results There can be divergence in the thresholds chosen by different estimators. The cut-point selected by different estimators is dependent on the relationship between the cut-points in ROC space and the different contours described by the estimators. In particular, asymmetry and the number of possible cut-points affects threshold selection. Conclusion Choice of MIC estimator is important. Different methods for choosing cut-points can lead to materially different MIC thresholds and thus affect results of responder analyses and trial conclusions. An estimator based on the smallest sum of squares of 1-sensitivity and 1-specificity is preferable when sensitivity and specificity are valued equally. Unlike other methods currently in use, the cut-point chosen by the sum of squares method always and efficiently chooses the cut-point closest to the top-left corner of ROC space, regardless of the shape of the ROC curve. PMID:25474472

A Direct Latent Variable Modeling Based Method for Point and Interval Estimation of Coefficient Alpha

ERIC Educational Resources Information Center

Raykov, Tenko; Marcoulides, George A.

2015-01-01

A direct approach to point and interval estimation of Cronbach's coefficient alpha for multiple component measuring instruments is outlined. The procedure is based on a latent variable modeling application with widely circulated software. As a by-product, using sample data the method permits ascertaining whether the population discrepancy…

Assessment of the point-source method for estimating dose rates to members of the public from exposure to patients with 131I thyroid treatment

DOE PAGES

Dewji, Shaheen Azim; Bellamy, Michael B.; Hertel, Nolan E.; ...

2015-09-01

The U.S. Nuclear Regulatory Commission (USNRC) initiated a contract with Oak Ridge National Laboratory (ORNL) to calculate radiation dose rates to members of the public that may result from exposure to patients recently administered iodine-131 ( 131I) as part of medical therapy. The main purpose was to compare dose rate estimates based on a point source and target with values derived from more realistic simulations that considered the time-dependent distribution of 131I in the patient and attenuation of emitted photons by the patient’s tissues. The external dose rate estimates were derived using Monte Carlo methods and two representations of themore » Phantom with Movable Arms and Legs, previously developed by ORNL and the USNRC, to model the patient and a nearby member of the public. Dose rates to tissues and effective dose rates were calculated for distances ranging from 10 to 300 cm between the phantoms and compared to estimates based on the point-source method, as well as to results of previous studies that estimated exposure from 131I patients. The point-source method overestimates dose rates to members of the public in very close proximity to an 131I patient but is a broadly accurate method of dose rate estimation at separation distances of 300 cm or more at times closer to administration.« less

A Simple Method for Deriving the Confidence Regions for the Penalized Cox’s Model via the Minimand Perturbation†

PubMed Central

Lin, Chen-Yen; Halabi, Susan

2017-01-01

We propose a minimand perturbation method to derive the confidence regions for the regularized estimators for the Cox’s proportional hazards model. Although the regularized estimation procedure produces a more stable point estimate, it remains challenging to provide an interval estimator or an analytic variance estimator for the associated point estimate. Based on the sandwich formula, the current variance estimator provides a simple approximation, but its finite sample performance is not entirely satisfactory. Besides, the sandwich formula can only provide variance estimates for the non-zero coefficients. In this article, we present a generic description for the perturbation method and then introduce a computation algorithm using the adaptive least absolute shrinkage and selection operator (LASSO) penalty. Through simulation studies, we demonstrate that our method can better approximate the limiting distribution of the adaptive LASSO estimator and produces more accurate inference compared with the sandwich formula. The simulation results also indicate the possibility of extending the applications to the adaptive elastic-net penalty. We further demonstrate our method using data from a phase III clinical trial in prostate cancer. PMID:29326496

A Simple Method for Deriving the Confidence Regions for the Penalized Cox's Model via the Minimand Perturbation.

PubMed

Lin, Chen-Yen; Halabi, Susan

2017-01-01

We propose a minimand perturbation method to derive the confidence regions for the regularized estimators for the Cox's proportional hazards model. Although the regularized estimation procedure produces a more stable point estimate, it remains challenging to provide an interval estimator or an analytic variance estimator for the associated point estimate. Based on the sandwich formula, the current variance estimator provides a simple approximation, but its finite sample performance is not entirely satisfactory. Besides, the sandwich formula can only provide variance estimates for the non-zero coefficients. In this article, we present a generic description for the perturbation method and then introduce a computation algorithm using the adaptive least absolute shrinkage and selection operator (LASSO) penalty. Through simulation studies, we demonstrate that our method can better approximate the limiting distribution of the adaptive LASSO estimator and produces more accurate inference compared with the sandwich formula. The simulation results also indicate the possibility of extending the applications to the adaptive elastic-net penalty. We further demonstrate our method using data from a phase III clinical trial in prostate cancer.

A maximum power point prediction method for group control of photovoltaic water pumping systems based on parameter identification

NASA Astrophysics Data System (ADS)

Chen, B.; Su, J. H.; Guo, L.; Chen, J.

2017-06-01

This paper puts forward a maximum power estimation method based on the photovoltaic array (PVA) model to solve the optimization problems about group control of the PV water pumping systems (PVWPS) at the maximum power point (MPP). This method uses the improved genetic algorithm (GA) for model parameters estimation and identification in view of multi P-V characteristic curves of a PVA model, and then corrects the identification results through least square method. On this basis, the irradiation level and operating temperature under any condition are able to estimate so an accurate PVA model is established and the MPP none-disturbance estimation is achieved. The simulation adopts the proposed GA to determine parameters, and the results verify the accuracy and practicability of the methods.

Fast Estimation of Defect Profiles from the Magnetic Flux Leakage Signal Based on a Multi-Power Affine Projection Algorithm

PubMed Central

Han, Wenhua; Shen, Xiaohui; Xu, Jun; Wang, Ping; Tian, Guiyun; Wu, Zhengyang

2014-01-01

Magnetic flux leakage (MFL) inspection is one of the most important and sensitive nondestructive testing approaches. For online MFL inspection of a long-range railway track or oil pipeline, a fast and effective defect profile estimating method based on a multi-power affine projection algorithm (MAPA) is proposed, where the depth of a sampling point is related with not only the MFL signals before it, but also the ones after it, and all of the sampling points related to one point appear as serials or multi-power. Defect profile estimation has two steps: regulating a weight vector in an MAPA filter and estimating a defect profile with the MAPA filter. Both simulation and experimental data are used to test the performance of the proposed method. The results demonstrate that the proposed method exhibits high speed while maintaining the estimated profiles clearly close to the desired ones in a noisy environment, thereby meeting the demand of accurate online inspection. PMID:25192314

Fast estimation of defect profiles from the magnetic flux leakage signal based on a multi-power affine projection algorithm.

PubMed

Han, Wenhua; Shen, Xiaohui; Xu, Jun; Wang, Ping; Tian, Guiyun; Wu, Zhengyang

2014-09-04

Magnetic flux leakage (MFL) inspection is one of the most important and sensitive nondestructive testing approaches. For online MFL inspection of a long-range railway track or oil pipeline, a fast and effective defect profile estimating method based on a multi-power affine projection algorithm (MAPA) is proposed, where the depth of a sampling point is related with not only the MFL signals before it, but also the ones after it, and all of the sampling points related to one point appear as serials or multi-power. Defect profile estimation has two steps: regulating a weight vector in an MAPA filter and estimating a defect profile with the MAPA filter. Both simulation and experimental data are used to test the performance of the proposed method. The results demonstrate that the proposed method exhibits high speed while maintaining the estimated profiles clearly close to the desired ones in a noisy environment, thereby meeting the demand of accurate online inspection.

Improved Estimates of Thermodynamic Parameters

NASA Technical Reports Server (NTRS)

Lawson, D. D.

1982-01-01

Techniques refined for estimating heat of vaporization and other parameters from molecular structure. Using parabolic equation with three adjustable parameters, heat of vaporization can be used to estimate boiling point, and vice versa. Boiling points and vapor pressures for some nonpolar liquids were estimated by improved method and compared with previously reported values. Technique for estimating thermodynamic parameters should make it easier for engineers to choose among candidate heat-exchange fluids for thermochemical cycles.

Terrestrial laser scanning to quantify above-ground biomass of structurally complex coastal wetland vegetation

NASA Astrophysics Data System (ADS)

Owers, Christopher J.; Rogers, Kerrylee; Woodroffe, Colin D.

2018-05-01

Above-ground biomass represents a small yet significant contributor to carbon storage in coastal wetlands. Despite this, above-ground biomass is often poorly quantified, particularly in areas where vegetation structure is complex. Traditional methods for providing accurate estimates involve harvesting vegetation to develop mangrove allometric equations and quantify saltmarsh biomass in quadrats. However broad scale application of these methods may not capture structural variability in vegetation resulting in a loss of detail and estimates with considerable uncertainty. Terrestrial laser scanning (TLS) collects high resolution three-dimensional point clouds capable of providing detailed structural morphology of vegetation. This study demonstrates that TLS is a suitable non-destructive method for estimating biomass of structurally complex coastal wetland vegetation. We compare volumetric models, 3-D surface reconstruction and rasterised volume, and point cloud elevation histogram modelling techniques to estimate biomass. Our results show that current volumetric modelling approaches for estimating TLS-derived biomass are comparable to traditional mangrove allometrics and saltmarsh harvesting. However, volumetric modelling approaches oversimplify vegetation structure by under-utilising the large amount of structural information provided by the point cloud. The point cloud elevation histogram model presented in this study, as an alternative to volumetric modelling, utilises all of the information within the point cloud, as opposed to sub-sampling based on specific criteria. This method is simple but highly effective for both mangrove (r2 = 0.95) and saltmarsh (r2 > 0.92) vegetation. Our results provide evidence that application of TLS in coastal wetlands is an effective non-destructive method to accurately quantify biomass for structurally complex vegetation.

An adhered-particle analysis system based on concave points

NASA Astrophysics Data System (ADS)

Wang, Wencheng; Guan, Fengnian; Feng, Lin

2018-04-01

Particles adhered together will influence the image analysis in computer vision system. In this paper, a method based on concave point is designed. First, corner detection algorithm is adopted to obtain a rough estimation of potential concave points after image segmentation. Then, it computes the area ratio of the candidates to accurately localize the final separation points. Finally, it uses the separation points of each particle and the neighboring pixels to estimate the original particles before adhesion and provides estimated profile images. The experimental results have shown that this approach can provide good results that match the human visual cognitive mechanism.

Learning-based subject-specific estimation of dynamic maps of cortical morphology at missing time points in longitudinal infant studies.

PubMed

Meng, Yu; Li, Gang; Gao, Yaozong; Lin, Weili; Shen, Dinggang

2016-11-01

Longitudinal neuroimaging analysis of the dynamic brain development in infants has received increasing attention recently. Many studies expect a complete longitudinal dataset in order to accurately chart the brain developmental trajectories. However, in practice, a large portion of subjects in longitudinal studies often have missing data at certain time points, due to various reasons such as the absence of scan or poor image quality. To make better use of these incomplete longitudinal data, in this paper, we propose a novel machine learning-based method to estimate the subject-specific, vertex-wise cortical morphological attributes at the missing time points in longitudinal infant studies. Specifically, we develop a customized regression forest, named dynamically assembled regression forest (DARF), as the core regression tool. DARF ensures the spatial smoothness of the estimated maps for vertex-wise cortical morphological attributes and also greatly reduces the computational cost. By employing a pairwise estimation followed by a joint refinement, our method is able to fully exploit the available information from both subjects with complete scans and subjects with missing scans for estimation of the missing cortical attribute maps. The proposed method has been applied to estimating the dynamic cortical thickness maps at missing time points in an incomplete longitudinal infant dataset, which includes 31 healthy infant subjects, each having up to five time points in the first postnatal year. The experimental results indicate that our proposed framework can accurately estimate the subject-specific vertex-wise cortical thickness maps at missing time points, with the average error less than 0.23 mm. Hum Brain Mapp 37:4129-4147, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Comparison of Optimization and Two-point Methods in Estimation of Soil Water Retention Curve

NASA Astrophysics Data System (ADS)

Ghanbarian-Alavijeh, B.; Liaghat, A. M.; Huang, G.

2009-04-01

Soil water retention curve (SWRC) is one of the soil hydraulic properties in which its direct measurement is time consuming and expensive. Since, its measurement is unavoidable in study of environmental sciences i.e. investigation of unsaturated hydraulic conductivity and solute transport, in this study the attempt is to predict soil water retention curve from two measured points. By using Cresswell and Paydar (1996) method (two-point method) and an optimization method developed in this study on the basis of two points of SWRC, parameters of Tyler and Wheatcraft (1990) model (fractal dimension and air entry value) were estimated and then water content at different matric potentials were estimated and compared with their measured values (n=180). For each method, we used both 3 and 1500 kPa (case 1) and 33 and 1500 kPa (case 2) as two points of SWRC. The calculated RMSE values showed that in the Creswell and Paydar (1996) method, there exists no significant difference between case 1 and case 2. However, the calculated RMSE value in case 2 (2.35) was slightly less than case 1 (2.37). The results also showed that the developed optimization method in this study had significantly less RMSE values for cases 1 (1.63) and 2 (1.33) rather than Cresswell and Paydar (1996) method.

Multi-Gaussian fitting for pulse waveform using Weighted Least Squares and multi-criteria decision making method.

PubMed

Wang, Lu; Xu, Lisheng; Feng, Shuting; Meng, Max Q-H; Wang, Kuanquan

2013-11-01

Analysis of pulse waveform is a low cost, non-invasive method for obtaining vital information related to the conditions of the cardiovascular system. In recent years, different Pulse Decomposition Analysis (PDA) methods have been applied to disclose the pathological mechanisms of the pulse waveform. All these methods decompose single-period pulse waveform into a constant number (such as 3, 4 or 5) of individual waves. Furthermore, those methods do not pay much attention to the estimation error of the key points in the pulse waveform. The estimation of human vascular conditions depends on the key points' positions of pulse wave. In this paper, we propose a Multi-Gaussian (MG) model to fit real pulse waveforms using an adaptive number (4 or 5 in our study) of Gaussian waves. The unknown parameters in the MG model are estimated by the Weighted Least Squares (WLS) method and the optimized weight values corresponding to different sampling points are selected by using the Multi-Criteria Decision Making (MCDM) method. Performance of the MG model and the WLS method has been evaluated by fitting 150 real pulse waveforms of five different types. The resulting Normalized Root Mean Square Error (NRMSE) was less than 2.0% and the estimation accuracy for the key points was satisfactory, demonstrating that our proposed method is effective in compressing, synthesizing and analyzing pulse waveforms. Copyright © 2013 Elsevier Ltd. All rights reserved.

Estimating Aircraft Heading Based on Laserscanner Derived Point Clouds

NASA Astrophysics Data System (ADS)

Koppanyi, Z.; Toth, C., K.

2015-03-01

Using LiDAR sensors for tracking and monitoring an operating aircraft is a new application. In this paper, we present data processing methods to estimate the heading of a taxiing aircraft using laser point clouds. During the data acquisition, a Velodyne HDL-32E laser scanner tracked a moving Cessna 172 airplane. The point clouds captured at different times were used for heading estimation. After addressing the problem and specifying the equation of motion to reconstruct the aircraft point cloud from the consecutive scans, three methods are investigated here. The first requires a reference model to estimate the relative angle from the captured data by fitting different cross-sections (horizontal profiles). In the second approach, iterative closest point (ICP) method is used between the consecutive point clouds to determine the horizontal translation of the captured aircraft body. Regarding the ICP, three different versions were compared, namely, the ordinary 3D, 3-DoF 3D and 2-DoF 3D ICP. It was found that 2-DoF 3D ICP provides the best performance. Finally, the last algorithm searches for the unknown heading and velocity parameters by minimizing the volume of the reconstructed plane. The three methods were compared using three test datatypes which are distinguished by object-sensor distance, heading and velocity. We found that the ICP algorithm fails at long distances and when the aircraft motion direction perpendicular to the scan plane, but the first and the third methods give robust and accurate results at 40m object distance and at ~12 knots for a small Cessna airplane.

Incorporating availability for detection in estimates of bird abundance

USGS Publications Warehouse

Diefenbach, D.R.; Marshall, M.R.; Mattice, J.A.; Brauning, D.W.

2007-01-01

Several bird-survey methods have been proposed that provide an estimated detection probability so that bird-count statistics can be used to estimate bird abundance. However, some of these estimators adjust counts of birds observed by the probability that a bird is detected and assume that all birds are available to be detected at the time of the survey. We marked male Henslow's Sparrows (Ammodramus henslowii) and Grasshopper Sparrows (A. savannarum) and monitored their behavior during May-July 2002 and 2003 to estimate the proportion of time they were available for detection. We found that the availability of Henslow's Sparrows declined in late June to <10% for 5- or 10-min point counts when a male had to sing and be visible to the observer; but during 20 May-19 June, males were available for detection 39.1% (SD = 27.3) of the time for 5-min point counts and 43.9% (SD = 28.9) of the time for 10-min point counts (n = 54). We detected no temporal changes in availability for Grasshopper Sparrows, but estimated availability to be much lower for 5-min point counts (10.3%, SD = 12.2) than for 10-min point counts (19.2%, SD = 22.3) when males had to be visible and sing during the sampling period (n = 80). For distance sampling, we estimated the availability of Henslow's Sparrows to be 44.2% (SD = 29.0) and the availability of Grasshopper Sparrows to be 20.6% (SD = 23.5). We show how our estimates of availability can be incorporated in the abundance and variance estimators for distance sampling and modify the abundance and variance estimators for the double-observer method. Methods that directly estimate availability from bird counts but also incorporate detection probabilities need further development and will be important for obtaining unbiased estimates of abundance for these species.

Developing accurate survey methods for estimating population sizes and trends of the critically endangered Nihoa Millerbird and Nihoa Finch.

USGS Publications Warehouse

Gorresen, P. Marcos; Camp, Richard J.; Brinck, Kevin W.; Farmer, Chris

2012-01-01

Point-transect surveys indicated that millerbirds were more abundant than shown by the striptransect method, and were estimated at 802 birds in 2010 (95%CI = 652 – 964) and 704 birds in 2011 (95%CI = 579 – 837). Point-transect surveys yielded population estimates with improved precision which will permit trends to be detected in shorter time periods and with greater statistical power than is available from strip-transect survey methods. Mean finch population estimates and associated uncertainty were not markedly different among the three survey methods, but the performance of models used to estimate density and population size are expected to improve as the data from additional surveys are incorporated. Using the pointtransect survey, the mean finch population size was estimated at 2,917 birds in 2010 (95%CI = 2,037 – 3,965) and 2,461 birds in 2011 (95%CI = 1,682 – 3,348). Preliminary testing of the line-transect method in 2011 showed that it would not generate sufficient detections to effectively model bird density, and consequently, relatively precise population size estimates. Both species were fairly evenly distributed across Nihoa and appear to occur in all or nearly all available habitat. The time expended and area traversed by observers was similar among survey methods; however, point-transect surveys do not require that observers walk a straight transect line, thereby allowing them to avoid culturally or biologically sensitive areas and minimize the adverse effects of recurrent travel to any particular area. In general, pointtransect surveys detect more birds than strip-survey methods, thereby improving precision and resulting population size and trend estimation. The method is also better suited for the steep and uneven terrain of Nihoa

Statistical plant set estimation using Schroeder-phased multisinusoidal input design

NASA Technical Reports Server (NTRS)

Bayard, D. S.

1992-01-01

A frequency domain method is developed for plant set estimation. The estimation of a plant 'set' rather than a point estimate is required to support many methods of modern robust control design. The approach here is based on using a Schroeder-phased multisinusoid input design which has the special property of placing input energy only at the discrete frequency points used in the computation. A detailed analysis of the statistical properties of the frequency domain estimator is given, leading to exact expressions for the probability distribution of the estimation error, and many important properties. It is shown that, for any nominal parametric plant estimate, one can use these results to construct an overbound on the additive uncertainty to any prescribed statistical confidence. The 'soft' bound thus obtained can be used to replace 'hard' bounds presently used in many robust control analysis and synthesis methods.

Monte Carlo approaches to sampling forested tracts with lines or points

Treesearch

Harry T. Valentine; Jeffrey H. Gove; Timothy G. Gregoire

2001-01-01

Several line- and point-based sampling methods can be employed to estimate the aggregate dimensions of trees standing on a forested tract or pieces of coarse woody debris lying on the forest floor. Line methods include line intersect sampling, horizontal line sampling, and transect relascope sampling; point methods include variable- and fixed-radius plot sampling, and...

Proof of concept Laplacian estimate derived for noninvasive tripolar concentric ring electrode with incorporated radius of the central disc and the widths of the concentric rings.

PubMed

Makeyev, Oleksandr; Lee, Colin; Besio, Walter G

2017-07-01

Tripolar concentric ring electrodes are showing great promise in a range of applications including braincomputer interface and seizure onset detection due to their superiority to conventional disc electrodes, in particular, in accuracy of surface Laplacian estimation. Recently, we proposed a general approach to estimation of the Laplacian for an (n + 1)-polar electrode with n rings using the (4n + 1)-point method for n ≥ 2 that allows cancellation of all the truncation terms up to the order of 2n. This approach has been used to introduce novel multipolar and variable inter-ring distances concentric ring electrode configurations verified using finite element method. The obtained results suggest their potential to improve Laplacian estimation compared to currently used constant interring distances tripolar concentric ring electrodes. One of the main limitations of the proposed (4n + 1)-point method is that the radius of the central disc and the widths of the concentric rings are not included and therefore cannot be optimized. This study incorporates these two parameters by representing the central disc and both concentric rings as clusters of points with specific radius and widths respectively as opposed to the currently used single point and concentric circles. A proof of concept Laplacian estimate is derived for a tripolar concentric ring electrode with non-negligible radius of the central disc and non-negligible widths of the concentric rings clearly demonstrating how both of these parameters can be incorporated into the (4n + 1)-point method.

A Maximum Power Point Tracking Control Method of a Photovoltaic Power Generator with Consideration of Dynamic Characteristics of Solar Cells

NASA Astrophysics Data System (ADS)

Watanabe, Takashi; Yoshida, Toshiya; Ohniwa, Katsumi

This paper discusses a new control strategy for photovoltaic power generation systems with consideration of dynamic characteristics of the photovoltaic cells. The controller estimates internal currents of an equivalent circuit for the cells. This estimated, or the virtual current and the actual voltage of the cells are fed to a conventional Maximum-Power-Point-Tracking (MPPT) controller. Consequently, this MPPT controller still tracks the optimum point even though it is so designed that the seeking speed of the operating point is extremely high. This system may suit for applications, which are installed in rapidly changeable insolation and temperature-conditions e.g. automobiles, trains, and airplanes. The proposed method is verified by experiment with a combination of this estimating function and the modified Boehringer's MPPT algorithm.

Critical point relascope sampling for unbiased volume estimation of downed coarse woody debris

Treesearch

Jeffrey H. Gove; Michael S. Williams; Mark J. Ducey; Mark J. Ducey

2005-01-01

Critical point relascope sampling is developed and shown to be design-unbiased for the estimation of log volume when used with point relascope sampling for downed coarse woody debris. The method is closely related to critical height sampling for standing trees when trees are first sampled with a wedge prism. Three alternative protocols for determining the critical...

Distributed processing of a GPS receiver network for a regional ionosphere map

NASA Astrophysics Data System (ADS)

Choi, Kwang Ho; Hoo Lim, Joon; Yoo, Won Jae; Lee, Hyung Keun

2018-01-01

This paper proposes a distributed processing method applicable to GPS receivers in a network to generate a regional ionosphere map accurately and reliably. For accuracy, the proposed method is operated by multiple local Kalman filters and Kriging estimators. Each local Kalman filter is applied to a dual-frequency receiver to estimate the receiver’s differential code bias and vertical ionospheric delays (VIDs) at different ionospheric pierce points. The Kriging estimator selects and combines several VID estimates provided by the local Kalman filters to generate the VID estimate at each ionospheric grid point. For reliability, the proposed method uses receiver fault detectors and satellite fault detectors. Each receiver fault detector compares the VID estimates of the same local area provided by different local Kalman filters. Each satellite fault detector compares the VID estimate of each local area with that projected from the other local areas. Compared with the traditional centralized processing method, the proposed method is advantageous in that it considerably reduces the computational burden of each single Kalman filter and enables flexible fault detection, isolation, and reconfiguration capability. To evaluate the performance of the proposed method, several experiments with field collected measurements were performed.

Damage diagnosis algorithm using a sequential change point detection method with an unknown distribution for damage

NASA Astrophysics Data System (ADS)

Noh, Hae Young; Rajagopal, Ram; Kiremidjian, Anne S.

2012-04-01

This paper introduces a damage diagnosis algorithm for civil structures that uses a sequential change point detection method for the cases where the post-damage feature distribution is unknown a priori. This algorithm extracts features from structural vibration data using time-series analysis and then declares damage using the change point detection method. The change point detection method asymptotically minimizes detection delay for a given false alarm rate. The conventional method uses the known pre- and post-damage feature distributions to perform a sequential hypothesis test. In practice, however, the post-damage distribution is unlikely to be known a priori. Therefore, our algorithm estimates and updates this distribution as data are collected using the maximum likelihood and the Bayesian methods. We also applied an approximate method to reduce the computation load and memory requirement associated with the estimation. The algorithm is validated using multiple sets of simulated data and a set of experimental data collected from a four-story steel special moment-resisting frame. Our algorithm was able to estimate the post-damage distribution consistently and resulted in detection delays only a few seconds longer than the delays from the conventional method that assumes we know the post-damage feature distribution. We confirmed that the Bayesian method is particularly efficient in declaring damage with minimal memory requirement, but the maximum likelihood method provides an insightful heuristic approach.

Estimating brain connectivity when few data points are available: Perspectives and limitations.

PubMed

Antonacci, Yuri; Toppi, Jlenia; Caschera, Stefano; Anzolin, Alessandra; Mattia, Donatella; Astolfi, Laura

2017-07-01

Methods based on the use of multivariate autoregressive modeling (MVAR) have proved to be an accurate and flexible tool for the estimation of brain functional connectivity. The multivariate approach, however, implies the use of a model whose complexity (in terms of number of parameters) increases quadratically with the number of signals included in the problem. This can often lead to an underdetermined problem and to the condition of multicollinearity. The aim of this paper is to introduce and test an approach based on Ridge Regression combined with a modified version of the statistics usually adopted for these methods, to broaden the estimation of brain connectivity to those conditions in which current methods fail, due to the lack of enough data points. We tested the performances of this new approach, in comparison with the classical approach based on ordinary least squares (OLS), by means of a simulation study implementing different ground-truth networks, under different network sizes and different levels of data points. Simulation results showed that the new approach provides better performances, in terms of accuracy of the parameters estimation and false positives/false negatives rates, in all conditions related to a low data points/model dimension ratio, and may thus be exploited to estimate and validate estimated patterns at single-trial level or when short time data segments are available.

Autoregressive-model-based missing value estimation for DNA microarray time series data.

PubMed

Choong, Miew Keen; Charbit, Maurice; Yan, Hong

2009-01-01

Missing value estimation is important in DNA microarray data analysis. A number of algorithms have been developed to solve this problem, but they have several limitations. Most existing algorithms are not able to deal with the situation where a particular time point (column) of the data is missing entirely. In this paper, we present an autoregressive-model-based missing value estimation method (ARLSimpute) that takes into account the dynamic property of microarray temporal data and the local similarity structures in the data. ARLSimpute is especially effective for the situation where a particular time point contains many missing values or where the entire time point is missing. Experiment results suggest that our proposed algorithm is an accurate missing value estimator in comparison with other imputation methods on simulated as well as real microarray time series datasets.

CREPT-MCNP code for efficiency calibration of HPGe detectors with the representative point method.

PubMed

Saegusa, Jun

2008-01-01

The representative point method for the efficiency calibration of volume samples has been previously proposed. For smoothly implementing the method, a calculation code named CREPT-MCNP has been developed. The code estimates the position of a representative point which is intrinsic to each shape of volume sample. The self-absorption correction factors are also given to make correction on the efficiencies measured at the representative point with a standard point source. Features of the CREPT-MCNP code are presented.

Point Set Denoising Using Bootstrap-Based Radial Basis Function.

PubMed

Liew, Khang Jie; Ramli, Ahmad; Abd Majid, Ahmad

2016-01-01

This paper examines the application of a bootstrap test error estimation of radial basis functions, specifically thin-plate spline fitting, in surface smoothing. The presence of noisy data is a common issue of the point set model that is generated from 3D scanning devices, and hence, point set denoising is one of the main concerns in point set modelling. Bootstrap test error estimation, which is applied when searching for the smoothing parameters of radial basis functions, is revisited. The main contribution of this paper is a smoothing algorithm that relies on a bootstrap-based radial basis function. The proposed method incorporates a k-nearest neighbour search and then projects the point set to the approximated thin-plate spline surface. Therefore, the denoising process is achieved, and the features are well preserved. A comparison of the proposed method with other smoothing methods is also carried out in this study.

A comparison of skyshine computational methods.

PubMed

Hertel, Nolan E; Sweezy, Jeremy E; Shultis, J Kenneth; Warkentin, J Karl; Rose, Zachary J

2005-01-01

A variety of methods employing radiation transport and point-kernel codes have been used to model two skyshine problems. The first problem is a 1 MeV point source of photons on the surface of the earth inside a 2 m tall and 1 m radius silo having black walls. The skyshine radiation downfield from the point source was estimated with and without a 30-cm-thick concrete lid on the silo. The second benchmark problem is to estimate the skyshine radiation downfield from 12 cylindrical canisters emplaced in a low-level radioactive waste trench. The canisters are filled with ion-exchange resin with a representative radionuclide loading, largely 60Co, 134Cs and 137Cs. The solution methods include use of the MCNP code to solve the problem by directly employing variance reduction techniques, the single-scatter point kernel code GGG-GP, the QADMOD-GP point kernel code, the COHORT Monte Carlo code, the NAC International version of the SKYSHINE-III code, the KSU hybrid method and the associated KSU skyshine codes.

Strain Rate Tensor Estimation in Cine Cardiac MRI Based on Elastic Image Registration

NASA Astrophysics Data System (ADS)

Sánchez-Ferrero, Gonzalo Vegas; Vega, Antonio Tristán; Grande, Lucilio Cordero; de La Higuera, Pablo Casaseca; Fernández, Santiago Aja; Fernández, Marcos Martín; López, Carlos Alberola

In this work we propose an alternative method to estimate and visualize the Strain Rate Tensor (SRT) in Magnetic Resonance Images (MRI) when Phase Contrast MRI (PCMRI) and Tagged MRI (TMRI) are not available. This alternative is based on image processing techniques. Concretely, image registration algorithms are used to estimate the movement of the myocardium at each point. Additionally, a consistency checking method is presented to validate the accuracy of the estimates when no golden standard is available. Results prove that the consistency checking method provides an upper bound of the mean squared error of the estimate. Our experiments with real data show that the registration algorithm provides a useful deformation field to estimate the SRT fields. A classification between regional normal and dysfunctional contraction patterns, as compared with experts diagnosis, points out that the parameters extracted from the estimated SRT can represent these patterns. Additionally, a scheme for visualizing and analyzing the local behavior of the SRT field is presented.

A method for automatic feature points extraction of human vertebrae three-dimensional model

NASA Astrophysics Data System (ADS)

Wu, Zhen; Wu, Junsheng

2017-05-01

A method for automatic extraction of the feature points of the human vertebrae three-dimensional model is presented. Firstly, the statistical model of vertebrae feature points is established based on the results of manual vertebrae feature points extraction. Then anatomical axial analysis of the vertebrae model is performed according to the physiological and morphological characteristics of the vertebrae. Using the axial information obtained from the analysis, a projection relationship between the statistical model and the vertebrae model to be extracted is established. According to the projection relationship, the statistical model is matched with the vertebrae model to get the estimated position of the feature point. Finally, by analyzing the curvature in the spherical neighborhood with the estimated position of feature points, the final position of the feature points is obtained. According to the benchmark result on multiple test models, the mean relative errors of feature point positions are less than 5.98%. At more than half of the positions, the error rate is less than 3% and the minimum mean relative error is 0.19%, which verifies the effectiveness of the method.

Relative Pose Estimation Using Image Feature Triplets

NASA Astrophysics Data System (ADS)

Chuang, T. Y.; Rottensteiner, F.; Heipke, C.

2015-03-01

A fully automated reconstruction of the trajectory of image sequences using point correspondences is turning into a routine practice. However, there are cases in which point features are hardly detectable, cannot be localized in a stable distribution, and consequently lead to an insufficient pose estimation. This paper presents a triplet-wise scheme for calibrated relative pose estimation from image point and line triplets, and investigates the effectiveness of the feature integration upon the relative pose estimation. To this end, we employ an existing point matching technique and propose a method for line triplet matching in which the relative poses are resolved during the matching procedure. The line matching method aims at establishing hypotheses about potential minimal line matches that can be used for determining the parameters of relative orientation (pose estimation) of two images with respect to the reference one; then, quantifying the agreement using the estimated orientation parameters. Rather than randomly choosing the line candidates in the matching process, we generate an associated lookup table to guide the selection of potential line matches. In addition, we integrate the homologous point and line triplets into a common adjustment procedure. In order to be able to also work with image sequences the adjustment is formulated in an incremental manner. The proposed scheme is evaluated with both synthetic and real datasets, demonstrating its satisfactory performance and revealing the effectiveness of image feature integration.

Do sampling methods differ in their utility for ecological monitoring? Comparison of line-point intercept, grid-point intercept, and ocular estimate methods

USDA-ARS?s Scientific Manuscript database

This study compared the utility of three sampling methods for ecological monitoring based on: interchangeability of data (rank correlations), precision (coefficient of variation), cost (minutes/transect), and potential of each method to generate multiple indicators. Species richness and foliar cover...

The Chebyshev-Legendre method: Implementing Legendre methods on Chebyshev points

NASA Technical Reports Server (NTRS)

Don, Wai Sun; Gottlieb, David

1993-01-01

We present a new collocation method for the numerical solution of partial differential equations. This method uses the Chebyshev collocation points, but because of the way the boundary conditions are implemented, it has all the advantages of the Legendre methods. In particular, L2 estimates can be obtained easily for hyperbolic and parabolic problems.

Improved method for measuring the apparent CO2 photocompensation point resolves the impact of multiple internal conductances to CO2 to net gas exchange

USDA-ARS?s Scientific Manuscript database

There has been growing concern about methods used to measure the CO2 photocompensation point, a vital parameter to model leaf photosynthesis. the CO2 photocompensation point is often measured as the common intercept of several CO2 response curves, but this method may over-estimate the CO2 photocompe...

Robust Variable Selection with Exponential Squared Loss.

PubMed

Wang, Xueqin; Jiang, Yunlu; Huang, Mian; Zhang, Heping

2013-04-01

Robust variable selection procedures through penalized regression have been gaining increased attention in the literature. They can be used to perform variable selection and are expected to yield robust estimates. However, to the best of our knowledge, the robustness of those penalized regression procedures has not been well characterized. In this paper, we propose a class of penalized robust regression estimators based on exponential squared loss. The motivation for this new procedure is that it enables us to characterize its robustness that has not been done for the existing procedures, while its performance is near optimal and superior to some recently developed methods. Specifically, under defined regularity conditions, our estimators are [Formula: see text] and possess the oracle property. Importantly, we show that our estimators can achieve the highest asymptotic breakdown point of 1/2 and that their influence functions are bounded with respect to the outliers in either the response or the covariate domain. We performed simulation studies to compare our proposed method with some recent methods, using the oracle method as the benchmark. We consider common sources of influential points. Our simulation studies reveal that our proposed method performs similarly to the oracle method in terms of the model error and the positive selection rate even in the presence of influential points. In contrast, other existing procedures have a much lower non-causal selection rate. Furthermore, we re-analyze the Boston Housing Price Dataset and the Plasma Beta-Carotene Level Dataset that are commonly used examples for regression diagnostics of influential points. Our analysis unravels the discrepancies of using our robust method versus the other penalized regression method, underscoring the importance of developing and applying robust penalized regression methods.

Robust Variable Selection with Exponential Squared Loss

PubMed Central

Wang, Xueqin; Jiang, Yunlu; Huang, Mian; Zhang, Heping

2013-01-01

Robust variable selection procedures through penalized regression have been gaining increased attention in the literature. They can be used to perform variable selection and are expected to yield robust estimates. However, to the best of our knowledge, the robustness of those penalized regression procedures has not been well characterized. In this paper, we propose a class of penalized robust regression estimators based on exponential squared loss. The motivation for this new procedure is that it enables us to characterize its robustness that has not been done for the existing procedures, while its performance is near optimal and superior to some recently developed methods. Specifically, under defined regularity conditions, our estimators are n-consistent and possess the oracle property. Importantly, we show that our estimators can achieve the highest asymptotic breakdown point of 1/2 and that their influence functions are bounded with respect to the outliers in either the response or the covariate domain. We performed simulation studies to compare our proposed method with some recent methods, using the oracle method as the benchmark. We consider common sources of influential points. Our simulation studies reveal that our proposed method performs similarly to the oracle method in terms of the model error and the positive selection rate even in the presence of influential points. In contrast, other existing procedures have a much lower non-causal selection rate. Furthermore, we re-analyze the Boston Housing Price Dataset and the Plasma Beta-Carotene Level Dataset that are commonly used examples for regression diagnostics of influential points. Our analysis unravels the discrepancies of using our robust method versus the other penalized regression method, underscoring the importance of developing and applying robust penalized regression methods. PMID:23913996

Wave directional spreading from point field measurements.

PubMed

McAllister, M L; Venugopal, V; Borthwick, A G L

2017-04-01

Ocean waves have multidirectional components. Most wave measurements are taken at a single point, and so fail to capture information about the relative directions of the wave components directly. Conventional means of directional estimation require a minimum of three concurrent time series of measurements at different spatial locations in order to derive information on local directional wave spreading. Here, the relationship between wave nonlinearity and directionality is utilized to estimate local spreading without the need for multiple concurrent measurements, following Adcock & Taylor (Adcock & Taylor 2009 Proc. R. Soc. A 465 , 3361-3381. (doi:10.1098/rspa.2009.0031)), with the assumption that directional spreading is frequency independent. The method is applied to measurements recorded at the North Alwyn platform in the northern North Sea, and the results compared against estimates of wave spreading by conventional measurement methods and hindcast data. Records containing freak waves were excluded. It is found that the method provides accurate estimates of wave spreading over a range of conditions experienced at North Alwyn, despite the noisy chaotic signals that characterize such ocean wave data. The results provide further confirmation that Adcock and Taylor's method is applicable to metocean data and has considerable future promise as a technique to recover estimates of wave spreading from single point wave measurement devices.

Wave directional spreading from point field measurements

PubMed Central

Venugopal, V.; Borthwick, A. G. L.

2017-01-01

Ocean waves have multidirectional components. Most wave measurements are taken at a single point, and so fail to capture information about the relative directions of the wave components directly. Conventional means of directional estimation require a minimum of three concurrent time series of measurements at different spatial locations in order to derive information on local directional wave spreading. Here, the relationship between wave nonlinearity and directionality is utilized to estimate local spreading without the need for multiple concurrent measurements, following Adcock & Taylor (Adcock & Taylor 2009 Proc. R. Soc. A 465, 3361–3381. (doi:10.1098/rspa.2009.0031)), with the assumption that directional spreading is frequency independent. The method is applied to measurements recorded at the North Alwyn platform in the northern North Sea, and the results compared against estimates of wave spreading by conventional measurement methods and hindcast data. Records containing freak waves were excluded. It is found that the method provides accurate estimates of wave spreading over a range of conditions experienced at North Alwyn, despite the noisy chaotic signals that characterize such ocean wave data. The results provide further confirmation that Adcock and Taylor's method is applicable to metocean data and has considerable future promise as a technique to recover estimates of wave spreading from single point wave measurement devices. PMID:28484326

Automatic Estimation of Verified Floating-Point Round-Off Errors via Static Analysis

NASA Technical Reports Server (NTRS)

Moscato, Mariano; Titolo, Laura; Dutle, Aaron; Munoz, Cesar A.

2017-01-01

This paper introduces a static analysis technique for computing formally verified round-off error bounds of floating-point functional expressions. The technique is based on a denotational semantics that computes a symbolic estimation of floating-point round-o errors along with a proof certificate that ensures its correctness. The symbolic estimation can be evaluated on concrete inputs using rigorous enclosure methods to produce formally verified numerical error bounds. The proposed technique is implemented in the prototype research tool PRECiSA (Program Round-o Error Certifier via Static Analysis) and used in the verification of floating-point programs of interest to NASA.

A Bayesian Framework for Human Body Pose Tracking from Depth Image Sequences

PubMed Central

Zhu, Youding; Fujimura, Kikuo

2010-01-01

This paper addresses the problem of accurate and robust tracking of 3D human body pose from depth image sequences. Recovering the large number of degrees of freedom in human body movements from a depth image sequence is challenging due to the need to resolve the depth ambiguity caused by self-occlusions and the difficulty to recover from tracking failure. Human body poses could be estimated through model fitting using dense correspondences between depth data and an articulated human model (local optimization method). Although it usually achieves a high accuracy due to dense correspondences, it may fail to recover from tracking failure. Alternately, human pose may be reconstructed by detecting and tracking human body anatomical landmarks (key-points) based on low-level depth image analysis. While this method (key-point based method) is robust and recovers from tracking failure, its pose estimation accuracy depends solely on image-based localization accuracy of key-points. To address these limitations, we present a flexible Bayesian framework for integrating pose estimation results obtained by methods based on key-points and local optimization. Experimental results are shown and performance comparison is presented to demonstrate the effectiveness of the proposed approach. PMID:22399933

Abdominal fat volume estimation by stereology on CT: a comparison with manual planimetry.

PubMed

Manios, G E; Mazonakis, M; Voulgaris, C; Karantanas, A; Damilakis, J

2016-03-01

To deploy and evaluate a stereological point-counting technique on abdominal CT for the estimation of visceral (VAF) and subcutaneous abdominal fat (SAF) volumes. Stereological volume estimations based on point counting and systematic sampling were performed on images from 14 consecutive patients who had undergone abdominal CT. For the optimization of the method, five sampling intensities in combination with 100 and 200 points were tested. The optimum stereological measurements were compared with VAF and SAF volumes derived by the standard technique of manual planimetry on the same scans. Optimization analysis showed that the selection of 200 points along with the sampling intensity 1/8 provided efficient volume estimations in less than 4 min for VAF and SAF together. The optimized stereology showed strong correlation with planimetry (VAF: r = 0.98; SAF: r = 0.98). No statistical differences were found between the two methods (VAF: P = 0.81; SAF: P = 0.83). The 95% limits of agreement were also acceptable (VAF: -16.5%, 16.1%; SAF: -10.8%, 10.7%) and the repeatability of stereology was good (VAF: CV = 4.5%, SAF: CV = 3.2%). Stereology may be successfully applied to CT images for the efficient estimation of abdominal fat volume and may constitute a good alternative to the conventional planimetric technique. Abdominal obesity is associated with increased risk of disease and mortality. Stereology may quantify visceral and subcutaneous abdominal fat accurately and consistently. The application of stereology to estimating abdominal volume fat reduces processing time. Stereology is an efficient alternative method for estimating abdominal fat volume.

Optimizing probability of detection point estimate demonstration

NASA Astrophysics Data System (ADS)

Koshti, Ajay M.

2017-04-01

The paper provides discussion on optimizing probability of detection (POD) demonstration experiments using point estimate method. The optimization is performed to provide acceptable value for probability of passing demonstration (PPD) and achieving acceptable value for probability of false (POF) calls while keeping the flaw sizes in the set as small as possible. POD Point estimate method is used by NASA for qualifying special NDE procedures. The point estimate method uses binomial distribution for probability density. Normally, a set of 29 flaws of same size within some tolerance are used in the demonstration. Traditionally largest flaw size in the set is considered to be a conservative estimate of the flaw size with minimum 90% probability and 95% confidence. The flaw size is denoted as α90/95PE. The paper investigates relationship between range of flaw sizes in relation to α90, i.e. 90% probability flaw size, to provide a desired PPD. The range of flaw sizes is expressed as a proportion of the standard deviation of the probability density distribution. Difference between median or average of the 29 flaws and α90 is also expressed as a proportion of standard deviation of the probability density distribution. In general, it is concluded that, if probability of detection increases with flaw size, average of 29 flaw sizes would always be larger than or equal to α90 and is an acceptable measure of α90/95PE. If NDE technique has sufficient sensitivity and signal-to-noise ratio, then the 29 flaw-set can be optimized to meet requirements of minimum required PPD, maximum allowable POF, requirements on flaw size tolerance about mean flaw size and flaw size detectability requirements. The paper provides procedure for optimizing flaw sizes in the point estimate demonstration flaw-set.

Motion estimation accuracy for visible-light/gamma-ray imaging fusion for portable portal monitoring

NASA Astrophysics Data System (ADS)

Karnowski, Thomas P.; Cunningham, Mark F.; Goddard, James S.; Cheriyadat, Anil M.; Hornback, Donald E.; Fabris, Lorenzo; Kerekes, Ryan A.; Ziock, Klaus-Peter; Gee, Timothy F.

2010-01-01

The use of radiation sensors as portal monitors is increasing due to heightened concerns over the smuggling of fissile material. Portable systems that can detect significant quantities of fissile material that might be present in vehicular traffic are of particular interest. We have constructed a prototype, rapid-deployment portal gamma-ray imaging portal monitor that uses machine vision and gamma-ray imaging to monitor multiple lanes of traffic. Vehicles are detected and tracked by using point detection and optical flow methods as implemented in the OpenCV software library. Points are clustered together but imperfections in the detected points and tracks cause errors in the accuracy of the vehicle position estimates. The resulting errors cause a "blurring" effect in the gamma image of the vehicle. To minimize these errors, we have compared a variety of motion estimation techniques including an estimate using the median of the clustered points, a "best-track" filtering algorithm, and a constant velocity motion estimation model. The accuracy of these methods are contrasted and compared to a manually verified ground-truth measurement by quantifying the rootmean- square differences in the times the vehicles cross the gamma-ray image pixel boundaries compared with a groundtruth manual measurement.

Comparison of point counts and territory mapping for detecting effects of forest management on songbirds

USGS Publications Warehouse

Newell, Felicity L.; Sheehan, James; Wood, Petra Bohall; Rodewald, Amanda D.; Buehler, David A.; Keyser, Patrick D.; Larkin, Jeffrey L.; Beachy, Tiffany A.; Bakermans, Marja H.; Boves, Than J.; Evans, Andrea; George, Gregory A.; McDermott, Molly E.; Perkins, Kelly A.; White, Matthew; Wigley, T. Bently

2013-01-01

Point counts are commonly used to assess changes in bird abundance, including analytical approaches such as distance sampling that estimate density. Point-count methods have come under increasing scrutiny because effects of detection probability and field error are difficult to quantify. For seven forest songbirds, we compared fixed-radii counts (50 m and 100 m) and density estimates obtained from distance sampling to known numbers of birds determined by territory mapping. We applied point-count analytic approaches to a typical forest management question and compared results to those obtained by territory mapping. We used a before–after control impact (BACI) analysis with a data set collected across seven study areas in the central Appalachians from 2006 to 2010. Using a 50-m fixed radius, variance in error was at least 1.5 times that of the other methods, whereas a 100-m fixed radius underestimated actual density by >3 territories per 10 ha for the most abundant species. Distance sampling improved accuracy and precision compared to fixed-radius counts, although estimates were affected by birds counted outside 10-ha units. In the BACI analysis, territory mapping detected an overall treatment effect for five of the seven species, and effects were generally consistent each year. In contrast, all point-count methods failed to detect two treatment effects due to variance and error in annual estimates. Overall, our results highlight the need for adequate sample sizes to reduce variance, and skilled observers to reduce the level of error in point-count data. Ultimately, the advantages and disadvantages of different survey methods should be considered in the context of overall study design and objectives, allowing for trade-offs among effort, accuracy, and power to detect treatment effects.

Detection limit for rate fluctuations in inhomogeneous Poisson processes

NASA Astrophysics Data System (ADS)

Shintani, Toshiaki; Shinomoto, Shigeru

2012-04-01

Estimations of an underlying rate from data points are inevitably disturbed by the irregular occurrence of events. Proper estimation methods are designed to avoid overfitting by discounting the irregular occurrence of data, and to determine a constant rate from irregular data derived from a constant probability distribution. However, it can occur that rapid or small fluctuations in the underlying density are undetectable when the data are sparse. For an estimation method, the maximum degree of undetectable rate fluctuations is uniquely determined as a phase transition, when considering an infinitely long series of events drawn from a fluctuating density. In this study, we analytically examine an optimized histogram and a Bayesian rate estimator with respect to their detectability of rate fluctuation, and determine whether their detectable-undetectable phase transition points are given by an identical formula defining a degree of fluctuation in an underlying rate. In addition, we numerically examine the variational Bayes hidden Markov model in its detectability of rate fluctuation, and determine whether the numerically obtained transition point is comparable to those of the other two methods. Such consistency among these three principled methods suggests the presence of a theoretical limit for detecting rate fluctuations.

Detection limit for rate fluctuations in inhomogeneous Poisson processes.

PubMed

Shintani, Toshiaki; Shinomoto, Shigeru

2012-04-01

Estimations of an underlying rate from data points are inevitably disturbed by the irregular occurrence of events. Proper estimation methods are designed to avoid overfitting by discounting the irregular occurrence of data, and to determine a constant rate from irregular data derived from a constant probability distribution. However, it can occur that rapid or small fluctuations in the underlying density are undetectable when the data are sparse. For an estimation method, the maximum degree of undetectable rate fluctuations is uniquely determined as a phase transition, when considering an infinitely long series of events drawn from a fluctuating density. In this study, we analytically examine an optimized histogram and a Bayesian rate estimator with respect to their detectability of rate fluctuation, and determine whether their detectable-undetectable phase transition points are given by an identical formula defining a degree of fluctuation in an underlying rate. In addition, we numerically examine the variational Bayes hidden Markov model in its detectability of rate fluctuation, and determine whether the numerically obtained transition point is comparable to those of the other two methods. Such consistency among these three principled methods suggests the presence of a theoretical limit for detecting rate fluctuations.

A model of distributed phase aberration for deblurring phase estimated from scattering.

PubMed

Tillett, Jason C; Astheimer, Jeffrey P; Waag, Robert C

2010-01-01

Correction of aberration in ultrasound imaging uses the response of a point reflector or its equivalent to characterize the aberration. Because a point reflector is usually unavailable, its equivalent is obtained using statistical methods, such as processing reflections from multiple focal regions in a random medium. However, the validity of methods that use reflections from multiple points is limited to isoplanatic patches for which the aberration is essentially the same. In this study, aberration is modeled by an offset phase screen to relax the isoplanatic restriction. Methods are developed to determine the depth and phase of the screen and to use the model for compensation of aberration as the beam is steered. Use of the model to enhance the performance of the noted statistical estimation procedure is also described. Experimental results obtained with tissue-mimicking phantoms that implement different models and produce different amounts of aberration are presented to show the efficacy of these methods. The improvement in b-scan resolution realized with the model is illustrated. The results show that the isoplanatic patch assumption for estimation of aberration can be relaxed and that propagation-path characteristics and aberration estimation are closely related.

Simultaneous quaternion estimation (QUEST) and bias determination

NASA Technical Reports Server (NTRS)

Markley, F. Landis

1989-01-01

Tests of a new method for the simultaneous estimation of spacecraft attitude and sensor biases, based on a quaternion estimation algorithm minimizing Wahba's loss function are presented. The new method is compared with a conventional batch least-squares differential correction algorithm. The estimates are based on data from strapdown gyros and star trackers, simulated with varying levels of Gaussian noise for both inertially-fixed and Earth-pointing reference attitudes. Both algorithms solve for the spacecraft attitude and the gyro drift rate biases. They converge to the same estimates at the same rate for inertially-fixed attitude, but the new algorithm converges more slowly than the differential correction for Earth-pointing attitude. The slower convergence of the new method for non-zero attitude rates is believed to be due to the use of an inadequate approximation for a partial derivative matrix. The new method requires about twice the computational effort of the differential correction. Improving the approximation for the partial derivative matrix in the new method is expected to improve its convergence at the cost of increased computational effort.

Comparison of methods for estimating density of forest songbirds from point counts

Treesearch

Jennifer L. Reidy; Frank R. Thompson; J. Wesley. Bailey

2011-01-01

New analytical methods have been promoted for estimating the probability of detection and density of birds from count data but few studies have compared these methods using real data. We compared estimates of detection probability and density from distance and time-removal models and survey protocols based on 5- or 10-min counts and outer radii of 50 or 100 m. We...

A Parametric k-Means Algorithm

PubMed Central

Tarpey, Thaddeus

2007-01-01

Summary The k points that optimally represent a distribution (usually in terms of a squared error loss) are called the k principal points. This paper presents a computationally intensive method that automatically determines the principal points of a parametric distribution. Cluster means from the k-means algorithm are nonparametric estimators of principal points. A parametric k-means approach is introduced for estimating principal points by running the k-means algorithm on a very large simulated data set from a distribution whose parameters are estimated using maximum likelihood. Theoretical and simulation results are presented comparing the parametric k-means algorithm to the usual k-means algorithm and an example on determining sizes of gas masks is used to illustrate the parametric k-means algorithm. PMID:17917692

Pilot points method for conditioning multiple-point statistical facies simulation on flow data

NASA Astrophysics Data System (ADS)

Ma, Wei; Jafarpour, Behnam

2018-05-01

We propose a new pilot points method for conditioning discrete multiple-point statistical (MPS) facies simulation on dynamic flow data. While conditioning MPS simulation on static hard data is straightforward, their calibration against nonlinear flow data is nontrivial. The proposed method generates conditional models from a conceptual model of geologic connectivity, known as a training image (TI), by strategically placing and estimating pilot points. To place pilot points, a score map is generated based on three sources of information: (i) the uncertainty in facies distribution, (ii) the model response sensitivity information, and (iii) the observed flow data. Once the pilot points are placed, the facies values at these points are inferred from production data and then are used, along with available hard data at well locations, to simulate a new set of conditional facies realizations. While facies estimation at the pilot points can be performed using different inversion algorithms, in this study the ensemble smoother (ES) is adopted to update permeability maps from production data, which are then used to statistically infer facies types at the pilot point locations. The developed method combines the information in the flow data and the TI by using the former to infer facies values at selected locations away from the wells and the latter to ensure consistent facies structure and connectivity where away from measurement locations. Several numerical experiments are used to evaluate the performance of the developed method and to discuss its important properties.

Assimilating Flow Data into Complex Multiple-Point Statistical Facies Models Using Pilot Points Method

NASA Astrophysics Data System (ADS)

Ma, W.; Jafarpour, B.

2017-12-01

We develop a new pilot points method for conditioning discrete multiple-point statistical (MPS) facies simulation on dynamic flow data. While conditioning MPS simulation on static hard data is straightforward, their calibration against nonlinear flow data is nontrivial. The proposed method generates conditional models from a conceptual model of geologic connectivity, known as a training image (TI), by strategically placing and estimating pilot points. To place pilot points, a score map is generated based on three sources of information:: (i) the uncertainty in facies distribution, (ii) the model response sensitivity information, and (iii) the observed flow data. Once the pilot points are placed, the facies values at these points are inferred from production data and are used, along with available hard data at well locations, to simulate a new set of conditional facies realizations. While facies estimation at the pilot points can be performed using different inversion algorithms, in this study the ensemble smoother (ES) and its multiple data assimilation variant (ES-MDA) are adopted to update permeability maps from production data, which are then used to statistically infer facies types at the pilot point locations. The developed method combines the information in the flow data and the TI by using the former to infer facies values at select locations away from the wells and the latter to ensure consistent facies structure and connectivity where away from measurement locations. Several numerical experiments are used to evaluate the performance of the developed method and to discuss its important properties.

A unified procedure for meta-analytic evaluation of surrogate end points in randomized clinical trials

PubMed Central

Dai, James Y.; Hughes, James P.

2012-01-01

The meta-analytic approach to evaluating surrogate end points assesses the predictiveness of treatment effect on the surrogate toward treatment effect on the clinical end point based on multiple clinical trials. Definition and estimation of the correlation of treatment effects were developed in linear mixed models and later extended to binary or failure time outcomes on a case-by-case basis. In a general regression setting that covers nonnormal outcomes, we discuss in this paper several metrics that are useful in the meta-analytic evaluation of surrogacy. We propose a unified 3-step procedure to assess these metrics in settings with binary end points, time-to-event outcomes, or repeated measures. First, the joint distribution of estimated treatment effects is ascertained by an estimating equation approach; second, the restricted maximum likelihood method is used to estimate the means and the variance components of the random treatment effects; finally, confidence intervals are constructed by a parametric bootstrap procedure. The proposed method is evaluated by simulations and applications to 2 clinical trials. PMID:22394448

Online machining error estimation method of numerical control gear grinding machine tool based on data analysis of internal sensors

NASA Astrophysics Data System (ADS)

Zhao, Fei; Zhang, Chi; Yang, Guilin; Chen, Chinyin

2016-12-01

This paper presents an online estimation method of cutting error by analyzing of internal sensor readings. The internal sensors of numerical control (NC) machine tool are selected to avoid installation problem. The estimation mathematic model of cutting error was proposed to compute the relative position of cutting point and tool center point (TCP) from internal sensor readings based on cutting theory of gear. In order to verify the effectiveness of the proposed model, it was simulated and experimented in gear generating grinding process. The cutting error of gear was estimated and the factors which induce cutting error were analyzed. The simulation and experiments verify that the proposed approach is an efficient way to estimate the cutting error of work-piece during machining process.

Estimating the Triple-Point Isotope Effect and the Corresponding Uncertainties for Cryogenic Fixed Points

NASA Astrophysics Data System (ADS)

Tew, W. L.

2008-02-01

The sensitivities of melting temperatures to isotopic variations in monatomic and diatomic atmospheric gases using both theoretical and semi-empirical methods are estimated. The current state of knowledge of the vapor-pressure isotope effects (VPIE) and triple-point isotope effects (TPIE) is briefly summarized for the noble gases (except He), and for selected diatomic molecules including oxygen. An approximate expression is derived to estimate the relative shift in the melting temperature with isotopic substitution. In general, the magnitude of the effects diminishes with increasing molecular mass and increasing temperature. Knowledge of the VPIE, molar volumes, and heat of fusion are sufficient to estimate the temperature shift or isotopic sensitivity coefficient via the derived expression. The usefulness of this approach is demonstrated in the estimation of isotopic sensitivities and uncertainties for triple points of xenon and molecular oxygen for which few documented estimates were previously available. The calculated sensitivities from this study are considerably higher than previous estimates for Xe, and lower than other estimates in the case of oxygen. In both these cases, the predicted sensitivities are small and the resulting variations in triple point temperatures due to mass fractionation effects are less than 20 μK.

A method for estimating mount isolations of powertrain mounting systems

NASA Astrophysics Data System (ADS)

Qin, Wu; Shangguan, Wen-Bin; Luo, Guohai; Xie, Zhengchao

2018-07-01

A method for calculating isolation ratios of mounts at a powertrain mounting systems (PMS) is proposed assuming a powertrain as a rigid body and using the identified powertrain excitation forces and the measured IPI (input point inertance) of mounting points at the body side. With measured accelerations of mounts at powertrain and body sides of one Vehicle (Vehicle A), the excitation forces of a powertrain are identified using conversational method firstly. Another Vehicle (Vehicle B) has the same powertrain as that of Vehicle A, but with different body and mount configuration. The accelerations of mounts at powertrain side of a PMS on Vehicle B are calculated using the powertrain excitation forces identified from Vehicle A. The identified forces of the powertrain are validated by comparing the calculated and the measured accelerations of mounts at the powertrain side of the powertrain on Vehicle B. A method for calculating acceleration of mounting point at body side for Vehicle B is presented using the identified powertrain excitation forces and the measured IPI at a connecting point between car body and mount. Using the calculated accelerations of mounts at powertrain side and body side at different directions, the isolation ratios of a mount are then estimated. The isolation ratios are validated using the experiment, which verified the proposed methods for estimating isolation ratios of mounts. The developed method is beneficial for optimizing mount stiffness to meet mount isolation requirements before prototype.

Determination of efficiency of an aged HPGe detector for gaseous sources by self absorption correction and point source methods

NASA Astrophysics Data System (ADS)

Sarangapani, R.; Jose, M. T.; Srinivasan, T. K.; Venkatraman, B.

2017-07-01

Methods for the determination of efficiency of an aged high purity germanium (HPGe) detector for gaseous sources have been presented in the paper. X-ray radiography of the detector has been performed to get detector dimensions for computational purposes. The dead layer thickness of HPGe detector has been ascertained from experiments and Monte Carlo computations. Experimental work with standard point and liquid sources in several cylindrical geometries has been undertaken for obtaining energy dependant efficiency. Monte Carlo simulations have been performed for computing efficiencies for point, liquid and gaseous sources. Self absorption correction factors have been obtained using mathematical equations for volume sources and MCNP simulations. Self-absorption correction and point source methods have been used to estimate the efficiency for gaseous sources. The efficiencies determined from the present work have been used to estimate activity of cover gas sample of a fast reactor.

Coherent-Anomaly Method in Critical Phenomena. III. Mean-Field Transfer-Matrix Method in the 2D Ising Model

NASA Astrophysics Data System (ADS)

Hu, Xiao; Katori, Makoto; Suzuki, Masuo

1987-11-01

Two kinds of systematic mean-field transfer-matrix methods are formulated in the 2-dimensional Ising spin system, by introducing Weiss-like and Bethe-like approximations. All the critical exponents as well as the true critical point can be estimated in these methods following the CAM procedure. The numerical results of the above system are Tc*≃2.271 (J/kB), γ{=}γ'≃1.749, β≃0.131 and δ≃15.1. The specific heat is confirmd to be continuous and to have a logarithmic divergence at the true critical point, i.e., α{=}α'{=}0. Thus, the finite-degree-of-approximation scaling ansatz is shown to be correct and very powerful in practical estimations of the critical exponents as well as the true critical point.

Use of screening tests to assess cancer risk and to estimate the risk of adult T-cell leukemia/lymphoma.

PubMed Central

Yanagawa, T; Tokudome, S

1990-01-01

We developed methods to assess the cancer risks by screening tests. These methods estimate the size of the high risk group adjusted for the characteristics of screening tests and estimate the incidence rates of cancer among the high risk group adjusted for the characteristics of the tests. A method was also developed for selecting the cut-off point of a screening test. Finally, the methods were applied to estimate the risk of the adult T-cell leukemia/lymphoma. PMID:2269244

Comparison of least squares and exponential sine sweep methods for Parallel Hammerstein Models estimation

NASA Astrophysics Data System (ADS)

Rebillat, Marc; Schoukens, Maarten

2018-05-01

Linearity is a common assumption for many real-life systems, but in many cases the nonlinear behavior of systems cannot be ignored and must be modeled and estimated. Among the various existing classes of nonlinear models, Parallel Hammerstein Models (PHM) are interesting as they are at the same time easy to interpret as well as to estimate. One way to estimate PHM relies on the fact that the estimation problem is linear in the parameters and thus that classical least squares (LS) estimation algorithms can be used. In that area, this article introduces a regularized LS estimation algorithm inspired on some of the recently developed regularized impulse response estimation techniques. Another mean to estimate PHM consists in using parametric or non-parametric exponential sine sweeps (ESS) based methods. These methods (LS and ESS) are founded on radically different mathematical backgrounds but are expected to tackle the same issue. A methodology is proposed here to compare them with respect to (i) their accuracy, (ii) their computational cost, and (iii) their robustness to noise. Tests are performed on simulated systems for several values of methods respective parameters and of signal to noise ratio. Results show that, for a given set of data points, the ESS method is less demanding in computational resources than the LS method but that it is also less accurate. Furthermore, the LS method needs parameters to be set in advance whereas the ESS method is not subject to conditioning issues and can be fully non-parametric. In summary, for a given set of data points, ESS method can provide a first, automatic, and quick overview of a nonlinear system than can guide more computationally demanding and precise methods, such as the regularized LS one proposed here.

Simultaneous estimation of cross-validation errors in least squares collocation applied for statistical testing and evaluation of the noise variance components

NASA Astrophysics Data System (ADS)

Behnabian, Behzad; Mashhadi Hossainali, Masoud; Malekzadeh, Ahad

2018-02-01

The cross-validation technique is a popular method to assess and improve the quality of prediction by least squares collocation (LSC). We present a formula for direct estimation of the vector of cross-validation errors (CVEs) in LSC which is much faster than element-wise CVE computation. We show that a quadratic form of CVEs follows Chi-squared distribution. Furthermore, a posteriori noise variance factor is derived by the quadratic form of CVEs. In order to detect blunders in the observations, estimated standardized CVE is proposed as the test statistic which can be applied when noise variances are known or unknown. We use LSC together with the methods proposed in this research for interpolation of crustal subsidence in the northern coast of the Gulf of Mexico. The results show that after detection and removing outliers, the root mean square (RMS) of CVEs and estimated noise standard deviation are reduced about 51 and 59%, respectively. In addition, RMS of LSC prediction error at data points and RMS of estimated noise of observations are decreased by 39 and 67%, respectively. However, RMS of LSC prediction error on a regular grid of interpolation points covering the area is only reduced about 4% which is a consequence of sparse distribution of data points for this case study. The influence of gross errors on LSC prediction results is also investigated by lower cutoff CVEs. It is indicated that after elimination of outliers, RMS of this type of errors is also reduced by 19.5% for a 5 km radius of vicinity. We propose a method using standardized CVEs for classification of dataset into three groups with presumed different noise variances. The noise variance components for each of the groups are estimated using restricted maximum-likelihood method via Fisher scoring technique. Finally, LSC assessment measures were computed for the estimated heterogeneous noise variance model and compared with those of the homogeneous model. The advantage of the proposed method is the reduction in estimated noise levels for those groups with the fewer number of noisy data points.

Cross-correlation of point series using a new method

NASA Technical Reports Server (NTRS)

Strothers, Richard B.

1994-01-01

Traditional methods of cross-correlation of two time series do not apply to point time series. Here, a new method, devised specifically for point series, utilizes a correlation measure that is based in the rms difference (or, alternatively, the median absolute difference) between nearest neightbors in overlapped segments of the two series. Error estimates for the observed locations of the points, as well as a systematic shift of one series with respect to the other to accommodate a constant, but unknown, lead or lag, are easily incorporated into the analysis using Monte Carlo techniques. A methodological restriction adopted here is that one series be treated as a template series against which the other, called the target series, is cross-correlated. To estimate a significance level for the correlation measure, the adopted alternative (null) hypothesis is that the target series arises from a homogeneous Poisson process. The new method is applied to cross-correlating the times of the greatest geomagnetic storms with the times of maximum in the undecennial solar activity cycle.

Benchmark Dose for Urinary Cadmium based on a Marker of Renal Dysfunction: A Meta-Analysis

PubMed Central

Woo, Hae Dong; Chiu, Weihsueh A.; Jo, Seongil; Kim, Jeongseon

2015-01-01

Background Low doses of cadmium can cause adverse health effects. Benchmark dose (BMD) and the one-sided 95% lower confidence limit of BMD (BMDL) to derive points of departure for urinary cadmium exposure have been estimated in several previous studies, but the methods to derive BMD and the estimated BMDs differ. Objectives We aimed to find the associated factors that affect BMD calculation in the general population, and to estimate the summary BMD for urinary cadmium using reported BMDs. Methods A meta-regression was performed and the pooled BMD/BMDL was estimated using studies reporting a BMD and BMDL, weighted by sample size, that were calculated from individual data based on markers of renal dysfunction. Results BMDs were highly heterogeneous across studies. Meta-regression analysis showed that a significant predictor of BMD was the cut-off point which denotes an abnormal level. Using the 95th percentile as a cut off, BMD5/BMDL5 estimates for 5% benchmark responses (BMR) of β2-microglobulinuria (β2-MG) estimated was 6.18/4.88 μg/g creatinine in conventional quantal analysis and 3.56/3.13 μg/g creatinine in the hybrid approach, and BMD5/BMDL5 estimates for 5% BMR of N-acetyl-β-d-glucosaminidase (NAG) was 10.31/7.61 μg/g creatinine in quantal analysis and 3.21/2.24 g/g creatinine in the hybrid approach. However, the meta-regression showed that BMD and BMDL were significantly associated with the cut-off point, but BMD calculation method did not significantly affect the results. The urinary cadmium BMDL5 of β2-MG was 1.9 μg/g creatinine in the lowest cut-off point group. Conclusion The BMD was significantly associated with the cut-off point defining the abnormal level of renal dysfunction markers. PMID:25970611

Precise determination of time to reach viral load set point after acute HIV-1 infection.

PubMed

Huang, Xiaojie; Chen, Hui; Li, Wei; Li, Haiying; Jin, Xia; Perelson, Alan S; Fox, Zoe; Zhang, Tong; Xu, Xiaoning; Wu, Hao

2012-12-01

The HIV viral load set point has long been used as a prognostic marker of disease progression and more recently as an end-point parameter in HIV vaccine clinical trials. The definition of set point, however, is variable. Moreover, the earliest time at which the set point is reached after the onset of infection has never been clearly defined. In this study, we obtained sequential plasma viral load data from 60 acutely HIV-infected Chinese patients among a cohort of men who have sex with men, mathematically determined viral load set point levels, and estimated time to attain set point after infection. We also compared the results derived from our models and that obtained from an empirical method. With novel uncomplicated mathematic model, we discovered that set points may vary from 21 to 119 days dependent on the patients' initial viral load trajectory. The viral load set points were 4.28 ± 0.86 and 4.25 ± 0.87 log10 copies per milliliter (P = 0.08), respectively, as determined by our model and an empirical method, suggesting an excellent agreement between the old and new methods. We provide a novel method to estimate viral load set point at the very early stage of HIV infection. Application of this model can accurately and reliably determine the set point, thus providing a new tool for physicians to better monitor early intervention strategies in acutely infected patients and scientists to rationally design preventative vaccine studies.

Computational circular dichroism estimation for point-of-care diagnostics via vortex half-wave retarders

NASA Astrophysics Data System (ADS)

Haider, Shahid A.; Tran, Megan Y.; Wong, Alexander

2018-02-01

Observing the circular dichroism (CD) caused by organic molecules in biological fluids can provide powerful indicators of patient health and provide diagnostic clues for treatment. Methods for this kind of analysis involve tabletop devices that weigh tens of kilograms with costs on the order of tens of thousands of dollars, making them prohibitive in point-of-care diagnostic applications. In an e ort to reduce the size, cost, and complexity of CD estimation systems for point-of-care diagnostics, we propose a novel method for CD estimation that leverages a vortex half-wave retarder in between two linear polarizers and a two-dimensional photodetector array to provide an overall complexity reduction in the system. This enables the measurement of polarization variations across multiple polarizations after they interact with a biological sample, simultaneously, without the need for mechanical actuation. We further discuss design considerations of this methodology in the context of practical applications to point-of-care diagnostics.

Estimation of cylinder orientation in three-dimensional point cloud using angular distance-based optimization

NASA Astrophysics Data System (ADS)

Su, Yun-Ting; Hu, Shuowen; Bethel, James S.

2017-05-01

Light detection and ranging (LIDAR) has become a widely used tool in remote sensing for mapping, surveying, modeling, and a host of other applications. The motivation behind this work is the modeling of piping systems in industrial sites, where cylinders are the most common primitive or shape. We focus on cylinder parameter estimation in three-dimensional point clouds, proposing a mathematical formulation based on angular distance to determine the cylinder orientation. We demonstrate the accuracy and robustness of the technique on synthetically generated cylinder point clouds (where the true axis orientation is known) as well as on real LIDAR data of piping systems. The proposed algorithm is compared with a discrete space Hough transform-based approach as well as a continuous space inlier approach, which iteratively discards outlier points to refine the cylinder parameter estimates. Results show that the proposed method is more computationally efficient than the Hough transform approach and is more accurate than both the Hough transform approach and the inlier method.

Second Iteration of Photogrammetric Pipeline to Enhance the Accuracy of Image Pose Estimation

NASA Astrophysics Data System (ADS)

Nguyen, T. G.; Pierrot-Deseilligny, M.; Muller, J.-M.; Thom, C.

2017-05-01

In classical photogrammetric processing pipeline, the automatic tie point extraction plays a key role in the quality of achieved results. The image tie points are crucial to pose estimation and have a significant influence on the precision of calculated orientation parameters. Therefore, both relative and absolute orientations of the 3D model can be affected. By improving the precision of image tie point measurement, one can enhance the quality of image orientation. The quality of image tie points is under the influence of several factors such as the multiplicity, the measurement precision and the distribution in 2D images as well as in 3D scenes. In complex acquisition scenarios such as indoor applications and oblique aerial images, tie point extraction is limited while only image information can be exploited. Hence, we propose here a method which improves the precision of pose estimation in complex scenarios by adding a second iteration to the classical processing pipeline. The result of a first iteration is used as a priori information to guide the extraction of new tie points with better quality. Evaluated with multiple case studies, the proposed method shows its validity and its high potiential for precision improvement.

Finite element method modeling to assess Laplacian estimates via novel variable inter-ring distances concentric ring electrodes.

PubMed

Makeyev, Oleksandr; Besio, Walter G

2016-08-01

Noninvasive concentric ring electrodes are a promising alternative to conventional disc electrodes. Currently, superiority of tripolar concentric ring electrodes over disc electrodes, in particular, in accuracy of Laplacian estimation has been demonstrated in a range of applications. In our recent work we have shown that accuracy of Laplacian estimation can be improved with multipolar concentric ring electrodes using a general approach to estimation of the Laplacian for an (n + 1)-polar electrode with n rings using the (4n + 1)-point method for n ≥ 2. This paper takes the next step toward further improving the Laplacian estimate by proposing novel variable inter-ring distances concentric ring electrodes. Derived using a modified (4n + 1)-point method, linearly increasing and decreasing inter-ring distances tripolar (n = 2) and quadripolar (n = 3) electrode configurations are compared to their constant inter-ring distances counterparts using finite element method modeling. Obtained results suggest that increasing inter-ring distances electrode configurations may decrease the estimation error resulting in more accurate Laplacian estimates compared to respective constant inter-ring distances configurations. For currently used tripolar electrode configuration the estimation error may be decreased more than two-fold while for the quadripolar configuration more than six-fold decrease is expected.

Combined point and distributed techniques for multidimensional estimation of spatial groundwater-stream water exchange in a heterogeneous sand bed-stream.

NASA Astrophysics Data System (ADS)

Gaona Garcia, J.; Lewandowski, J.; Bellin, A.

2017-12-01

Groundwater-stream water interactions in rivers determine water balances, but also chemical and biological processes in the streambed at different spatial and temporal scales. Due to the difficult identification and quantification of gaining, neutral and losing conditions, it is necessary to combine techniques with complementary capabilities and scale ranges. We applied this concept to a study site at the River Schlaube, East Brandenburg-Germany, a sand bed stream with intense sediment heterogeneity and complex environmental conditions. In our approach, point techniques such as temperature profiles of the streambed together with vertical hydraulic gradients provide data for the estimation of fluxes between groundwater and surface water with the numerical model 1DTempPro. On behalf of distributed techniques, fiber optic distributed temperature sensing identifies the spatial patterns of neutral, down- and up-welling areas by analysis of the changes in the thermal patterns at the streambed interface under certain flow. The study finally links point and surface temperatures to provide a method for upscaling of fluxes. Point techniques provide point flux estimates with essential depth detail to infer streambed structures while the results hardly represent the spatial distribution of fluxes caused by the heterogeneity of streambed properties. Fiber optics proved capable of providing spatial thermal patterns with enough resolution to observe distinct hyporheic thermal footprints at multiple scales. The relation of thermal footprint patterns and temporal behavior with flux results from point techniques enabled the use of methods for spatial flux estimates. The lack of detailed information of the physical driver's spatial distribution restricts the spatial flux estimation to the application of the T-proxy method, whose highly uncertain results mainly provide coarse spatial flux estimates. The study concludes that the upscaling of groundwater-stream water interactions using thermal measurements with combined point and distributed techniques requires the integration of physical drivers because of the heterogeneity of the flux patterns. Combined experimental and modeling approaches may help to obtain more reliable understanding of groundwater-surface water interactions at multiple scales.

FPA Depot - Web Application

NASA Technical Reports Server (NTRS)

Avila, Edwin M. Martinez; Muniz, Ricardo; Szafran, Jamie; Dalton, Adam

2011-01-01

Lines of code (LOC) analysis is one of the methods used to measure programmer productivity and estimate schedules of programming projects. The Launch Control System (LCS) had previously used this method to estimate the amount of work and to plan development efforts. The disadvantage of using LOC as a measure of effort is that one can only measure 30% to 35% of the total effort of software projects involves coding [8]. In the application, instead of using the LOC we are using function point for a better estimation of hours in each software to develop. Because of these disadvantages, Jamie Szafran of the System Software Branch of Control And Data Systems (NE-C3) at Kennedy Space Canter developed a web application called Function Point Analysis (FPA) Depot. The objective of this web application is that the LCS software architecture team can use the data to more accurately estimate the effort required to implement customer requirements. This paper describes the evolution of the domain model used for function point analysis as project managers continually strive to generate more accurate estimates.

Upscaling with data assimilation in soil hydrology

USDA-ARS?s Scientific Manuscript database

Most of measurements in soil hydrology are point-based, and methods are needed to use the point-based data for estimating soil water contents at larger societally-important scales, such as field, hillslope or watershed. One group of appropriate methods involves data assimilation which is a methodolo...

Coherent-Anomaly Method in Critical Phenomena. III.

NASA Astrophysics Data System (ADS)

Hu, Xiao; Katori, Makoto; Suzuki, Masuo

Two kinds of systematic mean-field transfer-matrix methods are formulated in the 2-dimensional Ising spin system, by introducing Weiss-like and Bethe-like approximations. All the critical exponents as well as the true critical point can be estimated in these methods following the CAM procedure. The numerical results of the above system are Tc* = 2.271 (J/kB), γ=γ' ≃ 1.749, β≃0.131 and δ ≃ 15.1. The specific heat is confirmed to be continuous and to have a logarithmic divergence at the true critical point, i.e., α=α'=0. Thus, the finite-degree-of-approximation scaling ansatz is shown to be correct and very powerful in practical estimations of the critical exponents as well as the true critical point.

Statistical aspects of point count sampling

USGS Publications Warehouse

Barker, R.J.; Sauer, J.R.; Ralph, C.J.; Sauer, J.R.; Droege, S.

1995-01-01

The dominant feature of point counts is that they do not census birds, but instead provide incomplete counts of individuals present within a survey plot. Considering a simple model for point count sampling, we demon-strate that use of these incomplete counts can bias estimators and testing procedures, leading to inappropriate conclusions. A large portion of the variability in point counts is caused by the incomplete counting, and this within-count variation can be confounded with ecologically meaningful varia-tion. We recommend caution in the analysis of estimates obtained from point counts. Using; our model, we also consider optimal allocation of sampling effort. The critical step in the optimization process is in determining the goals of the study and methods that will be used to meet these goals. By explicitly defining the constraints on sampling and by estimating the relationship between precision and bias of estimators and time spent counting, we can predict the optimal time at a point for each of several monitoring goals. In general, time spent at a point will differ depending on the goals of the study.

Automatic registration of terrestrial point clouds based on panoramic reflectance images and efficient BaySAC

NASA Astrophysics Data System (ADS)

Kang, Zhizhong

2013-10-01

This paper presents a new approach to automatic registration of terrestrial laser scanning (TLS) point clouds utilizing a novel robust estimation method by an efficient BaySAC (BAYes SAmpling Consensus). The proposed method directly generates reflectance images from 3D point clouds, and then using SIFT algorithm extracts keypoints to identify corresponding image points. The 3D corresponding points, from which transformation parameters between point clouds are computed, are acquired by mapping the 2D ones onto the point cloud. To remove false accepted correspondences, we implement a conditional sampling method to select the n data points with the highest inlier probabilities as a hypothesis set and update the inlier probabilities of each data point using simplified Bayes' rule for the purpose of improving the computation efficiency. The prior probability is estimated by the verification of the distance invariance between correspondences. The proposed approach is tested on four data sets acquired by three different scanners. The results show that, comparing with the performance of RANSAC, BaySAC leads to less iterations and cheaper computation cost when the hypothesis set is contaminated with more outliers. The registration results also indicate that, the proposed algorithm can achieve high registration accuracy on all experimental datasets.

Prediction of Sublimation Pressures of Low Volatility Solids

NASA Astrophysics Data System (ADS)

Drake, Bruce Douglas

Sublimation pressures are required for solid-vapor phase equilibrium models in design of processes such as supercritical fluid extraction, sublimation purification and vapor epitaxy. The objective of this work is to identify and compare alternative methods for predicting sublimation pressures. A bibliography of recent sublimation data is included. Corresponding states methods based on the triple point (rather than critical point) are examined. A modified Trouton's rule is the preferred method for estimating triple point pressure in the absence of any sublimation data. Only boiling and melting temperatures are required. Typical error in log_{10} P _{rm triple} is 0.3. For lower temperature estimates, the slope of the sublimation curve is predicted by a correlation based on molar volume. Typical error is 10% of slope. Molecular dynamics methods for surface modeling are tested as estimators of vapor pressure. The time constants of the vapor and solid phases are too different to allow the vapor to come to thermal equilibrium with the solid. The method shows no advantages in prediction of sublimation pressure but provides insight into appropriate models and experimental methods for sublimation. Density-dependent augmented van der Waals equations of state based on hard-sphere distribution functions are examined. The perturbation term is almost linear and is well fit by a simple quadratic. Use of the equation provides reasonable fitting of sublimation pressures from one data point. Order-of-magnitude estimation is possible from melting temperature and solid molar volume. The inverse -12 fluid is used to develop an additional equation of state. Sublimation pressure results, including quality of pressure predictions, are similar to the hard-sphere results. Three-body (Axilrod -Teller) interactions are used to improve results.

Assessment of maxillary position. Implant vs cephalometric methods.

PubMed

Verayannont, Panisha; Hägg, Urban; Wong, Ricky W K; McGrath, Colman; Yeung, Shadow

2010-09-01

To compare changes in maxillary position assessed from a maxillary implant and three cephalometric methods based on linear measurements. Series of tracings of the maxilla obtained around puberty from an implant study were analyzed. The displacement of the implant was used to determine the direction and amount of "actual" maxillary growth. Displacement of point A was measured according to three cephalometric methods. The values obtained from absolute, horizontal, and vertical displacement of point A by three cephalometric methods and by the implant method were compared. Results showed that estimation of displacement of the maxilla by three cephalometric methods (point A) was significantly larger than that of the implant method in all directions. The average difference in the horizontal plane was 0.7 mm, 1.2 mm, and 1.6 mm, respectively; the average difference in the vertical plane was 2.2 mm, 2.5 mm, and 3.6 mm, respectively. Estimations of changes in maxillary position by the implant method and by cephalometric methods were not proportional. All three cephalometric methods overestimated changes in the position of the maxilla.

A New Global Regression Analysis Method for the Prediction of Wind Tunnel Model Weight Corrections

NASA Technical Reports Server (NTRS)

Ulbrich, Norbert Manfred; Bridge, Thomas M.; Amaya, Max A.

2014-01-01

A new global regression analysis method is discussed that predicts wind tunnel model weight corrections for strain-gage balance loads during a wind tunnel test. The method determines corrections by combining "wind-on" model attitude measurements with least squares estimates of the model weight and center of gravity coordinates that are obtained from "wind-off" data points. The method treats the least squares fit of the model weight separate from the fit of the center of gravity coordinates. Therefore, it performs two fits of "wind- off" data points and uses the least squares estimator of the model weight as an input for the fit of the center of gravity coordinates. Explicit equations for the least squares estimators of the weight and center of gravity coordinates are derived that simplify the implementation of the method in the data system software of a wind tunnel. In addition, recommendations for sets of "wind-off" data points are made that take typical model support system constraints into account. Explicit equations of the confidence intervals on the model weight and center of gravity coordinates and two different error analyses of the model weight prediction are also discussed in the appendices of the paper.

New spatial upscaling methods for multi-point measurements: From normal to p-normal

NASA Astrophysics Data System (ADS)

Liu, Feng; Li, Xin

2017-12-01

Careful attention must be given to determining whether the geophysical variables of interest are normally distributed, since the assumption of a normal distribution may not accurately reflect the probability distribution of some variables. As a generalization of the normal distribution, the p-normal distribution and its corresponding maximum likelihood estimation (the least power estimation, LPE) were introduced in upscaling methods for multi-point measurements. Six methods, including three normal-based methods, i.e., arithmetic average, least square estimation, block kriging, and three p-normal-based methods, i.e., LPE, geostatistics LPE and inverse distance weighted LPE are compared in two types of experiments: a synthetic experiment to evaluate the performance of the upscaling methods in terms of accuracy, stability and robustness, and a real-world experiment to produce real-world upscaling estimates using soil moisture data obtained from multi-scale observations. The results show that the p-normal-based methods produced lower mean absolute errors and outperformed the other techniques due to their universality and robustness. We conclude that introducing appropriate statistical parameters into an upscaling strategy can substantially improve the estimation, especially if the raw measurements are disorganized; however, further investigation is required to determine which parameter is the most effective among variance, spatial correlation information and parameter p.

Mixed-Poisson Point Process with Partially-Observed Covariates: Ecological Momentary Assessment of Smoking.

PubMed

Neustifter, Benjamin; Rathbun, Stephen L; Shiffman, Saul

2012-01-01

Ecological Momentary Assessment is an emerging method of data collection in behavioral research that may be used to capture the times of repeated behavioral events on electronic devices, and information on subjects' psychological states through the electronic administration of questionnaires at times selected from a probability-based design as well as the event times. A method for fitting a mixed Poisson point process model is proposed for the impact of partially-observed, time-varying covariates on the timing of repeated behavioral events. A random frailty is included in the point-process intensity to describe variation among subjects in baseline rates of event occurrence. Covariate coefficients are estimated using estimating equations constructed by replacing the integrated intensity in the Poisson score equations with a design-unbiased estimator. An estimator is also proposed for the variance of the random frailties. Our estimators are robust in the sense that no model assumptions are made regarding the distribution of the time-varying covariates or the distribution of the random effects. However, subject effects are estimated under gamma frailties using an approximate hierarchical likelihood. The proposed approach is illustrated using smoking data.

Self-position estimation using terrain shadows for precise planetary landing

NASA Astrophysics Data System (ADS)

Kuga, Tomoki; Kojima, Hirohisa

2018-07-01

In recent years, the investigation of moons and planets has attracted increasing attention in several countries. Furthermore, recently developed landing systems are now expected to reach more scientifically interesting areas close to hazardous terrain, requiring precise landing capabilities within a 100 m range of the target point. To achieve this, terrain-relative navigation (capable of estimating the position of a lander relative to the target point on the ground surface is actively being studied as an effective method for achieving highly accurate landings. This paper proposes a self-position estimation method using shadows on the terrain based on edge extraction from image processing algorithms. The effectiveness of the proposed method is validated through numerical simulations using images generated from a digital elevation model of simulated terrains.

Development of Quadratic Programming Algorithm Based on Interior Point Method with Estimation Mechanism of Active Constraints

NASA Astrophysics Data System (ADS)

Hashimoto, Hiroyuki; Takaguchi, Yusuke; Nakamura, Shizuka

Instability of calculation process and increase of calculation time caused by increasing size of continuous optimization problem remain the major issues to be solved to apply the technique to practical industrial systems. This paper proposes an enhanced quadratic programming algorithm based on interior point method mainly for improvement of calculation stability. The proposed method has dynamic estimation mechanism of active constraints on variables, which fixes the variables getting closer to the upper/lower limit on them and afterwards releases the fixed ones as needed during the optimization process. It is considered as algorithm-level integration of the solution strategy of active-set method into the interior point method framework. We describe some numerical results on commonly-used bench-mark problems called “CUTEr” to show the effectiveness of the proposed method. Furthermore, the test results on large-sized ELD problem (Economic Load Dispatching problems in electric power supply scheduling) are also described as a practical industrial application.

Retrieving air humidity, global solar radiation, and reference evapotranspiration from daily temperatures: development and validation of new methods for Mexico. Part I: humidity

NASA Astrophysics Data System (ADS)

Lobit, P.; López Pérez, L.; Lhomme, J. P.; Gómez Tagle, A.

2017-07-01

This study evaluates the dew point method (Allen et al. 1998) to estimate atmospheric vapor pressure from minimum temperature, and proposes an improved model to estimate it from maximum and minimum temperature. Both methods were evaluated on 786 weather stations in Mexico. The dew point method induced positive bias in dry areas but also negative bias in coastal areas, and its average root mean square error for all evaluated stations was 0.38 kPa. The improved model assumed a bi-linear relation between estimated vapor pressure deficit (difference between saturated vapor pressure at minimum and average temperature) and measured vapor pressure deficit. The parameters of these relations were estimated from historical annual median values of relative humidity. This model removed bias and allowed for a root mean square error of 0.31 kPa. When no historical measurements of relative humidity were available, empirical relations were proposed to estimate it from latitude and altitude, with only a slight degradation on the model accuracy (RMSE = 0.33 kPa, bias = -0.07 kPa). The applicability of the method to other environments is discussed.

Parametrization of semiempirical models against ab initio crystal data: evaluation of lattice energies of nitrate salts.

PubMed

Beaucamp, Sylvain; Mathieu, Didier; Agafonov, Viatcheslav

2005-09-01

A method to estimate the lattice energies E(latt) of nitrate salts is put forward. First, E(latt) is approximated by its electrostatic component E(elec). Then, E(elec) is correlated with Mulliken atomic charges calculated on the species that make up the crystal, using a simple equation involving two empirical parameters. The latter are fitted against point charge estimates of E(elec) computed on available X-ray structures of nitrate crystals. The correlation thus obtained yields lattice energies within 0.5 kJ/g from point charge values. A further assessment of the method against experimental data suggests that the main source of error arises from the point charge approximation.

Similar negative impacts of temperature on global wheat yield estimated by three independent methods

USDA-ARS?s Scientific Manuscript database

The potential impact of global temperature change on global wheat production has recently been assessed with different methods, scaling and aggregation approaches. Here we show that grid-based simulations, point-based simulations, and statistical regressions produce similar estimates of temperature ...

Lidar method to estimate emission rates from extended sources

USDA-ARS?s Scientific Manuscript database

Currently, point measurements, often combined with models, are the primary means by which atmospheric emission rates are estimated from extended sources. However, these methods often fall short in their spatial and temporal resolution and accuracy. In recent years, lidar has emerged as a suitable to...

Advantages of estimating parameters of photosynthesis model by fitting A-Ci curves at multiple subsaturating light intensities

NASA Astrophysics Data System (ADS)

Fu, W.; Gu, L.; Hoffman, F. M.

2013-12-01

The photosynthesis model of Farquhar, von Caemmerer & Berry (1980) is an important tool for predicting the response of plants to climate change. So far, the critical parameters required by the model have been obtained from the leaf-level measurements of gas exchange, namely the net assimilation of CO2 against intercellular CO2 concentration (A-Ci) curves, made at saturating light conditions. With such measurements, most points are likely in the Rubisco-limited state for which the model is structurally overparameterized (the model is also overparameterized in the TPU-limited state). In order to reliably estimate photosynthetic parameters, there must be sufficient number of points in the RuBP regeneration-limited state, which has no structural over-parameterization. To improve the accuracy of A-Ci data analysis, we investigate the potential of using multiple A-Ci curves at subsaturating light intensities to generate some important parameter estimates more accurately. Using subsaturating light intensities allow more RuBp regeneration-limited points to be obtained. In this study, simulated examples are used to demonstrate how this method can eliminate the errors of conventional A-Ci curve fitting methods. Some fitted parameters like the photocompensation point and day respiration impose a significant limitation on modeling leaf CO2 exchange. The multiple A-Ci curves fitting can also improve over the so-called Laisk (1977) method, which was shown by some recent publication to produce incorrect estimates of photocompensation point and day respiration. We also test the approach with actual measurements, along with suggested measurement conditions to constrain measured A-Ci points to maximize the occurrence of RuBP regeneration-limited photosynthesis. Finally, we use our measured gas exchange datasets to quantify the magnitude of resistance of chloroplast and cell wall-plasmalemma and explore the effect of variable mesophyll conductance. The variable mesophyll conductance takes into account the influence of CO2 from mitochondria, comparing to the commonly used constant value of mesophyll conductance. We show that after considering this effect the other parameters of the photosynthesis model can be re-estimated. Our results indicate that variable mesophyll conductance has most effect on the estimation of the parameter of the maximum electron transport rate (Jmax), but has a negligible impact on the estimated day respiration (Rd) and photocompensation point (<2%).

Investigating Surface and Near-Surface Bushfire Fuel Attributes: A Comparison between Visual Assessments and Image-Based Point Clouds.

PubMed

Spits, Christine; Wallace, Luke; Reinke, Karin

2017-04-20

Visual assessment, following guides such as the Overall Fuel Hazard Assessment Guide (OFHAG), is a common approach for assessing the structure and hazard of varying bushfire fuel layers. Visual assessments can be vulnerable to imprecision due to subjectivity between assessors, while emerging techniques such as image-based point clouds can offer land managers potentially more repeatable descriptions of fuel structure. This study compared the variability of estimates of surface and near-surface fuel attributes generated by eight assessment teams using the OFHAG and Fuels3D, a smartphone method utilising image-based point clouds, within three assessment plots in an Australian lowland forest. Surface fuel hazard scores derived from underpinning attributes were also assessed. Overall, this study found considerable variability between teams on most visually assessed variables, resulting in inconsistent hazard scores. Variability was observed within point cloud estimates but was, however, on average two to eight times less than that seen in visual estimates, indicating greater consistency and repeatability of this method. It is proposed that while variability within the Fuels3D method may be overcome through improved methods and equipment, inconsistencies in the OFHAG are likely due to the inherent subjectivity between assessors, which may be more difficult to overcome. This study demonstrates the capability of the Fuels3D method to efficiently and consistently collect data on fuel hazard and structure, and, as such, this method shows potential for use in fire management practices where accurate and reliable data is essential.

Location Modification Factors for Potential Dose Estimation

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

Snyder, Sandra F.; Barnett, J. Matthew

2017-01-01

A Department of Energy facility must comply with the National Emission Standard for Hazardous Air Pollutants for radioactive air emissions. The standard is an effective dose of less than 0.1 mSv yr-1 to the maximum public receptor. Additionally, a lower dose level may be assigned to a specific emission point in a State issued permit. A method to efficiently estimate the expected dose for future emissions is described. This method is most appropriately applied to a research facility with several emission points with generally low emission levels of numerous isotopes.

Estimating occupancy and abundance using aerial images with imperfect detection

USGS Publications Warehouse

Williams, Perry J.; Hooten, Mevin B.; Womble, Jamie N.; Bower, Michael R.

2017-01-01

Species distribution and abundance are critical population characteristics for efficient management, conservation, and ecological insight. Point process models are a powerful tool for modelling distribution and abundance, and can incorporate many data types, including count data, presence-absence data, and presence-only data. Aerial photographic images are a natural tool for collecting data to fit point process models, but aerial images do not always capture all animals that are present at a site. Methods for estimating detection probability for aerial surveys usually include collecting auxiliary data to estimate the proportion of time animals are available to be detected.We developed an approach for fitting point process models using an N-mixture model framework to estimate detection probability for aerial occupancy and abundance surveys. Our method uses multiple aerial images taken of animals at the same spatial location to provide temporal replication of sample sites. The intersection of the images provide multiple counts of individuals at different times. We examined this approach using both simulated and real data of sea otters (Enhydra lutris kenyoni) in Glacier Bay National Park, southeastern Alaska.Using our proposed methods, we estimated detection probability of sea otters to be 0.76, the same as visual aerial surveys that have been used in the past. Further, simulations demonstrated that our approach is a promising tool for estimating occupancy, abundance, and detection probability from aerial photographic surveys.Our methods can be readily extended to data collected using unmanned aerial vehicles, as technology and regulations permit. The generality of our methods for other aerial surveys depends on how well surveys can be designed to meet the assumptions of N-mixture models.

Integral-equation based methods for parameter estimation in output pulses of radiation detectors: Application in nuclear medicine and spectroscopy

NASA Astrophysics Data System (ADS)

Mohammadian-Behbahani, Mohammad-Reza; Saramad, Shahyar

2018-04-01

Model based analysis methods are relatively new approaches for processing the output data of radiation detectors in nuclear medicine imaging and spectroscopy. A class of such methods requires fast algorithms for fitting pulse models to experimental data. In order to apply integral-equation based methods for processing the preamplifier output pulses, this article proposes a fast and simple method for estimating the parameters of the well-known bi-exponential pulse model by solving an integral equation. The proposed method needs samples from only three points of the recorded pulse as well as its first and second order integrals. After optimizing the sampling points, the estimation results were calculated and compared with two traditional integration-based methods. Different noise levels (signal-to-noise ratios from 10 to 3000) were simulated for testing the functionality of the proposed method, then it was applied to a set of experimental pulses. Finally, the effect of quantization noise was assessed by studying different sampling rates. Promising results by the proposed method endorse it for future real-time applications.

Error Distribution Evaluation of the Third Vanishing Point Based on Random Statistical Simulation

NASA Astrophysics Data System (ADS)

Li, C.

2012-07-01

POS, integrated by GPS / INS (Inertial Navigation Systems), has allowed rapid and accurate determination of position and attitude of remote sensing equipment for MMS (Mobile Mapping Systems). However, not only does INS have system error, but also it is very expensive. Therefore, in this paper error distributions of vanishing points are studied and tested in order to substitute INS for MMS in some special land-based scene, such as ground façade where usually only two vanishing points can be detected. Thus, the traditional calibration approach based on three orthogonal vanishing points is being challenged. In this article, firstly, the line clusters, which parallel to each others in object space and correspond to the vanishing points, are detected based on RANSAC (Random Sample Consensus) and parallelism geometric constraint. Secondly, condition adjustment with parameters is utilized to estimate nonlinear error equations of two vanishing points (VX, VY). How to set initial weights for the adjustment solution of single image vanishing points is presented. Solving vanishing points and estimating their error distributions base on iteration method with variable weights, co-factor matrix and error ellipse theory. Thirdly, under the condition of known error ellipses of two vanishing points (VX, VY) and on the basis of the triangle geometric relationship of three vanishing points, the error distribution of the third vanishing point (VZ) is calculated and evaluated by random statistical simulation with ignoring camera distortion. Moreover, Monte Carlo methods utilized for random statistical estimation are presented. Finally, experimental results of vanishing points coordinate and their error distributions are shown and analyzed.

Can Detectability Analysis Improve the Utility of Point Counts for Temperate Forest Raptors?

EPA Science Inventory

Temperate forest breeding raptors are poorly represented in typical point count surveys because these birds are cryptic and typically breed at low densities. In recent years, many new methods for estimating detectability during point counts have been developed, including distanc...

Evaluation of Criterion Validity for Scales with Congeneric Measures

ERIC Educational Resources Information Center

Raykov, Tenko

2007-01-01

A method for estimating criterion validity of scales with homogeneous components is outlined. It accomplishes point and interval estimation of interrelationship indices between composite scores and criterion variables and is useful for testing hypotheses about criterion validity of measurement instruments. The method can also be used with missing…

Study on Raman spectral imaging method for simultaneous estimation of ingredients concentration in food powder

USDA-ARS?s Scientific Manuscript database

This study investigated the potential of point scan Raman spectral imaging method for estimation of different ingredients and chemical contaminant concentration in food powder. Food powder sample was prepared by mixing sugar, vanillin, melamine and non-dairy cream at 5 different concentrations in a ...

Comparative study of building footprint estimation methods from LiDAR point clouds

NASA Astrophysics Data System (ADS)

Rozas, E.; Rivera, F. F.; Cabaleiro, J. C.; Pena, T. F.; Vilariño, D. L.

2017-10-01

Building area calculation from LiDAR points is still a difficult task with no clear solution. Their different characteristics, such as shape or size, have made the process too complex to automate. However, several algorithms and techniques have been used in order to obtain an approximated hull. 3D-building reconstruction or urban planning are examples of important applications that benefit of accurate building footprint estimations. In this paper, we have carried out a study of accuracy in the estimation of the footprint of buildings from LiDAR points. The analysis focuses on the processing steps following the object recognition and classification, assuming that labeling of building points have been previously performed. Then, we perform an in-depth analysis of the influence of the point density over the accuracy of the building area estimation. In addition, a set of buildings with different size and shape were manually classified, in such a way that they can be used as benchmark.

Groundwater flux estimation in streams: A thermal equilibrium approach

USGS Publications Warehouse

Zhou, Yan; Fox, Garey A.; Miller, Ron B.; Mollenhauer, Robert; Brewer, Shannon K.

2018-01-01

Stream and groundwater interactions play an essential role in regulating flow, temperature, and water quality for stream ecosystems. Temperature gradients have been used to quantify vertical water movement in the streambed since the 1960s, but advancements in thermal methods are still possible. Seepage runs are a method commonly used to quantify exchange rates through a series of streamflow measurements but can be labor and time intensive. The objective of this study was to develop and evaluate a thermal equilibrium method as a technique for quantifying groundwater flux using monitored stream water temperature at a single point and readily available hydrological and atmospheric data. Our primary assumption was that stream water temperature at the monitored point was at thermal equilibrium with the combination of all heat transfer processes, including mixing with groundwater. By expanding the monitored stream point into a hypothetical, horizontal one-dimensional thermal modeling domain, we were able to simulate the thermal equilibrium achieved with known atmospheric variables at the point and quantify unknown groundwater flux by calibrating the model to the resulting temperature signature. Stream water temperatures were monitored at single points at nine streams in the Ozark Highland ecoregion and five reaches of the Kiamichi River to estimate groundwater fluxes using the thermal equilibrium method. When validated by comparison with seepage runs performed at the same time and reach, estimates from the two methods agreed with each other with an R2 of 0.94, a root mean squared error (RMSE) of 0.08 (m/d) and a Nash–Sutcliffe efficiency (NSE) of 0.93. In conclusion, the thermal equilibrium method was a suitable technique for quantifying groundwater flux with minimal cost and simple field installation given that suitable atmospheric and hydrological data were readily available.

Groundwater flux estimation in streams: A thermal equilibrium approach

NASA Astrophysics Data System (ADS)

Zhou, Yan; Fox, Garey A.; Miller, Ron B.; Mollenhauer, Robert; Brewer, Shannon

2018-06-01

Stream and groundwater interactions play an essential role in regulating flow, temperature, and water quality for stream ecosystems. Temperature gradients have been used to quantify vertical water movement in the streambed since the 1960s, but advancements in thermal methods are still possible. Seepage runs are a method commonly used to quantify exchange rates through a series of streamflow measurements but can be labor and time intensive. The objective of this study was to develop and evaluate a thermal equilibrium method as a technique for quantifying groundwater flux using monitored stream water temperature at a single point and readily available hydrological and atmospheric data. Our primary assumption was that stream water temperature at the monitored point was at thermal equilibrium with the combination of all heat transfer processes, including mixing with groundwater. By expanding the monitored stream point into a hypothetical, horizontal one-dimensional thermal modeling domain, we were able to simulate the thermal equilibrium achieved with known atmospheric variables at the point and quantify unknown groundwater flux by calibrating the model to the resulting temperature signature. Stream water temperatures were monitored at single points at nine streams in the Ozark Highland ecoregion and five reaches of the Kiamichi River to estimate groundwater fluxes using the thermal equilibrium method. When validated by comparison with seepage runs performed at the same time and reach, estimates from the two methods agreed with each other with an R2 of 0.94, a root mean squared error (RMSE) of 0.08 (m/d) and a Nash-Sutcliffe efficiency (NSE) of 0.93. In conclusion, the thermal equilibrium method was a suitable technique for quantifying groundwater flux with minimal cost and simple field installation given that suitable atmospheric and hydrological data were readily available.

A conceptual guide to detection probability for point counts and other count-based survey methods

Treesearch

D. Archibald McCallum

2005-01-01

Accurate and precise estimates of numbers of animals are vitally needed both to assess population status and to evaluate management decisions. Various methods exist for counting birds, but most of those used with territorial landbirds yield only indices, not true estimates of population size. The need for valid density estimates has spawned a number of models for...

Evaluation of the 5 and 8 pH point titration methods for monitoring anaerobic digesters treating solid waste.

PubMed

Vannecke, T P W; Lampens, D R A; Ekama, G A; Volcke, E I P

2015-01-01

Simple titration methods certainly deserve consideration for on-site routine monitoring of volatile fatty acid (VFA) concentration and alkalinity during anaerobic digestion (AD), because of their simplicity, speed and cost-effectiveness. In this study, the 5 and 8 pH point titration methods for measuring the VFA concentration and carbonate system alkalinity (H2CO3*-alkalinity) were assessed and compared. For this purpose, synthetic solutions with known H2CO3*-alkalinity and VFA concentration as well as samples from anaerobic digesters treating three different kind of solid wastes were analysed. The results of these two related titration methods were verified with photometric and high-pressure liquid chromatography measurements. It was shown that photometric measurements lead to overestimations of the VFA concentration in the case of coloured samples. In contrast, the 5 pH point titration method provides an accurate estimation of the VFA concentration, clearly corresponding with the true value. Concerning the H2CO3*-alkalinity, the most accurate and precise estimations, showing very similar results for repeated measurements, were obtained using the 8 pH point titration. Overall, it was concluded that the 5 pH point titration method is the preferred method for the practical monitoring of AD of solid wastes due to its robustness, cost efficiency and user-friendliness.

Sequential structural damage diagnosis algorithm using a change point detection method

NASA Astrophysics Data System (ADS)

Noh, H.; Rajagopal, R.; Kiremidjian, A. S.

2013-11-01

This paper introduces a damage diagnosis algorithm for civil structures that uses a sequential change point detection method. The general change point detection method uses the known pre- and post-damage feature distributions to perform a sequential hypothesis test. In practice, however, the post-damage distribution is unlikely to be known a priori, unless we are looking for a known specific type of damage. Therefore, we introduce an additional algorithm that estimates and updates this distribution as data are collected using the maximum likelihood and the Bayesian methods. We also applied an approximate method to reduce the computation load and memory requirement associated with the estimation. The algorithm is validated using a set of experimental data collected from a four-story steel special moment-resisting frame and multiple sets of simulated data. Various features of different dimensions have been explored, and the algorithm was able to identify damage, particularly when it uses multidimensional damage sensitive features and lower false alarm rates, with a known post-damage feature distribution. For unknown feature distribution cases, the post-damage distribution was consistently estimated and the detection delays were only a few time steps longer than the delays from the general method that assumes we know the post-damage feature distribution. We confirmed that the Bayesian method is particularly efficient in declaring damage with minimal memory requirement, but the maximum likelihood method provides an insightful heuristic approach.

Development and application of a modified dynamic time warping algorithm (DTW-S) to analyses of primate brain expression time series

PubMed Central

2011-01-01

Background Comparing biological time series data across different conditions, or different specimens, is a common but still challenging task. Algorithms aligning two time series represent a valuable tool for such comparisons. While many powerful computation tools for time series alignment have been developed, they do not provide significance estimates for time shift measurements. Results Here, we present an extended version of the original DTW algorithm that allows us to determine the significance of time shift estimates in time series alignments, the DTW-Significance (DTW-S) algorithm. The DTW-S combines important properties of the original algorithm and other published time series alignment tools: DTW-S calculates the optimal alignment for each time point of each gene, it uses interpolated time points for time shift estimation, and it does not require alignment of the time-series end points. As a new feature, we implement a simulation procedure based on parameters estimated from real time series data, on a series-by-series basis, allowing us to determine the false positive rate (FPR) and the significance of the estimated time shift values. We assess the performance of our method using simulation data and real expression time series from two published primate brain expression datasets. Our results show that this method can provide accurate and robust time shift estimates for each time point on a gene-by-gene basis. Using these estimates, we are able to uncover novel features of the biological processes underlying human brain development and maturation. Conclusions The DTW-S provides a convenient tool for calculating accurate and robust time shift estimates at each time point for each gene, based on time series data. The estimates can be used to uncover novel biological features of the system being studied. The DTW-S is freely available as an R package TimeShift at http://www.picb.ac.cn/Comparative/data.html. PMID:21851598

Development and application of a modified dynamic time warping algorithm (DTW-S) to analyses of primate brain expression time series.

PubMed

Yuan, Yuan; Chen, Yi-Ping Phoebe; Ni, Shengyu; Xu, Augix Guohua; Tang, Lin; Vingron, Martin; Somel, Mehmet; Khaitovich, Philipp

2011-08-18

Comparing biological time series data across different conditions, or different specimens, is a common but still challenging task. Algorithms aligning two time series represent a valuable tool for such comparisons. While many powerful computation tools for time series alignment have been developed, they do not provide significance estimates for time shift measurements. Here, we present an extended version of the original DTW algorithm that allows us to determine the significance of time shift estimates in time series alignments, the DTW-Significance (DTW-S) algorithm. The DTW-S combines important properties of the original algorithm and other published time series alignment tools: DTW-S calculates the optimal alignment for each time point of each gene, it uses interpolated time points for time shift estimation, and it does not require alignment of the time-series end points. As a new feature, we implement a simulation procedure based on parameters estimated from real time series data, on a series-by-series basis, allowing us to determine the false positive rate (FPR) and the significance of the estimated time shift values. We assess the performance of our method using simulation data and real expression time series from two published primate brain expression datasets. Our results show that this method can provide accurate and robust time shift estimates for each time point on a gene-by-gene basis. Using these estimates, we are able to uncover novel features of the biological processes underlying human brain development and maturation. The DTW-S provides a convenient tool for calculating accurate and robust time shift estimates at each time point for each gene, based on time series data. The estimates can be used to uncover novel biological features of the system being studied. The DTW-S is freely available as an R package TimeShift at http://www.picb.ac.cn/Comparative/data.html.

Estimating corresponding locations in ipsilateral breast tomosynthesis views

NASA Astrophysics Data System (ADS)

van Schie, Guido; Tanner, Christine; Karssemeijer, Nico

2011-03-01

To improve cancer detection in mammography, breast exams usually consist of two views per breast. To combine information from both views, radiologists and multiview computer-aided detection (CAD) systems need to match corresponding regions in the two views. In digital breast tomosynthesis (DBT), finding corresponding regions in ipsilateral volumes may be a difficult and time-consuming task for radiologists, because many slices have to be inspected individually. In this study we developed a method to quickly estimate corresponding locations in ipsilateral tomosynthesis views by applying a mathematical transformation. First a compressed breast model is matched to the tomosynthesis view containing a point of interest. Then we decompress, rotate and compress again to estimate the location of the corresponding point in the ipsilateral view. In this study we use a simple elastically deformable sphere model to obtain an analytical solution for the transformation in a given DBT case. The model is matched to the volume by using automatic segmentation of the pectoral muscle, breast tissue and nipple. For validation we annotated 181 landmarks in both views and applied our method to each location. Results show a median 3D distance between the actual location and estimated location of 1.5 cm; a good starting point for a feature based local search method to link lesions for a multiview CAD system. Half of the estimated locations were at most 1 slice away from the actual location, making our method useful as a tool in mammographic workstations to interactively find corresponding locations in ipsilateral tomosynthesis views.

Estimation of time-delayed mutual information and bias for irregularly and sparsely sampled time-series

PubMed Central

Albers, D. J.; Hripcsak, George

2012-01-01

A method to estimate the time-dependent correlation via an empirical bias estimate of the time-delayed mutual information for a time-series is proposed. In particular, the bias of the time-delayed mutual information is shown to often be equivalent to the mutual information between two distributions of points from the same system separated by infinite time. Thus intuitively, estimation of the bias is reduced to estimation of the mutual information between distributions of data points separated by large time intervals. The proposed bias estimation techniques are shown to work for Lorenz equations data and glucose time series data of three patients from the Columbia University Medical Center database. PMID:22536009

Terrestrial laser scanning point clouds time series for the monitoring of slope movements: displacement measurement using image correlation and 3D feature tracking

NASA Astrophysics Data System (ADS)

Bornemann, Pierrick; Jean-Philippe, Malet; André, Stumpf; Anne, Puissant; Julien, Travelletti

2016-04-01

Dense multi-temporal point clouds acquired with terrestrial laser scanning (TLS) have proved useful for the study of structure and kinematics of slope movements. Most of the existing deformation analysis methods rely on the use of interpolated data. Approaches that use multiscale image correlation provide a precise and robust estimation of the observed movements; however, for non-rigid motion patterns, these methods tend to underestimate all the components of the movement. Further, for rugged surface topography, interpolated data introduce a bias and a loss of information in some local places where the point cloud information is not sufficiently dense. Those limits can be overcome by using deformation analysis exploiting directly the original 3D point clouds assuming some hypotheses on the deformation (e.g. the classic ICP algorithm requires an initial guess by the user of the expected displacement patterns). The objective of this work is therefore to propose a deformation analysis method applied to a series of 20 3D point clouds covering the period October 2007 - October 2015 at the Super-Sauze landslide (South East French Alps). The dense point clouds have been acquired with a terrestrial long-range Optech ILRIS-3D laser scanning device from the same base station. The time series are analyzed using two approaches: 1) a method of correlation of gradient images, and 2) a method of feature tracking in the raw 3D point clouds. The estimated surface displacements are then compared with GNSS surveys on reference targets. Preliminary results tend to show that the image correlation method provides a good estimation of the displacement fields at first order, but shows limitations such as the inability to track some deformation patterns, and the use of a perspective projection that does not maintain original angles and distances in the correlated images. Results obtained with 3D point clouds comparison algorithms (C2C, ICP, M3C2) bring additional information on the displacement fields. Displacement fields derived from both approaches are then combined and provide a better understanding of the landslide kinematics.

Strengths and weaknesses of temporal stability analysis for monitoring and estimating grid-mean soil moisture in a high-intensity irrigated agricultural landscape

NASA Astrophysics Data System (ADS)

Ran, Youhua; Li, Xin; Jin, Rui; Kang, Jian; Cosh, Michael H.

2017-01-01

Monitoring and estimating grid-mean soil moisture is very important for assessing many hydrological, biological, and biogeochemical processes and for validating remotely sensed surface soil moisture products. Temporal stability analysis (TSA) is a valuable tool for identifying a small number of representative sampling points to estimate the grid-mean soil moisture content. This analysis was evaluated and improved using high-quality surface soil moisture data that were acquired by a wireless sensor network in a high-intensity irrigated agricultural landscape in an arid region of northwestern China. The performance of the TSA was limited in areas where the representative error was dominated by random events, such as irrigation events. This shortcoming can be effectively mitigated by using a stratified TSA (STSA) method, proposed in this paper. In addition, the following methods were proposed for rapidly and efficiently identifying representative sampling points when using TSA. (1) Instantaneous measurements can be used to identify representative sampling points to some extent; however, the error resulting from this method is significant when validating remotely sensed soil moisture products. Thus, additional representative sampling points should be considered to reduce this error. (2) The calibration period can be determined from the time span of the full range of the grid-mean soil moisture content during the monitoring period. (3) The representative error is sensitive to the number of calibration sampling points, especially when only a few representative sampling points are used. Multiple sampling points are recommended to reduce data loss and improve the likelihood of representativeness at two scales.

Direct sampling for stand density index

Treesearch

Mark J. Ducey; Harry T. Valentine

2008-01-01

A direct method of estimating stand density index in the field, without complex calculations, would be useful in a variety of silvicultural situations. We present just such a method. The approach uses an ordinary prism or other angle gauge, but it involves deliberately "pushing the point" or, in some cases, "pulling the point." This adjusts the...

Multistage point relascope and randomized branch sampling for downed coarse woody debris estimation

Treesearch

Jeffrey H. Gove; Mark J. Ducey; Harry T. Valentine

2002-01-01

New sampling methods have recently been introduced that allow estimation of downed coarse woody debris using an angle gauge, or relascope. The theory behind these methods is based on sampling straight pieces of downed coarse woody debris. When pieces deviate from this ideal situation, auxillary methods must be employed. We describe a two-stage procedure where the...

Estimating botanical composition by the dry-weight-rank method in California's annual grasslands

Treesearch

Raymond D. Ratliff; William E. Frost

1990-01-01

The dry-weight-rank method of estimating botanical composition on California's annual grasslands is a viable alternative to harvesting and sorting or methods using points. Two data sets of sorted species weights were available. One spanned nine years with quadrats harvested at peak of production. The second spanned one growing season with 20 harvest dates. Two...

An Evaluation of the Plant Density Estimator the Point-Centred Quarter Method (PCQM) Using Monte Carlo Simulation.

PubMed

Khan, Md Nabiul Islam; Hijbeek, Renske; Berger, Uta; Koedam, Nico; Grueters, Uwe; Islam, S M Zahirul; Hasan, Md Asadul; Dahdouh-Guebas, Farid

2016-01-01

In the Point-Centred Quarter Method (PCQM), the mean distance of the first nearest plants in each quadrant of a number of random sample points is converted to plant density. It is a quick method for plant density estimation. In recent publications the estimator equations of simple PCQM (PCQM1) and higher order ones (PCQM2 and PCQM3, which uses the distance of the second and third nearest plants, respectively) show discrepancy. This study attempts to review PCQM estimators in order to find the most accurate equation form. We tested the accuracy of different PCQM equations using Monte Carlo Simulations in simulated (having 'random', 'aggregated' and 'regular' spatial patterns) plant populations and empirical ones. PCQM requires at least 50 sample points to ensure a desired level of accuracy. PCQM with a corrected estimator is more accurate than with a previously published estimator. The published PCQM versions (PCQM1, PCQM2 and PCQM3) show significant differences in accuracy of density estimation, i.e. the higher order PCQM provides higher accuracy. However, the corrected PCQM versions show no significant differences among them as tested in various spatial patterns except in plant assemblages with a strong repulsion (plant competition). If N is number of sample points and R is distance, the corrected estimator of PCQM1 is 4(4N - 1)/(π ∑ R2) but not 12N/(π ∑ R2), of PCQM2 is 4(8N - 1)/(π ∑ R2) but not 28N/(π ∑ R2) and of PCQM3 is 4(12N - 1)/(π ∑ R2) but not 44N/(π ∑ R2) as published. If the spatial pattern of a plant association is random, PCQM1 with a corrected equation estimator and over 50 sample points would be sufficient to provide accurate density estimation. PCQM using just the nearest tree in each quadrant is therefore sufficient, which facilitates sampling of trees, particularly in areas with just a few hundred trees per hectare. PCQM3 provides the best density estimations for all types of plant assemblages including the repulsion process. Since in practice, the spatial pattern of a plant association remains unknown before starting a vegetation survey, for field applications the use of PCQM3 along with the corrected estimator is recommended. However, for sparse plant populations, where the use of PCQM3 may pose practical limitations, the PCQM2 or PCQM1 would be applied. During application of PCQM in the field, care should be taken to summarize the distance data based on 'the inverse summation of squared distances' but not 'the summation of inverse squared distances' as erroneously published.

Estimation of correlation functions by stochastic approximation.

NASA Technical Reports Server (NTRS)

Habibi, A.; Wintz, P. A.

1972-01-01

Consideration of the autocorrelation function of a zero-mean stationary random process. The techniques are applicable to processes with nonzero mean provided the mean is estimated first and subtracted. Two recursive techniques are proposed, both of which are based on the method of stochastic approximation and assume a functional form for the correlation function that depends on a number of parameters that are recursively estimated from successive records. One technique uses a standard point estimator of the correlation function to provide estimates of the parameters that minimize the mean-square error between the point estimates and the parametric function. The other technique provides estimates of the parameters that maximize a likelihood function relating the parameters of the function to the random process. Examples are presented.

Similar Estimates of Temperature Impacts on Global Wheat Yield by Three Independent Methods

NASA Technical Reports Server (NTRS)

Liu, Bing; Asseng, Senthold; Muller, Christoph; Ewart, Frank; Elliott, Joshua; Lobell, David B.; Martre, Pierre; Ruane, Alex C.; Wallach, Daniel; Jones, James W.;

Similar estimates of temperature impacts on global wheat yield by three independent methods

NASA Astrophysics Data System (ADS)

Liu, Bing; Asseng, Senthold; Müller, Christoph; Ewert, Frank; Elliott, Joshua; Lobell, David B.; Martre, Pierre; Ruane, Alex C.; Wallach, Daniel; Jones, James W.; Rosenzweig, Cynthia; Aggarwal, Pramod K.; Alderman, Phillip D.; Anothai, Jakarat; Basso, Bruno; Biernath, Christian; Cammarano, Davide; Challinor, Andy; Deryng, Delphine; Sanctis, Giacomo De; Doltra, Jordi; Fereres, Elias; Folberth, Christian; Garcia-Vila, Margarita; Gayler, Sebastian; Hoogenboom, Gerrit; Hunt, Leslie A.; Izaurralde, Roberto C.; Jabloun, Mohamed; Jones, Curtis D.; Kersebaum, Kurt C.; Kimball, Bruce A.; Koehler, Ann-Kristin; Kumar, Soora Naresh; Nendel, Claas; O'Leary, Garry J.; Olesen, Jørgen E.; Ottman, Michael J.; Palosuo, Taru; Prasad, P. V. Vara; Priesack, Eckart; Pugh, Thomas A. M.; Reynolds, Matthew; Rezaei, Ehsan E.; Rötter, Reimund P.; Schmid, Erwin; Semenov, Mikhail A.; Shcherbak, Iurii; Stehfest, Elke; Stöckle, Claudio O.; Stratonovitch, Pierre; Streck, Thilo; Supit, Iwan; Tao, Fulu; Thorburn, Peter; Waha, Katharina; Wall, Gerard W.; Wang, Enli; White, Jeffrey W.; Wolf, Joost; Zhao, Zhigan; Zhu, Yan

2016-12-01

The potential impact of global temperature change on global crop yield has recently been assessed with different methods. Here we show that grid-based and point-based simulations and statistical regressions (from historic records), without deliberate adaptation or CO2 fertilization effects, produce similar estimates of temperature impact on wheat yields at global and national scales. With a 1 °C global temperature increase, global wheat yield is projected to decline between 4.1% and 6.4%. Projected relative temperature impacts from different methods were similar for major wheat-producing countries China, India, USA and France, but less so for Russia. Point-based and grid-based simulations, and to some extent the statistical regressions, were consistent in projecting that warmer regions are likely to suffer more yield loss with increasing temperature than cooler regions. By forming a multi-method ensemble, it was possible to quantify `method uncertainty’ in addition to model uncertainty. This significantly improves confidence in estimates of climate impacts on global food security.

A new mosaic method for three-dimensional surface

NASA Astrophysics Data System (ADS)

Yuan, Yun; Zhu, Zhaokun; Ding, Yongjun

2011-08-01

Three-dimensional (3-D) data mosaic is a indispensable link in surface measurement and digital terrain map generation. With respect to the mosaic problem of the local unorganized cloud points with rude registration and mass mismatched points, a new mosaic method for 3-D surface based on RANSAC is proposed. Every circular of this method is processed sequentially by random sample with additional shape constraint, data normalization of cloud points, absolute orientation, data denormalization of cloud points, inlier number statistic, etc. After N random sample trials the largest consensus set is selected, and at last the model is re-estimated using all the points in the selected subset. The minimal subset is composed of three non-colinear points which form a triangle. The shape of triangle is considered in random sample selection in order to make the sample selection reasonable. A new coordinate system transformation algorithm presented in this paper is used to avoid the singularity. The whole rotation transformation between the two coordinate systems can be solved by twice rotations expressed by Euler angle vector, each rotation has explicit physical means. Both simulation and real data are used to prove the correctness and validity of this mosaic method. This method has better noise immunity due to its robust estimation property, and has high accuracy as the shape constraint is added to random sample and the data normalization added to the absolute orientation. This method is applicable for high precision measurement of three-dimensional surface and also for the 3-D terrain mosaic.

Feature-Based Correlation and Topological Similarity for Interbeat Interval Estimation Using Ultrawideband Radar.

PubMed

Sakamoto, Takuya; Imasaka, Ryohei; Taki, Hirofumi; Sato, Toru; Yoshioka, Mototaka; Inoue, Kenichi; Fukuda, Takeshi; Sakai, Hiroyuki

2016-04-01

The objectives of this paper are to propose a method that can accurately estimate the human heart rate (HR) using an ultrawideband (UWB) radar system, and to determine the performance of the proposed method through measurements. The proposed method uses the feature points of a radar signal to estimate the HR efficiently and accurately. Fourier- and periodicity-based methods are inappropriate for estimation of instantaneous HRs in real time because heartbeat waveforms are highly variable, even within the beat-to-beat interval. We define six radar waveform features that enable correlation processing to be performed quickly and accurately. In addition, we propose a feature topology signal that is generated from a feature sequence without using amplitude information. This feature topology signal is used to find unreliable feature points, and thus, to suppress inaccurate HR estimates. Measurements were taken using UWB radar, while simultaneously performing electrocardiography measurements in an experiment that was conducted on nine participants. The proposed method achieved an average root-mean-square error in the interbeat interval of 7.17 ms for the nine participants. The results demonstrate the effectiveness and accuracy of the proposed method. The significance of this study for biomedical research is that the proposed method will be useful in the realization of a remote vital signs monitoring system that enables accurate estimation of HR variability, which has been used in various clinical settings for the treatment of conditions such as diabetes and arterial hypertension.

Comparison of two methods for estimating base flow in selected reaches of the South Platte River, Colorado

USGS Publications Warehouse

Capesius, Joseph P.; Arnold, L. Rick

2012-01-01

The Mass Balance results were quite variable over time such that they appeared suspect with respect to the concept of groundwater flow as being gradual and slow. The large degree of variability in the day-to-day and month-to-month Mass Balance results is likely the result of many factors. These factors could include ungaged stream inflows or outflows, short-term streamflow losses to and gains from temporary bank storage, and any lag in streamflow accounting owing to streamflow lag time of flow within a reach. The Pilot Point time series results were much less variable than the Mass Balance results and extreme values were effectively constrained. Less day-to-day variability, smaller magnitude extreme values, and smoother transitions in base-flow estimates provided by the Pilot Point method are more consistent with a conceptual model of groundwater flow being gradual and slow. The Pilot Point method provided a better fit to the conceptual model of groundwater flow and appeared to provide reasonable estimates of base flow.

Accurately estimating PSF with straight lines detected by Hough transform

NASA Astrophysics Data System (ADS)

Wang, Ruichen; Xu, Liangpeng; Fan, Chunxiao; Li, Yong

2018-04-01

This paper presents an approach to estimating point spread function (PSF) from low resolution (LR) images. Existing techniques usually rely on accurate detection of ending points of the profile normal to edges. In practice however, it is often a great challenge to accurately localize profiles of edges from a LR image, which hence leads to a poor PSF estimation of the lens taking the LR image. For precisely estimating the PSF, this paper proposes firstly estimating a 1-D PSF kernel with straight lines, and then robustly obtaining the 2-D PSF from the 1-D kernel by least squares techniques and random sample consensus. Canny operator is applied to the LR image for obtaining edges and then Hough transform is utilized to extract straight lines of all orientations. Estimating 1-D PSF kernel with straight lines effectively alleviates the influence of the inaccurate edge detection on PSF estimation. The proposed method is investigated on both natural and synthetic images for estimating PSF. Experimental results show that the proposed method outperforms the state-ofthe- art and does not rely on accurate edge detection.

Directional kriging implementation for gridded data interpolation and comparative study with common methods

NASA Astrophysics Data System (ADS)

Mahmoudabadi, H.; Briggs, G.

2016-12-01

Gridded data sets, such as geoid models or datum shift grids, are commonly used in coordinate transformation algorithms. Grid files typically contain known or measured values at regular fixed intervals. The process of computing a value at an unknown location from the values in the grid data set is called "interpolation". Generally, interpolation methods predict a value at a given point by computing a weighted average of the known values in the neighborhood of the point. Geostatistical Kriging is a widely used interpolation method for irregular networks. Kriging interpolation first analyzes the spatial structure of the input data, then generates a general model to describe spatial dependencies. This model is used to calculate values at unsampled locations by finding direction, shape, size, and weight of neighborhood points. Because it is based on a linear formulation for the best estimation, Kriging it the optimal interpolation method in statistical terms. The Kriging interpolation algorithm produces an unbiased prediction, as well as the ability to calculate the spatial distribution of uncertainty, allowing you to estimate the errors in an interpolation for any particular point. Kriging is not widely used in geospatial applications today, especially applications that run on low power devices or deal with large data files. This is due to the computational power and memory requirements of standard Kriging techniques. In this paper, improvements are introduced in directional kriging implementation by taking advantage of the structure of the grid files. The regular spacing of points simplifies finding the neighborhood points and computing their pairwise distances, reducing the the complexity and improving the execution time of the Kriging algorithm. Also, the proposed method iteratively loads small portion of interest areas in different directions to reduce the amount of required memory. This makes the technique feasible on almost any computer processor. Comparison between kriging and other standard interpolation methods demonstrated more accurate estimations in less denser data files.

Pose estimation for augmented reality applications using genetic algorithm.

PubMed

Yu, Ying Kin; Wong, Kin Hong; Chang, Michael Ming Yuen

2005-12-01

This paper describes a genetic algorithm that tackles the pose-estimation problem in computer vision. Our genetic algorithm can find the rotation and translation of an object accurately when the three-dimensional structure of the object is given. In our implementation, each chromosome encodes both the pose and the indexes to the selected point features of the object. Instead of only searching for the pose as in the existing work, our algorithm, at the same time, searches for a set containing the most reliable feature points in the process. This mismatch filtering strategy successfully makes the algorithm more robust under the presence of point mismatches and outliers in the images. Our algorithm has been tested with both synthetic and real data with good results. The accuracy of the recovered pose is compared to the existing algorithms. Our approach outperformed the Lowe's method and the other two genetic algorithms under the presence of point mismatches and outliers. In addition, it has been used to estimate the pose of a real object. It is shown that the proposed method is applicable to augmented reality applications.

Gaussian Decomposition of Laser Altimeter Waveforms

NASA Technical Reports Server (NTRS)

Hofton, Michelle A.; Minster, J. Bernard; Blair, J. Bryan

1999-01-01

We develop a method to decompose a laser altimeter return waveform into its Gaussian components assuming that the position of each Gaussian within the waveform can be used to calculate the mean elevation of a specific reflecting surface within the laser footprint. We estimate the number of Gaussian components from the number of inflection points of a smoothed copy of the laser waveform, and obtain initial estimates of the Gaussian half-widths and positions from the positions of its consecutive inflection points. Initial amplitude estimates are obtained using a non-negative least-squares method. To reduce the likelihood of fitting the background noise within the waveform and to minimize the number of Gaussians needed in the approximation, we rank the "importance" of each Gaussian in the decomposition using its initial half-width and amplitude estimates. The initial parameter estimates of all Gaussians ranked "important" are optimized using the Levenburg-Marquardt method. If the sum of the Gaussians does not approximate the return waveform to a prescribed accuracy, then additional Gaussians are included in the optimization procedure. The Gaussian decomposition method is demonstrated on data collected by the airborne Laser Vegetation Imaging Sensor (LVIS) in October 1997 over the Sequoia National Forest, California.

Responsiveness and MCID Estimates for CAT, CCQ, and HADS in Patients With COPD Undergoing Pulmonary Rehabilitation: A Prospective Analysis.

PubMed

Smid, Dionne E; Franssen, Frits M E; Houben-Wilke, Sarah; Vanfleteren, Lowie E G W; Janssen, Daisy J A; Wouters, Emiel F M; Spruit, Martijn A

2017-01-01

Pulmonary rehabilitation enhances health status and mood status in patients with chronic obstructive pulmonary disease (COPD). The aim was to determine the responsiveness of St. George's Respiratory Questionnaire (SGRQ), COPD Assessment Test (CAT), COPD Clinical Questionnaire (CCQ), and Hospital Anxiety and Depression Scale (HADS) to pulmonary rehabilitation in patients with COPD, and estimate minimum clinically important differences (MCIDs) for CAT, CCQ, and HADS. A prospective analysis. MCIDs were estimated with anchor-based (anchor: SGRQ) and distribution-based methods. Newly estimated MCIDs were compared to known MCID estimates from a systematic literature search. Newly estimated MCIDs were calculated in patients treated in pulmonary rehabilitation. A subsample of 419 individuals with COPD (55.4% male, mean age 64.3 ± 8.8 years) were included from the Chance study. Health status was measured with SGRQ, CAT, and CCQ, before and after pulmonary rehabilitation. Mood status was assessed using HADS. 419 patients with COPD (forced expiratory volume in the first second 37.3% ± 12.1% predicted) completed pulmonary rehabilitation. SGRQ (-9.1 ± 14.0 points), CAT (-3.0 ± 6.8 points), CCQ (-0.6 ± 0.9 points), HADS-Anxiety (-1.7 ± 3.7 points), and HADS-Depression (-2.1 ± 3.7 points) improved significantly. New MCIDs were estimated for CAT (range: -3.8 to -1.0 points), CCQ (range: -0.8 to -0.2 points), HADS-Anxiety (range: -2.0 to -1.1 points), and HADS-Depression (range: -1.8 to -1.4 points). The SGRQ, CAT, CCQ, and HADS are responsive to pulmonary rehabilitation in patients with COPD. We propose MCID estimates ranging between -3.0 and -2.0 points for CAT; -0.5 and -0.3 points for CCQ, -1.8 and -1.3 points for HADS-Anxiety, and -1.7 and -1.5 points for HADS-Depression. Copyright © 2016 AMDA – The Society for Post-Acute and Long-Term Care Medicine. Published by Elsevier Inc. All rights reserved.

Estimating Contraceptive Prevalence Using Logistics Data for Short-Acting Methods: Analysis Across 30 Countries

PubMed Central

Cunningham, Marc; Brown, Niquelle; Sacher, Suzy; Hatch, Benjamin; Inglis, Andrew; Aronovich, Dana

2015-01-01

Background: Contraceptive prevalence rate (CPR) is a vital indicator used by country governments, international donors, and other stakeholders for measuring progress in family planning programs against country targets and global initiatives as well as for estimating health outcomes. Because of the need for more frequent CPR estimates than population-based surveys currently provide, alternative approaches for estimating CPRs are being explored, including using contraceptive logistics data. Methods: Using data from the Demographic and Health Surveys (DHS) in 30 countries, population data from the United States Census Bureau International Database, and logistics data from the Procurement Planning and Monitoring Report (PPMR) and the Pipeline Monitoring and Procurement Planning System (PipeLine), we developed and evaluated 3 models to generate country-level, public-sector contraceptive prevalence estimates for injectable contraceptives, oral contraceptives, and male condoms. Models included: direct estimation through existing couple-years of protection (CYP) conversion factors, bivariate linear regression, and multivariate linear regression. Model evaluation consisted of comparing the referent DHS prevalence rates for each short-acting method with the model-generated prevalence rate using multiple metrics, including mean absolute error and proportion of countries where the modeled prevalence rate for each method was within 1, 2, or 5 percentage points of the DHS referent value. Results: For the methods studied, family planning use estimates from public-sector logistics data were correlated with those from the DHS, validating the quality and accuracy of current public-sector logistics data. Logistics data for oral and injectable contraceptives were significantly associated (P<.05) with the referent DHS values for both bivariate and multivariate models. For condoms, however, that association was only significant for the bivariate model. With the exception of the CYP-based model for condoms, models were able to estimate public-sector prevalence rates for each short-acting method to within 2 percentage points in at least 85% of countries. Conclusions: Public-sector contraceptive logistics data are strongly correlated with public-sector prevalence rates for short-acting methods, demonstrating the quality of current logistics data and their ability to provide relatively accurate prevalence estimates. The models provide a starting point for generating interim estimates of contraceptive use when timely survey data are unavailable. All models except the condoms CYP model performed well; the regression models were most accurate but the CYP model offers the simplest calculation method. Future work extending the research to other modern methods, relating subnational logistics data with prevalence rates, and tracking that relationship over time is needed. PMID:26374805

Disturbance torque rejection properties of the NASA/JPL 70-meter antenna axis servos

NASA Technical Reports Server (NTRS)

Hill, R. E.

1989-01-01

Analytic methods for evaluating pointing errors caused by external disturbance torques are developed and applied to determine the effects of representative values of wind and friction torque. The expressions relating pointing errors to disturbance torques are shown to be strongly dependent upon the state estimator parameters, as well as upon the state feedback gain and the flow versus pressure characteristics of the hydraulic system. Under certain conditions, when control is derived from an uncorrected estimate of integral position error, the desired type 2 servo properties are not realized and finite steady-state position errors result. Methods for reducing these errors to negligible proportions through the proper selection of control gain and estimator correction parameters are demonstrated. The steady-state error produced by a disturbance torque is found to be directly proportional to the hydraulic internal leakage. This property can be exploited to provide a convenient method of determining system leakage from field measurements of estimator error, axis rate, and hydraulic differential pressure.

Eye gaze tracking using correlation filters

NASA Astrophysics Data System (ADS)

Karakaya, Mahmut; Bolme, David; Boehnen, Chris

2014-03-01

In this paper, we studied a method for eye gaze tracking that provide gaze estimation from a standard webcam with a zoom lens and reduce the setup and calibration requirements for new users. Specifically, we have developed a gaze estimation method based on the relative locations of points on the top of the eyelid and eye corners. Gaze estimation method in this paper is based on the distances between top point of the eyelid and eye corner detected by the correlation filters. Advanced correlation filters were found to provide facial landmark detections that are accurate enough to determine the subjects gaze direction up to angle of approximately 4-5 degrees although calibration errors often produce a larger overall shift in the estimates. This is approximately a circle of diameter 2 inches for a screen that is arm's length from the subject. At this accuracy it is possible to figure out what regions of text or images the subject is looking but it falls short of being able to determine which word the subject has looked at.

Estimating population trends with a linear model

USGS Publications Warehouse

Bart, Jonathan; Collins, Brian D.; Morrison, R.I.G.

2003-01-01

We describe a simple and robust method for estimating trends in population size. The method may be used with Breeding Bird Survey data, aerial surveys, point counts, or any other program of repeated surveys at permanent locations. Surveys need not be made at each location during each survey period. The method differs from most existing methods in being design based, rather than model based. The only assumptions are that the nominal sampling plan is followed and that sample size is large enough for use of the t-distribution. Simulations based on two bird data sets from natural populations showed that the point estimate produced by the linear model was essentially unbiased even when counts varied substantially and 25% of the complete data set was missing. The estimating-equation approach, often used to analyze Breeding Bird Survey data, performed similarly on one data set but had substantial bias on the second data set, in which counts were highly variable. The advantages of the linear model are its simplicity, flexibility, and that it is self-weighting. A user-friendly computer program to carry out the calculations is available from the senior author.

Projections onto Convex Sets Super-Resolution Reconstruction Based on Point Spread Function Estimation of Low-Resolution Remote Sensing Images

PubMed Central

Fan, Chong; Wu, Chaoyun; Li, Grand; Ma, Jun

2017-01-01

To solve the problem on inaccuracy when estimating the point spread function (PSF) of the ideal original image in traditional projection onto convex set (POCS) super-resolution (SR) reconstruction, this paper presents an improved POCS SR algorithm based on PSF estimation of low-resolution (LR) remote sensing images. The proposed algorithm can improve the spatial resolution of the image and benefit agricultural crop visual interpolation. The PSF of the high-resolution (HR) image is unknown in reality. Therefore, analysis of the relationship between the PSF of the HR image and the PSF of the LR image is important to estimate the PSF of the HR image by using multiple LR images. In this study, the linear relationship between the PSFs of the HR and LR images can be proven. In addition, the novel slant knife-edge method is employed, which can improve the accuracy of the PSF estimation of LR images. Finally, the proposed method is applied to reconstruct airborne digital sensor 40 (ADS40) three-line array images and the overlapped areas of two adjacent GF-2 images by embedding the estimated PSF of the HR image to the original POCS SR algorithm. Experimental results show that the proposed method yields higher quality of reconstructed images than that produced by the blind SR method and the bicubic interpolation method. PMID:28208837

Interpolating precipitation and its relation to runoff and non-point source pollution.

PubMed

Chang, Chia-Ling; Lo, Shang-Lien; Yu, Shaw-L

2005-01-01

When rainfall spatially varies, complete rainfall data for each region with different rainfall characteristics are very important. Numerous interpolation methods have been developed for estimating unknown spatial characteristics. However, no interpolation method is suitable for all circumstances. In this study, several methods, including the arithmetic average method, the Thiessen Polygons method, the traditional inverse distance method, and the modified inverse distance method, were used to interpolate precipitation. The modified inverse distance method considers not only horizontal distances but also differences between the elevations of the region with no rainfall records and of its surrounding rainfall stations. The results show that when the spatial variation of rainfall is strong, choosing a suitable interpolation method is very important. If the rainfall is uniform, the precipitation estimated using any interpolation method would be quite close to the actual precipitation. When rainfall is heavy in locations with high elevation, the rainfall changes with the elevation. In this situation, the modified inverse distance method is much more effective than any other method discussed herein for estimating the rainfall input for WinVAST to estimate runoff and non-point source pollution (NPSP). When the spatial variation of rainfall is random, regardless of the interpolation method used to yield rainfall input, the estimation errors of runoff and NPSP are large. Moreover, the relationship between the relative error of the predicted runoff and predicted pollutant loading of SS is high. However, the pollutant concentration is affected by both runoff and pollutant export, so the relationship between the relative error of the predicted runoff and the predicted pollutant concentration of SS may be unstable.

A Robust Linear Feature-Based Procedure for Automated Registration of Point Clouds

PubMed Central

Poreba, Martyna; Goulette, François

2015-01-01

With the variety of measurement techniques available on the market today, fusing multi-source complementary information into one dataset is a matter of great interest. Target-based, point-based and feature-based methods are some of the approaches used to place data in a common reference frame by estimating its corresponding transformation parameters. This paper proposes a new linear feature-based method to perform accurate registration of point clouds, either in 2D or 3D. A two-step fast algorithm called Robust Line Matching and Registration (RLMR), which combines coarse and fine registration, was developed. The initial estimate is found from a triplet of conjugate line pairs, selected by a RANSAC algorithm. Then, this transformation is refined using an iterative optimization algorithm. Conjugates of linear features are identified with respect to a similarity metric representing a line-to-line distance. The efficiency and robustness to noise of the proposed method are evaluated and discussed. The algorithm is valid and ensures valuable results when pre-aligned point clouds with the same scale are used. The studies show that the matching accuracy is at least 99.5%. The transformation parameters are also estimated correctly. The error in rotation is better than 2.8% full scale, while the translation error is less than 12.7%. PMID:25594589

Investigating Surface and Near-Surface Bushfire Fuel Attributes: A Comparison between Visual Assessments and Image-Based Point Clouds

PubMed Central

Spits, Christine; Wallace, Luke; Reinke, Karin

2017-01-01

Visual assessment, following guides such as the Overall Fuel Hazard Assessment Guide (OFHAG), is a common approach for assessing the structure and hazard of varying bushfire fuel layers. Visual assessments can be vulnerable to imprecision due to subjectivity between assessors, while emerging techniques such as image-based point clouds can offer land managers potentially more repeatable descriptions of fuel structure. This study compared the variability of estimates of surface and near-surface fuel attributes generated by eight assessment teams using the OFHAG and Fuels3D, a smartphone method utilising image-based point clouds, within three assessment plots in an Australian lowland forest. Surface fuel hazard scores derived from underpinning attributes were also assessed. Overall, this study found considerable variability between teams on most visually assessed variables, resulting in inconsistent hazard scores. Variability was observed within point cloud estimates but was, however, on average two to eight times less than that seen in visual estimates, indicating greater consistency and repeatability of this method. It is proposed that while variability within the Fuels3D method may be overcome through improved methods and equipment, inconsistencies in the OFHAG are likely due to the inherent subjectivity between assessors, which may be more difficult to overcome. This study demonstrates the capability of the Fuels3D method to efficiently and consistently collect data on fuel hazard and structure, and, as such, this method shows potential for use in fire management practices where accurate and reliable data is essential. PMID:28425957

Four points function fitted and first derivative procedure for determining the end points in potentiometric titration curves: statistical analysis and method comparison.

PubMed

Kholeif, S A

2001-06-01

A new method that belongs to the differential category for determining the end points from potentiometric titration curves is presented. It uses a preprocess to find first derivative values by fitting four data points in and around the region of inflection to a non-linear function, and then locate the end point, usually as a maximum or minimum, using an inverse parabolic interpolation procedure that has an analytical solution. The behavior and accuracy of the sigmoid and cumulative non-linear functions used are investigated against three factors. A statistical evaluation of the new method using linear least-squares method validation and multifactor data analysis are covered. The new method is generally applied to symmetrical and unsymmetrical potentiometric titration curves, and the end point is calculated using numerical procedures only. It outperforms the "parent" regular differential method in almost all factors levels and gives accurate results comparable to the true or estimated true end points. Calculated end points from selected experimental titration curves compatible with the equivalence point category of methods, such as Gran or Fortuin, are also compared with the new method.

Shear Elasticity and Shear Viscosity Imaging in Soft Tissue

NASA Astrophysics Data System (ADS)

Yang, Yiqun

In this thesis, a new approach is introduced that provides estimates of shear elasticity and shear viscosity using time-domain measurements of shear waves in viscoelastic media. Simulations of shear wave particle displacements induced by an acoustic radiation force are accelerated significantly by a GPU. The acoustic radiation force is first calculated using the fast near field method (FNM) and the angular spectrum approach (ASA). The shear waves induced by the acoustic radiation force are then simulated in elastic and viscoelastic media using Green's functions. A parallel algorithm is developed to perform these calculations on a GPU, where the shear wave particle displacements at different observation points are calculated in parallel. The resulting speed increase enables rapid evaluation of shear waves at discrete points, in 2D planes, and for push beams with different spatial samplings and for different values of the f-number (f/#). The results of these simulations show that push beams with smaller f/# require a higher spatial sampling rate. The significant amount of acceleration achieved by this approach suggests that shear wave simulations with the Green's function approach are ideally suited for high-performance GPUs. Shear wave elasticity imaging determines the mechanical parameters of soft tissue by analyzing measured shear waves induced by an acoustic radiation force. To estimate the shear elasticity value, the widely used time-of-flight method calculates the correlation between shear wave particle velocities at adjacent lateral observation points. Although this method provides accurate estimates of the shear elasticity in purely elastic media, our experience suggests that the time-of-flight (TOF) method consistently overestimates the shear elasticity values in viscoelastic media because the combined effects of diffraction, attenuation, and dispersion are not considered. To address this problem, we have developed an approach that directly accounts for all of these effects when estimating the shear elasticity. This new approach simulates shear wave particle velocities using a Green's function-based approach for the Voigt model, where the shear elasticity and viscosity values are estimated using an optimization-based approach that compares measured shear wave particle velocities with simulated shear wave particle velocities in the time-domain. The results are evaluated on a point-by-point basis to generate images. There is good agreement between the simulated and measured shear wave particle velocities, where the new approach yields much better images of the shear elasticity and shear viscosity than the TOF method. The new estimation approach is accelerated with an approximate viscoelastic Green's function model that is evaluated with shear wave data obtained from in vivo human livers. Instead of calculating shear waves with combinations of different shear elasticities and shear viscosities, shear waves are calculated with different shear elasticities on the GPU and then convolved with a viscous loss model, which accelerates the calculation dramatically. The shear elasticity and shear viscosity values are then estimated using an optimization-based approach by minimizing the difference between measured and simulated shear wave particle velocities. Shear elasticity and shear viscosity images are generated at every spatial point in a two-dimensional (2D) field-of-view (FOV). The new approach is applied to measured shear wave data obtained from in vivo human livers, and the results show that this new approach successfully generates shear elasticity and shear viscosity images from this data. The results also indicate that the shear elasticity values estimated with this approach are significantly smaller than the values estimated with the conventional TOF method and that the new approach demonstrates more consistent values for these estimates compared with the TOF method. This experience suggests that the new method is an effective approach for estimating the shear elasticity and the shear viscosity in liver and in other soft tissue.

Data Combination and Instrumental Variables in Linear Models

ERIC Educational Resources Information Center

Khawand, Christopher

2012-01-01

Instrumental variables (IV) methods allow for consistent estimation of causal effects, but suffer from poor finite-sample properties and data availability constraints. IV estimates also tend to have relatively large standard errors, often inhibiting the interpretability of differences between IV and non-IV point estimates. Lastly, instrumental…

Improving Estimations of Spatial Distribution of Soil Respiration Using the Bayesian Maximum Entropy Algorithm and Soil Temperature as Auxiliary Data.

PubMed

Hu, Junguo; Zhou, Jian; Zhou, Guomo; Luo, Yiqi; Xu, Xiaojun; Li, Pingheng; Liang, Junyi

2016-01-01

Soil respiration inherently shows strong spatial variability. It is difficult to obtain an accurate characterization of soil respiration with an insufficient number of monitoring points. However, it is expensive and cumbersome to deploy many sensors. To solve this problem, we proposed employing the Bayesian Maximum Entropy (BME) algorithm, using soil temperature as auxiliary information, to study the spatial distribution of soil respiration. The BME algorithm used the soft data (auxiliary information) effectively to improve the estimation accuracy of the spatiotemporal distribution of soil respiration. Based on the functional relationship between soil temperature and soil respiration, the BME algorithm satisfactorily integrated soil temperature data into said spatial distribution. As a means of comparison, we also applied the Ordinary Kriging (OK) and Co-Kriging (Co-OK) methods. The results indicated that the root mean squared errors (RMSEs) and absolute values of bias for both Day 1 and Day 2 were the lowest for the BME method, thus demonstrating its higher estimation accuracy. Further, we compared the performance of the BME algorithm coupled with auxiliary information, namely soil temperature data, and the OK method without auxiliary information in the same study area for 9, 21, and 37 sampled points. The results showed that the RMSEs for the BME algorithm (0.972 and 1.193) were less than those for the OK method (1.146 and 1.539) when the number of sampled points was 9 and 37, respectively. This indicates that the former method using auxiliary information could reduce the required number of sampling points for studying spatial distribution of soil respiration. Thus, the BME algorithm, coupled with soil temperature data, can not only improve the accuracy of soil respiration spatial interpolation but can also reduce the number of sampling points.

Improving Estimations of Spatial Distribution of Soil Respiration Using the Bayesian Maximum Entropy Algorithm and Soil Temperature as Auxiliary Data

PubMed Central

Hu, Junguo; Zhou, Jian; Zhou, Guomo; Luo, Yiqi; Xu, Xiaojun; Li, Pingheng; Liang, Junyi

2016-01-01

Soil respiration inherently shows strong spatial variability. It is difficult to obtain an accurate characterization of soil respiration with an insufficient number of monitoring points. However, it is expensive and cumbersome to deploy many sensors. To solve this problem, we proposed employing the Bayesian Maximum Entropy (BME) algorithm, using soil temperature as auxiliary information, to study the spatial distribution of soil respiration. The BME algorithm used the soft data (auxiliary information) effectively to improve the estimation accuracy of the spatiotemporal distribution of soil respiration. Based on the functional relationship between soil temperature and soil respiration, the BME algorithm satisfactorily integrated soil temperature data into said spatial distribution. As a means of comparison, we also applied the Ordinary Kriging (OK) and Co-Kriging (Co-OK) methods. The results indicated that the root mean squared errors (RMSEs) and absolute values of bias for both Day 1 and Day 2 were the lowest for the BME method, thus demonstrating its higher estimation accuracy. Further, we compared the performance of the BME algorithm coupled with auxiliary information, namely soil temperature data, and the OK method without auxiliary information in the same study area for 9, 21, and 37 sampled points. The results showed that the RMSEs for the BME algorithm (0.972 and 1.193) were less than those for the OK method (1.146 and 1.539) when the number of sampled points was 9 and 37, respectively. This indicates that the former method using auxiliary information could reduce the required number of sampling points for studying spatial distribution of soil respiration. Thus, the BME algorithm, coupled with soil temperature data, can not only improve the accuracy of soil respiration spatial interpolation but can also reduce the number of sampling points. PMID:26807579

Advantage of population pharmacokinetic method for evaluating the bioequivalence and accuracy of parameter estimation of pidotimod.

PubMed

Huang, Jihan; Li, Mengying; Lv, Yinghua; Yang, Juan; Xu, Ling; Wang, Jingjing; Chen, Junchao; Wang, Kun; He, Yingchun; Zheng, Qingshan

2016-09-01

This study was aimed at exploring the accuracy of population pharmacokinetic method in evaluating the bioequivalence of pidotimod with sparse data profiles and whether this method is suitable for bioequivalence evaluation in special populations such as children with fewer samplings. Methods In this single-dose, two-period crossover study, 20 healthy male Chinese volunteers were randomized 1 : 1 to receive either the test or reference formulation, with a 1-week washout before receiving the alternative formulation. Noncompartmental and population compartmental pharmacokinetic analyses were conducted. Simulated data were analyzed to graphically evaluate the model and the pharmacokinetic characteristics of the two pidotimod formulations. Various sparse sampling scenarios were generated from the real bioequivalence clinical trial data and evaluated by population pharmacokinetic method. The 90% confidence intervals (CIs) for AUC0-12h, AUC0-∞, and Cmax were 97.3 - 118.7%, 96.9 - 118.7%, and 95.1 - 109.8%, respectively, within the 80 - 125% range for bioequivalence using noncompartmental analysis. The population compartmental pharmacokinetics of pidotimod were described using a one-compartment model with first-order absorption and lag time. In the comparison of estimations in different dataset, the estimation of random three- and< fixed four-point sampling strategies can provide results similar to those obtained through rich sampling. The nonlinear mixed-effects model requires fewer data points. Moreover, compared with the noncompartmental analysis method, the pharmacokinetic parameters can be more accurately estimated using nonlinear mixed-effects model. The population pharmacokinetic modeling method was used to assess the bioequivalence of two pidotimod formulations with relatively few sampling points and further validated the bioequivalence of the two formulations. This method may provide useful information for regulating bioequivalence evaluation in special populations.

Impedance-estimation methods, modeling methods, articles of manufacture, impedance-modeling devices, and estimated-impedance monitoring systems

DOEpatents

Richardson, John G [Idaho Falls, ID

2009-11-17

An impedance estimation method includes measuring three or more impedances of an object having a periphery using three or more probes coupled to the periphery. The three or more impedance measurements are made at a first frequency. Three or more additional impedance measurements of the object are made using the three or more probes. The three or more additional impedance measurements are made at a second frequency different from the first frequency. An impedance of the object at a point within the periphery is estimated based on the impedance measurements and the additional impedance measurements.

Evaluation of Piloted Inputs for Onboard Frequency Response Estimation

NASA Technical Reports Server (NTRS)

Grauer, Jared A.; Martos, Borja

2013-01-01

Frequency response estimation results are presented using piloted inputs and a real-time estimation method recently developed for multisine inputs. A nonlinear simulation of the F-16 and a Piper Saratoga research aircraft were subjected to different piloted test inputs while the short period stabilator/elevator to pitch rate frequency response was estimated. Results show that the method can produce accurate results using wide-band piloted inputs instead of multisines. A new metric is introduced for evaluating which data points to include in the analysis and recommendations are provided for applying this method with piloted inputs.

Displacement fields from point cloud data: Application of particle imaging velocimetry to landslide geodesy

USGS Publications Warehouse

Aryal, Arjun; Brooks, Benjamin A.; Reid, Mark E.; Bawden, Gerald W.; Pawlak, Geno

2012-01-01

Acquiring spatially continuous ground-surface displacement fields from Terrestrial Laser Scanners (TLS) will allow better understanding of the physical processes governing landslide motion at detailed spatial and temporal scales. Problems arise, however, when estimating continuous displacement fields from TLS point-clouds because reflecting points from sequential scans of moving ground are not defined uniquely, thus repeat TLS surveys typically do not track individual reflectors. Here, we implemented the cross-correlation-based Particle Image Velocimetry (PIV) method to derive a surface deformation field using TLS point-cloud data. We estimated associated errors using the shape of the cross-correlation function and tested the method's performance with synthetic displacements applied to a TLS point cloud. We applied the method to the toe of the episodically active Cleveland Corral Landslide in northern California using TLS data acquired in June 2005–January 2007 and January–May 2010. Estimated displacements ranged from decimeters to several meters and they agreed well with independent measurements at better than 9% root mean squared (RMS) error. For each of the time periods, the method provided a smooth, nearly continuous displacement field that coincides with independently mapped boundaries of the slide and permits further kinematic and mechanical inference. For the 2010 data set, for instance, the PIV-derived displacement field identified a diffuse zone of displacement that preceded by over a month the development of a new lateral shear zone. Additionally, the upslope and downslope displacement gradients delineated by the dense PIV field elucidated the non-rigid behavior of the slide.

Estimating Contraceptive Prevalence Using Logistics Data for Short-Acting Methods: Analysis Across 30 Countries.

PubMed

Cunningham, Marc; Bock, Ariella; Brown, Niquelle; Sacher, Suzy; Hatch, Benjamin; Inglis, Andrew; Aronovich, Dana

2015-09-01

Contraceptive prevalence rate (CPR) is a vital indicator used by country governments, international donors, and other stakeholders for measuring progress in family planning programs against country targets and global initiatives as well as for estimating health outcomes. Because of the need for more frequent CPR estimates than population-based surveys currently provide, alternative approaches for estimating CPRs are being explored, including using contraceptive logistics data. Using data from the Demographic and Health Surveys (DHS) in 30 countries, population data from the United States Census Bureau International Database, and logistics data from the Procurement Planning and Monitoring Report (PPMR) and the Pipeline Monitoring and Procurement Planning System (PipeLine), we developed and evaluated 3 models to generate country-level, public-sector contraceptive prevalence estimates for injectable contraceptives, oral contraceptives, and male condoms. Models included: direct estimation through existing couple-years of protection (CYP) conversion factors, bivariate linear regression, and multivariate linear regression. Model evaluation consisted of comparing the referent DHS prevalence rates for each short-acting method with the model-generated prevalence rate using multiple metrics, including mean absolute error and proportion of countries where the modeled prevalence rate for each method was within 1, 2, or 5 percentage points of the DHS referent value. For the methods studied, family planning use estimates from public-sector logistics data were correlated with those from the DHS, validating the quality and accuracy of current public-sector logistics data. Logistics data for oral and injectable contraceptives were significantly associated (P<.05) with the referent DHS values for both bivariate and multivariate models. For condoms, however, that association was only significant for the bivariate model. With the exception of the CYP-based model for condoms, models were able to estimate public-sector prevalence rates for each short-acting method to within 2 percentage points in at least 85% of countries. Public-sector contraceptive logistics data are strongly correlated with public-sector prevalence rates for short-acting methods, demonstrating the quality of current logistics data and their ability to provide relatively accurate prevalence estimates. The models provide a starting point for generating interim estimates of contraceptive use when timely survey data are unavailable. All models except the condoms CYP model performed well; the regression models were most accurate but the CYP model offers the simplest calculation method. Future work extending the research to other modern methods, relating subnational logistics data with prevalence rates, and tracking that relationship over time is needed. © Cunningham et al.

Automated Transition State Theory Calculations for High-Throughput Kinetics.

PubMed

Bhoorasingh, Pierre L; Slakman, Belinda L; Seyedzadeh Khanshan, Fariba; Cain, Jason Y; West, Richard H

2017-09-21

A scarcity of known chemical kinetic parameters leads to the use of many reaction rate estimates, which are not always sufficiently accurate, in the construction of detailed kinetic models. To reduce the reliance on these estimates and improve the accuracy of predictive kinetic models, we have developed a high-throughput, fully automated, reaction rate calculation method, AutoTST. The algorithm integrates automated saddle-point geometry search methods and a canonical transition state theory kinetics calculator. The automatically calculated reaction rates compare favorably to existing estimated rates. Comparison against high level theoretical calculations show the new automated method performs better than rate estimates when the estimate is made by a poor analogy. The method will improve by accounting for internal rotor contributions and by improving methods to determine molecular symmetry.

Loose fusion based on SLAM and IMU for indoor environment

NASA Astrophysics Data System (ADS)

Zhu, Haijiang; Wang, Zhicheng; Zhou, Jinglin; Wang, Xuejing

2018-04-01

The simultaneous localization and mapping (SLAM) method based on the RGB-D sensor is widely researched in recent years. However, the accuracy of the RGB-D SLAM relies heavily on correspondence feature points, and the position would be lost in case of scenes with sparse textures. Therefore, plenty of fusion methods using the RGB-D information and inertial measurement unit (IMU) data have investigated to improve the accuracy of SLAM system. However, these fusion methods usually do not take into account the size of matched feature points. The pose estimation calculated by RGB-D information may not be accurate while the number of correct matches is too few. Thus, considering the impact of matches in SLAM system and the problem of missing position in scenes with few textures, a loose fusion method combining RGB-D with IMU is proposed in this paper. In the proposed method, we design a loose fusion strategy based on the RGB-D camera information and IMU data, which is to utilize the IMU data for position estimation when the corresponding point matches are quite few. While there are a lot of matches, the RGB-D information is still used to estimate position. The final pose would be optimized by General Graph Optimization (g2o) framework to reduce error. The experimental results show that the proposed method is better than the RGB-D camera's method. And this method can continue working stably for indoor environment with sparse textures in the SLAM system.

Robust estimation of pulse wave transit time using group delay.

PubMed

Meloni, Antonella; Zymeski, Heather; Pepe, Alessia; Lombardi, Massimo; Wood, John C

2014-03-01

To evaluate the efficiency of a novel transit time (Δt) estimation method from cardiovascular magnetic resonance flow curves. Flow curves were estimated from phase contrast images of 30 patients. Our method (TT-GD: transit time group delay) operates in the frequency domain and models the ascending aortic waveform as an input passing through a discrete-component "filter," producing the observed descending aortic waveform. The GD of the filter represents the average time delay (Δt) across individual frequency bands of the input. This method was compared with two previously described time-domain methods: TT-point using the half-maximum of the curves and TT-wave using cross-correlation. High temporal resolution flow images were studied at multiple downsampling rates to study the impact of differences in temporal resolution. Mean Δts obtained with the three methods were comparable. The TT-GD method was the most robust to reduced temporal resolution. While the TT-GD and the TT-wave produced comparable results for velocity and flow waveforms, the TT-point resulted in significant shorter Δts when calculated from velocity waveforms (difference: 1.8±2.7 msec; coefficient of variability: 8.7%). The TT-GD method was the most reproducible, with an intraobserver variability of 3.4% and an interobserver variability of 3.7%. Compared to the traditional TT-point and TT-wave methods, the TT-GD approach was more robust to the choice of temporal resolution, waveform type, and observer. Copyright © 2013 Wiley Periodicals, Inc.

Why Might Relative Fit Indices Differ between Estimators?

ERIC Educational Resources Information Center

Weng, Li-Jen; Cheng, Chung-Ping

1997-01-01

Relative fit indices using the null model as the reference point in computation may differ across estimation methods, as this article illustrates by comparing maximum likelihood, ordinary least squares, and generalized least squares estimation in structural equation modeling. The illustration uses a covariance matrix for six observed variables…

Joint Processing of Envelope Alignment and Phase Compensation for Isar Imaging

NASA Astrophysics Data System (ADS)

Chen, Tao; Jin, Guanghu; Dong, Zhen

2018-04-01

Range envelope alignment and phase compensation are spilt into two isolated parts in the classical methods of translational motion compensation in Inverse Synthetic Aperture Radar (ISAR) imaging. In classic method of the rotating object imaging, the two reference points of the envelope alignment and the Phase Difference (PD) estimation are probably not the same point, making it difficult to uncouple the coupling term by conducting the correction of Migration Through Resolution Cell (MTRC). In this paper, an improved approach of joint processing which chooses certain scattering point as the sole reference point is proposed to perform with utilizing the Prominent Point Processing (PPP) method. With this end in view, we firstly get the initial image using classical methods from which a certain scattering point can be chose. The envelope alignment and phase compensation using the selected scattering point as the same reference point are subsequently conducted. The keystone transform is thus smoothly applied to further improve imaging quality. Both simulation experiments and real data processing are provided to demonstrate the performance of the proposed method compared with classical method.

A removal model for estimating detection probabilities from point-count surveys

USGS Publications Warehouse

Farnsworth, G.L.; Pollock, K.H.; Nichols, J.D.; Simons, T.R.; Hines, J.E.; Sauer, J.R.

2002-01-01

Use of point-count surveys is a popular method for collecting data on abundance and distribution of birds. However, analyses of such data often ignore potential differences in detection probability. We adapted a removal model to directly estimate detection probability during point-count surveys. The model assumes that singing frequency is a major factor influencing probability of detection when birds are surveyed using point counts. This may be appropriate for surveys in which most detections are by sound. The model requires counts to be divided into several time intervals. Point counts are often conducted for 10 min, where the number of birds recorded is divided into those first observed in the first 3 min, the subsequent 2 min, and the last 5 min. We developed a maximum-likelihood estimator for the detectability of birds recorded during counts divided into those intervals. This technique can easily be adapted to point counts divided into intervals of any length. We applied this method to unlimited-radius counts conducted in Great Smoky Mountains National Park. We used model selection criteria to identify whether detection probabilities varied among species, throughout the morning, throughout the season, and among different observers. We found differences in detection probability among species. Species that sing frequently such as Winter Wren (Troglodytes troglodytes) and Acadian Flycatcher (Empidonax virescens) had high detection probabilities (∼90%) and species that call infrequently such as Pileated Woodpecker (Dryocopus pileatus) had low detection probability (36%). We also found detection probabilities varied with the time of day for some species (e.g. thrushes) and between observers for other species. We used the same approach to estimate detection probability and density for a subset of the observations with limited-radius point counts.

Estimating pore and cement volumes in thin section

USGS Publications Warehouse

Halley, R.B.

1978-01-01

Point count estimates of pore, grain and cement volumes from thin sections are inaccurate, often by more than 100 percent, even though they may be surprisingly precise (reproducibility + or - 3 percent). Errors are produced by: 1) inclusion of submicroscopic pore space within solid volume and 2) edge effects caused by grain curvature within a 30-micron thick thin section. Submicroscopic porosity may be measured by various physical tests or may be visually estimated from scanning electron micrographs. Edge error takes the form of an envelope around grains and increases with decreasing grain size and sorting, increasing grain irregularity and tighter grain packing. Cements are greatly involved in edge error because of their position at grain peripheries and their generally small grain size. Edge error is minimized by methods which reduce the thickness of the sample viewed during point counting. Methods which effectively reduce thickness include use of ultra-thin thin sections or acetate peels, point counting in reflected light, or carefully focusing and counting on the upper surface of the thin section.

New Hybrid Algorithms for Estimating Tree Stem Diameters at Breast Height Using a Two Dimensional Terrestrial Laser Scanner

PubMed Central

Kong, Jianlei; Ding, Xiaokang; Liu, Jinhao; Yan, Lei; Wang, Jianli

2015-01-01

In this paper, a new algorithm to improve the accuracy of estimating diameter at breast height (DBH) for tree trunks in forest areas is proposed. First, the information is collected by a two-dimensional terrestrial laser scanner (2DTLS), which emits laser pulses to generate a point cloud. After extraction and filtration, the laser point clusters of the trunks are obtained, which are optimized by an arithmetic means method. Then, an algebraic circle fitting algorithm in polar form is non-linearly optimized by the Levenberg-Marquardt method to form a new hybrid algorithm, which is used to acquire the diameters and positions of the trees. Compared with previous works, this proposed method improves the accuracy of diameter estimation of trees significantly and effectively reduces the calculation time. Moreover, the experimental results indicate that this method is stable and suitable for the most challenging conditions, which has practical significance in improving the operating efficiency of forest harvester and reducing the risk of causing accidents. PMID:26147726

Application of the Optimized Summed Scored Attributes Method to Sex Estimation in Asian Crania.

PubMed

Tallman, Sean D; Go, Matthew C

2018-05-01

The optimized summed scored attributes (OSSA) method was recently introduced and validated for nonmetric ancestry estimation between American Black and White individuals. The method proceeds by scoring, dichotomizing, and subsequently summing ordinal morphoscopic trait scores to maximize between-group differences. This study tests the applicability of the OSSA method for sex estimation using five cranial traits given the methodological similarities between classifying sex and ancestry. A large sample of documented crania from Japan and Thailand (n = 744 males, 320 females) are used to develop a heuristically selected OSSA sectioning point of ≤1 separating males and females. This sectioning point is validated using a holdout sample of Japanese, Thai, and Filipino (n = 178 males, 82 females) individuals. The results indicate a general correct classification rate of 82% using all five traits, and 81% when excluding the mental eminence. Designating an OSSA score of 2 as indeterminate is recommended. © 2017 American Academy of Forensic Sciences.

Non-destructive lichen biomass estimation in northwestern Alaska: a comparison of methods.

PubMed

Rosso, Abbey; Neitlich, Peter; Smith, Robert J

2014-01-01

Terrestrial lichen biomass is an important indicator of forage availability for caribou in northern regions, and can indicate vegetation shifts due to climate change, air pollution or changes in vascular plant community structure. Techniques for estimating lichen biomass have traditionally required destructive harvesting that is painstaking and impractical, so we developed models to estimate biomass from relatively simple cover and height measurements. We measured cover and height of forage lichens (including single-taxon and multi-taxa "community" samples, n = 144) at 73 sites on the Seward Peninsula of northwestern Alaska, and harvested lichen biomass from the same plots. We assessed biomass-to-volume relationships using zero-intercept regressions, and compared differences among two non-destructive cover estimation methods (ocular vs. point count), among four landcover types in two ecoregions, and among single-taxon vs. multi-taxa samples. Additionally, we explored the feasibility of using lichen height (instead of volume) as a predictor of stand-level biomass. Although lichen taxa exhibited unique biomass and bulk density responses that varied significantly by growth form, we found that single-taxon sampling consistently under-estimated true biomass and was constrained by the need for taxonomic experts. We also found that the point count method provided little to no improvement over ocular methods, despite increased effort. Estimated biomass of lichen-dominated communities (mean lichen cover: 84.9±1.4%) using multi-taxa, ocular methods differed only nominally among landcover types within ecoregions (range: 822 to 1418 g m-2). Height alone was a poor predictor of lichen biomass and should always be weighted by cover abundance. We conclude that the multi-taxa (whole-community) approach, when paired with ocular estimates, is the most reasonable and practical method for estimating lichen biomass at landscape scales in northwest Alaska.

Non-Destructive Lichen Biomass Estimation in Northwestern Alaska: A Comparison of Methods

PubMed Central

Rosso, Abbey; Neitlich, Peter; Smith, Robert J.

2014-01-01

Terrestrial lichen biomass is an important indicator of forage availability for caribou in northern regions, and can indicate vegetation shifts due to climate change, air pollution or changes in vascular plant community structure. Techniques for estimating lichen biomass have traditionally required destructive harvesting that is painstaking and impractical, so we developed models to estimate biomass from relatively simple cover and height measurements. We measured cover and height of forage lichens (including single-taxon and multi-taxa “community” samples, n = 144) at 73 sites on the Seward Peninsula of northwestern Alaska, and harvested lichen biomass from the same plots. We assessed biomass-to-volume relationships using zero-intercept regressions, and compared differences among two non-destructive cover estimation methods (ocular vs. point count), among four landcover types in two ecoregions, and among single-taxon vs. multi-taxa samples. Additionally, we explored the feasibility of using lichen height (instead of volume) as a predictor of stand-level biomass. Although lichen taxa exhibited unique biomass and bulk density responses that varied significantly by growth form, we found that single-taxon sampling consistently under-estimated true biomass and was constrained by the need for taxonomic experts. We also found that the point count method provided little to no improvement over ocular methods, despite increased effort. Estimated biomass of lichen-dominated communities (mean lichen cover: 84.9±1.4%) using multi-taxa, ocular methods differed only nominally among landcover types within ecoregions (range: 822 to 1418 g m−2). Height alone was a poor predictor of lichen biomass and should always be weighted by cover abundance. We conclude that the multi-taxa (whole-community) approach, when paired with ocular estimates, is the most reasonable and practical method for estimating lichen biomass at landscape scales in northwest Alaska. PMID:25079228

A comparison of methods for determining HIV viral set point.

PubMed

Mei, Y; Wang, L; Holte, S E

2008-01-15

During a course of human immunodeficiency virus (HIV-1) infection, the viral load usually increases sharply to a peak following infection and then drops rapidly to a steady state, where it remains until progression to AIDS. This steady state is often referred to as the viral set point. It is believed that the HIV viral set point results from an equilibrium between the HIV virus and immune response and is an important indicator of AIDS disease progression. In this paper, we analyze a real data set of viral loads measured before antiretroviral therapy is initiated, and propose two-phase regression models to utilize all available data to estimate the viral set point. The advantages of the proposed methods are illustrated by comparing them with two empirical methods, and the reason behind the improvement is also studied. Our results illustrate that for our data set, the viral load data are highly correlated and it is cost effective to estimate the viral set point based on one or two measurements obtained between 5 and 12 months after HIV infection. The utility and limitations of this recommendation will be discussed. Copyright (c) 2007 John Wiley & Sons, Ltd.

Fast Edge Detection and Segmentation of Terrestrial Laser Scans Through Normal Variation Analysis

NASA Astrophysics Data System (ADS)

Che, E.; Olsen, M. J.

2017-09-01

Terrestrial Laser Scanning (TLS) utilizes light detection and ranging (lidar) to effectively and efficiently acquire point cloud data for a wide variety of applications. Segmentation is a common procedure of post-processing to group the point cloud into a number of clusters to simplify the data for the sequential modelling and analysis needed for most applications. This paper presents a novel method to rapidly segment TLS data based on edge detection and region growing. First, by computing the projected incidence angles and performing the normal variation analysis, the silhouette edges and intersection edges are separated from the smooth surfaces. Then a modified region growing algorithm groups the points lying on the same smooth surface. The proposed method efficiently exploits the gridded scan pattern utilized during acquisition of TLS data from most sensors and takes advantage of parallel programming to process approximately 1 million points per second. Moreover, the proposed segmentation does not require estimation of the normal at each point, which limits the errors in normal estimation propagating to segmentation. Both an indoor and outdoor scene are used for an experiment to demonstrate and discuss the effectiveness and robustness of the proposed segmentation method.

Design with limited anthropometric data: A method of interpreting sums of percentiles in anthropometric design.

PubMed

Albin, Thomas J

2017-07-01

Occasionally practitioners must work with single dimensions defined as combinations (sums or differences) of percentile values, but lack information (e.g. variances) to estimate the accommodation achieved. This paper describes methods to predict accommodation proportions for such combinations of percentile values, e.g. two 90th percentile values. Kreifeldt and Nah z-score multipliers were used to estimate the proportions accommodated by combinations of percentile values of 2-15 variables; two simplified versions required less information about variance and/or correlation. The estimates were compared to actual observed proportions; for combinations of 2-15 percentile values the average absolute differences ranged between 0.5 and 1.5 percentage points. The multipliers were also used to estimate adjusted percentile values, that, when combined, estimate a desired proportion of the combined measurements. For combinations of two and three adjusted variables, the average absolute difference between predicted and observed proportions ranged between 0.5 and 3.0 percentage points. Copyright © 2017 Elsevier Ltd. All rights reserved.

a Threshold-Free Filtering Algorithm for Airborne LIDAR Point Clouds Based on Expectation-Maximization

NASA Astrophysics Data System (ADS)

Hui, Z.; Cheng, P.; Ziggah, Y. Y.; Nie, Y.

2018-04-01

Filtering is a key step for most applications of airborne LiDAR point clouds. Although lots of filtering algorithms have been put forward in recent years, most of them suffer from parameters setting or thresholds adjusting, which will be time-consuming and reduce the degree of automation of the algorithm. To overcome this problem, this paper proposed a threshold-free filtering algorithm based on expectation-maximization. The proposed algorithm is developed based on an assumption that point clouds are seen as a mixture of Gaussian models. The separation of ground points and non-ground points from point clouds can be replaced as a separation of a mixed Gaussian model. Expectation-maximization (EM) is applied for realizing the separation. EM is used to calculate maximum likelihood estimates of the mixture parameters. Using the estimated parameters, the likelihoods of each point belonging to ground or object can be computed. After several iterations, point clouds can be labelled as the component with a larger likelihood. Furthermore, intensity information was also utilized to optimize the filtering results acquired using the EM method. The proposed algorithm was tested using two different datasets used in practice. Experimental results showed that the proposed method can filter non-ground points effectively. To quantitatively evaluate the proposed method, this paper adopted the dataset provided by the ISPRS for the test. The proposed algorithm can obtain a 4.48 % total error which is much lower than most of the eight classical filtering algorithms reported by the ISPRS.

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

Shear wave speed estimation by adaptive random sample consensus method.

PubMed

Lin, Haoming; Wang, Tianfu; Chen, Siping

2014-01-01

This paper describes a new method for shear wave velocity estimation that is capable of extruding outliers automatically without preset threshold. The proposed method is an adaptive random sample consensus (ARANDSAC) and the metric used here is finding the certain percentage of inliers according to the closest distance criterion. To evaluate the method, the simulation and phantom experiment results were compared using linear regression with all points (LRWAP) and radon sum transform (RS) method. The assessment reveals that the relative biases of mean estimation are 20.00%, 4.67% and 5.33% for LRWAP, ARANDSAC and RS respectively for simulation, 23.53%, 4.08% and 1.08% for phantom experiment. The results suggested that the proposed ARANDSAC algorithm is accurate in shear wave speed estimation.

Using shape contexts method for registration of contra lateral breasts in thermal images.

PubMed

Etehadtavakol, Mahnaz; Ng, Eddie Yin-Kwee; Gheissari, Niloofar

2014-12-10

To achieve symmetric boundaries for left and right breasts boundaries in thermal images by registration. The proposed method for registration consists of two steps. In the first step, shape context, an approach as presented by Belongie and Malik was applied for registration of two breast boundaries. The shape context is an approach to measure shape similarity. Two sets of finite sample points from shape contours of two breasts are then presented. Consequently, the correspondences between the two shapes are found. By finding correspondences, the sample point which has the most similar shape context is obtained. In this study, a line up transformation which maps one shape onto the other has been estimated in order to complete shape. The used of a thin plate spline permitted good estimation of a plane transformation which has capability to map unselective points from one shape onto the other. The obtained aligning transformation of boundaries points has been applied successfully to map the two breasts interior points. Some of advantages for using shape context method in this work are as follows: (1) no special land marks or key points are needed; (2) it is tolerant to all common shape deformation; and (3) although it is uncomplicated and straightforward to use, it gives remarkably powerful descriptor for point sets significantly upgrading point set registration. Results are very promising. The proposed algorithm was implemented for 32 cases. Boundary registration is done perfectly for 28 cases. We used shape contexts method that is simple and easy to implement to achieve symmetric boundaries for left and right breasts boundaries in thermal images.

Estimating abundance and survival in the endangered Point Arena Mountain beaver using noninvasive genetic methods

Treesearch

William J. Zielinski; Fredrick V. Schlexer; T. Luke George; Kristine L. Pilgrim; Michael K. Schwartz

2013-01-01

The Point Arena mountain beaver (Aplodontia rufa nigra) is federally listed as an endangered subspecies that is restricted to a small geographic range in coastal Mendocino County, California. Management of this imperiled taxon requires accurate information on its demography and vital rates. We developed noninvasive survey methods, using hair snares to sample DNA and to...

Right ventricular strain analysis from three-dimensional echocardiography by using temporally diffeomorphic motion estimation.

PubMed

Zhang, Zhijun; Zhu, Meihua; Ashraf, Muhammad; Broberg, Craig S; Sahn, David J; Song, Xubo

2014-12-01

Quantitative analysis of right ventricle (RV) motion is important for study of the mechanism of congenital and acquired diseases. Unlike left ventricle (LV), motion estimation of RV is more difficult because of its complex shape and thin myocardium. Although attempts of finite element models on MR images and speckle tracking on echocardiography have shown promising results on RV strain analysis, these methods can be improved since the temporal smoothness of the motion is not considered. The authors have proposed a temporally diffeomorphic motion estimation method in which a spatiotemporal transformation is estimated by optimization of a registration energy functional of the velocity field in their earlier work. The proposed motion estimation method is a fully automatic process for general image sequences. The authors apply the method by combining with a semiautomatic myocardium segmentation method to the RV strain analysis of three-dimensional (3D) echocardiographic sequences of five open-chest pigs under different steady states. The authors compare the peak two-point strains derived by their method with those estimated from the sonomicrometry, the results show that they have high correlation. The motion of the right ventricular free wall is studied by using segmental strains. The baseline sequence results show that the segmental strains in their methods are consistent with results obtained by other image modalities such as MRI. The image sequences of pacing steady states show that segments with the largest strain variation coincide with the pacing sites. The high correlation of the peak two-point strains of their method and sonomicrometry under different steady states demonstrates that their RV motion estimation has high accuracy. The closeness of the segmental strain of their method to those from MRI shows the feasibility of their method in the study of RV function by using 3D echocardiography. The strain analysis of the pacing steady states shows the potential utility of their method in study on RV diseases.

Estimate Soil Erodibility Factors Distribution for Maioli Block

NASA Astrophysics Data System (ADS)

Lee, Wen-Ying

2014-05-01

The natural conditions in Taiwan are poor. Because of the steep slopes, rushing river and fragile geology, soil erosion turn into a serious problem. Not only undermine the sloping landscape, but also created sediment disaster like that reservoir sedimentation, river obstruction…etc. Therefore, predict and control the amount of soil erosion has become an important research topic. Soil erodibility factor (K) is a quantitative index of distinguish the ability of soil to resist the erosion separation and handling. Taiwan soil erodibility factors have been calculated 280 soil samples' erodibility factors by Wann and Huang (1989) use the Wischmeier and Smith nomorgraph. 221 samples were collected at the Maioli block in Miaoli. The coordinates of every sample point and the land use situations were recorded. The physical properties were analyzed for each sample. Three estimation methods, consist of Kriging, Inverse Distance Weighted (IDW) and Spline, were applied to estimate soil erodibility factors distribution for Maioli block by using 181 points data, and the remaining 40 points for the validation. Then, the SPSS regression analysis was used to comparison of the accuracy of the training data and validation data by three different methods. Then, the best method can be determined. In the future, we can used this method to predict the soil erodibility factors in other areas.

Loss Factor Estimation Using the Impulse Response Decay Method on a Stiffened Structure

NASA Technical Reports Server (NTRS)

Cabell, Randolph; Schiller, Noah; Allen, Albert; Moeller, Mark

2009-01-01

High-frequency vibroacoustic modeling is typically performed using energy-based techniques such as Statistical Energy Analysis (SEA). Energy models require an estimate of the internal damping loss factor. Unfortunately, the loss factor is difficult to estimate analytically, and experimental methods such as the power injection method can require extensive measurements over the structure of interest. This paper discusses the implications of estimating damping loss factors using the impulse response decay method (IRDM) from a limited set of response measurements. An automated procedure for implementing IRDM is described and then evaluated using data from a finite element model of a stiffened, curved panel. Estimated loss factors are compared with loss factors computed using a power injection method and a manual curve fit. The paper discusses the sensitivity of the IRDM loss factor estimates to damping of connected subsystems and the number and location of points in the measurement ensemble.

Collapsing lattice animals and lattice trees in two dimensions

NASA Astrophysics Data System (ADS)

Hsu, Hsiao-Ping; Grassberger, Peter

2005-06-01

We present high statistics simulations of weighted lattice bond animals and lattice trees on the square lattice, with fugacities for each non-bonded contact and for each bond between two neighbouring monomers. The simulations are performed using a newly developed sequential sampling method with resampling, very similar to the pruned-enriched Rosenbluth method (PERM) used for linear chain polymers. We determine with high precision the line of second-order transitions from an extended to a collapsed phase in the resulting two-dimensional phase diagram. This line includes critical bond percolation as a multicritical point, and we verify that this point divides the line into different universality classes. One of them corresponds to the collapse driven by contacts and includes the collapse of (weakly embeddable) trees. There is some evidence that the other is subdivided again into two parts with different universality classes. One of these (at the far side from collapsing trees) is bond driven and is represented by the Derrida-Herrmann model of animals having bonds only (no contacts). Between the critical percolation point and this bond-driven collapse seems to be an intermediate regime, whose other end point is a multicritical point P* where a transition line between two collapsed phases (one bond driven and the other contact driven) sparks off. This point P* seems to be attractive (in the renormalization group sense) from the side of the intermediate regime, so there are four universality classes on the transition line (collapsing trees, critical percolation, intermediate regime, and Derrida-Herrmann). We obtain very precise estimates for all critical exponents for collapsing trees. It is already harder to estimate the critical exponents for the intermediate regime. Finally, it is very difficult to obtain with our method good estimates of the critical parameters of the Derrida-Herrmann universality class. As regards the bond-driven to contact-driven transition in the collapsed phase, we have some evidence for its existence and rough location, but no precise estimates of critical exponents.

Probing-error compensation using 5 degree of freedom force/moment sensor for coordinate measuring machine

NASA Astrophysics Data System (ADS)

Lee, Minho; Cho, Nahm-Gyoo

2013-09-01

A new probing and compensation method is proposed to improve the three-dimensional (3D) measuring accuracy of 3D shapes, including irregular surfaces. A new tactile coordinate measuring machine (CMM) probe with a five-degree of freedom (5-DOF) force/moment sensor using carbon fiber plates was developed. The proposed method efficiently removes the anisotropic sensitivity error and decreases the stylus deformation and the actual contact point estimation errors that are major error components of shape measurement using touch probes. The relationship between the measuring force and estimation accuracy of the actual contact point error and stylus deformation error are examined for practical use of the proposed method. The appropriate measuring force condition is presented for the precision measurement.

Distortion correction of echo planar images applying the concept of finite rate of innovation to point spread function mapping (FRIP).

PubMed

Nunes, Rita G; Hajnal, Joseph V

2018-06-01

Point spread function (PSF) mapping enables estimating the displacement fields required for distortion correction of echo planar images. Recently, a highly accelerated approach was introduced for estimating displacements from the phase slope of under-sampled PSF mapping data. Sampling schemes with varying spacing were proposed requiring stepwise phase unwrapping. To avoid unwrapping errors, an alternative approach applying the concept of finite rate of innovation to PSF mapping (FRIP) is introduced, using a pattern search strategy to locate the PSF peak, and the two methods are compared. Fully sampled PSF data was acquired in six subjects at 3.0 T, and distortion maps were estimated after retrospective under-sampling. The two methods were compared for both previously published and newly optimized sampling patterns. Prospectively under-sampled data were also acquired. Shift maps were estimated and deviations relative to the fully sampled reference map were calculated. The best performance was achieved when using FRIP with a previously proposed sampling scheme. The two methods were comparable for the remaining schemes. The displacement field errors tended to be lower as the number of samples or their spacing increased. A robust method for estimating the position of the PSF peak has been introduced.

Dimension from covariance matrices.

PubMed

Carroll, T L; Byers, J M

2017-02-01

We describe a method to estimate embedding dimension from a time series. This method includes an estimate of the probability that the dimension estimate is valid. Such validity estimates are not common in algorithms for calculating the properties of dynamical systems. The algorithm described here compares the eigenvalues of covariance matrices created from an embedded signal to the eigenvalues for a covariance matrix of a Gaussian random process with the same dimension and number of points. A statistical test gives the probability that the eigenvalues for the embedded signal did not come from the Gaussian random process.

Robust estimation of adaptive tensors of curvature by tensor voting.

PubMed

Tong, Wai-Shun; Tang, Chi-Keung

2005-03-01

Although curvature estimation from a given mesh or regularly sampled point set is a well-studied problem, it is still challenging when the input consists of a cloud of unstructured points corrupted by misalignment error and outlier noise. Such input is ubiquitous in computer vision. In this paper, we propose a three-pass tensor voting algorithm to robustly estimate curvature tensors, from which accurate principal curvatures and directions can be calculated. Our quantitative estimation is an improvement over the previous two-pass algorithm, where only qualitative curvature estimation (sign of Gaussian curvature) is performed. To overcome misalignment errors, our improved method automatically corrects input point locations at subvoxel precision, which also rejects outliers that are uncorrectable. To adapt to different scales locally, we define the RadiusHit of a curvature tensor to quantify estimation accuracy and applicability. Our curvature estimation algorithm has been proven with detailed quantitative experiments, performing better in a variety of standard error metrics (percentage error in curvature magnitudes, absolute angle difference in curvature direction) in the presence of a large amount of misalignment noise.

Uncertainties for two-dimensional models of solar rotation from helioseismic eigenfrequency splitting

NASA Technical Reports Server (NTRS)

Genovese, Christopher R.; Stark, Philip B.; Thompson, Michael J.

1995-01-01

Observed solar p-mode frequency splittings can be used to estimate angular velocity as a function of position in the solar interior. Formal uncertainties of such estimates depend on the method of estimation (e.g., least-squares), the distribution of errors in the observations, and the parameterization imposed on the angular velocity. We obtain lower bounds on the uncertainties that do not depend on the method of estimation; the bounds depend on an assumed parameterization, but the fact that they are lower bounds for the 'true' uncertainty does not. Ninety-five percent confidence intervals for estimates of the angular velocity from 1986 Big Bear Solar Observatory (BBSO) data, based on a 3659 element tensor-product cubic-spline parameterization, are everywhere wider than 120 nHz, and exceed 60,000 nHz near the core. When compared with estimates of the solar rotation, these bounds reveal that useful inferences based on pointwise estimates of the angular velocity using 1986 BBSO splitting data are not feasible over most of the Sun's volume. The discouraging size of the uncertainties is due principally to the fact that helioseismic measurements are insensitive to changes in the angular velocity at individual points, so estimates of point values based on splittings are extremely uncertain. Functionals that measure distributed 'smooth' properties are, in general, better constrained than estimates of the rotation at a point. For example, the uncertainties in estimated differences of average rotation between adjacent blocks of about 0.001 solar volumes across the base of the convective zone are much smaller, and one of several estimated differences we compute appears significant at the 95% level.

Curve Set Feature-Based Robust and Fast Pose Estimation Algorithm

PubMed Central

Hashimoto, Koichi

2017-01-01

Bin picking refers to picking the randomly-piled objects from a bin for industrial production purposes, and robotic bin picking is always used in automated assembly lines. In order to achieve a higher productivity, a fast and robust pose estimation algorithm is necessary to recognize and localize the randomly-piled parts. This paper proposes a pose estimation algorithm for bin picking tasks using point cloud data. A novel descriptor Curve Set Feature (CSF) is proposed to describe a point by the surface fluctuation around this point and is also capable of evaluating poses. The Rotation Match Feature (RMF) is proposed to match CSF efficiently. The matching process combines the idea of the matching in 2D space of origin Point Pair Feature (PPF) algorithm with nearest neighbor search. A voxel-based pose verification method is introduced to evaluate the poses and proved to be more than 30-times faster than the kd-tree-based verification method. Our algorithm is evaluated against a large number of synthetic and real scenes and proven to be robust to noise, able to detect metal parts, more accurately and more than 10-times faster than PPF and Oriented, Unique and Repeatable (OUR)-Clustered Viewpoint Feature Histogram (CVFH). PMID:28771216

Influence of spatial temperature estimation method in ecohydrologic modeling in the western Oregon Cascades

Treesearch

E. Garcia; C.L. Tague; J. Choate

2013-01-01

Most spatially explicit hydrologic models require estimates of air temperature patterns. For these models, empirical relationships between elevation and air temperature are frequently used to upscale point measurements or downscale regional and global climate model estimates of air temperature. Mountainous environments are particularly sensitive to air temperature...

Adjusting for radiotelemetry error to improve estimates of habitat use.

Treesearch

Scott L. Findholt; Bruce K. Johnson; Lyman L. McDonald; John W. Kern; Alan Ager; Rosemary J. Stussy; Larry D. Bryant

2002-01-01

Animal locations estimated from radiotelemetry have traditionally been treated as error-free when analyzed in relation to habitat variables. Location error lowers the power of statistical tests of habitat selection. We describe a method that incorporates the error surrounding point estimates into measures of environmental variables determined from a geographic...

Effect of distance-related heterogeneity on population size estimates from point counts

USGS Publications Warehouse

Efford, Murray G.; Dawson, Deanna K.

2009-01-01

Point counts are used widely to index bird populations. Variation in the proportion of birds counted is a known source of error, and for robust inference it has been advocated that counts be converted to estimates of absolute population size. We used simulation to assess nine methods for the conduct and analysis of point counts when the data included distance-related heterogeneity of individual detection probability. Distance from the observer is a ubiquitous source of heterogeneity, because nearby birds are more easily detected than distant ones. Several recent methods (dependent double-observer, time of first detection, time of detection, independent multiple-observer, and repeated counts) do not account for distance-related heterogeneity, at least in their simpler forms. We assessed bias in estimates of population size by simulating counts with fixed radius w over four time intervals (occasions). Detection probability per occasion was modeled as a half-normal function of distance with scale parameter sigma and intercept g(0) = 1.0. Bias varied with sigma/w; values of sigma inferred from published studies were often 50% for a 100-m fixed-radius count. More critically, the bias of adjusted counts sometimes varied more than that of unadjusted counts, and inference from adjusted counts would be less robust. The problem was not solved by using mixture models or including distance as a covariate. Conventional distance sampling performed well in simulations, but its assumptions are difficult to meet in the field. We conclude that no existing method allows effective estimation of population size from point counts.

Improving the Curie depth estimation through optimizing the spectral block dimensions of the aeromagnetic data in the Sabalan geothermal field

NASA Astrophysics Data System (ADS)

Akbar, Somaieh; Fathianpour, Nader

2016-12-01

The Curie point depth is of great importance in characterizing geothermal resources. In this study, the Curie iso-depth map was provided using the well-known method of dividing the aeromagnetic dataset into overlapping blocks and analyzing the power spectral density of each block separately. Determining the optimum block dimension is vital in improving the resolution and accuracy of estimating Curie point depth. To investigate the relation between the optimal block size and power spectral density, a forward magnetic modeling was implemented on an artificial prismatic body with specified characteristics. The top, centroid, and bottom depths of the body were estimated by the spectral analysis method for different block dimensions. The result showed that the optimal block size could be considered as the smallest possible block size whose corresponding power spectrum represents an absolute maximum in small wavenumbers. The Curie depth map of the Sabalan geothermal field and its surrounding areas, in the northwestern Iran, was produced using a grid of 37 blocks with different dimensions from 10 × 10 to 50 × 50 km2, which showed at least 50% overlapping with adjacent blocks. The Curie point depth was estimated in the range of 5 to 21 km. The promising areas with the Curie point depths less than 8.5 km are located around Mountain Sabalan encompassing more than 90% of known geothermal resources in the study area. Moreover, the Curie point depth estimated by the improved spectral analysis is in good agreement with the depth calculated from the thermal gradient data measured in one of the exploratory wells in the region.

stochastic estimation of transmissivity fields conditioned to flow connectivity data

NASA Astrophysics Data System (ADS)

Freixas, Genis; Fernàndez-Garcia, Daniel; Sanchez-vila, Xavier

2017-04-01

Most methods for hydraulic parameter interpretation rely on a number of simplifications regarding the homogeneity of the underlying porous media. This way, the actual heterogeneity of any natural parameter, such as transmissivity, is transferred to the estimated in a way heavily dependent on the interpretation method used. An example is a pumping test, in most cases interpreted by means of the Cooper-Jacob method, which implicitly assumes a homogeneous isotropic confined aquifer. It was shown that the estimates obtained from this method when applied to a real site are not local values, but still have a physical meaning; the estimated transmissivity is equal to the effective transmissivity characteristic of the regional scale, while the log-ratio of the estimated storage coefficient with respect to the actual real value (assumed constant), indicated by , is an indicator of flow connectivity, representative of the scale given by the distance between the pumping and the observation wells. In this work we propose a methodology to use together with actual measurements of the log transmissivity at selected points to obtain a map of the best local transmissivity estimates using cokriging. Since the interpolation involves two variables measured at different support scales, a critical point is the estimation of the covariance and crosscovariance matrices, involving some quadratures that are obtained using some simplified approach. The method was applied to a synthetic field displaying statistical anisotropy, showing that the use of connectivity indicators mixed with the local values provide a better representation of the local value map, in particular regarding the enhanced representation of the continuity of structures corresponding to either high or low values.

Methods of albumin estimation in clinical biochemistry: Past, present, and future.

PubMed

Kumar, Deepak; Banerjee, Dibyajyoti

2017-06-01

Estimation of serum and urinary albumin is routinely performed in clinical biochemistry laboratories. In the past, precipitation-based methods were popular for estimation of human serum albumin (HSA). Currently, dye-binding or immunochemical methods are widely practiced. Each of these methods has its limitations. Research endeavors to overcome such limitations are on-going. The current trends in methodological aspects of albumin estimation guiding the field have not been reviewed. Therefore, it is the need of the hour to review several aspects of albumin estimation. The present review focuses on the modern trends of research from a conceptual point of view and gives an overview of recent developments to offer the readers a comprehensive understanding of the subject. Copyright © 2017 Elsevier B.V. All rights reserved.

A Bayesian Approach to Determination of F, D, and Z Values Used in Steam Sterilization Validation.

PubMed

Faya, Paul; Stamey, James D; Seaman, John W

2017-01-01

For manufacturers of sterile drug products, steam sterilization is a common method used to provide assurance of the sterility of manufacturing equipment and products. The validation of sterilization processes is a regulatory requirement and relies upon the estimation of key resistance parameters of microorganisms. Traditional methods have relied upon point estimates for the resistance parameters. In this paper, we propose a Bayesian method for estimation of the well-known D T , z , and F o values that are used in the development and validation of sterilization processes. A Bayesian approach allows the uncertainty about these values to be modeled using probability distributions, thereby providing a fully risk-based approach to measures of sterility assurance. An example is given using the survivor curve and fraction negative methods for estimation of resistance parameters, and we present a means by which a probabilistic conclusion can be made regarding the ability of a process to achieve a specified sterility criterion. LAY ABSTRACT: For manufacturers of sterile drug products, steam sterilization is a common method used to provide assurance of the sterility of manufacturing equipment and products. The validation of sterilization processes is a regulatory requirement and relies upon the estimation of key resistance parameters of microorganisms. Traditional methods have relied upon point estimates for the resistance parameters. In this paper, we propose a Bayesian method for estimation of the critical process parameters that are evaluated in the development and validation of sterilization processes. A Bayesian approach allows the uncertainty about these parameters to be modeled using probability distributions, thereby providing a fully risk-based approach to measures of sterility assurance. An example is given using the survivor curve and fraction negative methods for estimation of resistance parameters, and we present a means by which a probabilistic conclusion can be made regarding the ability of a process to achieve a specified sterility criterion. © PDA, Inc. 2017.

A comparison of alternative methods for estimating the self-thinning boundary line

Treesearch

Lianjun Zhang; Huiquan Bi; Jeffrey H. Gove; Linda S. Heath

2005-01-01

The fundamental validity of the self-thinning "law" has been debated over the last three decades. A long-sanding concern centers on how to objectively select data points for fitting the self-thinning line and the most appropriate regression method for estimating the two coefficients. Using data from an even-aged Pinus strobus L. stand as an...

The estimation of branching curves in the presence of subject-specific random effects.

PubMed

Elmi, Angelo; Ratcliffe, Sarah J; Guo, Wensheng

2014-12-20

Branching curves are a technique for modeling curves that change trajectory at a change (branching) point. Currently, the estimation framework is limited to independent data, and smoothing splines are used for estimation. This article aims to extend the branching curve framework to the longitudinal data setting where the branching point varies by subject. If the branching point is modeled as a random effect, then the longitudinal branching curve framework is a semiparametric nonlinear mixed effects model. Given existing issues with using random effects within a smoothing spline, we express the model as a B-spline based semiparametric nonlinear mixed effects model. Simple, clever smoothness constraints are enforced on the B-splines at the change point. The method is applied to Women's Health data where we model the shape of the labor curve (cervical dilation measured longitudinally) before and after treatment with oxytocin (a labor stimulant). Copyright © 2014 John Wiley & Sons, Ltd.

Object recognition and localization from 3D point clouds by maximum-likelihood estimation

NASA Astrophysics Data System (ADS)

Dantanarayana, Harshana G.; Huntley, Jonathan M.

2017-08-01

We present an algorithm based on maximum-likelihood analysis for the automated recognition of objects, and estimation of their pose, from 3D point clouds. Surfaces segmented from depth images are used as the features, unlike `interest point'-based algorithms which normally discard such data. Compared to the 6D Hough transform, it has negligible memory requirements, and is computationally efficient compared to iterative closest point algorithms. The same method is applicable to both the initial recognition/pose estimation problem as well as subsequent pose refinement through appropriate choice of the dispersion of the probability density functions. This single unified approach therefore avoids the usual requirement for different algorithms for these two tasks. In addition to the theoretical description, a simple 2 degrees of freedom (d.f.) example is given, followed by a full 6 d.f. analysis of 3D point cloud data from a cluttered scene acquired by a projected fringe-based scanner, which demonstrated an RMS alignment error as low as 0.3 mm.

Vanishing Point Extraction and Refinement for Robust Camera Calibration

PubMed Central

Tsai, Fuan

2017-01-01

This paper describes a flexible camera calibration method using refined vanishing points without prior information. Vanishing points are estimated from human-made features like parallel lines and repeated patterns. With the vanishing points extracted from the three mutually orthogonal directions, the interior and exterior orientation parameters can be further calculated using collinearity condition equations. A vanishing point refinement process is proposed to reduce the uncertainty caused by vanishing point localization errors. The fine-tuning algorithm is based on the divergence of grouped feature points projected onto the reference plane, minimizing the standard deviation of each of the grouped collinear points with an O(1) computational complexity. This paper also presents an automated vanishing point estimation approach based on the cascade Hough transform. The experiment results indicate that the vanishing point refinement process can significantly improve camera calibration parameters and the root mean square error (RMSE) of the constructed 3D model can be reduced by about 30%. PMID:29280966

A Direct Georeferencing Method for Terrestrial Laser Scanning Using GNSS Data and the Vertical Deflection from Global Earth Gravity Models

PubMed Central

Borkowski, Andrzej; Owczarek-Wesołowska, Magdalena; Gromczak, Anna

2017-01-01

Terrestrial laser scanning is an efficient technique in providing highly accurate point clouds for various geoscience applications. The point clouds have to be transformed to a well-defined reference frame, such as the global Geodetic Reference System 1980. The transformation to the geocentric coordinate frame is based on estimating seven Helmert parameters using several GNSS (Global Navigation Satellite System) referencing points. This paper proposes a method for direct point cloud georeferencing that provides coordinates in the geocentric frame. The proposed method employs the vertical deflection from an external global Earth gravity model and thus demands a minimum number of GNSS measurements. The proposed method can be helpful when the number of georeferencing GNSS points is limited, for instance in city corridors. It needs only two georeferencing points. The validation of the method in a field test reveals that the differences between the classical georefencing and the proposed method amount at maximum to 7 mm with the standard deviation of 8 mm for all of three coordinate components. The proposed method may serve as an alternative for the laser scanning data georeferencing, especially when the number of GNSS points is insufficient for classical methods. PMID:28672795

A Direct Georeferencing Method for Terrestrial Laser Scanning Using GNSS Data and the Vertical Deflection from Global Earth Gravity Models.

PubMed

Osada, Edward; Sośnica, Krzysztof; Borkowski, Andrzej; Owczarek-Wesołowska, Magdalena; Gromczak, Anna

2017-06-24

Terrestrial laser scanning is an efficient technique in providing highly accurate point clouds for various geoscience applications. The point clouds have to be transformed to a well-defined reference frame, such as the global Geodetic Reference System 1980. The transformation to the geocentric coordinate frame is based on estimating seven Helmert parameters using several GNSS (Global Navigation Satellite System) referencing points. This paper proposes a method for direct point cloud georeferencing that provides coordinates in the geocentric frame. The proposed method employs the vertical deflection from an external global Earth gravity model and thus demands a minimum number of GNSS measurements. The proposed method can be helpful when the number of georeferencing GNSS points is limited, for instance in city corridors. It needs only two georeferencing points. The validation of the method in a field test reveals that the differences between the classical georefencing and the proposed method amount at maximum to 7 mm with the standard deviation of 8 mm for all of three coordinate components. The proposed method may serve as an alternative for the laser scanning data georeferencing, especially when the number of GNSS points is insufficient for classical methods.

Eye Gaze Tracking using Correlation Filters

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

Karakaya, Mahmut; Boehnen, Chris Bensing; Bolme, David S

In this paper, we studied a method for eye gaze tracking that provide gaze estimation from a standard webcam with a zoom lens and reduce the setup and calibration requirements for new users. Specifically, we have developed a gaze estimation method based on the relative locations of points on the top of the eyelid and eye corners. Gaze estimation method in this paper is based on the distances between top point of the eyelid and eye corner detected by the correlation filters. Advanced correlation filters were found to provide facial landmark detections that are accurate enough to determine the subjectsmore » gaze direction up to angle of approximately 4-5 degrees although calibration errors often produce a larger overall shift in the estimates. This is approximately a circle of diameter 2 inches for a screen that is arm s length from the subject. At this accuracy it is possible to figure out what regions of text or images the subject is looking but it falls short of being able to determine which word the subject has looked at.« less

Sample size planning for composite reliability coefficients: accuracy in parameter estimation via narrow confidence intervals.

PubMed

Terry, Leann; Kelley, Ken

2012-11-01

Composite measures play an important role in psychology and related disciplines. Composite measures almost always have error. Correspondingly, it is important to understand the reliability of the scores from any particular composite measure. However, the point estimates of the reliability of composite measures are fallible and thus all such point estimates should be accompanied by a confidence interval. When confidence intervals are wide, there is much uncertainty in the population value of the reliability coefficient. Given the importance of reporting confidence intervals for estimates of reliability, coupled with the undesirability of wide confidence intervals, we develop methods that allow researchers to plan sample size in order to obtain narrow confidence intervals for population reliability coefficients. We first discuss composite reliability coefficients and then provide a discussion on confidence interval formation for the corresponding population value. Using the accuracy in parameter estimation approach, we develop two methods to obtain accurate estimates of reliability by planning sample size. The first method provides a way to plan sample size so that the expected confidence interval width for the population reliability coefficient is sufficiently narrow. The second method ensures that the confidence interval width will be sufficiently narrow with some desired degree of assurance (e.g., 99% assurance that the 95% confidence interval for the population reliability coefficient will be less than W units wide). The effectiveness of our methods was verified with Monte Carlo simulation studies. We demonstrate how to easily implement the methods with easy-to-use and freely available software. ©2011 The British Psychological Society.

Screening-level estimates of mass discharge uncertainty from point measurement methods

EPA Science Inventory

The uncertainty of mass discharge measurements associated with point-scale measurement techniques was investigated by deriving analytical solutions for the mass discharge coefficient of variation for two simplified, conceptual models. In the first case, a depth-averaged domain w...

Improving the Accuracy of Laplacian Estimation with Novel Variable Inter-Ring Distances Concentric Ring Electrodes

PubMed Central

Makeyev, Oleksandr; Besio, Walter G.

2016-01-01

Noninvasive concentric ring electrodes are a promising alternative to conventional disc electrodes. Currently, the superiority of tripolar concentric ring electrodes over disc electrodes, in particular, in accuracy of Laplacian estimation, has been demonstrated in a range of applications. In our recent work, we have shown that accuracy of Laplacian estimation can be improved with multipolar concentric ring electrodes using a general approach to estimation of the Laplacian for an (n + 1)-polar electrode with n rings using the (4n + 1)-point method for n ≥ 2. This paper takes the next step toward further improving the Laplacian estimate by proposing novel variable inter-ring distances concentric ring electrodes. Derived using a modified (4n + 1)-point method, linearly increasing and decreasing inter-ring distances tripolar (n = 2) and quadripolar (n = 3) electrode configurations are compared to their constant inter-ring distances counterparts. Finite element method modeling and analytic results are consistent and suggest that increasing inter-ring distances electrode configurations may decrease the truncation error resulting in more accurate Laplacian estimates compared to respective constant inter-ring distances configurations. For currently used tripolar electrode configuration, the truncation error may be decreased more than two-fold, while for the quadripolar configuration more than a six-fold decrease is expected. PMID:27294933

Improving the Accuracy of Laplacian Estimation with Novel Variable Inter-Ring Distances Concentric Ring Electrodes.

PubMed

Makeyev, Oleksandr; Besio, Walter G

2016-06-10

Noninvasive concentric ring electrodes are a promising alternative to conventional disc electrodes. Currently, the superiority of tripolar concentric ring electrodes over disc electrodes, in particular, in accuracy of Laplacian estimation, has been demonstrated in a range of applications. In our recent work, we have shown that accuracy of Laplacian estimation can be improved with multipolar concentric ring electrodes using a general approach to estimation of the Laplacian for an (n + 1)-polar electrode with n rings using the (4n + 1)-point method for n ≥ 2. This paper takes the next step toward further improving the Laplacian estimate by proposing novel variable inter-ring distances concentric ring electrodes. Derived using a modified (4n + 1)-point method, linearly increasing and decreasing inter-ring distances tripolar (n = 2) and quadripolar (n = 3) electrode configurations are compared to their constant inter-ring distances counterparts. Finite element method modeling and analytic results are consistent and suggest that increasing inter-ring distances electrode configurations may decrease the truncation error resulting in more accurate Laplacian estimates compared to respective constant inter-ring distances configurations. For currently used tripolar electrode configuration, the truncation error may be decreased more than two-fold, while for the quadripolar configuration more than a six-fold decrease is expected.

Filtering method of star control points for geometric correction of remote sensing image based on RANSAC algorithm

NASA Astrophysics Data System (ADS)

Tan, Xiangli; Yang, Jungang; Deng, Xinpu

2018-04-01

In the process of geometric correction of remote sensing image, occasionally, a large number of redundant control points may result in low correction accuracy. In order to solve this problem, a control points filtering algorithm based on RANdom SAmple Consensus (RANSAC) was proposed. The basic idea of the RANSAC algorithm is that using the smallest data set possible to estimate the model parameters and then enlarge this set with consistent data points. In this paper, unlike traditional methods of geometric correction using Ground Control Points (GCPs), the simulation experiments are carried out to correct remote sensing images, which using visible stars as control points. In addition, the accuracy of geometric correction without Star Control Points (SCPs) optimization is also shown. The experimental results show that the SCPs's filtering method based on RANSAC algorithm has a great improvement on the accuracy of remote sensing image correction.

Instantaneous and time-averaged dispersion and measurement models for estimation theory applications with elevated point source plumes

NASA Technical Reports Server (NTRS)

Diamante, J. M.; Englar, T. S., Jr.; Jazwinski, A. H.

1977-01-01

Estimation theory, which originated in guidance and control research, is applied to the analysis of air quality measurements and atmospheric dispersion models to provide reliable area-wide air quality estimates. A method for low dimensional modeling (in terms of the estimation state vector) of the instantaneous and time-average pollutant distributions is discussed. In particular, the fluctuating plume model of Gifford (1959) is extended to provide an expression for the instantaneous concentration due to an elevated point source. Individual models are also developed for all parameters in the instantaneous and the time-average plume equations, including the stochastic properties of the instantaneous fluctuating plume.

Debris-flow runout predictions based on the average channel slope (ACS)

USGS Publications Warehouse

Prochaska, A.B.; Santi, P.M.; Higgins, J.D.; Cannon, S.H.

2008-01-01

Prediction of the runout distance of a debris flow is an important element in the delineation of potentially hazardous areas on alluvial fans and for the siting of mitigation structures. Existing runout estimation methods rely on input parameters that are often difficult to estimate, including volume, velocity, and frictional factors. In order to provide a simple method for preliminary estimates of debris-flow runout distances, we developed a model that provides runout predictions based on the average channel slope (ACS model) for non-volcanic debris flows that emanate from confined channels and deposit on well-defined alluvial fans. This model was developed from 20 debris-flow events in the western United States and British Columbia. Based on a runout estimation method developed for snow avalanches, this model predicts debris-flow runout as an angle of reach from a fixed point in the drainage channel to the end of the runout zone. The best fixed point was found to be the mid-point elevation of the drainage channel, measured from the apex of the alluvial fan to the top of the drainage basin. Predicted runout lengths were more consistent than those obtained from existing angle-of-reach estimation methods. Results of the model compared well with those of laboratory flume tests performed using the same range of channel slopes. The robustness of this model was tested by applying it to three debris-flow events not used in its development: predicted runout ranged from 82 to 131% of the actual runout for these three events. Prediction interval multipliers were also developed so that the user may calculate predicted runout within specified confidence limits. ?? 2008 Elsevier B.V. All rights reserved.

Generalized shrunken type-GM estimator and its application

NASA Astrophysics Data System (ADS)

Ma, C. Z.; Du, Y. L.

2014-03-01

The parameter estimation problem in linear model is considered when multicollinearity and outliers exist simultaneously. A class of new robust biased estimator, Generalized Shrunken Type-GM Estimation, with their calculated methods are established by combination of GM estimator and biased estimator include Ridge estimate, Principal components estimate and Liu estimate and so on. A numerical example shows that the most attractive advantage of these new estimators is that they can not only overcome the multicollinearity of coefficient matrix and outliers but also have the ability to control the influence of leverage points.

A Comparative Study of Distribution System Parameter Estimation Methods

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

Sun, Yannan; Williams, Tess L.; Gourisetti, Sri Nikhil Gup

2016-07-17

In this paper, we compare two parameter estimation methods for distribution systems: residual sensitivity analysis and state-vector augmentation with a Kalman filter. These two methods were originally proposed for transmission systems, and are still the most commonly used methods for parameter estimation. Distribution systems have much lower measurement redundancy than transmission systems. Therefore, estimating parameters is much more difficult. To increase the robustness of parameter estimation, the two methods are applied with combined measurement snapshots (measurement sets taken at different points in time), so that the redundancy for computing the parameter values is increased. The advantages and disadvantages of bothmore » methods are discussed. The results of this paper show that state-vector augmentation is a better approach for parameter estimation in distribution systems. Simulation studies are done on a modified version of IEEE 13-Node Test Feeder with varying levels of measurement noise and non-zero error in the other system model parameters.« less

An adjoint-based simultaneous estimation method of the asthenosphere's viscosity and afterslip using a fast and scalable finite-element adjoint solver

NASA Astrophysics Data System (ADS)

Agata, Ryoichiro; Ichimura, Tsuyoshi; Hori, Takane; Hirahara, Kazuro; Hashimoto, Chihiro; Hori, Muneo

2018-04-01

The simultaneous estimation of the asthenosphere's viscosity and coseismic slip/afterslip is expected to improve largely the consistency of the estimation results to observation data of crustal deformation collected in widely spread observation points, compared to estimations of slips only. Such an estimate can be formulated as a non-linear inverse problem of material properties of viscosity and input force that is equivalent to fault slips based on large-scale finite-element (FE) modeling of crustal deformation, in which the degree of freedom is in the order of 109. We formulated and developed a computationally efficient adjoint-based estimation method for this inverse problem, together with a fast and scalable FE solver for the associated forward and adjoint problems. In a numerical experiment that imitates the 2011 Tohoku-Oki earthquake, the advantage of the proposed method is confirmed by comparing the estimated results with those obtained using simplified estimation methods. The computational cost required for the optimization shows that the proposed method enabled the targeted estimation to be completed with moderate amount of computational resources.

Motion estimation using point cluster method and Kalman filter.

PubMed

Senesh, M; Wolf, A

2009-05-01

The most frequently used method in a three dimensional human gait analysis involves placing markers on the skin of the analyzed segment. This introduces a significant artifact, which strongly influences the bone position and orientation and joint kinematic estimates. In this study, we tested and evaluated the effect of adding a Kalman filter procedure to the previously reported point cluster technique (PCT) in the estimation of a rigid body motion. We demonstrated the procedures by motion analysis of a compound planar pendulum from indirect opto-electronic measurements of markers attached to an elastic appendage that is restrained to slide along the rigid body long axis. The elastic frequency is close to the pendulum frequency, as in the biomechanical problem, where the soft tissue frequency content is similar to the actual movement of the bones. Comparison of the real pendulum angle to that obtained by several estimation procedures--PCT, Kalman filter followed by PCT, and low pass filter followed by PCT--enables evaluation of the accuracy of the procedures. When comparing the maximal amplitude, no effect was noted by adding the Kalman filter; however, a closer look at the signal revealed that the estimated angle based only on the PCT method was very noisy with fluctuation, while the estimated angle based on the Kalman filter followed by the PCT was a smooth signal. It was also noted that the instantaneous frequencies obtained from the estimated angle based on the PCT method is more dispersed than those obtained from the estimated angle based on Kalman filter followed by the PCT method. Addition of a Kalman filter to the PCT method in the estimation procedure of rigid body motion results in a smoother signal that better represents the real motion, with less signal distortion than when using a digital low pass filter. Furthermore, it can be concluded that adding a Kalman filter to the PCT procedure substantially reduces the dispersion of the maximal and minimal instantaneous frequencies.

Temporal Data Set Reduction Based on D-Optimality for Quantitative FLIM-FRET Imaging.

PubMed

Omer, Travis; Intes, Xavier; Hahn, Juergen

2015-01-01

Fluorescence lifetime imaging (FLIM) when paired with Förster resonance energy transfer (FLIM-FRET) enables the monitoring of nanoscale interactions in living biological samples. FLIM-FRET model-based estimation methods allow the quantitative retrieval of parameters such as the quenched (interacting) and unquenched (non-interacting) fractional populations of the donor fluorophore and/or the distance of the interactions. The quantitative accuracy of such model-based approaches is dependent on multiple factors such as signal-to-noise ratio and number of temporal points acquired when sampling the fluorescence decays. For high-throughput or in vivo applications of FLIM-FRET, it is desirable to acquire a limited number of temporal points for fast acquisition times. Yet, it is critical to acquire temporal data sets with sufficient information content to allow for accurate FLIM-FRET parameter estimation. Herein, an optimal experimental design approach based upon sensitivity analysis is presented in order to identify the time points that provide the best quantitative estimates of the parameters for a determined number of temporal sampling points. More specifically, the D-optimality criterion is employed to identify, within a sparse temporal data set, the set of time points leading to optimal estimations of the quenched fractional population of the donor fluorophore. Overall, a reduced set of 10 time points (compared to a typical complete set of 90 time points) was identified to have minimal impact on parameter estimation accuracy (≈5%), with in silico and in vivo experiment validations. This reduction of the number of needed time points by almost an order of magnitude allows the use of FLIM-FRET for certain high-throughput applications which would be infeasible if the entire number of time sampling points were used.

Use of dew-point hygrometry, direct sweat collection, and measurement of body water losses to determine sweating rates in exercising horses.

PubMed

Kingston, J K; Geor, R J; McCutcheon, L J

1997-02-01

To compare dew-point hygrometry, direct sweat collection, and measurement of body water loss as methods for determination of sweating rate (SR) in exercising horses. 6 exercise-trained Thoroughbreds. SR was measured in 6 horses exercising at 40% of the speed that elicited maximum oxygen consumption for 45 km, with a 15-minute rest at the end of each 15-km phase. Each horse completed 2 exercise trials. Dew-point hygrometry, as a method of local SR determination, was validated in vitro by measurement of rate of evaporative water loss. During exercise, local SR was determined every 10 minutes by the following 2 methods: (1) dew-point hygrometry on the neck and lateral area of the thorax, and (2) on the basis of the volume of sweat collected from a sealed plastic pouch attached to the lateral area of the thorax. Mean whole body SR was calculated from total body water loss incurred during exercise. Evaporation rate measured by use of dew-point hygrometry was significantly correlated (r2 = 0.92) with the actual rate of evaporative water loss. There was a similar pattern of change in SR measured by dew-point hygrometry on the neck and lateral area of the thorax during exercise, with a significantly higher SR on the neck. The SR measured on the thorax by direct sweat collection and by dew-point hygrometry were of similar magnitude. Mean whole body SR calculated from total body water loss was not significantly different from mean whole body SR estimated from direct sweat collection or dew-point hygrometry measurements on the thorax. Dew-point hygrometry and direct sweat collection are useful methods for determination of local SR in horses during prolonged, steady-state exercise in moderate ambient conditions. Both methods of local SR determination provide an accurate estimated of whole body SR.

Accuracy of Non-Destructive Testing of PBRs to Estimate Fragilities

NASA Astrophysics Data System (ADS)

Brune, J. N.; Brune, R.; Biasi, G. P.; Anooshehpoor, R.; Purvance, M.

2011-12-01

Prior studies of Precariously Balanced Rocks (PBRs) have involved various methods of documenting rock shapes and fragilities. These have included non-destructive testing (NDT) methods such as photomodeling, and potentially destructive testing (PDT) such as forced tilt tests. PDT methods usually have the potential of damaging or disturbing the rock or its pedestal so that the PBR usefulness for future generations is compromised. To date we have force-tilt tested approximately 28 PBRs, and of these we believe 7 have been compromised. We suggest here that given other inherent uncertainties in the current methodologies, NDT methods are now sufficiently advanced as to be adequate for the current state of the art use for comparison with Ground Motion Prediction Equations (GMPEs) and seismic hazard maps (SHMs). Here we compare tilt-test static toppling estimates to three non-destructive methods: (1) 3-D photographic modeling (2) profile analysis assuming the rock is 2-D, and (3) expert judgments from photographs. 3-D modeling uses the commercial Photomodeler program and photographs in the field taken from numerous directions around the rock. The output polyhedral shape is analyzed in Matlab determine the center of mass and in Autocad to estimate the static overturning angle alpha. For the 2-D method we chose the photograph in profile looking perpendicular to the estimated direction of toppling. The rock is outlined as a 2-D object in Matlab. Rock dimensions, rocking points, and a vertical reference are supplied by the photo analyst to estimate the center of gravity and static force overturning angles. For the expert opinion method we used additional photographs taken from different directions to improve the estimates of the center of mass and the rocking points. We used 7 rocks for comparisons. The error in estimating tan alpha from 3-D modeling is about 0.05. For 2-D estimates an average error is about 0.1 (?). For expert opinion estimates the error is about 0.06. For individual rocks the uncertainties may be reduced with more extensive study. The one case (*) where tilt-testing differs materially from 3-D is because an irregular base on the rock allowed the rock to begin to tilt at a lower angle onto a second rocking point with higher alpha. 2-D methods perform well enough to use as a screening method for the larger archive, and reserve the more accurate photographic analyses for the rocks deemed most important. The table below gives a list of the tan alpha data:
Tilt vs. NDT Tan(alpha) values

D Point Cloud Model Colorization by Dense Registration of Digital Images

NASA Astrophysics Data System (ADS)

Crombez, N.; Caron, G.; Mouaddib, E.

2015-02-01

Architectural heritage is a historic and artistic property which has to be protected, preserved, restored and must be shown to the public. Modern tools like 3D laser scanners are more and more used in heritage documentation. Most of the time, the 3D laser scanner is completed by a digital camera which is used to enrich the accurate geometric informations with the scanned objects colors. However, the photometric quality of the acquired point clouds is generally rather low because of several problems presented below. We propose an accurate method for registering digital images acquired from any viewpoints on point clouds which is a crucial step for a good colorization by colors projection. We express this image-to-geometry registration as a pose estimation problem. The camera pose is computed using the entire images intensities under a photometric visual and virtual servoing (VVS) framework. The camera extrinsic and intrinsic parameters are automatically estimated. Because we estimates the intrinsic parameters we do not need any informations about the camera which took the used digital image. Finally, when the point cloud model and the digital image are correctly registered, we project the 3D model in the digital image frame and assign new colors to the visible points. The performance of the approach is proven in simulation and real experiments on indoor and outdoor datasets of the cathedral of Amiens, which highlight the success of our method, leading to point clouds with better photometric quality and resolution.

An adaptive gridless methodology in one dimension

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

Snyder, N.T.; Hailey, C.E.

1996-09-01

Gridless numerical analysis offers great potential for accurately solving for flow about complex geometries or moving boundary problems. Because gridless methods do not require point connection, the mesh cannot twist or distort. The gridless method utilizes a Taylor series about each point to obtain the unknown derivative terms from the current field variable estimates. The governing equation is then numerically integrated to determine the field variables for the next iteration. Effects of point spacing and Taylor series order on accuracy are studied, and they follow similar trends of traditional numerical techniques. Introducing adaption by point movement using a spring analogymore » allows the solution method to track a moving boundary. The adaptive gridless method models linear, nonlinear, steady, and transient problems. Comparison with known analytic solutions is given for these examples. Although point movement adaption does not provide a significant increase in accuracy, it helps capture important features and provides an improved solution.« less

An adaptive finite element method for the inequality-constrained Reynolds equation

NASA Astrophysics Data System (ADS)

Gustafsson, Tom; Rajagopal, Kumbakonam R.; Stenberg, Rolf; Videman, Juha

2018-07-01

We present a stabilized finite element method for the numerical solution of cavitation in lubrication, modeled as an inequality-constrained Reynolds equation. The cavitation model is written as a variable coefficient saddle-point problem and approximated by a residual-based stabilized method. Based on our recent results on the classical obstacle problem, we present optimal a priori estimates and derive novel a posteriori error estimators. The method is implemented as a Nitsche-type finite element technique and shown in numerical computations to be superior to the usually applied penalty methods.

Blind estimation of blur in hyperspectral images

NASA Astrophysics Data System (ADS)

Zhang, Mo; Vozel, Benoit; Chehdi, Kacem; Uss, Mykhail; Abramov, Sergey; Lukin, Vladimir

2017-10-01

Hyperspectral images acquired by remote sensing systems are generally degraded by noise and can be sometimes more severely degraded by blur. When no knowledge is available about the degradations present on the original image, blind restoration methods can only be considered. By blind, we mean absolutely no knowledge neither of the blur point spread function (PSF) nor the original latent channel and the noise level. In this study, we address the blind restoration of the degraded channels component-wise, according to a sequential scheme. For each degraded channel, the sequential scheme estimates the blur point spread function (PSF) in a first stage and deconvolves the degraded channel in a second and final stage by means of using the PSF previously estimated. We propose a new component-wise blind method for estimating effectively and accurately the blur point spread function. This method follows recent approaches suggesting the detection, selection and use of sufficiently salient edges in the current processed channel for supporting the regularized blur PSF estimation. Several modifications are beneficially introduced in our work. A new selection of salient edges through thresholding adequately the cumulative distribution of their corresponding gradient magnitudes is introduced. Besides, quasi-automatic and spatially adaptive tuning of the involved regularization parameters is considered. To prove applicability and higher efficiency of the proposed method, we compare it against the method it originates from and four representative edge-sparsifying regularized methods of the literature already assessed in a previous work. Our attention is mainly paid to the objective analysis (via ݈l1-norm) of the blur PSF error estimation accuracy. The tests are performed on a synthetic hyperspectral image. This synthetic hyperspectral image has been built from various samples from classified areas of a real-life hyperspectral image, in order to benefit from realistic spatial distribution of reference spectral signatures to recover after synthetic degradation. The synthetic hyperspectral image has been successively degraded with eight real blurs taken from the literature, each of a different support size. Conclusions, practical recommendations and perspectives are drawn from the results experimentally obtained.

Estimation of boiling points using density functional theory with polarized continuum model solvent corrections.

PubMed

Chan, Poh Yin; Tong, Chi Ming; Durrant, Marcus C

2011-09-01

An empirical method for estimation of the boiling points of organic molecules based on density functional theory (DFT) calculations with polarized continuum model (PCM) solvent corrections has been developed. The boiling points are calculated as the sum of three contributions. The first term is calculated directly from the structural formula of the molecule, and is related to its effective surface area. The second is a measure of the electronic interactions between molecules, based on the DFT-PCM solvation energy, and the third is employed only for planar aromatic molecules. The method is applicable to a very diverse range of organic molecules, with normal boiling points in the range of -50 to 500 °C, and includes ten different elements (C, H, Br, Cl, F, N, O, P, S and Si). Plots of observed versus calculated boiling points gave R²=0.980 for a training set of 317 molecules, and R²=0.979 for a test set of 74 molecules. The role of intramolecular hydrogen bonding in lowering the boiling points of certain molecules is quantitatively discussed. Crown Copyright © 2011. Published by Elsevier Inc. All rights reserved.

Simulation of design-unbiased point-to-particle sampling compared to alternatives on plantation rows

Treesearch

Thomas B. Lynch; David Hamlin; Mark J. Ducey

2016-01-01

Total quantities of tree attributes can be estimated in plantations by sampling on plantation rows using several methods. At random sample points on a row, either fixed row lengths or variable row lengths with a fixed number of sample trees can be assessed. Ratio of means or mean of ratios estimators can be developed for the fixed number of trees option but are not...

Drogue tracking using 3D flash lidar for autonomous aerial refueling

NASA Astrophysics Data System (ADS)

Chen, Chao-I.; Stettner, Roger

2011-06-01

Autonomous aerial refueling (AAR) is an important capability for an unmanned aerial vehicle (UAV) to increase its flying range and endurance without increasing its size. This paper presents a novel tracking method that utilizes both 2D intensity and 3D point-cloud data acquired with a 3D Flash LIDAR sensor to establish relative position and orientation between the receiver vehicle and drogue during an aerial refueling process. Unlike classic, vision-based sensors, a 3D Flash LIDAR sensor can provide 3D point-cloud data in real time without motion blur, in the day or night, and is capable of imaging through fog and clouds. The proposed method segments out the drogue through 2D analysis and estimates the center of the drogue from 3D point-cloud data for flight trajectory determination. A level-set front propagation routine is first employed to identify the target of interest and establish its silhouette information. Sufficient domain knowledge, such as the size of the drogue and the expected operable distance, is integrated into our approach to quickly eliminate unlikely target candidates. A statistical analysis along with a random sample consensus (RANSAC) is performed on the target to reduce noise and estimate the center of the drogue after all 3D points on the drogue are identified. The estimated center and drogue silhouette serve as the seed points to efficiently locate the target in the next frame.

An analysis of neural receptive field plasticity by point process adaptive filtering

PubMed Central

Brown, Emery N.; Nguyen, David P.; Frank, Loren M.; Wilson, Matthew A.; Solo, Victor

2001-01-01

Neural receptive fields are plastic: with experience, neurons in many brain regions change their spiking responses to relevant stimuli. Analysis of receptive field plasticity from experimental measurements is crucial for understanding how neural systems adapt their representations of relevant biological information. Current analysis methods using histogram estimates of spike rate functions in nonoverlapping temporal windows do not track the evolution of receptive field plasticity on a fine time scale. Adaptive signal processing is an established engineering paradigm for estimating time-varying system parameters from experimental measurements. We present an adaptive filter algorithm for tracking neural receptive field plasticity based on point process models of spike train activity. We derive an instantaneous steepest descent algorithm by using as the criterion function the instantaneous log likelihood of a point process spike train model. We apply the point process adaptive filter algorithm in a study of spatial (place) receptive field properties of simulated and actual spike train data from rat CA1 hippocampal neurons. A stability analysis of the algorithm is sketched in the Appendix. The adaptive algorithm can update the place field parameter estimates on a millisecond time scale. It reliably tracked the migration, changes in scale, and changes in maximum firing rate characteristic of hippocampal place fields in a rat running on a linear track. Point process adaptive filtering offers an analytic method for studying the dynamics of neural receptive fields. PMID:11593043

Carbon Sequestration Estimation of Street Trees Based on Point Cloud from Vehicle-Borne Laser Scanning System

NASA Astrophysics Data System (ADS)

Zhao, Y.; Hu, Q.

2017-09-01

Continuous development of urban road traffic system requests higher standards of road ecological environment. Ecological benefits of street trees are getting more attention. Carbon sequestration of street trees refers to the carbon stocks of street trees, which can be a measurement for ecological benefits of street trees. Estimating carbon sequestration in a traditional way is costly and inefficient. In order to solve above problems, a carbon sequestration estimation approach for street trees based on 3D point cloud from vehicle-borne laser scanning system is proposed in this paper. The method can measure the geometric parameters of a street tree, including tree height, crown width, diameter at breast height (DBH), by processing and analyzing point cloud data of an individual tree. Four Chinese scholartree trees and four camphor trees are selected for experiment. The root mean square error (RMSE) of tree height is 0.11m for Chinese scholartree and 0.02m for camphor. Crown widths in X direction and Y direction, as well as the average crown width are calculated. And the RMSE of average crown width is 0.22m for Chinese scholartree and 0.10m for camphor. The last calculated parameter is DBH, the RMSE of DBH is 0.5cm for both Chinese scholartree and camphor. Combining the measured geometric parameters and an appropriate carbon sequestration calculation model, the individual tree's carbon sequestration will be estimated. The proposed method can help enlarge application range of vehicle-borne laser point cloud data, improve the efficiency of estimating carbon sequestration, construct urban ecological environment and manage landscape.

Section-Based Tree Species Identification Using Airborne LIDAR Point Cloud

NASA Astrophysics Data System (ADS)

Yao, C.; Zhang, X.; Liu, H.

2017-09-01

The application of LiDAR data in forestry initially focused on mapping forest community, particularly and primarily intended for largescale forest management and planning. Then with the smaller footprint and higher sampling density LiDAR data available, detecting individual tree overstory, estimating crowns parameters and identifying tree species are demonstrated practicable. This paper proposes a section-based protocol of tree species identification taking palm tree as an example. Section-based method is to detect objects through certain profile among different direction, basically along X-axis or Y-axis. And this method improve the utilization of spatial information to generate accurate results. Firstly, separate the tree points from manmade-object points by decision-tree-based rules, and create Crown Height Mode (CHM) by subtracting the Digital Terrain Model (DTM) from the digital surface model (DSM). Then calculate and extract key points to locate individual trees, thus estimate specific tree parameters related to species information, such as crown height, crown radius, and cross point etc. Finally, with parameters we are able to identify certain tree species. Comparing to species information measured on ground, the portion correctly identified trees on all plots could reach up to 90.65 %. The identification result in this research demonstrate the ability to distinguish palm tree using LiDAR point cloud. Furthermore, with more prior knowledge, section-based method enable the process to classify trees into different classes.

Estimating the remaining useful life of bearings using a neuro-local linear estimator-based method.

PubMed

Ahmad, Wasim; Ali Khan, Sheraz; Kim, Jong-Myon

2017-05-01

Estimating the remaining useful life (RUL) of a bearing is required for maintenance scheduling. While the degradation behavior of a bearing changes during its lifetime, it is usually assumed to follow a single model. In this letter, bearing degradation is modeled by a monotonically increasing function that is globally non-linear and locally linearized. The model is generated using historical data that is smoothed with a local linear estimator. A neural network learns this model and then predicts future levels of vibration acceleration to estimate the RUL of a bearing. The proposed method yields reasonably accurate estimates of the RUL of a bearing at different points during its operational life.

Methods for Estimation of Market Power in Electric Power Industry

NASA Astrophysics Data System (ADS)

Turcik, M.; Oleinikova, I.; Junghans, G.; Kolcun, M.

2012-01-01

The article is related to a topical issue of the newly-arisen market power phenomenon in the electric power industry. The authors point out to the importance of effective instruments and methods for credible estimation of the market power on liberalized electricity market as well as the forms and consequences of market power abuse. The fundamental principles and methods of the market power estimation are given along with the most common relevant indicators. Furthermore, in the work a proposal for determination of the relevant market place taking into account the specific features of power system and a theoretical example of estimating the residual supply index (RSI) in the electricity market are given.

Measurement Uncertainty of Dew-Point Temperature in a Two-Pressure Humidity Generator

NASA Astrophysics Data System (ADS)

Martins, L. Lages; Ribeiro, A. Silva; Alves e Sousa, J.; Forbes, Alistair B.

2012-09-01

This article describes the measurement uncertainty evaluation of the dew-point temperature when using a two-pressure humidity generator as a reference standard. The estimation of the dew-point temperature involves the solution of a non-linear equation for which iterative solution techniques, such as the Newton-Raphson method, are required. Previous studies have already been carried out using the GUM method and the Monte Carlo method but have not discussed the impact of the approximate numerical method used to provide the temperature estimation. One of the aims of this article is to take this approximation into account. Following the guidelines presented in the GUM Supplement 1, two alternative approaches can be developed: the forward measurement uncertainty propagation by the Monte Carlo method when using the Newton-Raphson numerical procedure; and the inverse measurement uncertainty propagation by Bayesian inference, based on prior available information regarding the usual dispersion of values obtained by the calibration process. The measurement uncertainties obtained using these two methods can be compared with previous results. Other relevant issues concerning this research are the broad application to measurements that require hygrometric conditions obtained from two-pressure humidity generators and, also, the ability to provide a solution that can be applied to similar iterative models. The research also studied the factors influencing both the use of the Monte Carlo method (such as the seed value and the convergence parameter) and the inverse uncertainty propagation using Bayesian inference (such as the pre-assigned tolerance, prior estimate, and standard deviation) in terms of their accuracy and adequacy.

A model for estimation of potential generation of waste electrical and electronic equipment in Brazil

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

Araujo, Marcelo Guimaraes, E-mail: marcel_g@uol.com.br; Magrini, Alessandra; Mahler, Claudio Fernando

2012-02-15

Highlights: Black-Right-Pointing-Pointer Literature of WEEE generation in developing countries is reviewed. Black-Right-Pointing-Pointer We analyse existing estimates of WEEE generation for Brazil. Black-Right-Pointing-Pointer We present a model for WEEE generation estimate. Black-Right-Pointing-Pointer WEEE generation of 3.77 kg/capita year for 2008 is estimated. Black-Right-Pointing-Pointer Use of constant lifetime should be avoided for non-mature market products. - Abstract: Sales of electrical and electronic equipment are increasing dramatically in developing countries. Usually, there are no reliable data about quantities of the waste generated. A new law for solid waste management was enacted in Brazil in 2010, and the infrastructure to treat this waste mustmore » be planned, considering the volumes of the different types of electrical and electronic equipment generated. This paper reviews the literature regarding estimation of waste electrical and electronic equipment (WEEE), focusing on developing countries, particularly in Latin America. It briefly describes the current WEEE system in Brazil and presents an updated estimate of generation of WEEE. Considering the limited available data in Brazil, a model for WEEE generation estimation is proposed in which different methods are used for mature and non-mature market products. The results showed that the most important variable is the equipment lifetime, which requires a thorough understanding of consumer behavior to estimate. Since Brazil is a rapidly expanding market, the 'boom' in waste generation is still to come. In the near future, better data will provide more reliable estimation of waste generation and a clearer interpretation of the lifetime variable throughout the years.« less

A Comprehensive Motion Estimation Technique for the Improvement of EIS Methods Based on the SURF Algorithm and Kalman Filter.

PubMed

Cheng, Xuemin; Hao, Qun; Xie, Mengdi

2016-04-07

Video stabilization is an important technology for removing undesired motion in videos. This paper presents a comprehensive motion estimation method for electronic image stabilization techniques, integrating the speeded up robust features (SURF) algorithm, modified random sample consensus (RANSAC), and the Kalman filter, and also taking camera scaling and conventional camera translation and rotation into full consideration. Using SURF in sub-pixel space, feature points were located and then matched. The false matched points were removed by modified RANSAC. Global motion was estimated by using the feature points and modified cascading parameters, which reduced the accumulated errors in a series of frames and improved the peak signal to noise ratio (PSNR) by 8.2 dB. A specific Kalman filter model was established by considering the movement and scaling of scenes. Finally, video stabilization was achieved with filtered motion parameters using the modified adjacent frame compensation. The experimental results proved that the target images were stabilized even when the vibrating amplitudes of the video become increasingly large.

Robust Stereo Visual Odometry Using Improved RANSAC-Based Methods for Mobile Robot Localization

PubMed Central

Liu, Yanqing; Gu, Yuzhang; Li, Jiamao; Zhang, Xiaolin

2017-01-01

In this paper, we present a novel approach for stereo visual odometry with robust motion estimation that is faster and more accurate than standard RANSAC (Random Sample Consensus). Our method makes improvements in RANSAC in three aspects: first, the hypotheses are preferentially generated by sampling the input feature points on the order of ages and similarities of the features; second, the evaluation of hypotheses is performed based on the SPRT (Sequential Probability Ratio Test) that makes bad hypotheses discarded very fast without verifying all the data points; third, we aggregate the three best hypotheses to get the final estimation instead of only selecting the best hypothesis. The first two aspects improve the speed of RANSAC by generating good hypotheses and discarding bad hypotheses in advance, respectively. The last aspect improves the accuracy of motion estimation. Our method was evaluated in the KITTI (Karlsruhe Institute of Technology and Toyota Technological Institute) and the New Tsukuba dataset. Experimental results show that the proposed method achieves better results for both speed and accuracy than RANSAC. PMID:29027935

Mapping stream habitats with a global positioning system: Accuracy, precision, and comparison with traditional methods

USGS Publications Warehouse

Dauwalter, D.C.; Fisher, W.L.; Belt, K.C.

2006-01-01

We tested the precision and accuracy of the Trimble GeoXT??? global positioning system (GPS) handheld receiver on point and area features and compared estimates of stream habitat dimensions (e.g., lengths and areas of riffles and pools) that were made in three different Oklahoma streams using the GPS receiver and a tape measure. The precision of differentially corrected GPS (DGPS) points was not affected by the number of GPS position fixes (i.e., geographic location estimates) averaged per DGPS point. Horizontal error of points ranged from 0.03 to 2.77 m and did not differ with the number of position fixes per point. The error of area measurements ranged from 0.1% to 110.1% but decreased as the area increased. Again, error was independent of the number of position fixes averaged per polygon corner. The estimates of habitat lengths, widths, and areas did not differ when measured using two methods of data collection (GPS and a tape measure), nor did the differences among methods change at three stream sites with contrasting morphologies. Measuring features with a GPS receiver was up to 3.3 times faster on average than using a tape measure, although signal interference from high streambanks or overhanging vegetation occasionally limited satellite signal availability and prolonged measurements with a GPS receiver. There were also no differences in precision of habitat dimensions when mapped using a continuous versus a position fix average GPS data collection method. Despite there being some disadvantages to using the GPS in stream habitat studies, measuring stream habitats with a GPS resulted in spatially referenced data that allowed the assessment of relative habitat position and changes in habitats over time, and was often faster than using a tape measure. For most spatial scales of interest, the precision and accuracy of DGPS data are adequate and have logistical advantages when compared to traditional methods of measurement. ?? 2006 Springer Science+Business Media, Inc.

A double-observer approach for estimating detection probability and abundance from point counts

USGS Publications Warehouse

Nichols, J.D.; Hines, J.E.; Sauer, J.R.; Fallon, F.W.; Fallon, J.E.; Heglund, P.J.

2000-01-01

Although point counts are frequently used in ornithological studies, basic assumptions about detection probabilities often are untested. We apply a double-observer approach developed to estimate detection probabilities for aerial surveys (Cook and Jacobson 1979) to avian point counts. At each point count, a designated 'primary' observer indicates to another ('secondary') observer all birds detected. The secondary observer records all detections of the primary observer as well as any birds not detected by the primary observer. Observers alternate primary and secondary roles during the course of the survey. The approach permits estimation of observer-specific detection probabilities and bird abundance. We developed a set of models that incorporate different assumptions about sources of variation (e.g. observer, bird species) in detection probability. Seventeen field trials were conducted, and models were fit to the resulting data using program SURVIV. Single-observer point counts generally miss varying proportions of the birds actually present, and observer and bird species were found to be relevant sources of variation in detection probabilities. Overall detection probabilities (probability of being detected by at least one of the two observers) estimated using the double-observer approach were very high (>0.95), yielding precise estimates of avian abundance. We consider problems with the approach and recommend possible solutions, including restriction of the approach to fixed-radius counts to reduce the effect of variation in the effective radius of detection among various observers and to provide a basis for using spatial sampling to estimate bird abundance on large areas of interest. We believe that most questions meriting the effort required to carry out point counts also merit serious attempts to estimate detection probabilities associated with the counts. The double-observer approach is a method that can be used for this purpose.

Modeling PSInSAR time series without phase unwrapping

USGS Publications Warehouse

Zhang, L.; Ding, X.; Lu, Z.

2011-01-01

In this paper, we propose a least-squares-based method for multitemporal synthetic aperture radar interferometry that allows one to estimate deformations without the need of phase unwrapping. The method utilizes a series of multimaster wrapped differential interferograms with short baselines and focuses on arcs at which there are no phase ambiguities. An outlier detector is used to identify and remove the arcs with phase ambiguities, and a pseudoinverse of the variance-covariance matrix is used as the weight matrix of the correlated observations. The deformation rates at coherent points are estimated with a least squares model constrained by reference points. The proposed approach is verified with a set of simulated data.

A convenient method of obtaining percentile norms and accompanying interval estimates for self-report mood scales (DASS, DASS-21, HADS, PANAS, and sAD).

PubMed

Crawford, John R; Garthwaite, Paul H; Lawrie, Caroline J; Henry, Julie D; MacDonald, Marie A; Sutherland, Jane; Sinha, Priyanka

2009-06-01

A series of recent papers have reported normative data from the general adult population for commonly used self-report mood scales. To bring together and supplement these data in order to provide a convenient means of obtaining percentile norms for the mood scales. A computer program was developed that provides point and interval estimates of the percentile rank corresponding to raw scores on the various self-report scales. The program can be used to obtain point and interval estimates of the percentile rank of an individual's raw scores on the DASS, DASS-21, HADS, PANAS, and sAD mood scales, based on normative sample sizes ranging from 758 to 3822. The interval estimates can be obtained using either classical or Bayesian methods as preferred. The computer program (which can be downloaded at www.abdn.ac.uk/~psy086/dept/MoodScore.htm) provides a convenient and reliable means of supplementing existing cut-off scores for self-report mood scales.

Adaptive recovery of motion blur point spread function from differently exposed images

NASA Astrophysics Data System (ADS)

Albu, Felix; Florea, Corneliu; Drîmbarean, Alexandru; Zamfir, Adrian

2010-01-01

Motion due to digital camera movement during the image capture process is a major factor that degrades the quality of images and many methods for camera motion removal have been developed. Central to all techniques is the correct recovery of what is known as the Point Spread Function (PSF). A very popular technique to estimate the PSF relies on using a pair of gyroscopic sensors to measure the hand motion. However, the errors caused either by the loss of the translational component of the movement or due to the lack of precision in gyro-sensors measurements impede the achievement of a good quality restored image. In order to compensate for this, we propose a method that begins with an estimation of the PSF obtained from 2 gyro sensors and uses a pair of under-exposed image together with the blurred image to adaptively improve it. The luminance of the under-exposed image is equalized with that of the blurred image. An initial estimation of the PSF is generated from the output signal of 2 gyro sensors. The PSF coefficients are updated using 2D-Least Mean Square (LMS) algorithms with a coarse-to-fine approach on a grid of points selected from both images. This refined PSF is used to process the blurred image using known deblurring methods. Our results show that the proposed method leads to superior PSF support and coefficient estimation. Also the quality of the restored image is improved compared to 2 gyro only approach or to blind image de-convolution results.

Navigable points estimation for mobile robots using binary image skeletonization

NASA Astrophysics Data System (ADS)

Martinez S., Fernando; Jacinto G., Edwar; Montiel A., Holman

2017-02-01

This paper describes the use of image skeletonization for the estimation of all the navigable points, inside a scene of mobile robots navigation. Those points are used for computing a valid navigation path, using standard methods. The main idea is to find the middle and the extreme points of the obstacles in the scene, taking into account the robot size, and create a map of navigable points, in order to reduce the amount of information for the planning algorithm. Those points are located by means of the skeletonization of a binary image of the obstacles and the scene background, along with some other digital image processing algorithms. The proposed algorithm automatically gives a variable number of navigable points per obstacle, depending on the complexity of its shape. As well as, the way how the algorithm can change some of their parameters in order to change the final number of the resultant key points is shown. The results shown here were obtained applying different kinds of digital image processing algorithms on static scenes.

Survival analysis with error-prone time-varying covariates: a risk set calibration approach

PubMed Central

Liao, Xiaomei; Zucker, David M.; Li, Yi; Spiegelman, Donna

2010-01-01

Summary Occupational, environmental, and nutritional epidemiologists are often interested in estimating the prospective effect of time-varying exposure variables such as cumulative exposure or cumulative updated average exposure, in relation to chronic disease endpoints such as cancer incidence and mortality. From exposure validation studies, it is apparent that many of the variables of interest are measured with moderate to substantial error. Although the ordinary regression calibration approach is approximately valid and efficient for measurement error correction of relative risk estimates from the Cox model with time-independent point exposures when the disease is rare, it is not adaptable for use with time-varying exposures. By re-calibrating the measurement error model within each risk set, a risk set regression calibration method is proposed for this setting. An algorithm for a bias-corrected point estimate of the relative risk using an RRC approach is presented, followed by the derivation of an estimate of its variance, resulting in a sandwich estimator. Emphasis is on methods applicable to the main study/external validation study design, which arises in important applications. Simulation studies under several assumptions about the error model were carried out, which demonstrated the validity and efficiency of the method in finite samples. The method was applied to a study of diet and cancer from Harvard’s Health Professionals Follow-up Study (HPFS). PMID:20486928

C-learning: A new classification framework to estimate optimal dynamic treatment regimes.

PubMed

Zhang, Baqun; Zhang, Min

2017-12-11

A dynamic treatment regime is a sequence of decision rules, each corresponding to a decision point, that determine that next treatment based on each individual's own available characteristics and treatment history up to that point. We show that identifying the optimal dynamic treatment regime can be recast as a sequential optimization problem and propose a direct sequential optimization method to estimate the optimal treatment regimes. In particular, at each decision point, the optimization is equivalent to sequentially minimizing a weighted expected misclassification error. Based on this classification perspective, we propose a powerful and flexible C-learning algorithm to learn the optimal dynamic treatment regimes backward sequentially from the last stage until the first stage. C-learning is a direct optimization method that directly targets optimizing decision rules by exploiting powerful optimization/classification techniques and it allows incorporation of patient's characteristics and treatment history to improve performance, hence enjoying advantages of both the traditional outcome regression-based methods (Q- and A-learning) and the more recent direct optimization methods. The superior performance and flexibility of the proposed methods are illustrated through extensive simulation studies. © 2017, The International Biometric Society.

A Horizontal Tilt Correction Method for Ship License Numbers Recognition

NASA Astrophysics Data System (ADS)

Liu, Baolong; Zhang, Sanyuan; Hong, Zhenjie; Ye, Xiuzi

2018-02-01

An automatic ship license numbers (SLNs) recognition system plays a significant role in intelligent waterway transportation systems since it can be used to identify ships by recognizing the characters in SLNs. Tilt occurs frequently in many SLNs because the monitors and the ships usually have great vertical or horizontal angles, which decreases the accuracy and robustness of a SLNs recognition system significantly. In this paper, we present a horizontal tilt correction method for SLNs. For an input tilt SLN image, the proposed method accomplishes the correction task through three main steps. First, a MSER-based characters’ center-points computation algorithm is designed to compute the accurate center-points of the characters contained in the input SLN image. Second, a L 1- L 2 distance-based straight line is fitted to the computed center-points using M-estimator algorithm. The tilt angle is estimated at this stage. Finally, based on the computed tilt angle, an affine transformation rotation is conducted to rotate and to correct the input SLN horizontally. At last, the proposed method is tested on 200 tilt SLN images, the proposed method is proved to be effective with a tilt correction rate of 80.5%.

A source-attractor approach to network detection of radiation sources

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

Wu, Qishi; Barry, M. L..; Grieme, M.

Radiation source detection using a network of detectors is an active field of research for homeland security and defense applications. We propose Source-attractor Radiation Detection (SRD) method to aggregate measurements from a network of detectors for radiation source detection. SRD method models a potential radiation source as a magnet -like attractor that pulls in pre-computed virtual points from the detector locations. A detection decision is made if a sufficient level of attraction, quantified by the increase in the clustering of the shifted virtual points, is observed. Compared with traditional methods, SRD has the following advantages: i) it does not requiremore » an accurate estimate of the source location from limited and noise-corrupted sensor readings, unlike the localizationbased methods, and ii) its virtual point shifting and clustering calculation involve simple arithmetic operations based on the number of detectors, avoiding the high computational complexity of grid-based likelihood estimation methods. We evaluate its detection performance using canonical datasets from Domestic Nuclear Detection Office s (DNDO) Intelligence Radiation Sensors Systems (IRSS) tests. SRD achieves both lower false alarm rate and false negative rate compared to three existing algorithms for network source detection.« less

Spatial analysis of groundwater levels using Fuzzy Logic and geostatistical tools

NASA Astrophysics Data System (ADS)

Theodoridou, P. G.; Varouchakis, E. A.; Karatzas, G. P.

2017-12-01

The spatial variability evaluation of the water table of an aquifer provides useful information in water resources management plans. Geostatistical methods are often employed to map the free surface of an aquifer. In geostatistical analysis using Kriging techniques the selection of the optimal variogram is very important for the optimal method performance. This work compares three different criteria to assess the theoretical variogram that fits to the experimental one: the Least Squares Sum method, the Akaike Information Criterion and the Cressie's Indicator. Moreover, variable distance metrics such as the Euclidean, Minkowski, Manhattan, Canberra and Bray-Curtis are applied to calculate the distance between the observation and the prediction points, that affects both the variogram calculation and the Kriging estimator. A Fuzzy Logic System is then applied to define the appropriate neighbors for each estimation point used in the Kriging algorithm. The two criteria used during the Fuzzy Logic process are the distance between observation and estimation points and the groundwater level value at each observation point. The proposed techniques are applied to a data set of 250 hydraulic head measurements distributed over an alluvial aquifer. The analysis showed that the Power-law variogram model and Manhattan distance metric within ordinary kriging provide the best results when the comprehensive geostatistical analysis process is applied. On the other hand, the Fuzzy Logic approach leads to a Gaussian variogram model and significantly improves the estimation performance. The two different variogram models can be explained in terms of a fractional Brownian motion approach and of aquifer behavior at local scale. Finally, maps of hydraulic head spatial variability and of predictions uncertainty are constructed for the area with the two different approaches comparing their advantages and drawbacks.

Photometric calibration of the COMBO-17 survey with the Softassign Procrustes Matching method

NASA Astrophysics Data System (ADS)

Sheikhbahaee, Z.; Nakajima, R.; Erben, T.; Schneider, P.; Hildebrandt, H.; Becker, A. C.

2017-11-01

Accurate photometric calibration of optical data is crucial for photometric redshift estimation. We present the Softassign Procrustes Matching (SPM) method to improve the colour calibration upon the commonly used Stellar Locus Regression (SLR) method for the COMBO-17 survey. Our colour calibration approach can be categorised as a point-set matching method, which is frequently used in medical imaging and pattern recognition. We attain a photometric redshift precision Δz/(1 + zs) of better than 2 per cent. Our method is based on aligning the stellar locus of the uncalibrated stars to that of a spectroscopic sample of the Sloan Digital Sky Survey standard stars. We achieve our goal by finding a correspondence matrix between the two point-sets and applying the matrix to estimate the appropriate translations in multidimensional colour space. The SPM method is able to find the translation between two point-sets, despite the existence of noise and incompleteness of the common structures in the sets, as long as there is a distinct structure in at least one of the colour-colour pairs. We demonstrate the precision of our colour calibration method with a mock catalogue. The SPM colour calibration code is publicly available at https://neuronphysics@bitbucket.org/neuronphysics/spm.git.

COSMIC MICROWAVE BACKGROUND POLARIZATION AND TEMPERATURE POWER SPECTRA ESTIMATION USING LINEAR COMBINATION OF WMAP 5 YEAR MAPS

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

Samal, Pramoda Kumar; Jain, Pankaj; Saha, Rajib

We estimate cosmic microwave background (CMB) polarization and temperature power spectra using Wilkinson Microwave Anisotropy Probe (WMAP) 5 year foreground contaminated maps. The power spectrum is estimated by using a model-independent method, which does not utilize directly the diffuse foreground templates nor the detector noise model. The method essentially consists of two steps: (1) removal of diffuse foregrounds contamination by making linear combination of individual maps in harmonic space and (2) cross-correlation of foreground cleaned maps to minimize detector noise bias. For the temperature power spectrum we also estimate and subtract residual unresolved point source contamination in the cross-power spectrummore » using the point source model provided by the WMAP science team. Our TT, TE, and EE power spectra are in good agreement with the published results of the WMAP science team. We perform detailed numerical simulations to test for bias in our procedure. We find that the bias is small in almost all cases. A negative bias at low l in TT power spectrum has been pointed out in an earlier publication. We find that the bias-corrected quadrupole power (l(l + 1)C{sub l} /2{pi}) is 532 {mu}K{sup 2}, approximately 2.5 times the estimate (213.4 {mu}K{sup 2}) made by the WMAP team.« less

A new comparison method for dew-point generators

NASA Astrophysics Data System (ADS)

Heinonen, Martti

1999-12-01

A new method for comparing dew-point generators was developed at the Centre for Metrology and Accreditation. In this method, the generators participating in a comparison are compared with a transportable saturator unit using a dew-point comparator. The method was tested by constructing a test apparatus and by comparing it with the MIKES primary dew-point generator several times in the dew-point temperature range from -40 to +75 °C. The expanded uncertainty (k = 2) of the apparatus was estimated to be between 0.05 and 0.07 °C and the difference between the comparator system and the generator is well within these limits. In particular, all of the results obtained in the range below 0 °C are within ±0.03 °C. It is concluded that a new type of a transfer standard with characteristics most suitable for dew-point comparisons can be developed on the basis of the principles presented in this paper.

Accuracy or precision: Implications of sample design and methodology on abundance estimation

USGS Publications Warehouse

Kowalewski, Lucas K.; Chizinski, Christopher J.; Powell, Larkin A.; Pope, Kevin L.; Pegg, Mark A.

2015-01-01

Sampling by spatially replicated counts (point-count) is an increasingly popular method of estimating population size of organisms. Challenges exist when sampling by point-count method, and it is often impractical to sample entire area of interest and impossible to detect every individual present. Ecologists encounter logistical limitations that force them to sample either few large-sample units or many small sample-units, introducing biases to sample counts. We generated a computer environment and simulated sampling scenarios to test the role of number of samples, sample unit area, number of organisms, and distribution of organisms in the estimation of population sizes using N-mixture models. Many sample units of small area provided estimates that were consistently closer to true abundance than sample scenarios with few sample units of large area. However, sample scenarios with few sample units of large area provided more precise abundance estimates than abundance estimates derived from sample scenarios with many sample units of small area. It is important to consider accuracy and precision of abundance estimates during the sample design process with study goals and objectives fully recognized, although and with consequence, consideration of accuracy and precision of abundance estimates is often an afterthought that occurs during the data analysis process.

a Preliminary Work on Layout Slam for Reconstruction of Indoor Corridor Environments

NASA Astrophysics Data System (ADS)

Baligh Jahromi, A.; Sohn, G.; Shahbazi, M.; Kang, J.

2017-09-01

We propose a real time indoor corridor layout estimation method based on visual Simultaneous Localization and Mapping (SLAM). The proposed method adopts the Manhattan World Assumption at indoor spaces and uses the detected single image straight line segments and their corresponding orthogonal vanishing points to improve the feature matching scheme in the adopted visual SLAM system. Using the proposed real time indoor corridor layout estimation method, the system is able to build an online sparse map of structural corner point features. The challenges presented by abrupt camera rotation in the 3D space are successfully handled through matching vanishing directions of consecutive video frames on the Gaussian sphere. Using the single image based indoor layout features for initializing the system, permitted the proposed method to perform real time layout estimation and camera localization in indoor corridor areas. For layout structural corner points matching, we adopted features which are invariant under scale, translation, and rotation. We proposed a new feature matching cost function which considers both local and global context information. The cost function consists of a unary term, which measures pixel to pixel orientation differences of the matched corners, and a binary term, which measures the amount of angle differences between directly connected layout corner features. We have performed the experiments on real scenes at York University campus buildings and the available RAWSEEDS dataset. The incoming results depict that the proposed method robustly performs along with producing very limited position and orientation errors.

Robust curb detection with fusion of 3D-Lidar and camera data.

PubMed

Tan, Jun; Li, Jian; An, Xiangjing; He, Hangen

2014-05-21

Curb detection is an essential component of Autonomous Land Vehicles (ALV), especially important for safe driving in urban environments. In this paper, we propose a fusion-based curb detection method through exploiting 3D-Lidar and camera data. More specifically, we first fuse the sparse 3D-Lidar points and high-resolution camera images together to recover a dense depth image of the captured scene. Based on the recovered dense depth image, we propose a filter-based method to estimate the normal direction within the image. Then, by using the multi-scale normal patterns based on the curb's geometric property, curb point features fitting the patterns are detected in the normal image row by row. After that, we construct a Markov Chain to model the consistency of curb points which utilizes the continuous property of the curb, and thus the optimal curb path which links the curb points together can be efficiently estimated by dynamic programming. Finally, we perform post-processing operations to filter the outliers, parameterize the curbs and give the confidence scores on the detected curbs. Extensive evaluations clearly show that our proposed method can detect curbs with strong robustness at real-time speed for both static and dynamic scenes.

THE IMPACT OF POINT-SOURCE SUBTRACTION RESIDUALS ON 21 cm EPOCH OF REIONIZATION ESTIMATION

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

Trott, Cathryn M.; Wayth, Randall B.; Tingay, Steven J., E-mail: cathryn.trott@curtin.edu.au

Precise subtraction of foreground sources is crucial for detecting and estimating 21 cm H I signals from the Epoch of Reionization (EoR). We quantify how imperfect point-source subtraction due to limitations of the measurement data set yields structured residual signal in the data set. We use the Cramer-Rao lower bound, as a metric for quantifying the precision with which a parameter may be measured, to estimate the residual signal in a visibility data set due to imperfect point-source subtraction. We then propagate these residuals into two metrics of interest for 21 cm EoR experiments-the angular power spectrum and two-dimensional powermore » spectrum-using a combination of full analytic covariant derivation, analytic variant derivation, and covariant Monte Carlo simulations. This methodology differs from previous work in two ways: (1) it uses information theory to set the point-source position error, rather than assuming a global rms error, and (2) it describes a method for propagating the errors analytically, thereby obtaining the full correlation structure of the power spectra. The methods are applied to two upcoming low-frequency instruments that are proposing to perform statistical EoR experiments: the Murchison Widefield Array and the Precision Array for Probing the Epoch of Reionization. In addition to the actual antenna configurations, we apply the methods to minimally redundant and maximally redundant configurations. We find that for peeling sources above 1 Jy, the amplitude of the residual signal, and its variance, will be smaller than the contribution from thermal noise for the observing parameters proposed for upcoming EoR experiments, and that optimal subtraction of bright point sources will not be a limiting factor for EoR parameter estimation. We then use the formalism to provide an ab initio analytic derivation motivating the 'wedge' feature in the two-dimensional power spectrum, complementing previous discussion in the literature.« less

Protocol for monitoring forest-nesting birds in National Park Service parks

USGS Publications Warehouse

Dawson, Deanna K.; Efford, Murray G.

2013-01-01

These documents detail the protocol for monitoring forest-nesting birds in National Park Service parks in the National Capital Region Network (NCRN). In the first year of sampling, counts of birds should be made at 384 points on the NCRN spatially randomized grid, developed to sample terrestrial resources. Sampling should begin on or about May 20 and continue into early July; on each day the sampling period begins at sunrise and ends five hours later. Each point should be counted twice, once in the first half of the field season and once in the second half, with visits made by different observers, balancing the within-season coverage of points and their spatial coverage by observers, and allowing observer differences to be tested. Three observers, skilled in identifying birds of the region by sight and sound and with previous experience in conducting timed counts of birds, will be needed for this effort. Observers should be randomly assigned to ‘routes’ consisting of eight points, in close proximity and, ideally, in similar habitat, that can be covered in one morning. Counts are 10 minutes in length, subdivided into four 2.5-min intervals. Within each time interval, new birds (i.e., those not already detected) are recorded as within or beyond 50 m of the point, based on where first detected. Binomial distance methods are used to calculate annual estimates of density for species. The data are also amenable to estimation of abundance and detection probability via the removal method. Generalized linear models can be used to assess between-year changes in density estimates or unadjusted count data. This level of sampling is expected to be sufficient to detect a 50% decline in 10 years for approximately 50 bird species, including 14 of 19 species that are priorities for conservation efforts, if analyses are based on unadjusted count data, and for 30 species (6 priority species) if analyses are based on density estimates. The estimates of required sample sizes are based on the mean number of individuals detected per 10 minutes in available data from surveys in three NCRN parks. Once network-wide data from the first year of sampling are available, this and other aspects of the protocol should be re-assessed, and changes made as desired or necessary before the start of the second field season. Thereafter, changes should not be made to the field methods, and sampling should be conducted annually for at least ten years. NCRN staff should keep apprised of new analytical methods developed for analysis of point-count data.

Estimating discharge measurement uncertainty using the interpolated variance estimator

USGS Publications Warehouse

Cohn, T.; Kiang, J.; Mason, R.

2012-01-01

Methods for quantifying the uncertainty in discharge measurements typically identify various sources of uncertainty and then estimate the uncertainty from each of these sources by applying the results of empirical or laboratory studies. If actual measurement conditions are not consistent with those encountered in the empirical or laboratory studies, these methods may give poor estimates of discharge uncertainty. This paper presents an alternative method for estimating discharge measurement uncertainty that uses statistical techniques and at-site observations. This Interpolated Variance Estimator (IVE) estimates uncertainty based on the data collected during the streamflow measurement and therefore reflects the conditions encountered at the site. The IVE has the additional advantage of capturing all sources of random uncertainty in the velocity and depth measurements. It can be applied to velocity-area discharge measurements that use a velocity meter to measure point velocities at multiple vertical sections in a channel cross section.

Leaching of indium from obsolete liquid crystal displays: Comparing grinding with electrical disintegration in context of LCA

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

Dodbiba, Gjergj, E-mail: dodbiba@sys.t.u-tokyo.ac.jp; Nagai, Hiroki; Wang Lipang

2012-10-15

Highlights: Black-Right-Pointing-Pointer Two pre-treatment methods, prior to leaching of indium from obsolete LCD modules, were described. Black-Right-Pointing-Pointer Conventional grinding and electrical disintegration have been evaluated and compared in the context of LCA. Black-Right-Pointing-Pointer Experimental data on the leaching capacity for indium and the electricity consumption of equipment were inputted into the LCA model in order to compare the environmental performance of each method. Black-Right-Pointing-Pointer An estimate for the environmental performance was calculated as the sum of six impact categories. Black-Right-Pointing-Pointer Electrical disintegration method outperforms conventional grinding in all impact categories. - Abstract: In order to develop an effective recycling systemmore » for obsolete Liquid Crystal Displays (LCDs), which would enable both the leaching of indium (In) and the recovery of a pure glass fraction for recycling, an effective liberation or size-reduction method would be an important pre-treatment step. Therefore, in this study, two different types of liberation methods: (1) conventional grinding, and (2) electrical disintegration have been tested and evaluated in the context of Life Cycle Assessment (LCA). In other words, the above-mentioned methods were compared in order to find out the one that ensures the highest leaching capacity for indium, as well as the lowest environmental burden. One of the main findings of this study was that the electrical disintegration was the most effective liberation method, since it fully liberated the indium containing-layer, ensuring a leaching capacity of 968.5 mg-In/kg-LCD. In turn, the estimate for the environmental burden was approximately five times smaller when compared with the conventional grinding.« less

A systematic evaluation of contemporary impurity correction methods in ITS-90 aluminium fixed point cells

NASA Astrophysics Data System (ADS)

da Silva, Rodrigo; Pearce, Jonathan V.; Machin, Graham

2017-06-01

The fixed points of the International Temperature Scale of 1990 (ITS-90) are the basis of the calibration of standard platinum resistance thermometers (SPRTs). Impurities in the fixed point material at the level of parts per million can give rise to an elevation or depression of the fixed point temperature of order of millikelvins, which often represents the most significant contribution to the uncertainty of SPRT calibrations. A number of methods for correcting for the effect of impurities have been advocated, but it is becoming increasingly evident that no single method can be used in isolation. In this investigation, a suite of five aluminium fixed point cells (defined ITS-90 freezing temperature 660.323 °C) have been constructed, each cell using metal sourced from a different supplier. The five cells have very different levels and types of impurities. For each cell, chemical assays based on the glow discharge mass spectroscopy (GDMS) technique have been obtained from three separate laboratories. In addition a series of high quality, long duration freezing curves have been obtained for each cell, using three different high quality SPRTs, all measured under nominally identical conditions. The set of GDMS analyses and freezing curves were then used to compare the different proposed impurity correction methods. It was found that the most consistent corrections were obtained with a hybrid correction method based on the sum of individual estimates (SIE) and overall maximum estimate (OME), namely the SIE/Modified-OME method. Also highly consistent was the correction technique based on fitting a Scheil solidification model to the measured freezing curves, provided certain well defined constraints are applied. Importantly, the most consistent methods are those which do not depend significantly on the chemical assay.

Convergence of Newton's method for a single real equation

NASA Technical Reports Server (NTRS)

Campbell, C. W.

1985-01-01

Newton's method for finding the zeroes of a single real function is investigated in some detail. Convergence is generally checked using the Contraction Mapping Theorem which yields sufficient but not necessary conditions for convergence of the general single point iteration method. The resulting convergence intervals are frequently considerably smaller than actual convergence zones. For a specific single point iteration method, such as Newton's method, better estimates of regions of convergence should be possible. A technique is described which, under certain conditions (frequently satisfied by well behaved functions) gives much larger zones where convergence is guaranteed.

Assessing Interval Estimation Methods for Hill Model Parameters in a High-Throughput Screening Context (SOT)

EPA Science Inventory

The Hill model of concentration-response is ubiquitous in toxicology, perhaps because its parameters directly relate to biologically significant metrics of toxicity such as efficacy and potency. Point estimates of these parameters obtained through least squares regression or maxi...

Assessing Interval Estimation Methods for Hill Model Parameters in a High-Throughput Screening Context (IVIVE meeting)

EPA Science Inventory

The Hill model of concentration-response is ubiquitous in toxicology, perhaps because its parameters directly relate to biologically significant metrics of toxicity such as efficacy and potency. Point estimates of these parameters obtained through least squares regression or maxi...

Using the ratio of the magnetic field to the analytic signal of the magnetic gradient tensor in determining the position of simple shaped magnetic anomalies

NASA Astrophysics Data System (ADS)

Karimi, Kurosh; Shirzaditabar, Farzad

2017-08-01

The analytic signal of magnitude of the magnetic field’s components and its first derivatives have been employed for locating magnetic structures, which can be considered as point-dipoles or line of dipoles. Although similar methods have been used for locating such magnetic anomalies, they cannot estimate the positions of anomalies in noisy states with an acceptable accuracy. The methods are also inexact in determining the depth of deep anomalies. In noisy cases and in places other than poles, the maximum points of the magnitude of the magnetic vector components and Az are not located exactly above 3D bodies. Consequently, the horizontal location estimates of bodies are accompanied by errors. Here, the previous methods are altered and generalized to locate deeper models in the presence of noise even at lower magnetic latitudes. In addition, a statistical technique is presented for working in noisy areas and a new method, which is resistant to noise by using a ‘depths mean’ method, is made. Reduction to the pole transformation is also used to find the most possible actual horizontal body location. Deep models are also well estimated. The method is tested on real magnetic data over an urban gas pipeline in the vicinity of Kermanshah province, Iran. The estimated location of the pipeline is accurate in accordance with the result of the half-width method.

Order Under Uncertainty: Robust Differential Expression Analysis Using Probabilistic Models for Pseudotime Inference

PubMed Central

Campbell, Kieran R.

2016-01-01

Single cell gene expression profiling can be used to quantify transcriptional dynamics in temporal processes, such as cell differentiation, using computational methods to label each cell with a ‘pseudotime’ where true time series experimentation is too difficult to perform. However, owing to the high variability in gene expression between individual cells, there is an inherent uncertainty in the precise temporal ordering of the cells. Pre-existing methods for pseudotime estimation have predominantly given point estimates precluding a rigorous analysis of the implications of uncertainty. We use probabilistic modelling techniques to quantify pseudotime uncertainty and propagate this into downstream differential expression analysis. We demonstrate that reliance on a point estimate of pseudotime can lead to inflated false discovery rates and that probabilistic approaches provide greater robustness and measures of the temporal resolution that can be obtained from pseudotime inference. PMID:27870852

Detector Position Estimation for PET Scanners.

PubMed

Pierce, Larry; Miyaoka, Robert; Lewellen, Tom; Alessio, Adam; Kinahan, Paul

2012-06-11

Physical positioning of scintillation crystal detector blocks in Positron Emission Tomography (PET) scanners is not always exact. We test a proof of concept methodology for the determination of the six degrees of freedom for detector block positioning errors by utilizing a rotating point source over stepped axial intervals. To test our method, we created computer simulations of seven Micro Crystal Element Scanner (MiCES) PET systems with randomized positioning errors. The computer simulations show that our positioning algorithm can estimate the positions of the block detectors to an average of one-seventh of the crystal pitch tangentially, and one-third of the crystal pitch axially. Virtual acquisitions of a point source grid and a distributed phantom show that our algorithm improves both the quantitative and qualitative accuracy of the reconstructed objects. We believe this estimation algorithm is a practical and accurate method for determining the spatial positions of scintillation detector blocks.

Comparison of variance estimators for meta-analysis of instrumental variable estimates

PubMed Central

Schmidt, AF; Hingorani, AD; Jefferis, BJ; White, J; Groenwold, RHH; Dudbridge, F

2016-01-01

Abstract Background: Mendelian randomization studies perform instrumental variable (IV) analysis using genetic IVs. Results of individual Mendelian randomization studies can be pooled through meta-analysis. We explored how different variance estimators influence the meta-analysed IV estimate. Methods: Two versions of the delta method (IV before or after pooling), four bootstrap estimators, a jack-knife estimator and a heteroscedasticity-consistent (HC) variance estimator were compared using simulation. Two types of meta-analyses were compared, a two-stage meta-analysis pooling results, and a one-stage meta-analysis pooling datasets. Results: Using a two-stage meta-analysis, coverage of the point estimate using bootstrapped estimators deviated from nominal levels at weak instrument settings and/or outcome probabilities ≤ 0.10. The jack-knife estimator was the least biased resampling method, the HC estimator often failed at outcome probabilities ≤ 0.50 and overall the delta method estimators were the least biased. In the presence of between-study heterogeneity, the delta method before meta-analysis performed best. Using a one-stage meta-analysis all methods performed equally well and better than two-stage meta-analysis of greater or equal size. Conclusions: In the presence of between-study heterogeneity, two-stage meta-analyses should preferentially use the delta method before meta-analysis. Weak instrument bias can be reduced by performing a one-stage meta-analysis. PMID:27591262

Automated Coarse Registration of Point Clouds in 3d Urban Scenes Using Voxel Based Plane Constraint

NASA Astrophysics Data System (ADS)

Xu, Y.; Boerner, R.; Yao, W.; Hoegner, L.; Stilla, U.

2017-09-01

For obtaining a full coverage of 3D scans in a large-scale urban area, the registration between point clouds acquired via terrestrial laser scanning (TLS) is normally mandatory. However, due to the complex urban environment, the automatic registration of different scans is still a challenging problem. In this work, we propose an automatic marker free method for fast and coarse registration between point clouds using the geometric constrains of planar patches under a voxel structure. Our proposed method consists of four major steps: the voxelization of the point cloud, the approximation of planar patches, the matching of corresponding patches, and the estimation of transformation parameters. In the voxelization step, the point cloud of each scan is organized with a 3D voxel structure, by which the entire point cloud is partitioned into small individual patches. In the following step, we represent points of each voxel with the approximated plane function, and select those patches resembling planar surfaces. Afterwards, for matching the corresponding patches, a RANSAC-based strategy is applied. Among all the planar patches of a scan, we randomly select a planar patches set of three planar surfaces, in order to build a coordinate frame via their normal vectors and their intersection points. The transformation parameters between scans are calculated from these two coordinate frames. The planar patches set with its transformation parameters owning the largest number of coplanar patches are identified as the optimal candidate set for estimating the correct transformation parameters. The experimental results using TLS datasets of different scenes reveal that our proposed method can be both effective and efficient for the coarse registration task. Especially, for the fast orientation between scans, our proposed method can achieve a registration error of less than around 2 degrees using the testing datasets, and much more efficient than the classical baseline methods.

Correction for slope in point and transect relascope sampling of downed coarse woody debris

Treesearch

Goran Stahl; Anna Ringvall; Jeffrey H. Gove; Mark J. Ducey

2002-01-01

In this article, the effect of sloping terrain on estimates in point and transect relascope sampling (PRS and TRS, respectively) is studied. With these inventory methods, a wide angle relascope is used either from sample points (PRS) or along survey lines (TRS). Characteristics associated with line-shaped objects on the ground are assessed, e.g., the length or volume...

A pseudo-penalized quasi-likelihood approach to the spatial misalignment problem with non-normal data.

PubMed

Lopiano, Kenneth K; Young, Linda J; Gotway, Carol A

2014-09-01

Spatially referenced datasets arising from multiple sources are routinely combined to assess relationships among various outcomes and covariates. The geographical units associated with the data, such as the geographical coordinates or areal-level administrative units, are often spatially misaligned, that is, observed at different locations or aggregated over different geographical units. As a result, the covariate is often predicted at the locations where the response is observed. The method used to align disparate datasets must be accounted for when subsequently modeling the aligned data. Here we consider the case where kriging is used to align datasets in point-to-point and point-to-areal misalignment problems when the response variable is non-normally distributed. If the relationship is modeled using generalized linear models, the additional uncertainty induced from using the kriging mean as a covariate introduces a Berkson error structure. In this article, we develop a pseudo-penalized quasi-likelihood algorithm to account for the additional uncertainty when estimating regression parameters and associated measures of uncertainty. The method is applied to a point-to-point example assessing the relationship between low-birth weights and PM2.5 levels after the onset of the largest wildfire in Florida history, the Bugaboo scrub fire. A point-to-areal misalignment problem is presented where the relationship between asthma events in Florida's counties and PM2.5 levels after the onset of the fire is assessed. Finally, the method is evaluated using a simulation study. Our results indicate the method performs well in terms of coverage for 95% confidence intervals and naive methods that ignore the additional uncertainty tend to underestimate the variability associated with parameter estimates. The underestimation is most profound in Poisson regression models. © 2014, The International Biometric Society.

Model-based decoding, information estimation, and change-point detection techniques for multineuron spike trains.

PubMed

Pillow, Jonathan W; Ahmadian, Yashar; Paninski, Liam

2011-01-01

One of the central problems in systems neuroscience is to understand how neural spike trains convey sensory information. Decoding methods, which provide an explicit means for reading out the information contained in neural spike responses, offer a powerful set of tools for studying the neural coding problem. Here we develop several decoding methods based on point-process neural encoding models, or forward models that predict spike responses to stimuli. These models have concave log-likelihood functions, which allow efficient maximum-likelihood model fitting and stimulus decoding. We present several applications of the encoding model framework to the problem of decoding stimulus information from population spike responses: (1) a tractable algorithm for computing the maximum a posteriori (MAP) estimate of the stimulus, the most probable stimulus to have generated an observed single- or multiple-neuron spike train response, given some prior distribution over the stimulus; (2) a gaussian approximation to the posterior stimulus distribution that can be used to quantify the fidelity with which various stimulus features are encoded; (3) an efficient method for estimating the mutual information between the stimulus and the spike trains emitted by a neural population; and (4) a framework for the detection of change-point times (the time at which the stimulus undergoes a change in mean or variance) by marginalizing over the posterior stimulus distribution. We provide several examples illustrating the performance of these estimators with simulated and real neural data.

Statistical approaches to the analysis of point count data: A little extra information can go a long way

USGS Publications Warehouse

Farnsworth, G.L.; Nichols, J.D.; Sauer, J.R.; Fancy, S.G.; Pollock, K.H.; Shriner, S.A.; Simons, T.R.; Ralph, C. John; Rich, Terrell D.

2005-01-01

Point counts are a standard sampling procedure for many bird species, but lingering concerns still exist about the quality of information produced from the method. It is well known that variation in observer ability and environmental conditions can influence the detection probability of birds in point counts, but many biologists have been reluctant to abandon point counts in favor of more intensive approaches to counting. However, over the past few years a variety of statistical and methodological developments have begun to provide practical ways of overcoming some of the problems with point counts. We describe some of these approaches, and show how they can be integrated into standard point count protocols to greatly enhance the quality of the information. Several tools now exist for estimation of detection probability of birds during counts, including distance sampling, double observer methods, time-depletion (removal) methods, and hybrid methods that combine these approaches. Many counts are conducted in habitats that make auditory detection of birds much more likely than visual detection. As a framework for understanding detection probability during such counts, we propose separating two components of the probability a bird is detected during a count into (1) the probability a bird vocalizes during the count and (2) the probability this vocalization is detected by an observer. In addition, we propose that some measure of the area sampled during a count is necessary for valid inferences about bird populations. This can be done by employing fixed-radius counts or more sophisticated distance-sampling models. We recommend any studies employing point counts be designed to estimate detection probability and to include a measure of the area sampled.

The effect of tandem-ovoid titanium applicator on points A, B, bladder, and rectum doses in gynecological brachytherapy using 192Ir

PubMed Central

Sadeghi, Mohammad Hosein; Mehdizadeh, Amir; Faghihi, Reza; Moharramzadeh, Vahed; Meigooni, Ali Soleimani

2018-01-01

Purpose The dosimetry procedure by simple superposition accounts only for the self-shielding of the source and does not take into account the attenuation of photons by the applicators. The purpose of this investigation is an estimation of the effects of the tandem and ovoid applicator on dose distribution inside the phantom by MCNP5 Monte Carlo simulations. Material and methods In this study, the superposition method is used for obtaining the dose distribution in the phantom without using the applicator for a typical gynecological brachytherapy (superposition-1). Then, the sources are simulated inside the tandem and ovoid applicator to identify the effect of applicator attenuation (superposition-2), and the dose at points A, B, bladder, and rectum were compared with the results of superposition. The exact dwell positions, times of the source, and positions of the dosimetry points were determined in images of a patient and treatment data of an adult woman patient from a cancer center. The MCNP5 Monte Carlo (MC) code was used for simulation of the phantoms, applicators, and the sources. Results The results of this study showed no significant differences between the results of superposition method and the MC simulations for different dosimetry points. The difference in all important dosimetry points was found to be less than 5%. Conclusions According to the results, applicator attenuation has no significant effect on the calculated points dose, the superposition method, adding the dose of each source obtained by the MC simulation, can estimate the dose to points A, B, bladder, and rectum with good accuracy. PMID:29619061

Estimation of Lithological Classification in Taipei Basin: A Bayesian Maximum Entropy Method

NASA Astrophysics Data System (ADS)

Wu, Meng-Ting; Lin, Yuan-Chien; Yu, Hwa-Lung

2015-04-01

In environmental or other scientific applications, we must have a certain understanding of geological lithological composition. Because of restrictions of real conditions, only limited amount of data can be acquired. To find out the lithological distribution in the study area, many spatial statistical methods used to estimate the lithological composition on unsampled points or grids. This study applied the Bayesian Maximum Entropy (BME method), which is an emerging method of the geological spatiotemporal statistics field. The BME method can identify the spatiotemporal correlation of the data, and combine not only the hard data but the soft data to improve estimation. The data of lithological classification is discrete categorical data. Therefore, this research applied Categorical BME to establish a complete three-dimensional Lithological estimation model. Apply the limited hard data from the cores and the soft data generated from the geological dating data and the virtual wells to estimate the three-dimensional lithological classification in Taipei Basin. Keywords: Categorical Bayesian Maximum Entropy method, Lithological Classification, Hydrogeological Setting

An investigation of using an RQP based method to calculate parameter sensitivity derivatives

NASA Technical Reports Server (NTRS)

Beltracchi, Todd J.; Gabriele, Gary A.

1989-01-01

Estimation of the sensitivity of problem functions with respect to problem variables forms the basis for many of our modern day algorithms for engineering optimization. The most common application of problem sensitivities has been in the calculation of objective function and constraint partial derivatives for determining search directions and optimality conditions. A second form of sensitivity analysis, parameter sensitivity, has also become an important topic in recent years. By parameter sensitivity, researchers refer to the estimation of changes in the modeling functions and current design point due to small changes in the fixed parameters of the formulation. Methods for calculating these derivatives have been proposed by several authors (Armacost and Fiacco 1974, Sobieski et al 1981, Schmit and Chang 1984, and Vanderplaats and Yoshida 1985). Two drawbacks to estimating parameter sensitivities by current methods have been: (1) the need for second order information about the Lagrangian at the current point, and (2) the estimates assume no change in the active set of constraints. The first of these two problems is addressed here and a new algorithm is proposed that does not require explicit calculation of second order information.

FDD Massive MIMO Channel Estimation With Arbitrary 2D-Array Geometry

NASA Astrophysics Data System (ADS)

Dai, Jisheng; Liu, An; Lau, Vincent K. N.

2018-05-01

This paper addresses the problem of downlink channel estimation in frequency-division duplexing (FDD) massive multiple-input multiple-output (MIMO) systems. The existing methods usually exploit hidden sparsity under a discrete Fourier transform (DFT) basis to estimate the cdownlink channel. However, there are at least two shortcomings of these DFT-based methods: 1) they are applicable to uniform linear arrays (ULAs) only, since the DFT basis requires a special structure of ULAs, and 2) they always suffer from a performance loss due to the leakage of energy over some DFT bins. To deal with the above shortcomings, we introduce an off-grid model for downlink channel sparse representation with arbitrary 2D-array antenna geometry, and propose an efficient sparse Bayesian learning (SBL) approach for the sparse channel recovery and off-grid refinement. The main idea of the proposed off-grid method is to consider the sampled grid points as adjustable parameters. Utilizing an in-exact block majorization-minimization (MM) algorithm, the grid points are refined iteratively to minimize the off-grid gap. Finally, we further extend the solution to uplink-aided channel estimation by exploiting the angular reciprocity between downlink and uplink channels, which brings enhanced recovery performance.

Using multiple travel paths to estimate daily travel distance in arboreal, group-living primates.

PubMed

Steel, Ruth Irene

2015-01-01

Primate field studies often estimate daily travel distance (DTD) in order to estimate energy expenditure and/or test foraging hypotheses. In group-living species, the center of mass (CM) method is traditionally used to measure DTD; a point is marked at the group's perceived center of mass at a set time interval or upon each move, and the distance between consecutive points is measured and summed. However, for groups using multiple travel paths, the CM method potentially creates a central path that is shorter than the individual paths and/or traverses unused areas. These problems may compromise tests of foraging hypotheses, since distance and energy expenditure could be underestimated. To better understand the magnitude of these potential biases, I designed and tested the multiple travel paths (MTP) method, in which DTD was calculated by recording all travel paths taken by the group's members, weighting each path's distance based on its proportional use by the group, and summing the weighted distances. To compare the MTP and CM methods, DTD was calculated using both methods in three groups of Udzungwa red colobus monkeys (Procolobus gordonorum; group size 30-43) for a random sample of 30 days between May 2009 and March 2010. Compared to the CM method, the MTP method provided significantly longer estimates of DTD that were more representative of the actual distance traveled and the areas used by a group. The MTP method is more time-intensive and requires multiple observers compared to the CM method. However, it provides greater accuracy for testing ecological and foraging models.

Method for measuring thermal properties using a long-wavelength infrared thermal image

DOEpatents

Walker, Charles L [Albuquerque, NM; Costin, Laurence S [Albuquerque, NM; Smith, Jody L [Albuquerque, NM; Moya, Mary M [Albuquerque, NM; Mercier, Jeffrey A [Albuquerque, NM

2007-01-30

A method for estimating the thermal properties of surface materials using long-wavelength thermal imagery by exploiting the differential heating histories of ground points in the vicinity of shadows. The use of differential heating histories of different ground points of the same surface material allows the use of a single image acquisition step to provide the necessary variation in measured parameters for calculation of the thermal properties of surface materials.

Quantifying Biomass from Point Clouds by Connecting Representations of Ecosystem Structure

NASA Astrophysics Data System (ADS)

Hendryx, S. M.; Barron-Gafford, G.

2017-12-01

Quantifying terrestrial ecosystem biomass is an essential part of monitoring carbon stocks and fluxes within the global carbon cycle and optimizing natural resource management. Point cloud data such as from lidar and structure from motion can be effective for quantifying biomass over large areas, but significant challenges remain in developing effective models that allow for such predictions. Inference models that estimate biomass from point clouds are established in many environments, yet, are often scale-dependent, needing to be fitted and applied at the same spatial scale and grid size at which they were developed. Furthermore, training such models typically requires large in situ datasets that are often prohibitively costly or time-consuming to obtain. We present here a scale- and sensor-invariant framework for efficiently estimating biomass from point clouds. Central to this framework, we present a new algorithm, assignPointsToExistingClusters, that has been developed for finding matches between in situ data and clusters in remotely-sensed point clouds. The algorithm can be used for assessing canopy segmentation accuracy and for training and validating machine learning models for predicting biophysical variables. We demonstrate the algorithm's efficacy by using it to train a random forest model of above ground biomass in a shrubland environment in Southern Arizona. We show that by learning a nonlinear function to estimate biomass from segmented canopy features we can reduce error, especially in the presence of inaccurate clusterings, when compared to a traditional, deterministic technique to estimate biomass from remotely measured canopies. Our random forest on cluster features model extends established methods of training random forest regressions to predict biomass of subplots but requires significantly less training data and is scale invariant. The random forest on cluster features model reduced mean absolute error, when evaluated on all test data in leave one out cross validation, by 40.6% from deterministic mesquite allometry and 35.9% from the inferred ecosystem-state allometric function. Our framework should allow for the inference of biomass more efficiently than common subplot methods and more accurately than individual tree segmentation methods in densely vegetated environments.

Getting to the point: Rapid point selection and variable density InSAR time series for urban deformation monitoring

NASA Astrophysics Data System (ADS)

Spaans, K.; Hooper, A. J.

2017-12-01

The short revisit time and high data acquisition rates of current satellites have resulted in increased interest in the development of deformation monitoring and rapid disaster response capability, using InSAR. Fast, efficient data processing methodologies are required to deliver the timely results necessary for this, and also to limit computing resources required to process the large quantities of data being acquired. Contrary to volcano or earthquake applications, urban monitoring requires high resolution processing, in order to differentiate movements between buildings, or between buildings and the surrounding land. Here we present Rapid time series InSAR (RapidSAR), a method that can efficiently update high resolution time series of interferograms, and demonstrate its effectiveness over urban areas. The RapidSAR method estimates the coherence of pixels on an interferogram-by-interferogram basis. This allows for rapid ingestion of newly acquired images without the need to reprocess the earlier acquired part of the time series. The coherence estimate is based on ensembles of neighbouring pixels with similar amplitude behaviour through time, which are identified on an initial set of interferograms, and need be re-evaluated only occasionally. By taking into account scattering properties of points during coherence estimation, a high quality coherence estimate is achieved, allowing point selection at full resolution. The individual point selection maximizes the amount of information that can be extracted from each interferogram, as no selection compromise has to be reached between high and low coherence interferograms. In other words, points do not have to be coherent throughout the time series to contribute to the deformation time series. We demonstrate the effectiveness of our method over urban areas in the UK. We show how the algorithm successfully extracts high density time series from full resolution Sentinel-1 interferograms, and distinguish clearly between buildings and surrounding vegetation or streets. The fact that new interferograms can be processed separately from the remainder of the time series helps manage the high data volumes, both in space and time, generated by current missions.

Using CSLD Method to Calculate COD Pollution Load of Wei River Watershed above Huaxian Section, China

NASA Astrophysics Data System (ADS)

Zhu, Lei; Song, JinXi; Liu, WanQing

2017-12-01

Huaxian Section is the last hydrological and water quality monitoring section of Weihe River Watershed. Weihe River Watershed above Huaxian Section is taken as the research objective in this paper and COD is chosen as the water quality parameter. According to the discharge characteristics of point source pollutions and non-point source pollutions, a new method to estimate pollution loads—characteristic section load(CSLD) method is suggested and point source pollution and non-point source pollution loads of Weihe River Watershed above Huaxian Section are calculated in the rainy, normal and dry season in the year 2007. The results show that the monthly point source pollution loads of Weihe River Watershed above Huaxian Section discharge stably and the monthly non-point source pollution loads of Weihe River Watershed above Huaxian Section change greatly and the non-point source pollution load proportions of total pollution load of COD decrease in the normal, rainy and wet period in turn.

Calculating NH3-N pollution load of wei river watershed above Huaxian section using CSLD method

NASA Astrophysics Data System (ADS)

Zhu, Lei; Song, JinXi; Liu, WanQing

2018-02-01

Huaxian Section is the last hydrological and water quality monitoring section of Weihe River Watershed. So it is taken as the research objective in this paper and NH3-N is chosen as the water quality parameter. According to the discharge characteristics of point source pollutions and non-point source pollutions, a new method to estimate pollution loads—characteristic section load (CSLD)method is suggested and point source pollution and non-point source pollution loads of Weihe River Watershed above Huaxian Section are calculated in the rainy, normal and dry season in the year 2007. The results show that the monthly point source pollution loads of Weihe River Watershed above Huaxian Section discharge stably and the monthly non-point source pollution loads of Weihe River Watershed above Huaxian Section change greatly. The non-point source pollution load proportions of total pollution load of NH3-N decrease in the normal, rainy and wet period in turn.

Assessing Interval Estimation Methods for Hill Model ...

EPA Pesticide Factsheets

The Hill model of concentration-response is ubiquitous in toxicology, perhaps because its parameters directly relate to biologically significant metrics of toxicity such as efficacy and potency. Point estimates of these parameters obtained through least squares regression or maximum likelihood are commonly used in high-throughput risk assessment, but such estimates typically fail to include reliable information concerning confidence in (or precision of) the estimates. To address this issue, we examined methods for assessing uncertainty in Hill model parameter estimates derived from concentration-response data. In particular, using a sample of ToxCast concentration-response data sets, we applied four methods for obtaining interval estimates that are based on asymptotic theory, bootstrapping (two varieties), and Bayesian parameter estimation, and then compared the results. These interval estimation methods generally did not agree, so we devised a simulation study to assess their relative performance. We generated simulated data by constructing four statistical error models capable of producing concentration-response data sets comparable to those observed in ToxCast. We then applied the four interval estimation methods to the simulated data and compared the actual coverage of the interval estimates to the nominal coverage (e.g., 95%) in order to quantify performance of each of the methods in a variety of cases (i.e., different values of the true Hill model paramet

Monte Carlo point process estimation of electromyographic envelopes from motor cortical spikes for brain-machine interfaces

NASA Astrophysics Data System (ADS)

Liao, Yuxi; She, Xiwei; Wang, Yiwen; Zhang, Shaomin; Zhang, Qiaosheng; Zheng, Xiaoxiang; Principe, Jose C.

2015-12-01

Objective. Representation of movement in the motor cortex (M1) has been widely studied in brain-machine interfaces (BMIs). The electromyogram (EMG) has greater bandwidth than the conventional kinematic variables (such as position, velocity), and is functionally related to the discharge of cortical neurons. As the stochastic information of EMG is derived from the explicit spike time structure, point process (PP) methods will be a good solution for decoding EMG directly from neural spike trains. Previous studies usually assume linear or exponential tuning curves between neural firing and EMG, which may not be true. Approach. In our analysis, we estimate the tuning curves in a data-driven way and find both the traditional functional-excitatory and functional-inhibitory neurons, which are widely found across a rat’s motor cortex. To accurately decode EMG envelopes from M1 neural spike trains, the Monte Carlo point process (MCPP) method is implemented based on such nonlinear tuning properties. Main results. Better reconstruction of EMG signals is shown on baseline and extreme high peaks, as our method can better preserve the nonlinearity of the neural tuning during decoding. The MCPP improves the prediction accuracy (the normalized mean squared error) 57% and 66% on average compared with the adaptive point process filter using linear and exponential tuning curves respectively, for all 112 data segments across six rats. Compared to a Wiener filter using spike rates with an optimal window size of 50 ms, MCPP decoding EMG from a point process improves the normalized mean square error (NMSE) by 59% on average. Significance. These results suggest that neural tuning is constantly changing during task execution and therefore, the use of spike timing methodologies and estimation of appropriate tuning curves needs to be undertaken for better EMG decoding in motor BMIs.

Apportioning riverine DIN load to export coefficients of land uses in an urbanized watershed.

PubMed

Shih, Yu-Ting; Lee, Tsung-Yu; Huang, Jr-Chuan; Kao, Shuh-Ji; Chang

2016-08-01

The apportionment of riverine dissolved inorganic nitrogen (DIN) load to individual land use on a watershed scale demands the support of accurate DIN load estimation and differentiation of point and non-point sources, but both of them are rarely quantitatively determined in small montane watersheds. We introduced the Danshui River watershed of Taiwan, a mountainous urbanized watershed, to determine the export coefficients via a reverse Monte Carlo approach from riverine DIN load. The results showed that the dynamics of N fluctuation determines the load estimation method and sampling frequency. On a monthly sampling frequency basis, the average load estimation of the methods (GM, FW, and LI) outperformed that of individual method. Export coefficient analysis showed that the forest DIN yield of 521.5kg-Nkm(-2)yr(-1) was ~2.7-fold higher than the global riverine DIN yield (mainly from temperate large rivers with various land use compositions). Such a high yield was attributable to high rainfall and atmospheric N deposition. The export coefficient of agriculture was disproportionately larger than forest suggesting that a small replacement of forest to agriculture could lead to considerable change of DIN load. The analysis of differentiation between point and non-point sources showed that the untreated wastewater (non-point source), accounting for ~93% of the total human-associated wastewater, resulted in a high export coefficient of urban. The inclusion of the treated and untreated wastewater completes the N budget of wastewater. The export coefficient approach serves well to assess the riverine DIN load and to improve the understanding of N cascade. Copyright © 2016 Elsevier B.V. All rights reserved.

Tree STEM and Canopy Biomass Estimates from Terrestrial Laser Scanning Data

NASA Astrophysics Data System (ADS)

Olofsson, K.; Holmgren, J.

2017-10-01

In this study an automatic method for estimating both the tree stem and the tree canopy biomass is presented. The point cloud tree extraction techniques operate on TLS data and models the biomass using the estimated stem and canopy volume as independent variables. The regression model fit error is of the order of less than 5 kg, which gives a relative model error of about 5 % for the stem estimate and 10-15 % for the spruce and pine canopy biomass estimates. The canopy biomass estimate was improved by separating the models by tree species which indicates that the method is allometry dependent and that the regression models need to be recomputed for different areas with different climate and different vegetation.

Evaluation of Validity and Reliability for Hierarchical Scales Using Latent Variable Modeling

ERIC Educational Resources Information Center

Raykov, Tenko; Marcoulides, George A.

2012-01-01

A latent variable modeling method is outlined, which accomplishes estimation of criterion validity and reliability for a multicomponent measuring instrument with hierarchical structure. The approach provides point and interval estimates for the scale criterion validity and reliability coefficients, and can also be used for testing composite or…

Error vector magnitude based parameter estimation for digital filter back-propagation mitigating SOA distortions in 16-QAM.

PubMed

Amiralizadeh, Siamak; Nguyen, An T; Rusch, Leslie A

2013-08-26

We investigate the performance of digital filter back-propagation (DFBP) using coarse parameter estimation for mitigating SOA nonlinearity in coherent communication systems. We introduce a simple, low overhead method for parameter estimation for DFBP based on error vector magnitude (EVM) as a figure of merit. The bit error rate (BER) penalty achieved with this method has negligible penalty as compared to DFBP with fine parameter estimation. We examine different bias currents for two commercial SOAs used as booster amplifiers in our experiments to find optimum operating points and experimentally validate our method. The coarse parameter DFBP efficiently compensates SOA-induced nonlinearity for both SOA types in 80 km propagation of 16-QAM signal at 22 Gbaud.

Analytic assessment of Laplacian estimates via novel variable interring distances concentric ring electrodes.

PubMed

Makeyev, Oleksandr; Besio, Walter G

2016-08-01

Noninvasive concentric ring electrodes are a promising alternative to conventional disc electrodes. Currently, superiority of tripolar concentric ring electrodes over disc electrodes, in particular, in accuracy of Laplacian estimation has been demonstrated in a range of applications. In our recent work we have shown that accuracy of Laplacian estimation can be improved with multipolar concentric ring electrodes using a general approach to estimation of the Laplacian for an (n + 1)-polar electrode with n rings using the (4n + 1)-point method for n ≥ 2. This paper takes the next step toward further improving the Laplacian estimate by proposing novel variable inter-ring distances concentric ring electrodes. Derived using a modified (4n + 1)-point method, linearly increasing inter-ring distances tripolar (n = 2) and quadripolar (n = 3) electrode configurations are analytically compared to their constant inter-ring distances counterparts using coefficients of the Taylor series truncation terms. Obtained results suggest that increasing inter-ring distances electrode configurations may decrease the truncation error of the Laplacian estimation resulting in more accurate Laplacian estimates compared to respective constant inter-ring distances configurations. For currently used tripolar electrode configuration the truncation error may be decreased more than two-fold while for the quadripolar more than seven-fold decrease is expected.

Estimation of source location and ground impedance using a hybrid multiple signal classification and Levenberg-Marquardt approach

NASA Astrophysics Data System (ADS)

Tam, Kai-Chung; Lau, Siu-Kit; Tang, Shiu-Keung

2016-07-01

A microphone array signal processing method for locating a stationary point source over a locally reactive ground and for estimating ground impedance is examined in detail in the present study. A non-linear least square approach using the Levenberg-Marquardt method is proposed to overcome the problem of unknown ground impedance. The multiple signal classification method (MUSIC) is used to give the initial estimation of the source location, while the technique of forward backward spatial smoothing is adopted as a pre-processer of the source localization to minimize the effects of source coherence. The accuracy and robustness of the proposed signal processing method are examined. Results show that source localization in the horizontal direction by MUSIC is satisfactory. However, source coherence reduces drastically the accuracy in estimating the source height. The further application of Levenberg-Marquardt method with the results from MUSIC as the initial inputs improves significantly the accuracy of source height estimation. The present proposed method provides effective and robust estimation of the ground surface impedance.

High precision determination of the melting points of water TIP4P/2005 and water TIP4P/Ice models by the direct coexistence technique

NASA Astrophysics Data System (ADS)

Conde, M. M.; Rovere, M.; Gallo, P.

2017-12-01

An exhaustive study by molecular dynamics has been performed to analyze the factors that enhance the precision of the technique of direct coexistence for a system of ice and liquid water. The factors analyzed are the stochastic nature of the method, the finite size effects, and the influence of the initial ice configuration used. The results obtained show that the precision of estimates obtained through the technique of direct coexistence is markedly affected by the effects of finite size, requiring systems with a large number of molecules to reduce the error bar of the melting point. This increase in size causes an increase in the simulation time, but the estimate of the melting point with a great accuracy is important, for example, in studies on the ice surface. We also verified that the choice of the initial ice Ih configuration with different proton arrangements does not significantly affect the estimate of the melting point. Importantly this study leads us to estimate the melting point at ambient pressure of two of the most popular models of water, TIP4P/2005 and TIP4P/Ice, with the greatest precision to date.

Effect of Impurities on the Freezing Point of Zinc

NASA Astrophysics Data System (ADS)

Sun, Jianping; Rudtsch, Steffen; Niu, Yalu; Zhang, Lin; Wang, Wei; Den, Xiaolong

2017-03-01

The knowledge of the liquidus slope of impurities in fixed-point metal defined by the International Temperature Scale of 1990 is important for the estimation of uncertainties and correction of fixed point with the sum of individual estimates method. Great attentions are paid to the effect of ultra-trace impurities on the freezing point of zinc in the National Institute of Metrology. In the present work, the liquidus slopes of Ga-Zn, Ge-Zn were measured with the slim fixed-point cell developed through the doping experiments, and the temperature characteristics of the phase diagram of Fe-Zn were furthermore investigated. A quasi-adiabatic Zn fixed-point cell was developed with the thermometer well surrounded by the crucible with the pure metal, and the temperature uniformity of less than 20 mK in the region where the metal is located was obtained. The previous doping experiment of Pb-Zn with slim fixed-point cell was checked with quasi-adiabatic Zn fixed-point cell, and the result supports the previous liquidus slope measured with the traditional fixed-point realization.

Methods for determining time of death.

PubMed

Madea, Burkhard

2016-12-01

Medicolegal death time estimation must estimate the time since death reliably. Reliability can only be provided empirically by statistical analysis of errors in field studies. Determining the time since death requires the calculation of measurable data along a time-dependent curve back to the starting point. Various methods are used to estimate the time since death. The current gold standard for death time estimation is a previously established nomogram method based on the two-exponential model of body cooling. Great experimental and practical achievements have been realized using this nomogram method. To reduce the margin of error of the nomogram method, a compound method was developed based on electrical and mechanical excitability of skeletal muscle, pharmacological excitability of the iris, rigor mortis, and postmortem lividity. Further increasing the accuracy of death time estimation involves the development of conditional probability distributions for death time estimation based on the compound method. Although many studies have evaluated chemical methods of death time estimation, such methods play a marginal role in daily forensic practice. However, increased precision of death time estimation has recently been achieved by considering various influencing factors (i.e., preexisting diseases, duration of terminal episode, and ambient temperature). Putrefactive changes may be used for death time estimation in water-immersed bodies. Furthermore, recently developed technologies, such as H magnetic resonance spectroscopy, can be used to quantitatively study decompositional changes. This review addresses the gold standard method of death time estimation in forensic practice and promising technological and scientific developments in the field.

Bayesian inference for disease prevalence using negative binomial group testing

PubMed Central

Pritchard, Nicholas A.; Tebbs, Joshua M.

2011-01-01

Group testing, also known as pooled testing, and inverse sampling are both widely used methods of data collection when the goal is to estimate a small proportion. Taking a Bayesian approach, we consider the new problem of estimating disease prevalence from group testing when inverse (negative binomial) sampling is used. Using different distributions to incorporate prior knowledge of disease incidence and different loss functions, we derive closed form expressions for posterior distributions and resulting point and credible interval estimators. We then evaluate our new estimators, on Bayesian and classical grounds, and apply our methods to a West Nile Virus data set. PMID:21259308

Bone orientation and position estimation errors using Cosserat point elements and least squares methods: Application to gait.

PubMed

Solav, Dana; Camomilla, Valentina; Cereatti, Andrea; Barré, Arnaud; Aminian, Kamiar; Wolf, Alon

2017-09-06

The aim of this study was to analyze the accuracy of bone pose estimation based on sub-clusters of three skin-markers characterized by triangular Cosserat point elements (TCPEs) and to evaluate the capability of four instantaneous physical parameters, which can be measured non-invasively in vivo, to identify the most accurate TCPEs. Moreover, TCPE pose estimations were compared with the estimations of two least squares minimization methods applied to the cluster of all markers, using rigid body (RBLS) and homogeneous deformation (HDLS) assumptions. Analysis was performed on previously collected in vivo treadmill gait data composed of simultaneous measurements of the gold-standard bone pose by bi-plane fluoroscopy tracking the subjects' knee prosthesis and a stereophotogrammetric system tracking skin-markers affected by soft tissue artifact. Femur orientation and position errors estimated from skin-marker clusters were computed for 18 subjects using clusters of up to 35 markers. Results based on gold-standard data revealed that instantaneous subsets of TCPEs exist which estimate the femur pose with reasonable accuracy (median root mean square error during stance/swing: 1.4/2.8deg for orientation, 1.5/4.2mm for position). A non-invasive and instantaneous criteria to select accurate TCPEs for pose estimation (4.8/7.3deg, 5.8/12.3mm), was compared with RBLS (4.3/6.6deg, 6.9/16.6mm) and HDLS (4.6/7.6deg, 6.7/12.5mm). Accounting for homogeneous deformation, using HDLS or selected TCPEs, yielded more accurate position estimations than RBLS method, which, conversely, yielded more accurate orientation estimations. Further investigation is required to devise effective criteria for cluster selection that could represent a significant improvement in bone pose estimation accuracy. Copyright © 2017 Elsevier Ltd. All rights reserved.

Face pose tracking using the four-point algorithm

NASA Astrophysics Data System (ADS)

Fung, Ho Yin; Wong, Kin Hong; Yu, Ying Kin; Tsui, Kwan Pang; Kam, Ho Chuen

2017-06-01

In this paper, we have developed an algorithm to track the pose of a human face robustly and efficiently. Face pose estimation is very useful in many applications such as building virtual reality systems and creating an alternative input method for the disabled. Firstly, we have modified a face detection toolbox called DLib for the detection of a face in front of a camera. The detected face features are passed to a pose estimation method, known as the four-point algorithm, for pose computation. The theory applied and the technical problems encountered during system development are discussed in the paper. It is demonstrated that the system is able to track the pose of a face in real time using a consumer grade laptop computer.

A test of the 'one-point method' for estimating maximum carboxylation capacity from field-measured, light-saturated photosynthesis

DOE PAGES

Martin G. De Kauwe; Serbin, Shawn P.; Lin, Yan -Shih; ...

2015-12-31

Here, simulations of photosynthesis by terrestrial biosphere models typically need a specification of the maximum carboxylation rate (V cmax). Estimating this parameter using A–C i curves (net photosynthesis, A, vs intercellular CO 2 concentration, C i) is laborious, which limits availability of V cmax data. However, many multispecies field datasets include net photosynthetic rate at saturating irradiance and at ambient atmospheric CO 2 concentration (A sat) measurements, from which V cmax can be extracted using a ‘one-point method’.

Solution of the weighted symmetric similarity transformations based on quaternions

NASA Astrophysics Data System (ADS)

Mercan, H.; Akyilmaz, O.; Aydin, C.

2017-12-01

A new method through Gauss-Helmert model of adjustment is presented for the solution of the similarity transformations, either 3D or 2D, in the frame of errors-in-variables (EIV) model. EIV model assumes that all the variables in the mathematical model are contaminated by random errors. Total least squares estimation technique may be used to solve the EIV model. Accounting for the heteroscedastic uncertainty both in the target and the source coordinates, that is the more common and general case in practice, leads to a more realistic estimation of the transformation parameters. The presented algorithm can handle the heteroscedastic transformation problems, i.e., positions of the both target and the source points may have full covariance matrices. Therefore, there is no limitation such as the isotropic or the homogenous accuracy for the reference point coordinates. The developed algorithm takes the advantage of the quaternion definition which uniquely represents a 3D rotation matrix. The transformation parameters: scale, translations, and the quaternion (so that the rotation matrix) along with their covariances, are iteratively estimated with rapid convergence. Moreover, prior least squares (LS) estimation of the unknown transformation parameters is not required to start the iterations. We also show that the developed method can also be used to estimate the 2D similarity transformation parameters by simply treating the problem as a 3D transformation problem with zero (0) values assigned for the z-components of both target and source points. The efficiency of the new algorithm is presented with the numerical examples and comparisons with the results of the previous studies which use the same data set. Simulation experiments for the evaluation and comparison of the proposed and the conventional weighted LS (WLS) method is also presented.

Automated analysis of plethysmograms for functional studies of hemodynamics

NASA Astrophysics Data System (ADS)

Zatrudina, R. Sh.; Isupov, I. B.; Gribkov, V. Yu.

2018-04-01

The most promising method for the quantitative determination of cardiovascular tone indicators and of cerebral hemodynamics indicators is the method of impedance plethysmography. The accurate determination of these indicators requires the correct identification of the characteristic points in the thoracic impedance plethysmogram and the cranial impedance plethysmogram respectively. An algorithm for automatic analysis of these plethysmogram is presented. The algorithm is based on the hard temporal relationships between the phases of the cardiac cycle and the characteristic points of the plethysmogram. The proposed algorithm does not require estimation of initial data and selection of processing parameters. Use of the method on healthy subjects showed a very low detection error of characteristic points.

The expected value of possession in professional rugby league match-play.

PubMed

Kempton, Thomas; Kennedy, Nicholas; Coutts, Aaron J

2016-01-01

This study estimated the expected point value for starting possessions in different field locations during rugby league match-play and calculated the mean expected points for each subsequent play during the possession. It also examined the origin of tries scored according to the method of gaining possession. Play-by-play data were taken from all 768 regular-season National Rugby League (NRL) matches during 2010-2013. A probabilistic model estimated the expected point outcome based on the net difference in points scored by a team in possession in a given situation. An iterative method was used to approximate the value of each situation based on actual scoring outcomes. Possessions commencing close to the opposition's goal-line had the highest expected point equity, which decreased as the location of the possession moved towards the team's own goal-line. Possessions following an opposition error, penalty or goal-line dropout had the highest likelihood of a try being scored on the set subsequent to their occurrence. In contrast, possessions that follow an opposition completed set or a restart were least likely to result in a try. The expected point values framework from our model has applications for informing playing strategy and assessing individual and team performance in professional rugby league.

A method of 3D object recognition and localization in a cloud of points

NASA Astrophysics Data System (ADS)

Bielicki, Jerzy; Sitnik, Robert

2013-12-01

The proposed method given in this article is prepared for analysis of data in the form of cloud of points directly from 3D measurements. It is designed for use in the end-user applications that can directly be integrated with 3D scanning software. The method utilizes locally calculated feature vectors (FVs) in point cloud data. Recognition is based on comparison of the analyzed scene with reference object library. A global descriptor in the form of a set of spatially distributed FVs is created for each reference model. During the detection process, correlation of subsets of reference FVs with FVs calculated in the scene is computed. Features utilized in the algorithm are based on parameters, which qualitatively estimate mean and Gaussian curvatures. Replacement of differentiation with averaging in the curvatures estimation makes the algorithm more resistant to discontinuities and poor quality of the input data. Utilization of the FV subsets allows to detect partially occluded and cluttered objects in the scene, while additional spatial information maintains false positive rate at a reasonably low level.

The effect of tandem-ovoid titanium applicator on points A, B, bladder, and rectum doses in gynecological brachytherapy using 192Ir.

PubMed

Sadeghi, Mohammad Hosein; Sina, Sedigheh; Mehdizadeh, Amir; Faghihi, Reza; Moharramzadeh, Vahed; Meigooni, Ali Soleimani

2018-02-01

The dosimetry procedure by simple superposition accounts only for the self-shielding of the source and does not take into account the attenuation of photons by the applicators. The purpose of this investigation is an estimation of the effects of the tandem and ovoid applicator on dose distribution inside the phantom by MCNP5 Monte Carlo simulations. In this study, the superposition method is used for obtaining the dose distribution in the phantom without using the applicator for a typical gynecological brachytherapy (superposition-1). Then, the sources are simulated inside the tandem and ovoid applicator to identify the effect of applicator attenuation (superposition-2), and the dose at points A, B, bladder, and rectum were compared with the results of superposition. The exact dwell positions, times of the source, and positions of the dosimetry points were determined in images of a patient and treatment data of an adult woman patient from a cancer center. The MCNP5 Monte Carlo (MC) code was used for simulation of the phantoms, applicators, and the sources. The results of this study showed no significant differences between the results of superposition method and the MC simulations for different dosimetry points. The difference in all important dosimetry points was found to be less than 5%. According to the results, applicator attenuation has no significant effect on the calculated points dose, the superposition method, adding the dose of each source obtained by the MC simulation, can estimate the dose to points A, B, bladder, and rectum with good accuracy.

Effects of sampling strategy, detection probability, and independence of counts on the use of point counts

USGS Publications Warehouse

Pendleton, G.W.; Ralph, C. John; Sauer, John R.; Droege, Sam

1995-01-01

Many factors affect the use of point counts for monitoring bird populations, including sampling strategies, variation in detection rates, and independence of sample points. The most commonly used sampling plans are stratified sampling, cluster sampling, and systematic sampling. Each of these might be most useful for different objectives or field situations. Variation in detection probabilities and lack of independence among sample points can bias estimates and measures of precision. All of these factors should be con-sidered when using point count methods.

Correlating locations in ipsilateral breast tomosynthesis views using an analytical hemispherical compression model

NASA Astrophysics Data System (ADS)

van Schie, Guido; Tanner, Christine; Snoeren, Peter; Samulski, Maurice; Leifland, Karin; Wallis, Matthew G.; Karssemeijer, Nico

2011-08-01

To improve cancer detection in mammography, breast examinations usually consist of two views per breast. In order to combine information from both views, corresponding regions in the views need to be matched. In 3D digital breast tomosynthesis (DBT), this may be a difficult and time-consuming task for radiologists, because many slices have to be inspected individually. For multiview computer-aided detection (CAD) systems, matching corresponding regions is an essential step that needs to be automated. In this study, we developed an automatic method to quickly estimate corresponding locations in ipsilateral tomosynthesis views by applying a spatial transformation. First we match a model of a compressed breast to the tomosynthesis view containing a point of interest. Then we estimate the location of the corresponding point in the ipsilateral view by assuming that this model was decompressed, rotated and compressed again. In this study, we use a relatively simple, elastically deformable sphere model to obtain an analytical solution for the transformation in a given DBT case. We investigate three different methods to match the compression model to the data by using automatic segmentation of the pectoral muscle, breast tissue and nipple. For validation, we annotated 208 landmarks in both views of a total of 146 imaged breasts of 109 different patients and applied our method to each location. The best results are obtained by using the centre of gravity of the breast to define the central axis of the model, around which the breast is assumed to rotate between views. Results show a median 3D distance between the actual location and the estimated location of 14.6 mm, a good starting point for a registration method or a feature-based local search method to link suspicious regions in a multiview CAD system. Approximately half of the estimated locations are at most one slice away from the actual location, which makes the method useful as a mammographic workstation tool for radiologists to interactively find corresponding locations in ipsilateral tomosynthesis views.

Estimating the spatial position of marine mammals based on digital camera recordings

PubMed Central

Hoekendijk, Jeroen P A; de Vries, Jurre; van der Bolt, Krissy; Greinert, Jens; Brasseur, Sophie; Camphuysen, Kees C J; Aarts, Geert

2015-01-01

Estimating the spatial position of organisms is essential to quantify interactions between the organism and the characteristics of its surroundings, for example, predator–prey interactions, habitat selection, and social associations. Because marine mammals spend most of their time under water and may appear at the surface only briefly, determining their exact geographic location can be challenging. Here, we developed a photogrammetric method to accurately estimate the spatial position of marine mammals or birds at the sea surface. Digital recordings containing landscape features with known geographic coordinates can be used to estimate the distance and bearing of each sighting relative to the observation point. The method can correct for frame rotation, estimates pixel size based on the reference points, and can be applied to scenarios with and without a visible horizon. A set of R functions was written to process the images and obtain accurate geographic coordinates for each sighting. The method is applied to estimate the spatiotemporal fine-scale distribution of harbour porpoises in a tidal inlet. Video recordings of harbour porpoises were made from land, using a standard digital single-lens reflex (DSLR) camera, positioned at a height of 9.59 m above mean sea level. Porpoises were detected up to a distance of ∽3136 m (mean 596 m), with a mean location error of 12 m. The method presented here allows for multiple detections of different individuals within a single video frame and for tracking movements of individuals based on repeated sightings. In comparison with traditional methods, this method only requires a digital camera to provide accurate location estimates. It especially has great potential in regions with ample data on local (a)biotic conditions, to help resolve functional mechanisms underlying habitat selection and other behaviors in marine mammals in coastal areas. PMID:25691982

Gaussian process-based Bayesian nonparametric inference of population size trajectories from gene genealogies.

PubMed

Palacios, Julia A; Minin, Vladimir N

2013-03-01

Changes in population size influence genetic diversity of the population and, as a result, leave a signature of these changes in individual genomes in the population. We are interested in the inverse problem of reconstructing past population dynamics from genomic data. We start with a standard framework based on the coalescent, a stochastic process that generates genealogies connecting randomly sampled individuals from the population of interest. These genealogies serve as a glue between the population demographic history and genomic sequences. It turns out that only the times of genealogical lineage coalescences contain information about population size dynamics. Viewing these coalescent times as a point process, estimating population size trajectories is equivalent to estimating a conditional intensity of this point process. Therefore, our inverse problem is similar to estimating an inhomogeneous Poisson process intensity function. We demonstrate how recent advances in Gaussian process-based nonparametric inference for Poisson processes can be extended to Bayesian nonparametric estimation of population size dynamics under the coalescent. We compare our Gaussian process (GP) approach to one of the state-of-the-art Gaussian Markov random field (GMRF) methods for estimating population trajectories. Using simulated data, we demonstrate that our method has better accuracy and precision. Next, we analyze two genealogies reconstructed from real sequences of hepatitis C and human Influenza A viruses. In both cases, we recover more believed aspects of the viral demographic histories than the GMRF approach. We also find that our GP method produces more reasonable uncertainty estimates than the GMRF method. Copyright © 2013, The International Biometric Society.

Analysis of backward error recovery for concurrent processes with recovery blocks

NASA Technical Reports Server (NTRS)

Shin, K. G.; Lee, Y. H.

1982-01-01

Three different methods of implementing recovery blocks (RB's). These are the asynchronous, synchronous, and the pseudo recovery point implementations. Pseudo recovery points so that unbounded rollback may be avoided while maintaining process autonomy are proposed. Probabilistic models for analyzing these three methods under standard assumptions in computer performance analysis, i.e., exponential distributions for related random variables were developed. The interval between two successive recovery lines for asynchronous RB's mean loss in computation power for the synchronized method, and additional overhead and rollback distance in case PRP's are used were estimated.

Molar axis estimation from computed tomography images.

PubMed

Dongxia Zhang; Yangzhou Gan; Zeyang Xia; Xinwen Zhou; Shoubin Liu; Jing Xiong; Guanglin Li

2016-08-01

Estimation of tooth axis is needed for some clinical dental treatment. Existing methods require to segment the tooth volume from Computed Tomography (CT) images, and then estimate the axis from the tooth volume. However, they may fail during estimating molar axis due to that the tooth segmentation from CT images is challenging and current segmentation methods may get poor segmentation results especially for these molars with angle which will result in the failure of axis estimation. To resolve this problem, this paper proposes a new method for molar axis estimation from CT images. The key innovation point is that: instead of estimating the 3D axis of each molar from the segmented volume, the method estimates the 3D axis from two projection images. The method includes three steps. (1) The 3D images of each molar are projected to two 2D image planes. (2) The molar contour are segmented and the contour's 2D axis are extracted in each 2D projection image. Principal Component Analysis (PCA) and a modified symmetry axis detection algorithm are employed to extract the 2D axis from the segmented molar contour. (3) A 3D molar axis is obtained by combining the two 2D axes. Experimental results verified that the proposed method was effective to estimate the axis of molar from CT images.

A method to approximate a closest loadability limit using multiple load flow solutions

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

Yorino, Naoto; Harada, Shigemi; Cheng, Haozhong

A new method is proposed to approximate a closest loadability limit (CLL), or closest saddle node bifurcation point, using a pair of multiple load flow solutions. More strictly, the obtainable points by the method are the stationary points including not only CLL but also farthest and saddle points. An operating solution and a low voltage load flow solution are used to efficiently estimate the node injections at a CLL as well as the left and right eigenvectors corresponding to the zero eigenvalue of the load flow Jacobian. They can be used in monitoring loadability margin, in identification of weak spotsmore » in a power system and in the examination of an optimal control against voltage collapse. Most of the computation time of the proposed method is taken in calculating the load flow solution pair. The remaining computation time is less than that of an ordinary load flow.« less

The Andrews’ Principles of Risk, Need, and Responsivity as Applied in Drug Abuse Treatment Programs: Meta-Analysis of Crime and Drug Use Outcomes

PubMed Central

Prendergast, Michael L.; Pearson, Frank S.; Podus, Deborah; Hamilton, Zachary K.; Greenwell, Lisa

2013-01-01

Objectives The purpose of the present meta-analysis was to answer the question: Can the Andrews principles of risk, needs, and responsivity, originally developed for programs that treat offenders, be extended to programs that treat drug abusers? Methods Drawing from a dataset that included 243 independent comparisons, we conducted random-effects meta-regression and ANOVA-analog meta-analyses to test the Andrews principles by averaging crime and drug use outcomes over a diverse set of programs for drug abuse problems. Results For crime outcomes, in the meta-regressions the point estimates for each of the principles were substantial, consistent with previous studies of the Andrews principles. There was also a substantial point estimate for programs exhibiting a greater number of the principles. However, almost all of the 95% confidence intervals included the zero point. For drug use outcomes, in the meta-regressions the point estimates for each of the principles was approximately zero; however, the point estimate for programs exhibiting a greater number of the principles was somewhat positive. All of the estimates for the drug use principles had confidence intervals that included the zero point. Conclusions This study supports previous findings from primary research studies targeting the Andrews principles that those principles are effective in reducing crime outcomes, here in meta-analytic research focused on drug treatment programs. By contrast, programs that follow the principles appear to have very little effect on drug use outcomes. Primary research studies that experimentally test the Andrews principles in drug treatment programs are recommended. PMID:24058325

Covariate analysis of bivariate survival data

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

Bennett, L.E.

1992-01-01

The methods developed are used to analyze the effects of covariates on bivariate survival data when censoring and ties are present. The proposed method provides models for bivariate survival data that include differential covariate effects and censored observations. The proposed models are based on an extension of the univariate Buckley-James estimators which replace censored data points by their expected values, conditional on the censoring time and the covariates. For the bivariate situation, it is necessary to determine the expectation of the failure times for one component conditional on the failure or censoring time of the other component. Two different methodsmore » have been developed to estimate these expectations. In the semiparametric approach these expectations are determined from a modification of Burke's estimate of the bivariate empirical survival function. In the parametric approach censored data points are also replaced by their conditional expected values where the expected values are determined from a specified parametric distribution. The model estimation will be based on the revised data set, comprised of uncensored components and expected values for the censored components. The variance-covariance matrix for the estimated covariate parameters has also been derived for both the semiparametric and parametric methods. Data from the Demographic and Health Survey was analyzed by these methods. The two outcome variables are post-partum amenorrhea and breastfeeding; education and parity were used as the covariates. Both the covariate parameter estimates and the variance-covariance estimates for the semiparametric and parametric models will be compared. In addition, a multivariate test statistic was used in the semiparametric model to examine contrasts. The significance of the statistic was determined from a bootstrap distribution of the test statistic.« less

Designing and Testing a UAV Mapping System for Agricultural Field Surveying

PubMed Central

Skovsen, Søren

2017-01-01

A Light Detection and Ranging (LiDAR) sensor mounted on an Unmanned Aerial Vehicle (UAV) can map the overflown environment in point clouds. Mapped canopy heights allow for the estimation of crop biomass in agriculture. The work presented in this paper contributes to sensory UAV setup design for mapping and textual analysis of agricultural fields. LiDAR data are combined with data from Global Navigation Satellite System (GNSS) and Inertial Measurement Unit (IMU) sensors to conduct environment mapping for point clouds. The proposed method facilitates LiDAR recordings in an experimental winter wheat field. Crop height estimates ranging from 0.35–0.58 m are correlated to the applied nitrogen treatments of 0–300 kgNha. The LiDAR point clouds are recorded, mapped, and analysed using the functionalities of the Robot Operating System (ROS) and the Point Cloud Library (PCL). Crop volume estimation is based on a voxel grid with a spatial resolution of 0.04 × 0.04 × 0.001 m. Two different flight patterns are evaluated at an altitude of 6 m to determine the impacts of the mapped LiDAR measurements on crop volume estimations. PMID:29168783

Replica approach to mean-variance portfolio optimization

NASA Astrophysics Data System (ADS)

Varga-Haszonits, Istvan; Caccioli, Fabio; Kondor, Imre

2016-12-01

We consider the problem of mean-variance portfolio optimization for a generic covariance matrix subject to the budget constraint and the constraint for the expected return, with the application of the replica method borrowed from the statistical physics of disordered systems. We find that the replica symmetry of the solution does not need to be assumed, but emerges as the unique solution of the optimization problem. We also check the stability of this solution and find that the eigenvalues of the Hessian are positive for r  =  N/T  <  1, where N is the dimension of the portfolio and T the length of the time series used to estimate the covariance matrix. At the critical point r  =  1 a phase transition is taking place. The out of sample estimation error blows up at this point as 1/(1  -  r), independently of the covariance matrix or the expected return, displaying the universality not only of the critical exponent, but also the critical point. As a conspicuous illustration of the dangers of in-sample estimates, the optimal in-sample variance is found to vanish at the critical point inversely proportional to the divergent estimation error.

Designing and Testing a UAV Mapping System for Agricultural Field Surveying.

PubMed

Christiansen, Martin Peter; Laursen, Morten Stigaard; Jørgensen, Rasmus Nyholm; Skovsen, Søren; Gislum, René

2017-11-23

A Light Detection and Ranging (LiDAR) sensor mounted on an Unmanned Aerial Vehicle (UAV) can map the overflown environment in point clouds. Mapped canopy heights allow for the estimation of crop biomass in agriculture. The work presented in this paper contributes to sensory UAV setup design for mapping and textual analysis of agricultural fields. LiDAR data are combined with data from Global Navigation Satellite System (GNSS) and Inertial Measurement Unit (IMU) sensors to conduct environment mapping for point clouds. The proposed method facilitates LiDAR recordings in an experimental winter wheat field. Crop height estimates ranging from 0.35-0.58 m are correlated to the applied nitrogen treatments of 0-300 kg N ha . The LiDAR point clouds are recorded, mapped, and analysed using the functionalities of the Robot Operating System (ROS) and the Point Cloud Library (PCL). Crop volume estimation is based on a voxel grid with a spatial resolution of 0.04 × 0.04 × 0.001 m. Two different flight patterns are evaluated at an altitude of 6 m to determine the impacts of the mapped LiDAR measurements on crop volume estimations.

Control optimization of a lifting body entry problem by an improved and a modified method of perturbation function. Ph.D. Thesis - Houston Univ.

NASA Technical Reports Server (NTRS)

Garcia, F., Jr.

1974-01-01

A study of the solution problem of a complex entry optimization was studied. The problem was transformed into a two-point boundary value problem by using classical calculus of variation methods. Two perturbation methods were devised. These methods attempted to desensitize the contingency of the solution of this type of problem on the required initial co-state estimates. Also numerical results are presented for the optimal solution resulting from a number of different initial co-states estimates. The perturbation methods were compared. It is found that they are an improvement over existing methods.

Structure-From for Calibration of a Vehicle Camera System with Non-Overlapping Fields-Of in AN Urban Environment

NASA Astrophysics Data System (ADS)

Hanel, A.; Stilla, U.

2017-05-01

Vehicle environment cameras observing traffic participants in the area around a car and interior cameras observing the car driver are important data sources for driver intention recognition algorithms. To combine information from both camera groups, a camera system calibration can be performed. Typically, there is no overlapping field-of-view between environment and interior cameras. Often no marked reference points are available in environments, which are a large enough to cover a car for the system calibration. In this contribution, a calibration method for a vehicle camera system with non-overlapping camera groups in an urban environment is described. A-priori images of an urban calibration environment taken with an external camera are processed with the structure-frommotion method to obtain an environment point cloud. Images of the vehicle interior, taken also with an external camera, are processed to obtain an interior point cloud. Both point clouds are tied to each other with images of both image sets showing the same real-world objects. The point clouds are transformed into a self-defined vehicle coordinate system describing the vehicle movement. On demand, videos can be recorded with the vehicle cameras in a calibration drive. Poses of vehicle environment cameras and interior cameras are estimated separately using ground control points from the respective point cloud. All poses of a vehicle camera estimated for different video frames are optimized in a bundle adjustment. In an experiment, a point cloud is created from images of an underground car park, as well as a point cloud of the interior of a Volkswagen test car is created. Videos of two environment and one interior cameras are recorded. Results show, that the vehicle camera poses are estimated successfully especially when the car is not moving. Position standard deviations in the centimeter range can be achieved for all vehicle cameras. Relative distances between the vehicle cameras deviate between one and ten centimeters from tachymeter reference measurements.

Travel Time Estimation Using Freeway Point Detector Data Based on Evolving Fuzzy Neural Inference System.

PubMed

Tang, Jinjun; Zou, Yajie; Ash, John; Zhang, Shen; Liu, Fang; Wang, Yinhai

2016-01-01

Travel time is an important measurement used to evaluate the extent of congestion within road networks. This paper presents a new method to estimate the travel time based on an evolving fuzzy neural inference system. The input variables in the system are traffic flow data (volume, occupancy, and speed) collected from loop detectors located at points both upstream and downstream of a given link, and the output variable is the link travel time. A first order Takagi-Sugeno fuzzy rule set is used to complete the inference. For training the evolving fuzzy neural network (EFNN), two learning processes are proposed: (1) a K-means method is employed to partition input samples into different clusters, and a Gaussian fuzzy membership function is designed for each cluster to measure the membership degree of samples to the cluster centers. As the number of input samples increases, the cluster centers are modified and membership functions are also updated; (2) a weighted recursive least squares estimator is used to optimize the parameters of the linear functions in the Takagi-Sugeno type fuzzy rules. Testing datasets consisting of actual and simulated data are used to test the proposed method. Three common criteria including mean absolute error (MAE), root mean square error (RMSE), and mean absolute relative error (MARE) are utilized to evaluate the estimation performance. Estimation results demonstrate the accuracy and effectiveness of the EFNN method through comparison with existing methods including: multiple linear regression (MLR), instantaneous model (IM), linear model (LM), neural network (NN), and cumulative plots (CP).

Travel Time Estimation Using Freeway Point Detector Data Based on Evolving Fuzzy Neural Inference System

PubMed Central

Tang, Jinjun; Zou, Yajie; Ash, John; Zhang, Shen; Liu, Fang; Wang, Yinhai

2016-01-01

Travel time is an important measurement used to evaluate the extent of congestion within road networks. This paper presents a new method to estimate the travel time based on an evolving fuzzy neural inference system. The input variables in the system are traffic flow data (volume, occupancy, and speed) collected from loop detectors located at points both upstream and downstream of a given link, and the output variable is the link travel time. A first order Takagi-Sugeno fuzzy rule set is used to complete the inference. For training the evolving fuzzy neural network (EFNN), two learning processes are proposed: (1) a K-means method is employed to partition input samples into different clusters, and a Gaussian fuzzy membership function is designed for each cluster to measure the membership degree of samples to the cluster centers. As the number of input samples increases, the cluster centers are modified and membership functions are also updated; (2) a weighted recursive least squares estimator is used to optimize the parameters of the linear functions in the Takagi-Sugeno type fuzzy rules. Testing datasets consisting of actual and simulated data are used to test the proposed method. Three common criteria including mean absolute error (MAE), root mean square error (RMSE), and mean absolute relative error (MARE) are utilized to evaluate the estimation performance. Estimation results demonstrate the accuracy and effectiveness of the EFNN method through comparison with existing methods including: multiple linear regression (MLR), instantaneous model (IM), linear model (LM), neural network (NN), and cumulative plots (CP). PMID:26829639

A pose estimation method for unmanned ground vehicles in GPS denied environments

NASA Astrophysics Data System (ADS)

Tamjidi, Amirhossein; Ye, Cang

2012-06-01

This paper presents a pose estimation method based on the 1-Point RANSAC EKF (Extended Kalman Filter) framework. The method fuses the depth data from a LIDAR and the visual data from a monocular camera to estimate the pose of a Unmanned Ground Vehicle (UGV) in a GPS denied environment. Its estimation framework continuy updates the vehicle's 6D pose state and temporary estimates of the extracted visual features' 3D positions. In contrast to the conventional EKF-SLAM (Simultaneous Localization And Mapping) frameworks, the proposed method discards feature estimates from the extended state vector once they are no longer observed for several steps. As a result, the extended state vector always maintains a reasonable size that is suitable for online calculation. The fusion of laser and visual data is performed both in the feature initialization part of the EKF-SLAM process and in the motion prediction stage. A RANSAC pose calculation procedure is devised to produce pose estimate for the motion model. The proposed method has been successfully tested on the Ford campus's LIDAR-Vision dataset. The results are compared with the ground truth data of the dataset and the estimation error is ~1.9% of the path length.

orbit-estimation: Fast orbital parameters estimator

NASA Astrophysics Data System (ADS)

Mackereth, J. Ted; Bovy, Jo

2018-04-01

orbit-estimation tests and evaluates the Stäckel approximation method for estimating orbit parameters in galactic potentials. It relies on the approximation of the Galactic potential as a Stäckel potential, in a prolate confocal coordinate system, under which the vertical and horizontal motions decouple. By solving the Hamilton Jacobi equations at the turning points of the horizontal and vertical motions, it is possible to determine the spatial boundary of the orbit, and hence calculate the desired orbit parameters.

Prescription-drug-related risk in driving: comparing conventional and lasso shrinkage logistic regressions.

PubMed

Avalos, Marta; Adroher, Nuria Duran; Lagarde, Emmanuel; Thiessard, Frantz; Grandvalet, Yves; Contrand, Benjamin; Orriols, Ludivine

2012-09-01

Large data sets with many variables provide particular challenges when constructing analytic models. Lasso-related methods provide a useful tool, although one that remains unfamiliar to most epidemiologists. We illustrate the application of lasso methods in an analysis of the impact of prescribed drugs on the risk of a road traffic crash, using a large French nationwide database (PLoS Med 2010;7:e1000366). In the original case-control study, the authors analyzed each exposure separately. We use the lasso method, which can simultaneously perform estimation and variable selection in a single model. We compare point estimates and confidence intervals using (1) a separate logistic regression model for each drug with a Bonferroni correction and (2) lasso shrinkage logistic regression analysis. Shrinkage regression had little effect on (bias corrected) point estimates, but led to less conservative results, noticeably for drugs with moderate levels of exposure. Carbamates, carboxamide derivative and fatty acid derivative antiepileptics, drugs used in opioid dependence, and mineral supplements of potassium showed stronger associations. Lasso is a relevant method in the analysis of databases with large number of exposures and can be recommended as an alternative to conventional strategies.

Potential and Limitations of an Improved Method to Produce Dynamometric Wheels

PubMed Central

García de Jalón, Javier

2018-01-01

A new methodology for the estimation of tyre-contact forces is presented. The new procedure is an evolution of a previous method based on harmonic elimination techniques developed with the aim of producing low cost dynamometric wheels. While the original method required stress measurement in many rim radial lines and the fulfillment of some rigid conditions of symmetry, the new methodology described in this article significantly reduces the number of required measurement points and greatly relaxes symmetry constraints. This can be done without compromising the estimation error level. The reduction of the number of measuring radial lines increases the ripple of demodulated signals due to non-eliminated higher order harmonics. Therefore, it is necessary to adapt the calibration procedure to this new scenario. A new calibration procedure that takes into account angular position of the wheel is completely described. This new methodology is tested on a standard commercial five-spoke car wheel. Obtained results are qualitatively compared to those derived from the application of former methodology leading to the conclusion that the new method is both simpler and more robust due to the reduction in the number of measuring points, while contact forces’ estimation error remains at an acceptable level. PMID:29439427

Fitting ordinary differential equations to short time course data.

PubMed

Brewer, Daniel; Barenco, Martino; Callard, Robin; Hubank, Michael; Stark, Jaroslav

2008-02-28

Ordinary differential equations (ODEs) are widely used to model many systems in physics, chemistry, engineering and biology. Often one wants to compare such equations with observed time course data, and use this to estimate parameters. Surprisingly, practical algorithms for doing this are relatively poorly developed, particularly in comparison with the sophistication of numerical methods for solving both initial and boundary value problems for differential equations, and for locating and analysing bifurcations. A lack of good numerical fitting methods is particularly problematic in the context of systems biology where only a handful of time points may be available. In this paper, we present a survey of existing algorithms and describe the main approaches. We also introduce and evaluate a new efficient technique for estimating ODEs linear in parameters particularly suited to situations where noise levels are high and the number of data points is low. It employs a spline-based collocation scheme and alternates linear least squares minimization steps with repeated estimates of the noise-free values of the variables. This is reminiscent of expectation-maximization methods widely used for problems with nuisance parameters or missing data.

Efficient robust doubly adaptive regularized regression with applications.

PubMed

Karunamuni, Rohana J; Kong, Linglong; Tu, Wei

2018-01-01

We consider the problem of estimation and variable selection for general linear regression models. Regularized regression procedures have been widely used for variable selection, but most existing methods perform poorly in the presence of outliers. We construct a new penalized procedure that simultaneously attains full efficiency and maximum robustness. Furthermore, the proposed procedure satisfies the oracle properties. The new procedure is designed to achieve sparse and robust solutions by imposing adaptive weights on both the decision loss and the penalty function. The proposed method of estimation and variable selection attains full efficiency when the model is correct and, at the same time, achieves maximum robustness when outliers are present. We examine the robustness properties using the finite-sample breakdown point and an influence function. We show that the proposed estimator attains the maximum breakdown point. Furthermore, there is no loss in efficiency when there are no outliers or the error distribution is normal. For practical implementation of the proposed method, we present a computational algorithm. We examine the finite-sample and robustness properties using Monte Carlo studies. Two datasets are also analyzed.

A Point Kinetics Model for Estimating Neutron Multiplication of Bare Uranium Metal in Tagged Neutron Measurements

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

Tweardy, Matthew C.; McConchie, Seth; Hayward, Jason P.

An extension of the point kinetics model is developed in this paper to describe the neutron multiplicity response of a bare uranium object under interrogation by an associated particle imaging deuterium-tritium (D-T) measurement system. This extended model is used to estimate the total neutron multiplication of the uranium. Both MCNPX-PoliMi simulations and data from active interrogation measurements of highly enriched and depleted uranium geometries are used to evaluate the potential of this method and to identify the sources of systematic error. The detection efficiency correction for measured coincidence response is identified as a large source of systematic error. If themore » detection process is not considered, results suggest that the method can estimate total multiplication to within 13% of the simulated value. Values for multiplicity constants in the point kinetics equations are sensitive to enrichment due to (n, xn) interactions by D-T neutrons and can introduce another significant source of systematic bias. This can theoretically be corrected if isotopic composition is known a priori. Finally, the spatial dependence of multiplication is also suspected of introducing further systematic bias for high multiplication uranium objects.« less

A Point Kinetics Model for Estimating Neutron Multiplication of Bare Uranium Metal in Tagged Neutron Measurements

DOE PAGES

Tweardy, Matthew C.; McConchie, Seth; Hayward, Jason P.

2017-06-13

An extension of the point kinetics model is developed in this paper to describe the neutron multiplicity response of a bare uranium object under interrogation by an associated particle imaging deuterium-tritium (D-T) measurement system. This extended model is used to estimate the total neutron multiplication of the uranium. Both MCNPX-PoliMi simulations and data from active interrogation measurements of highly enriched and depleted uranium geometries are used to evaluate the potential of this method and to identify the sources of systematic error. The detection efficiency correction for measured coincidence response is identified as a large source of systematic error. If themore » detection process is not considered, results suggest that the method can estimate total multiplication to within 13% of the simulated value. Values for multiplicity constants in the point kinetics equations are sensitive to enrichment due to (n, xn) interactions by D-T neutrons and can introduce another significant source of systematic bias. This can theoretically be corrected if isotopic composition is known a priori. Finally, the spatial dependence of multiplication is also suspected of introducing further systematic bias for high multiplication uranium objects.« less

Computing travel time when the exact address is unknown: a comparison of point and polygon ZIP code approximation methods.

PubMed

Berke, Ethan M; Shi, Xun

2009-04-29

Travel time is an important metric of geographic access to health care. We compared strategies of estimating travel times when only subject ZIP code data were available. Using simulated data from New Hampshire and Arizona, we estimated travel times to nearest cancer centers by using: 1) geometric centroid of ZIP code polygons as origins, 2) population centroids as origin, 3) service area rings around each cancer center, assigning subjects to rings by assuming they are evenly distributed within their ZIP code, 4) service area rings around each center, assuming the subjects follow the population distribution within the ZIP code. We used travel times based on street addresses as true values to validate estimates. Population-based methods have smaller errors than geometry-based methods. Within categories (geometry or population), centroid and service area methods have similar errors. Errors are smaller in urban areas than in rural areas. Population-based methods are superior to the geometry-based methods, with the population centroid method appearing to be the best choice for estimating travel time. Estimates in rural areas are less reliable.

The small low SNR target tracking using sparse representation information

NASA Astrophysics Data System (ADS)

Yin, Lifan; Zhang, Yiqun; Wang, Shuo; Sun, Chenggang

2017-11-01

Tracking small targets, such as missile warheads, from a remote distance is a difficult task since the targets are "points" which are similar to sensor's noise points. As a result, traditional tracking algorithms only use the information contained in point measurement, such as the position information and intensity information, as characteristics to identify targets from noise points. But in fact, as a result of the diffusion of photon, any small target is not a point in the focal plane array and it occupies an area which is larger than one sensor cell. So, if we can take the geometry characteristic into account as a new dimension of information, it will be of helpful in distinguishing targets from noise points. In this paper, we use a novel method named sparse representation (SR) to depict the geometry information of target intensity and define it as the SR information of target. Modeling the intensity spread and solving its SR coefficients, the SR information is represented by establishing its likelihood function. Further, the SR information likelihood is incorporated in the conventional Probability Hypothesis Density (PHD) filter algorithm with point measurement. To illustrate the different performances of algorithm with or without the SR information, the detection capability and estimation error have been compared through simulation. Results demonstrate the proposed method has higher estimation accuracy and probability of detecting target than the conventional algorithm without the SR information.

Ex Post Facto Monte Carlo Variance Reduction

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

Booth, Thomas E.

The variance in Monte Carlo particle transport calculations is often dominated by a few particles whose importance increases manyfold on a single transport step. This paper describes a novel variance reduction method that uses a large importance change as a trigger to resample the offending transport step. That is, the method is employed only after (ex post facto) a random walk attempts a transport step that would otherwise introduce a large variance in the calculation.Improvements in two Monte Carlo transport calculations are demonstrated empirically using an ex post facto method. First, the method is shown to reduce the variance inmore » a penetration problem with a cross-section window. Second, the method empirically appears to modify a point detector estimator from an infinite variance estimator to a finite variance estimator.« less

Bone Pose Estimation in the Presence of Soft Tissue Artifact Using Triangular Cosserat Point Elements.

PubMed

Solav, Dana; Rubin, M B; Cereatti, Andrea; Camomilla, Valentina; Wolf, Alon

2016-04-01

Accurate estimation of the position and orientation (pose) of a bone from a cluster of skin markers is limited mostly by the relative motion between the bone and the markers, which is known as the soft tissue artifact (STA). This work presents a method, based on continuum mechanics, to describe the kinematics of a cluster affected by STA. The cluster is characterized by triangular cosserat point elements (TCPEs) defined by all combinations of three markers. The effects of the STA on the TCPEs are quantified using three parameters describing the strain in each TCPE and the relative rotation and translation between TCPEs. The method was evaluated using previously collected ex vivo kinematic data. Femur pose was estimated from 12 skin markers on the thigh, while its reference pose was measured using bone pins. Analysis revealed that instantaneous subsets of TCPEs exist which estimate bone position and orientation more accurately than the Procrustes Superimposition applied to the cluster of all markers. It has been shown that some of these parameters correlate well with femur pose errors, which suggests that they can be used to select, at each instant, subsets of TCPEs leading an improved estimation of the underlying bone pose.

Calculation of the ELISA's cut-off based on the change-point analysis method for detection of Trypanosoma cruzi infection in Bolivian dogs in the absence of controls.

PubMed

Lardeux, Frédéric; Torrico, Gino; Aliaga, Claudia

2016-07-04

In ELISAs, sera of individuals infected by Trypanosoma cruzi show absorbance values above a cut-off value. The cut-off is generally computed by means of formulas that need absorbance readings of negative (and sometimes positive) controls, which are included in the titer plates amongst the unknown samples. When no controls are available, other techniques should be employed such as change-point analysis. The method was applied to Bolivian dog sera processed by ELISA to diagnose T. cruzi infection. In each titer plate, the change-point analysis estimated a step point which correctly discriminated among known positive and known negative sera, unlike some of the six usual cut-off formulas tested. To analyse the ELISAs results, the change-point method was as good as the usual cut-off formula of the form "mean + 3 standard deviation of negative controls". Change-point analysis is therefore an efficient alternative method to analyse ELISA absorbance values when no controls are available.

Improving the blind restoration of retinal images by means of point-spread-function estimation assessment

NASA Astrophysics Data System (ADS)

Marrugo, Andrés. G.; Millán, María. S.; Å orel, Michal; Kotera, Jan; Å roubek, Filip

2015-01-01

Retinal images often suffer from blurring which hinders disease diagnosis and progression assessment. The restoration of the images is carried out by means of blind deconvolution, but the success of the restoration depends on the correct estimation of the point-spread-function (PSF) that blurred the image. The restoration can be space-invariant or space-variant. Because a retinal image has regions without texture or sharp edges, the blind PSF estimation may fail. In this paper we propose a strategy for the correct assessment of PSF estimation in retinal images for restoration by means of space-invariant or space-invariant blind deconvolution. Our method is based on a decomposition in Zernike coefficients of the estimated PSFs to identify valid PSFs. This significantly improves the quality of the image restoration revealed by the increased visibility of small details like small blood vessels and by the lack of restoration artifacts.

Automated Mounting Bias Calibration for Airborne LIDAR System

NASA Astrophysics Data System (ADS)

Zhang, J.; Jiang, W.; Jiang, S.

2012-07-01

Mounting bias is the major error source of Airborne LIDAR system. In this paper, an automated calibration method for estimating LIDAR system mounting parameters is introduced. LIDAR direct geo-referencing model is used to calculate systematic errors. Due to LIDAR footprints discretely sampled, the real corresponding laser points are hardly existence among different strips. The traditional corresponding point methodology does not seem to apply to LIDAR strip registration. We proposed a Virtual Corresponding Point Model to resolve the corresponding problem among discrete laser points. Each VCPM contains a corresponding point and three real laser footprints. Two rules are defined to calculate tie point coordinate from real laser footprints. The Scale Invariant Feature Transform (SIFT) is used to extract corresponding points in LIDAR strips, and the automatic flow of LIDAR system calibration based on VCPM is detailed described. The practical examples illustrate the feasibility and effectiveness of the proposed calibration method.

Toward a Value for Guided Rafting on Southern Rivers

Treesearch

J. Michael Bowker; Donald B.K. English; Jason A. Donovan

1996-01-01

This study examines per trip consumer surplus associated with guided whitewater rafting on two southern rivers. First, household recreation demand functions are estimated based on the individual travel cost model using truncated count data regression methods and alternative price specifications. Findings show mean per trip consumer surplus point estimates between $89...

Incorporating variability in point estimates in risk assessment: Bridging the gap between LC50 and population endpoints.

PubMed

Stark, John D; Vargas, Roger I; Banks, John E

2015-07-01

Historically, point estimates such as the median lethal concentration (LC50) have been instrumental in assessing risks associated with toxicants to rare or economically important species. In recent years, growing awareness of the shortcomings of this approach has led to an increased focus on analyses using population endpoints. However, risk assessment of pesticides still relies heavily on large amounts of LC50 data amassed over decades in the laboratory. Despite the fact that these data are generally well replicated, little or no attention has been given to the sometime high levels of variability associated with the generation of point estimates. This is especially important in agroecosystems where arthropod predator-prey interactions are often disrupted by the use of pesticides. Using laboratory derived data of 4 economically important species (2 fruit fly pest species and 2 braconid parasitoid species) and matrix based population models, the authors demonstrate in the present study a method for bridging traditional point estimate risk assessments with population outcomes. The results illustrate that even closely related species can show strikingly divergent responses to the same exposures to pesticides. Furthermore, the authors show that using different values within the 95% confidence intervals of LC50 values can result in very different population outcomes, ranging from quick recovery to extinction for both pest and parasitoid species. The authors discuss the implications of these results and emphasize the need to incorporate variability and uncertainty in point estimates for use in risk assessment. © 2015 SETAC.

Estimation of the latent mediated effect with ordinal data using the limited-information and Bayesian full-information approaches.

PubMed

Chen, Jinsong; Zhang, Dake; Choi, Jaehwa

2015-12-01

It is common to encounter latent variables with ordinal data in social or behavioral research. Although a mediated effect of latent variables (latent mediated effect, or LME) with ordinal data may appear to be a straightforward combination of LME with continuous data and latent variables with ordinal data, the methodological challenges to combine the two are not trivial. This research covers model structures as complex as LME and formulates both point and interval estimates of LME for ordinal data using the Bayesian full-information approach. We also combine weighted least squares (WLS) estimation with the bias-corrected bootstrapping (BCB; Efron Journal of the American Statistical Association, 82, 171-185, 1987) method or the traditional delta method as the limited-information approach. We evaluated the viability of these different approaches across various conditions through simulation studies, and provide an empirical example to illustrate the approaches. We found that the Bayesian approach with reasonably informative priors is preferred when both point and interval estimates are of interest and the sample size is 200 or above.

Robust Curb Detection with Fusion of 3D-Lidar and Camera Data

PubMed Central

Tan, Jun; Li, Jian; An, Xiangjing; He, Hangen

2014-01-01

Curb detection is an essential component of Autonomous Land Vehicles (ALV), especially important for safe driving in urban environments. In this paper, we propose a fusion-based curb detection method through exploiting 3D-Lidar and camera data. More specifically, we first fuse the sparse 3D-Lidar points and high-resolution camera images together to recover a dense depth image of the captured scene. Based on the recovered dense depth image, we propose a filter-based method to estimate the normal direction within the image. Then, by using the multi-scale normal patterns based on the curb's geometric property, curb point features fitting the patterns are detected in the normal image row by row. After that, we construct a Markov Chain to model the consistency of curb points which utilizes the continuous property of the curb, and thus the optimal curb path which links the curb points together can be efficiently estimated by dynamic programming. Finally, we perform post-processing operations to filter the outliers, parameterize the curbs and give the confidence scores on the detected curbs. Extensive evaluations clearly show that our proposed method can detect curbs with strong robustness at real-time speed for both static and dynamic scenes. PMID:24854364

Application of Acoustic and Optic Methods for Estimating Suspended-Solids Concentrations in the St. Lucie River Estuary, Florida

USGS Publications Warehouse

Patino, Eduardo; Byrne, Michael J.

2004-01-01

Acoustic and optic methods were applied to estimate suspended-solids concentrations in the St. Lucie River Estuary, southeastern Florida. Acoustic Doppler velocity meters were installed at the North Fork, Speedy Point, and Steele Point sites within the estuary. These sites provide varying flow, salinity, water-quality, and channel cross-sectional characteristics. The monitoring site at Steele Point was not used in the analyses because repeated instrument relocations (due to bridge construction) prevented a sufficient number of samples from being collected at the various locations. Acoustic and optic instruments were installed to collect water velocity, acoustic backscatter strength (ABS), and turbidity data that were used to assess the feasibility of estimating suspended-solids concentrations in the estuary. Other data collected at the monitoring sites include tidal stage, salinity, temperature, and periodic discharge measurements. Regression analyses were used to determine the relations of suspended-solids concentration to ABS and suspended-solids concentration to turbidity at the North Fork and Speedy Point sites. For samples used in regression analyses, measured suspended-solids concentrations at the North Fork and Speedy Point sites ranged from 3 to 37 milligrams per liter, and organic content ranged from 50 to 83 percent. Corresponding salinity for these samples ranged from 0.12 to 22.7 parts per thousand, and corresponding temperature ranged from 19.4 to 31.8 ?C. Relations determined using this technique are site specific and only describe suspended-solids concentrations at locations where data were collected. The suspended-solids concentration to ABS relation resulted in correlation coefficients of 0.78 and 0.63 at the North Fork and Speedy Point sites, respectively. The suspended-solids concentration to turbidity relation resulted in correlation coefficients of 0.73 and 0.89 at the North Fork and Speedy Point sites, respectively. The adequacy of the empirical equations seems to be limited by the number and distribution of suspended-solids samples collected throughout the expected concentration range at the North Fork and Speedy Point sites. Additionally, the ABS relations for both sites seem to overestimate at the low end and underestimate at the high end of the concentration range. Based on the sensitivity analysis, temperature had a greater effect than salinity on estimated suspended-solids concentrations. Temperature also appeared to affect ABS data, perhaps by changing the absorptive and reflective characteristics of the suspended material. Salinity and temperature had no observed effects on the turbidity relation at the North Fork and Speedy Point sites. Estimates of suspended-solids concentrations using ABS data were less 'erratic' than estimates using turbidity data. Combining ABS and turbidity data into one equation did not improve the accuracy of results, and therefore, was not considered.

Marker Registration Technique for Handwritten Text Marker in Augmented Reality Applications

NASA Astrophysics Data System (ADS)

Thanaborvornwiwat, N.; Patanukhom, K.

2018-04-01

Marker registration is a fundamental process to estimate camera poses in marker-based Augmented Reality (AR) systems. We developed AR system that creates correspondence virtual objects on handwritten text markers. This paper presents a new method for registration that is robust for low-content text markers, variation of camera poses, and variation of handwritten styles. The proposed method uses Maximally Stable Extremal Regions (MSER) and polygon simplification for a feature point extraction. The experiment shows that we need to extract only five feature points per image which can provide the best registration results. An exhaustive search is used to find the best matching pattern of the feature points in two images. We also compared performance of the proposed method to some existing registration methods and found that the proposed method can provide better accuracy and time efficiency.

Automatic registration of fused lidar/digital imagery (texel images) for three-dimensional image creation

NASA Astrophysics Data System (ADS)

Budge, Scott E.; Badamikar, Neeraj S.; Xie, Xuan

2015-03-01

Several photogrammetry-based methods have been proposed that the derive three-dimensional (3-D) information from digital images from different perspectives, and lidar-based methods have been proposed that merge lidar point clouds and texture the merged point clouds with digital imagery. Image registration alone has difficulty with smooth regions with low contrast, whereas point cloud merging alone has difficulty with outliers and a lack of proper convergence in the merging process. This paper presents a method to create 3-D images that uses the unique properties of texel images (pixel-fused lidar and digital imagery) to improve the quality and robustness of fused 3-D images. The proposed method uses both image processing and point-cloud merging to combine texel images in an iterative technique. Since the digital image pixels and the lidar 3-D points are fused at the sensor level, more accurate 3-D images are generated because registration of image data automatically improves the merging of the point clouds, and vice versa. Examples illustrate the value of this method over other methods. The proposed method also includes modifications for the situation where an estimate of position and attitude of the sensor is known, when obtained from low-cost global positioning systems and inertial measurement units sensors.

Sparse Unorganized Point Cloud Based Relative Pose Estimation for Uncooperative Space Target.

PubMed

Yin, Fang; Chou, Wusheng; Wu, Yun; Yang, Guang; Xu, Song

2018-03-28

This paper proposes an autonomous algorithm to determine the relative pose between the chaser spacecraft and the uncooperative space target, which is essential in advanced space applications, e.g., on-orbit serving missions. The proposed method, named Congruent Tetrahedron Align (CTA) algorithm, uses the very sparse unorganized 3D point cloud acquired by a LIDAR sensor, and does not require any prior pose information. The core of the method is to determine the relative pose by looking for the congruent tetrahedron in scanning point cloud and model point cloud on the basis of its known model. The two-level index hash table is built for speeding up the search speed. In addition, the Iterative Closest Point (ICP) algorithm is used for pose tracking after CTA. In order to evaluate the method in arbitrary initial attitude, a simulated system is presented. Specifically, the performance of the proposed method to provide the initial pose needed for the tracking algorithm is demonstrated, as well as their robustness against noise. Finally, a field experiment is conducted and the results demonstrated the effectiveness of the proposed method.

Sparse Unorganized Point Cloud Based Relative Pose Estimation for Uncooperative Space Target

PubMed Central

Chou, Wusheng; Wu, Yun; Yang, Guang; Xu, Song

2018-01-01

This paper proposes an autonomous algorithm to determine the relative pose between the chaser spacecraft and the uncooperative space target, which is essential in advanced space applications, e.g., on-orbit serving missions. The proposed method, named Congruent Tetrahedron Align (CTA) algorithm, uses the very sparse unorganized 3D point cloud acquired by a LIDAR sensor, and does not require any prior pose information. The core of the method is to determine the relative pose by looking for the congruent tetrahedron in scanning point cloud and model point cloud on the basis of its known model. The two-level index hash table is built for speeding up the search speed. In addition, the Iterative Closest Point (ICP) algorithm is used for pose tracking after CTA. In order to evaluate the method in arbitrary initial attitude, a simulated system is presented. Specifically, the performance of the proposed method to provide the initial pose needed for the tracking algorithm is demonstrated, as well as their robustness against noise. Finally, a field experiment is conducted and the results demonstrated the effectiveness of the proposed method. PMID:29597323

Variation of ultrasound image lateral spectrum with assumed speed of sound and true scatterer density.

PubMed

Gyöngy, Miklós; Kollár, Sára

2015-02-01

One method of estimating sound speed in diagnostic ultrasound imaging consists of choosing the speed of sound that generates the sharpest image, as evaluated by the lateral frequency spectrum of the squared B-mode image. In the current work, simulated and experimental data on a typical (47 mm aperture, 3.3-10.0 MHz response) linear array transducer are used to investigate the accuracy of this method. A range of candidate speeds of sound (1240-1740 m/s) was used, with a true speed of sound of 1490 m/s in simulations and 1488 m/s in experiments. Simulations of single point scatterers and two interfering point scatterers at various locations with respect to each other gave estimate errors of 0.0-2.0%. Simulations and experiments of scatterer distributions with a mean scatterer spacing of at least 0.5 mm gave estimate errors of 0.1-4.0%. In the case of lower scatterer spacing, the speed of sound estimates become unreliable due to a decrease in contrast of the sharpness measure between different candidate speeds of sound. This suggests that in estimating speed of sound in tissue, the region of interest should be dominated by a few, sparsely spaced scatterers. Conversely, the decreasing sensitivity of the sharpness measure to speed of sound errors for higher scatterer concentrations suggests a potential method for estimating mean scatterer spacing. Copyright © 2014 Elsevier B.V. All rights reserved.

Rainfall Observed Over Bangladesh 2000-2008: A Comparison of Spatial Interpolation Methods

NASA Astrophysics Data System (ADS)

Pervez, M.; Henebry, G. M.

2010-12-01

In preparation for a hydrometeorological study of freshwater resources in the greater Ganges-Brahmaputra region, we compared the results of four methods of spatial interpolation applied to point measurements of daily rainfall over Bangladesh during a seven year period (2000-2008). Two univariate (inverse distance weighted and spline-regularized and tension) and two multivariate geostatistical (ordinary kriging and kriging with external drift) methods were used to interpolate daily observations from a network of 221 rain gauges across Bangladesh spanning an area of 143,000 sq km. Elevation and topographic index were used as the covariates in the geostatistical methods. The validity of the interpolated maps was analyzed through cross-validation. The quality of the methods was assessed through the Pearson and Spearman correlations and root mean square error measurements of accuracy in cross-validation. Preliminary results indicated that the univariate methods performed better than the geostatistical methods at daily scales, likely due to the relatively dense sampled point measurements and a weak correlation between the rainfall and covariates at daily scales in this region. Inverse distance weighted produced the better results than the spline. For the days with extreme or high rainfall—spatially and quantitatively—the correlation between observed and interpolated estimates appeared to be high (r2 ~ 0.6 RMSE ~ 10mm), although for low rainfall days the correlations were poor (r2 ~ 0.1 RMSE ~ 3mm). The performance quality of these methods was influenced by the density of the sample point measurements, the quantity of the observed rainfall along with spatial extent, and an appropriate search radius defining the neighboring points. Results indicated that interpolated rainfall estimates at daily scales may introduce uncertainties in the successive hydrometeorological analysis. Interpolations at 5-day, 10-day, 15-day, and monthly time scales are currently under investigation.

Estimation of regionalized compositions: A comparison of three methods

USGS Publications Warehouse

Pawlowsky, V.; Olea, R.A.; Davis, J.C.

1995-01-01

A regionalized composition is a random vector function whose components are positive and sum to a constant at every point of the sampling region. Consequently, the components of a regionalized composition are necessarily spatially correlated. This spatial dependence-induced by the constant sum constraint-is a spurious spatial correlation and may lead to misinterpretations of statistical analyses. Furthermore, the cross-covariance matrices of the regionalized composition are singular, as is the coefficient matrix of the cokriging system of equations. Three methods of performing estimation or prediction of a regionalized composition at unsampled points are discussed: (1) the direct approach of estimating each variable separately; (2) the basis method, which is applicable only when a random function is available that can he regarded as the size of the regionalized composition under study; (3) the logratio approach, using the additive-log-ratio transformation proposed by J. Aitchison, which allows statistical analysis of compositional data. We present a brief theoretical review of these three methods and compare them using compositional data from the Lyons West Oil Field in Kansas (USA). It is shown that, although there are no important numerical differences, the direct approach leads to invalid results, whereas the basis method and the additive-log-ratio approach are comparable. ?? 1995 International Association for Mathematical Geology.

The algorithm of fast image stitching based on multi-feature extraction

NASA Astrophysics Data System (ADS)

Yang, Chunde; Wu, Ge; Shi, Jing

2018-05-01

This paper proposed an improved image registration method combining Hu-based invariant moment contour information and feature points detection, aiming to solve the problems in traditional image stitching algorithm, such as time-consuming feature points extraction process, redundant invalid information overload and inefficiency. First, use the neighborhood of pixels to extract the contour information, employing the Hu invariant moment as similarity measure to extract SIFT feature points in those similar regions. Then replace the Euclidean distance with Hellinger kernel function to improve the initial matching efficiency and get less mismatching points, further, estimate affine transformation matrix between the images. Finally, local color mapping method is adopted to solve uneven exposure, using the improved multiresolution fusion algorithm to fuse the mosaic images and realize seamless stitching. Experimental results confirm high accuracy and efficiency of method proposed in this paper.

Child Mortality Estimation 2013: An Overview of Updates in Estimation Methods by the United Nations Inter-Agency Group for Child Mortality Estimation

PubMed Central

Alkema, Leontine; New, Jin Rou; Pedersen, Jon; You, Danzhen

2014-01-01

Background In September 2013, the United Nations Inter-agency Group for Child Mortality Estimation (UN IGME) published an update of the estimates of the under-five mortality rate (U5MR) and under-five deaths for all countries. Compared to the UN IGME estimates published in 2012, updated data inputs and a new method for estimating the U5MR were used. Methods We summarize the new U5MR estimation method, which is a Bayesian B-spline Bias-reduction model, and highlight differences with the previously used method. Differences in UN IGME U5MR estimates as published in 2012 and those published in 2013 are presented and decomposed into differences due to the updated database and differences due to the new estimation method to explain and motivate changes in estimates. Findings Compared to the previously used method, the new UN IGME estimation method is based on a different trend fitting method that can track (recent) changes in U5MR more closely. The new method provides U5MR estimates that account for data quality issues. Resulting differences in U5MR point estimates between the UN IGME 2012 and 2013 publications are small for the majority of countries but greater than 10 deaths per 1,000 live births for 33 countries in 2011 and 19 countries in 1990. These differences can be explained by the updated database used, the curve fitting method as well as accounting for data quality issues. Changes in the number of deaths were less than 10% on the global level and for the majority of MDG regions. Conclusions The 2013 UN IGME estimates provide the most recent assessment of levels and trends in U5MR based on all available data and an improved estimation method that allows for closer-to-real-time monitoring of changes in the U5MR and takes account of data quality issues. PMID:25013954

Multivariate Meta-Analysis of Genetic Association Studies: A Simulation Study

PubMed Central

Neupane, Binod; Beyene, Joseph

2015-01-01

In a meta-analysis with multiple end points of interests that are correlated between or within studies, multivariate approach to meta-analysis has a potential to produce more precise estimates of effects by exploiting the correlation structure between end points. However, under random-effects assumption the multivariate estimation is more complex (as it involves estimation of more parameters simultaneously) than univariate estimation, and sometimes can produce unrealistic parameter estimates. Usefulness of multivariate approach to meta-analysis of the effects of a genetic variant on two or more correlated traits is not well understood in the area of genetic association studies. In such studies, genetic variants are expected to roughly maintain Hardy-Weinberg equilibrium within studies, and also their effects on complex traits are generally very small to modest and could be heterogeneous across studies for genuine reasons. We carried out extensive simulation to explore the comparative performance of multivariate approach with most commonly used univariate inverse-variance weighted approach under random-effects assumption in various realistic meta-analytic scenarios of genetic association studies of correlated end points. We evaluated the performance with respect to relative mean bias percentage, and root mean square error (RMSE) of the estimate and coverage probability of corresponding 95% confidence interval of the effect for each end point. Our simulation results suggest that multivariate approach performs similarly or better than univariate method when correlations between end points within or between studies are at least moderate and between-study variation is similar or larger than average within-study variation for meta-analyses of 10 or more genetic studies. Multivariate approach produces estimates with smaller bias and RMSE especially for the end point that has randomly or informatively missing summary data in some individual studies, when the missing data in the endpoint are imputed with null effects and quite large variance. PMID:26196398

Multivariate Meta-Analysis of Genetic Association Studies: A Simulation Study.

PubMed

Neupane, Binod; Beyene, Joseph

2015-01-01

In a meta-analysis with multiple end points of interests that are correlated between or within studies, multivariate approach to meta-analysis has a potential to produce more precise estimates of effects by exploiting the correlation structure between end points. However, under random-effects assumption the multivariate estimation is more complex (as it involves estimation of more parameters simultaneously) than univariate estimation, and sometimes can produce unrealistic parameter estimates. Usefulness of multivariate approach to meta-analysis of the effects of a genetic variant on two or more correlated traits is not well understood in the area of genetic association studies. In such studies, genetic variants are expected to roughly maintain Hardy-Weinberg equilibrium within studies, and also their effects on complex traits are generally very small to modest and could be heterogeneous across studies for genuine reasons. We carried out extensive simulation to explore the comparative performance of multivariate approach with most commonly used univariate inverse-variance weighted approach under random-effects assumption in various realistic meta-analytic scenarios of genetic association studies of correlated end points. We evaluated the performance with respect to relative mean bias percentage, and root mean square error (RMSE) of the estimate and coverage probability of corresponding 95% confidence interval of the effect for each end point. Our simulation results suggest that multivariate approach performs similarly or better than univariate method when correlations between end points within or between studies are at least moderate and between-study variation is similar or larger than average within-study variation for meta-analyses of 10 or more genetic studies. Multivariate approach produces estimates with smaller bias and RMSE especially for the end point that has randomly or informatively missing summary data in some individual studies, when the missing data in the endpoint are imputed with null effects and quite large variance.

Estimation of the displacements among distant events based on parallel tracking of events in seismic traces under uncertainty

NASA Astrophysics Data System (ADS)

Huamán Bustamante, Samuel G.; Cavalcanti Pacheco, Marco A.; Lazo Lazo, Juan G.

2018-07-01

The method we propose in this paper seeks to estimate interface displacements among strata related with reflection seismic events, in comparison to the interfaces at other reference points. To do so, we search for reflection events in the reference point of a second seismic trace taken from the same 3D survey and close to a well. However, the nature of the seismic data introduces uncertainty in the results. Therefore, we perform an uncertainty analysis using the standard deviation results from several experiments with cross-correlation of signals. To estimate the displacements of events in depth between two seismic traces, we create a synthetic seismic trace with an empirical wavelet and the sonic log of the well, close to the second seismic trace. Then, we relate the events of the seismic traces to the depth of the sonic log. Finally, we test the method with data from the Namorado Field in Brazil. The results show that the accuracy of the event estimated depth depends on the results of parallel cross-correlation, primarily those from the procedures used in the integration of seismic data with data from the well. The proposed approach can correctly identify several similar events in two seismic traces without requiring all seismic traces between two distant points of interest to correlate strata in the subsurface.

Hierarchical and symmetric infant image registration by robust longitudinal-example-guided correspondence detection

PubMed Central

Wu, Yao; Wu, Guorong; Wang, Li; Munsell, Brent C.; Wang, Qian; Lin, Weili; Feng, Qianjin; Chen, Wufan; Shen, Dinggang

2015-01-01

Purpose: To investigate anatomical differences across individual subjects, or longitudinal changes in early brain development, it is important to perform accurate image registration. However, due to fast brain development and dynamic tissue appearance changes, it is very difficult to align infant brain images acquired from birth to 1-yr-old. Methods: To solve this challenging problem, a novel image registration method is proposed to align two infant brain images, regardless of age at acquisition. The main idea is to utilize the growth trajectories, or spatial-temporal correspondences, learned from a set of longitudinal training images, for guiding the registration of two different time-point images with different image appearances. Specifically, in the training stage, an intrinsic growth trajectory is first estimated for each training subject using the longitudinal images. To register two new infant images with potentially a large age gap, the corresponding images patches between each new image and its respective training images with similar age are identified. Finally, the registration between the two new images can be assisted by the learned growth trajectories from one time point to another time point that have been established in the training stage. To further improve registration accuracy, the proposed method is combined with a hierarchical and symmetric registration framework that can iteratively add new key points in both images to steer the estimation of the deformation between the two infant brain images under registration. Results: To evaluate image registration accuracy, the proposed method is used to align 24 infant subjects at five different time points (2-week-old, 3-month-old, 6-month-old, 9-month-old, and 12-month-old). Compared to the state-of-the-art methods, the proposed method demonstrated superior registration performance. Conclusions: The proposed method addresses the difficulties in the infant brain registration and produces better results compared to existing state-of-the-art registration methods. PMID:26133617

Adaptive Localization of Focus Point Regions via Random Patch Probabilistic Density from Whole-Slide, Ki-67-Stained Brain Tumor Tissue

PubMed Central

Alomari, Yazan M.; MdZin, Reena Rahayu

2015-01-01

Analysis of whole-slide tissue for digital pathology images has been clinically approved to provide a second opinion to pathologists. Localization of focus points from Ki-67-stained histopathology whole-slide tissue microscopic images is considered the first step in the process of proliferation rate estimation. Pathologists use eye pooling or eagle-view techniques to localize the highly stained cell-concentrated regions from the whole slide under microscope, which is called focus-point regions. This procedure leads to a high variety of interpersonal observations and time consuming, tedious work and causes inaccurate findings. The localization of focus-point regions can be addressed as a clustering problem. This paper aims to automate the localization of focus-point regions from whole-slide images using the random patch probabilistic density method. Unlike other clustering methods, random patch probabilistic density method can adaptively localize focus-point regions without predetermining the number of clusters. The proposed method was compared with the k-means and fuzzy c-means clustering methods. Our proposed method achieves a good performance, when the results were evaluated by three expert pathologists. The proposed method achieves an average false-positive rate of 0.84% for the focus-point region localization error. Moreover, regarding RPPD used to localize tissue from whole-slide images, 228 whole-slide images have been tested; 97.3% localization accuracy was achieved. PMID:25793010

A diffusion tensor imaging tractography algorithm based on Navier-Stokes fluid mechanics.

PubMed

Hageman, Nathan S; Toga, Arthur W; Narr, Katherine L; Shattuck, David W

2009-03-01

We introduce a fluid mechanics based tractography method for estimating the most likely connection paths between points in diffusion tensor imaging (DTI) volumes. We customize the Navier-Stokes equations to include information from the diffusion tensor and simulate an artificial fluid flow through the DTI image volume. We then estimate the most likely connection paths between points in the DTI volume using a metric derived from the fluid velocity vector field. We validate our algorithm using digital DTI phantoms based on a helical shape. Our method segmented the structure of the phantom with less distortion than was produced using implementations of heat-based partial differential equation (PDE) and streamline based methods. In addition, our method was able to successfully segment divergent and crossing fiber geometries, closely following the ideal path through a digital helical phantom in the presence of multiple crossing tracts. To assess the performance of our algorithm on anatomical data, we applied our method to DTI volumes from normal human subjects. Our method produced paths that were consistent with both known anatomy and directionally encoded color images of the DTI dataset.

A Diffusion Tensor Imaging Tractography Algorithm Based on Navier-Stokes Fluid Mechanics

PubMed Central

Hageman, Nathan S.; Toga, Arthur W.; Narr, Katherine; Shattuck, David W.

2009-01-01

We introduce a fluid mechanics based tractography method for estimating the most likely connection paths between points in diffusion tensor imaging (DTI) volumes. We customize the Navier-Stokes equations to include information from the diffusion tensor and simulate an artificial fluid flow through the DTI image volume. We then estimate the most likely connection paths between points in the DTI volume using a metric derived from the fluid velocity vector field. We validate our algorithm using digital DTI phantoms based on a helical shape. Our method segmented the structure of the phantom with less distortion than was produced using implementations of heat-based partial differential equation (PDE) and streamline based methods. In addition, our method was able to successfully segment divergent and crossing fiber geometries, closely following the ideal path through a digital helical phantom in the presence of multiple crossing tracts. To assess the performance of our algorithm on anatomical data, we applied our method to DTI volumes from normal human subjects. Our method produced paths that were consistent with both known anatomy and directionally encoded color (DEC) images of the DTI dataset. PMID:19244007

A robust method of thin plate spline and its application to DEM construction

NASA Astrophysics Data System (ADS)

Chen, Chuanfa; Li, Yanyan

2012-11-01

In order to avoid the ill-conditioning problem of thin plate spline (TPS), the orthogonal least squares (OLS) method was introduced, and a modified OLS (MOLS) was developed. The MOLS of TPS (TPS-M) can not only select significant points, termed knots, from large and dense sampling data sets, but also easily compute the weights of the knots in terms of back-substitution. For interpolating large sampling points, we developed a local TPS-M, where some neighbor sampling points around the point being estimated are selected for computation. Numerical tests indicate that irrespective of sampling noise level, the average performance of TPS-M can advantage with smoothing TPS. Under the same simulation accuracy, the computational time of TPS-M decreases with the increase of the number of sampling points. The smooth fitting results on lidar-derived noise data indicate that TPS-M has an obvious smoothing effect, which is on par with smoothing TPS. The example of constructing a series of large scale DEMs, located in Shandong province, China, was employed to comparatively analyze the estimation accuracies of the two versions of TPS and the classical interpolation methods including inverse distance weighting (IDW), ordinary kriging (OK) and universal kriging with the second-order drift function (UK). Results show that regardless of sampling interval and spatial resolution, TPS-M is more accurate than the classical interpolation methods, except for the smoothing TPS at the finest sampling interval of 20 m, and the two versions of kriging at the spatial resolution of 15 m. In conclusion, TPS-M, which avoids the ill-conditioning problem, is considered as a robust method for DEM construction.

Population trends, survival, and sampling methodologies for a population of Rana draytonii

USGS Publications Warehouse

Fellers, Gary M.; Kleeman, Patrick M.; Miller, David A.W.; Halstead, Brian J.

2017-01-01

Estimating population trends provides valuable information for resource managers, but monitoring programs face trade-offs between the quality and quantity of information gained and the number of sites surveyed. We compared the effectiveness of monitoring techniques for estimating population trends of Rana draytonii (California Red-legged Frog) at Point Reyes National Seashore, California, USA, over a 13-yr period. Our primary goals were to: 1) estimate trends for a focal pond at Point Reyes National Seashore, and 2) evaluate whether egg mass counts could reliably estimate an index of abundance relative to more-intensive capture–mark–recapture methods. Capture–mark–recapture (CMR) surveys of males indicated a stable population from 2005 to 2009, despite low annual apparent survival (26.3%). Egg mass counts from 2000 to 2012 indicated that despite some large fluctuations, the breeding female population was generally stable or increasing, with annual abundance varying between 26 and 130 individuals. Minor modifications to egg mass counts, such as marking egg masses, can allow estimation of egg mass detection probabilities necessary to convert counts to abundance estimates, even when closure of egg mass abundance cannot be assumed within a breeding season. High egg mass detection probabilities (mean per-survey detection probability = 0.98 [0.89–0.99]) indicate that egg mass surveys can be an efficient and reliable method for monitoring population trends of federally threatened R. draytonii. Combining egg mass surveys to estimate trends at many sites with CMR methods to evaluate factors affecting adult survival at focal populations is likely a profitable path forward to enhance understanding and conservation of R. draytonii.

How Affiliation Disclosure and Control Over User-Generated Comments Affects Consumer Health Knowledge and Behavior: A Randomized Controlled Experiment of Pharmaceutical Direct-to-Consumer Advertising on Social Media

PubMed Central

Vendemia, Megan Ashley

2016-01-01

Background More people are seeking health information online than ever before and pharmaceutical companies are increasingly marketing their drugs through social media. Objective The aim was to examine two major concerns related to online direct-to-consumer pharmaceutical advertising: (1) how disclosing an affiliation with a pharmaceutical company affects how people respond to drug information produced by both health organizations and online commenters, and (2) how knowledge that health organizations control the display of user-generated comments affects consumer health knowledge and behavior. Methods We conducted a 2×2×2 between-subjects experiment (N=674). All participants viewed an infographic posted to Facebook by a health organization about a prescription allergy drug. Across conditions, the infographic varied in the degree to which the health organization and commenters appeared to be affiliated with a drug manufacturer, and the display of user-generated comments appeared to be controlled. Results Affiliation disclosure statements on a health organization’s Facebook post increased perceptions of an organization-drug manufacturer connection, which reduced trust in the organization (point estimate –0.45, 95% CI –0.69 to –0.24) and other users who posted comments about the drug (point estimate –0.44, 95% CI –0.68 to –0.22). Furthermore, increased perceptions of an organization-manufacturer connection reduced the likelihood that people would recommend the drug to important others (point estimate –0.35, 95% CI –0.59 to –0.15), and share the drug post with others on Facebook (point estimate –0.37, 95% CI –0.64 to –0.16). An affiliation cue next to the commenters' names increased perceptions that the commenters were affiliated with the drug manufacturer, which reduced trust in the comments (point estimate –0.81, 95% CI –1.04 to –0.59), the organization that made the post (point estimate –0.68, 95% CI –0.90 to –0.49), the likelihood of participants recommending the drug (point estimate –0.61, 95% CI –0.82 to –0.43), and sharing the post with others on Facebook (point estimate –0.63, 95% CI –0.87 to –0.43). Cues indicating that a health organization removed user-generated comments from a post increased perceptions that the drug manufacturer influenced the display of the comments, which negatively affected trust in the comments (point estimate –0.35, 95% CI –0.53 to –0.20), the organization (point estimate –0.31, 95% CI –0.47 to –0.17), the likelihood of recommending the drug (point estimate –0.26, 95% CI –0.41 to –0.14), and the likelihood of sharing the post with others on Facebook (point estimate –0.28, 95% CI –0.45 to –0.15). (All estimates are unstandardized indirect effects and 95% bias-corrected bootstrap confidence intervals.) Conclusions Concern over pharmaceutical companies hiding their affiliations and strategically controlling user-generated comments is well founded; these practices can greatly affect not only how viewers evaluate drug information online, but also how likely they are to propagate the information throughout their online and offline social networks. PMID:27435883

Rapid 3D Reconstruction for Image Sequence Acquired from UAV Camera

PubMed Central

Qu, Yufu; Huang, Jianyu; Zhang, Xuan

2018-01-01

In order to reconstruct three-dimensional (3D) structures from an image sequence captured by unmanned aerial vehicles’ camera (UAVs) and improve the processing speed, we propose a rapid 3D reconstruction method that is based on an image queue, considering the continuity and relevance of UAV camera images. The proposed approach first compresses the feature points of each image into three principal component points by using the principal component analysis method. In order to select the key images suitable for 3D reconstruction, the principal component points are used to estimate the interrelationships between images. Second, these key images are inserted into a fixed-length image queue. The positions and orientations of the images are calculated, and the 3D coordinates of the feature points are estimated using weighted bundle adjustment. With this structural information, the depth maps of these images can be calculated. Next, we update the image queue by deleting some of the old images and inserting some new images into the queue, and a structural calculation of all the images can be performed by repeating the previous steps. Finally, a dense 3D point cloud can be obtained using the depth–map fusion method. The experimental results indicate that when the texture of the images is complex and the number of images exceeds 100, the proposed method can improve the calculation speed by more than a factor of four with almost no loss of precision. Furthermore, as the number of images increases, the improvement in the calculation speed will become more noticeable. PMID:29342908

Rapid 3D Reconstruction for Image Sequence Acquired from UAV Camera.

PubMed

Qu, Yufu; Huang, Jianyu; Zhang, Xuan

2018-01-14

In order to reconstruct three-dimensional (3D) structures from an image sequence captured by unmanned aerial vehicles' camera (UAVs) and improve the processing speed, we propose a rapid 3D reconstruction method that is based on an image queue, considering the continuity and relevance of UAV camera images. The proposed approach first compresses the feature points of each image into three principal component points by using the principal component analysis method. In order to select the key images suitable for 3D reconstruction, the principal component points are used to estimate the interrelationships between images. Second, these key images are inserted into a fixed-length image queue. The positions and orientations of the images are calculated, and the 3D coordinates of the feature points are estimated using weighted bundle adjustment. With this structural information, the depth maps of these images can be calculated. Next, we update the image queue by deleting some of the old images and inserting some new images into the queue, and a structural calculation of all the images can be performed by repeating the previous steps. Finally, a dense 3D point cloud can be obtained using the depth-map fusion method. The experimental results indicate that when the texture of the images is complex and the number of images exceeds 100, the proposed method can improve the calculation speed by more than a factor of four with almost no loss of precision. Furthermore, as the number of images increases, the improvement in the calculation speed will become more noticeable.

Use of petroleum-based correlations and estimation methods for synthetic fuels

NASA Technical Reports Server (NTRS)

Antoine, A. C.

1980-01-01

Correlations of hydrogen content with aromatics content, heat of combustion, and smoke point are derived for some synthetic fuels prepared from oil and coal syncrudes. Comparing the results of the aromatics content with correlations derived for petroleum fuels shows that the shale-derived fuels fit the petroleum-based correlations, but the coal-derived fuels do not. The correlations derived for heat of combustion and smoke point are comparable to some found for petroleum-based correlations. Calculated values of hydrogen content and of heat of combustion are obtained for the synthetic fuels by use of ASTM estimation methods. Comparisons of the measured and calculated values show biases in the equations that exceed the critical statistics values. Comparison of the measured hydrogen content by the standard ASTM combustion method with that by a nuclear magnetic resonance (NMR) method shows a decided bias. The comparison of the calculated and measured NMR hydrogen contents shows a difference similar to that found with petroleum fuels.

Convergence results for pseudospectral approximations of hyperbolic systems by a penalty type boundary treatment

NASA Technical Reports Server (NTRS)

Funaro, Daniele; Gottlieb, David

1989-01-01

A new method of imposing boundary conditions in the pseudospectral approximation of hyperbolic systems of equations is proposed. It is suggested to collocate the equations, not only at the inner grid points, but also at the boundary points and use the boundary conditions as penalty terms. In the pseudo-spectral Legrendre method with the new boundary treatment, a stability analysis for the case of a constant coefficient hyperbolic system is presented and error estimates are derived.

Low cost, microcontroller based heating device for multi-wavelength differential scanning fluorimetry.

PubMed

Hoeser, Jo; Gnandt, Emmanuel; Friedrich, Thorsten

2018-01-23

Differential scanning fluorimetry is a popular method to estimate the stability of a protein in distinct buffer conditions by determining its 'melting point'. The method requires a temperature controlled fluorescence spectrometer or a RT-PCR machine. Here, we introduce a low-budget version of a microcontroller based heating device implemented into a 96-well plate reader that is connected to a standard fluorescence spectrometer. We demonstrate its potential to determine the 'melting point' of soluble and membranous proteins at various buffer conditions.

The Bassi Rebay 1 scheme is a special case of the Symmetric Interior Penalty formulation for discontinuous Galerkin discretisations with Gauss-Lobatto points

NASA Astrophysics Data System (ADS)

Manzanero, Juan; Rueda-Ramírez, Andrés M.; Rubio, Gonzalo; Ferrer, Esteban

2018-06-01

In the discontinuous Galerkin (DG) community, several formulations have been proposed to solve PDEs involving second-order spatial derivatives (e.g. elliptic problems). In this paper, we show that, when the discretisation is restricted to the usage of Gauss-Lobatto points, there are important similarities between two common choices: the Bassi-Rebay 1 (BR1) method, and the Symmetric Interior Penalty (SIP) formulation. This equivalence enables the extrapolation of properties from one scheme to the other: a sharper estimation of the minimum penalty parameter for the SIP stability (compared to the more general estimate proposed by Shahbazi [1]), more efficient implementations of the BR1 scheme, and the compactness of the BR1 method for straight quadrilateral and hexahedral meshes.

Network Reconstruction From High-Dimensional Ordinary Differential Equations.

PubMed

Chen, Shizhe; Shojaie, Ali; Witten, Daniela M

2017-01-01

We consider the task of learning a dynamical system from high-dimensional time-course data. For instance, we might wish to estimate a gene regulatory network from gene expression data measured at discrete time points. We model the dynamical system nonparametrically as a system of additive ordinary differential equations. Most existing methods for parameter estimation in ordinary differential equations estimate the derivatives from noisy observations. This is known to be challenging and inefficient. We propose a novel approach that does not involve derivative estimation. We show that the proposed method can consistently recover the true network structure even in high dimensions, and we demonstrate empirical improvement over competing approaches. Supplementary materials for this article are available online.

A New Method to Compare Statistical Tree Growth Curves: The PL-GMANOVA Model and Its Application with Dendrochronological Data

PubMed Central

Ricker, Martin; Peña Ramírez, Víctor M.; von Rosen, Dietrich

2014-01-01

Growth curves are monotonically increasing functions that measure repeatedly the same subjects over time. The classical growth curve model in the statistical literature is the Generalized Multivariate Analysis of Variance (GMANOVA) model. In order to model the tree trunk radius (r) over time (t) of trees on different sites, GMANOVA is combined here with the adapted PL regression model Q = A·T+E, where for and for , A =  initial relative growth to be estimated, , and E is an error term for each tree and time point. Furthermore, Ei[–b·r]  = , , with TPR being the turning point radius in a sigmoid curve, and at is an estimated calibrating time-radius point. Advantages of the approach are that growth rates can be compared among growth curves with different turning point radiuses and different starting points, hidden outliers are easily detectable, the method is statistically robust, and heteroscedasticity of the residuals among time points is allowed. The model was implemented with dendrochronological data of 235 Pinus montezumae trees on ten Mexican volcano sites to calculate comparison intervals for the estimated initial relative growth . One site (at the Popocatépetl volcano) stood out, with being 3.9 times the value of the site with the slowest-growing trees. Calculating variance components for the initial relative growth, 34% of the growth variation was found among sites, 31% among trees, and 35% over time. Without the Popocatépetl site, the numbers changed to 7%, 42%, and 51%. Further explanation of differences in growth would need to focus on factors that vary within sites and over time. PMID:25402427

Terrain shape estimation from optical flow, using Kalman filtering

NASA Astrophysics Data System (ADS)

Hoff, William A.; Sklair, Cheryl W.

1990-01-01

As one moves through a static environment, the visual world as projected on the retina seems to flow past. This apparent motion, called optical flow, can be an important source of depth perception for autonomous robots. An important application is in planetary exploration -the landing vehicle must find a safe landing site in rugged terrain, and an autonomous rover must be able to navigate safely through this terrain. In this paper, we describe a solution to this problem. Image edge points are tracked between frames of a motion sequence, and the range to the points is calculated from the displacement of the edge points and the known motion of the camera. Kalman filtering is used to incrementally improve the range estimates to those points, and provide an estimate of the uncertainty in each range. Errors in camera motion and image point measurement can also be modelled with Kalman filtering. A surface is then interpolated to these points, providing a complete map from which hazards such as steeply sloping areas can be detected. Using the method of extended Kalman filtering, our approach allows arbitrary camera motion. Preliminary results of an implementation are presented, and show that the resulting range accuracy is on the order of 1-2% of the range.

Child mortality estimation 2013: an overview of updates in estimation methods by the United Nations Inter-agency Group for Child Mortality Estimation.

PubMed

Alkema, Leontine; New, Jin Rou; Pedersen, Jon; You, Danzhen

2014-01-01

In September 2013, the United Nations Inter-agency Group for Child Mortality Estimation (UN IGME) published an update of the estimates of the under-five mortality rate (U5MR) and under-five deaths for all countries. Compared to the UN IGME estimates published in 2012, updated data inputs and a new method for estimating the U5MR were used. We summarize the new U5MR estimation method, which is a Bayesian B-spline Bias-reduction model, and highlight differences with the previously used method. Differences in UN IGME U5MR estimates as published in 2012 and those published in 2013 are presented and decomposed into differences due to the updated database and differences due to the new estimation method to explain and motivate changes in estimates. Compared to the previously used method, the new UN IGME estimation method is based on a different trend fitting method that can track (recent) changes in U5MR more closely. The new method provides U5MR estimates that account for data quality issues. Resulting differences in U5MR point estimates between the UN IGME 2012 and 2013 publications are small for the majority of countries but greater than 10 deaths per 1,000 live births for 33 countries in 2011 and 19 countries in 1990. These differences can be explained by the updated database used, the curve fitting method as well as accounting for data quality issues. Changes in the number of deaths were less than 10% on the global level and for the majority of MDG regions. The 2013 UN IGME estimates provide the most recent assessment of levels and trends in U5MR based on all available data and an improved estimation method that allows for closer-to-real-time monitoring of changes in the U5MR and takes account of data quality issues.

Implicit assimilation for marine ecological models

NASA Astrophysics Data System (ADS)

Weir, B.; Miller, R.; Spitz, Y. H.

2012-12-01

We use a new data assimilation method to estimate the parameters of a marine ecological model. At a given point in the ocean, the estimated values of the parameters determine the behaviors of the modeled planktonic groups, and thus indicate which species are dominant. To begin, we assimilate in situ observations, e.g., the Bermuda Atlantic Time-series Study, the Hawaii Ocean Time-series, and Ocean Weather Station Papa. From there, we estimate the parameters at surrounding points in space based on satellite observations of ocean color. Given the variation of the estimated parameters, we divide the ocean into regions meant to represent distinct ecosystems. An important feature of the data assimilation approach is that it refines the confidence limits of the optimal Gaussian approximation to the distribution of the parameters. This enables us to determine the ecological divisions with greater accuracy.

Multiscale Structure of UXO Site Characterization: Spatial Estimation and Uncertainty Quantification

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

Ostrouchov, George; Doll, William E.; Beard, Les P.

2009-01-01

Unexploded ordnance (UXO) site characterization must consider both how the contamination is generated and how we observe that contamination. Within the generation and observation processes, dependence structures can be exploited at multiple scales. We describe a conceptual site characterization process, the dependence structures available at several scales, and consider their statistical estimation aspects. It is evident that most of the statistical methods that are needed to address the estimation problems are known but their application-specific implementation may not be available. We demonstrate estimation at one scale and propose a representation for site contamination intensity that takes full account of uncertainty,more » is flexible enough to answer regulatory requirements, and is a practical tool for managing detailed spatial site characterization and remediation. The representation is based on point process spatial estimation methods that require modern computational resources for practical application. These methods have provisions for including prior and covariate information.« less

An analysis of estimation of pulmonary blood flow by the single-breath method

NASA Technical Reports Server (NTRS)

Srinivasan, R.

1986-01-01

The single-breath method represents a simple noninvasive technique for the assessment of capillary blood flow across the lung. However, this method has not gained widespread acceptance, because its accuracy is still being questioned. A rigorous procedure is described for estimating pulmonary blood flow (PBF) using data obtained with the aid of the single-breath method. Attention is given to the minimization of data-processing errors in the presence of measurement errors and to questions regarding a correction for possible loss of CO2 in the lung tissue. It is pointed out that the estimations are based on the exact solution of the underlying differential equations which describe the dynamics of gas exchange in the lung. The reported study demonstrates the feasibility of obtaining highly reliable estimates of PBF from expiratory data in the presence of random measurement errors.

Calculation of the confidence intervals for transformation parameters in the registration of medical images

PubMed Central

Bansal, Ravi; Staib, Lawrence H.; Laine, Andrew F.; Xu, Dongrong; Liu, Jun; Posecion, Lainie F.; Peterson, Bradley S.

2010-01-01

Images from different individuals typically cannot be registered precisely because anatomical features within the images differ across the people imaged and because the current methods for image registration have inherent technological limitations that interfere with perfect registration. Quantifying the inevitable error in image registration is therefore of crucial importance in assessing the effects that image misregistration may have on subsequent analyses in an imaging study. We have developed a mathematical framework for quantifying errors in registration by computing the confidence intervals of the estimated parameters (3 translations, 3 rotations, and 1 global scale) for the similarity transformation. The presence of noise in images and the variability in anatomy across individuals ensures that estimated registration parameters are always random variables. We assume a functional relation among intensities across voxels in the images, and we use the theory of nonlinear, least-squares estimation to show that the parameters are multivariate Gaussian distributed. We then use the covariance matrix of this distribution to compute the confidence intervals of the transformation parameters. These confidence intervals provide a quantitative assessment of the registration error across the images. Because transformation parameters are nonlinearly related to the coordinates of landmark points in the brain, we subsequently show that the coordinates of those landmark points are also multivariate Gaussian distributed. Using these distributions, we then compute the confidence intervals of the coordinates for landmark points in the image. Each of these confidence intervals in turn provides a quantitative assessment of the registration error at a particular landmark point. Because our method is computationally intensive, however, its current implementation is limited to assessing the error of the parameters in the similarity transformation across images. We assessed the performance of our method in computing the error in estimated similarity parameters by applying that method to real world dataset. Our results showed that the size of the confidence intervals computed using our method decreased – i.e. our confidence in the registration of images from different individuals increased – for increasing amounts of blur in the images. Moreover, the size of the confidence intervals increased for increasing amounts of noise, misregistration, and differing anatomy. Thus, our method precisely quantified confidence in the registration of images that contain varying amounts of misregistration and varying anatomy across individuals. PMID:19138877

A general theory on frequency and time-frequency analysis of irregularly sampled time series based on projection methods - Part 1: Frequency analysis

NASA Astrophysics Data System (ADS)

Lenoir, Guillaume; Crucifix, Michel

2018-03-01

We develop a general framework for the frequency analysis of irregularly sampled time series. It is based on the Lomb-Scargle periodogram, but extended to algebraic operators accounting for the presence of a polynomial trend in the model for the data, in addition to a periodic component and a background noise. Special care is devoted to the correlation between the trend and the periodic component. This new periodogram is then cast into the Welch overlapping segment averaging (WOSA) method in order to reduce its variance. We also design a test of significance for the WOSA periodogram, against the background noise. The model for the background noise is a stationary Gaussian continuous autoregressive-moving-average (CARMA) process, more general than the classical Gaussian white or red noise processes. CARMA parameters are estimated following a Bayesian framework. We provide algorithms that compute the confidence levels for the WOSA periodogram and fully take into account the uncertainty in the CARMA noise parameters. Alternatively, a theory using point estimates of CARMA parameters provides analytical confidence levels for the WOSA periodogram, which are more accurate than Markov chain Monte Carlo (MCMC) confidence levels and, below some threshold for the number of data points, less costly in computing time. We then estimate the amplitude of the periodic component with least-squares methods, and derive an approximate proportionality between the squared amplitude and the periodogram. This proportionality leads to a new extension for the periodogram: the weighted WOSA periodogram, which we recommend for most frequency analyses with irregularly sampled data. The estimated signal amplitude also permits filtering in a frequency band. Our results generalise and unify methods developed in the fields of geosciences, engineering, astronomy and astrophysics. They also constitute the starting point for an extension to the continuous wavelet transform developed in a companion article (Lenoir and Crucifix, 2018). All the methods presented in this paper are available to the reader in the Python package WAVEPAL.

Comparison of local- to regional-scale estimates of ground-water recharge in Minnesota, USA

USGS Publications Warehouse

Delin, G.N.; Healy, R.W.; Lorenz, D.L.; Nimmo, J.R.

2007-01-01

Regional ground-water recharge estimates for Minnesota were compared to estimates made on the basis of four local- and basin-scale methods. Three local-scale methods (unsaturated-zone water balance, water-table fluctuations (WTF) using three approaches, and age dating of ground water) yielded point estimates of recharge that represent spatial scales from about 1 to about 1000 m2. A fourth method (RORA, a basin-scale analysis of streamflow records using a recession-curve-displacement technique) yielded recharge estimates at a scale of 10–1000s of km2. The RORA basin-scale recharge estimates were regionalized to estimate recharge for the entire State of Minnesota on the basis of a regional regression recharge (RRR) model that also incorporated soil and climate data. Recharge rates estimated by the RRR model compared favorably to the local and basin-scale recharge estimates. RRR estimates at study locations were about 41% less on average than the unsaturated-zone water-balance estimates, ranged from 44% greater to 12% less than estimates that were based on the three WTF approaches, were about 4% less than the age dating of ground-water estimates, and were about 5% greater than the RORA estimates. Of the methods used in this study, the WTF method is the simplest and easiest to apply. Recharge estimates made on the basis of the UZWB method were inconsistent with the results from the other methods. Recharge estimates using the RRR model could be a good source of input for regional ground-water flow models; RRR model results currently are being applied for this purpose in USGS studies elsewhere.

Cost-of-illness studies of atrial fibrillation: methodological considerations.

PubMed

Becker, Christian

2014-10-01

Atrial fibrillation (AF) is the most common heart rhythm arrhythmia, which has considerable economic consequences. This study aims to identify the current cost-of-illness estimates of AF; a focus was put on describing the studies' methodology. A literature review was conducted. Twenty-eight cost-of-illness studies were identified. Cost-of-illness estimates exist for health insurance members, hospital and primary care populations. In addition, the cost of stroke in AF patients and the costs of post-operative AF were calculated. The methods used were heterogeneous, mostly studies calculated excess costs. The identified annual excess costs varied, even among studies from the USA (∼US$1900 to ∼US$19,000). While pointing toward considerable costs, the cost-of-illness studies' relevance could be improved by focusing on subpopulations and treatment mixes. As possible starting points for subsequent economic studies, the methodology of cost-of-illness studies should be taken into account using methods, allowing stakeholders to find suitable studies and validate estimates.

A method to estimate statistical errors of properties derived from charge-density modelling

PubMed Central

Lecomte, Claude

2018-01-01

Estimating uncertainties of property values derived from a charge-density model is not straightforward. A methodology, based on calculation of sample standard deviations (SSD) of properties using randomly deviating charge-density models, is proposed with the MoPro software. The parameter shifts applied in the deviating models are generated in order to respect the variance–covariance matrix issued from the least-squares refinement. This ‘SSD methodology’ procedure can be applied to estimate uncertainties of any property related to a charge-density model obtained by least-squares fitting. This includes topological properties such as critical point coordinates, electron density, Laplacian and ellipticity at critical points and charges integrated over atomic basins. Errors on electrostatic potentials and interaction energies are also available now through this procedure. The method is exemplified with the charge density of compound (E)-5-phenylpent-1-enylboronic acid, refined at 0.45 Å resolution. The procedure is implemented in the freely available MoPro program dedicated to charge-density refinement and modelling. PMID:29724964

Reducing the risk of injury from table saw use: the potential benefits and costs of automatic protection.

PubMed

Graham, John D; Chang, Joice

2015-02-01

The use of table saws in the United States is associated with approximately 28,000 emergency department (ED) visits and 2,000 cases of finger amputation per year. This article provides a quantitative estimate of the economic benefits of automatic protection systems that could be designed into new table saw products. Benefits are defined as reduced health-care costs, enhanced production at work, and diminished pain and suffering. The present value of the benefits of automatic protection over the life of the table saw are interpreted as the switch-point cost value, the maximum investment in automatic protection that can be justified by benefit-cost comparison. Using two alternative methods for monetizing pain and suffering, the study finds switch-point cost values of $753 and $561 per saw. These point estimates are sensitive to the values of inputs, especially the average cost of injury. The various switch-point cost values are substantially higher than rough estimates of the incremental cost of automatic protection systems. Uncertainties and future research needs are discussed. © 2014 Society for Risk Analysis.

Motion illusions in optical art presented for long durations are temporally distorted.

PubMed

Nather, Francisco Carlos; Mecca, Fernando Figueiredo; Bueno, José Lino Oliveira

2013-01-01

Static figurative images implying human body movements observed for shorter and longer durations affect the perception of time. This study examined whether images of static geometric shapes would affect the perception of time. Undergraduate participants observed two Optical Art paintings by Bridget Riley for 9 or 36 s (group G9 and G36, respectively). Paintings implying different intensities of movement (2.0 and 6.0 point stimuli) were randomly presented. The prospective paradigm in the reproduction method was used to record time estimations. Data analysis did not show time distortions in the G9 group. In the G36 group the paintings were differently perceived: that for the 2.0 point one are estimated to be shorter than that for the 6.0 point one. Also for G36, the 2.0 point painting was underestimated in comparison with the actual time of exposure. Motion illusions in static images affected time estimation according to the attention given to the complexity of movement by the observer, probably leading to changes in the storage velocity of internal clock pulses.

Assessing and adjusting for differences between HIV prevalence estimates derived from national population-based surveys and antenatal care surveillance, with applications for Spectrum 2013

PubMed Central

Marsh, Kimberly; Mahy, Mary; Salomon, Joshua A.; Hogan, Daniel R.

2014-01-01

Objective(s): To assess differences between HIV prevalence estimates derived from national population surveys and antenatal care (ANC) surveillance sites and to improve the calibration of ANC-derived estimates in Spectrum 2013 to more appropriately account for differences between these data. Design: Retrospective analysis of national population survey and ANC surveillance data from 25 countries with generalized epidemics in sub-Saharan Africa and 8 countries with concentrated epidemics. Methods: Adult national population survey and ANC surveillance HIV prevalence estimates were compared for all available national population survey data points for the years 1999–2012. For sub-Saharan Africa, a mixed-effects linear regression model determined whether the relationship between national population and ANC estimates was constant across surveys. A new calibration method was developed to incorporate national population survey data directly into the likelihood for HIV prevalence in countries with generalized epidemics. Results were used to develop default rules for adjusting ANC data for countries with no national population surveys. Results: ANC surveillance data typically overestimate population prevalence, although a wide variation, particularly in rural areas, is observed across countries and survey years. The new calibration method yields similar point estimates to previous approaches, but leads to an average 44% increase in the width of 95% uncertainty intervals. Conclusion: Important biases remain in ANC surveillance data for HIV prevalence. The new approach to model-fitting in Spectrum 2013 more appropriately accounts for this bias when producing national estimates in countries with generalized epidemics. In countries with concentrated epidemics, local sex ratios should be used to calibrate ANC surveillance estimates. PMID:25203158

Facial motion parameter estimation and error criteria in model-based image coding

NASA Astrophysics Data System (ADS)

Liu, Yunhai; Yu, Lu; Yao, Qingdong

2000-04-01

Model-based image coding has been given extensive attention due to its high subject image quality and low bit-rates. But the estimation of object motion parameter is still a difficult problem, and there is not a proper error criteria for the quality assessment that are consistent with visual properties. This paper presents an algorithm of the facial motion parameter estimation based on feature point correspondence and gives the motion parameter error criteria. The facial motion model comprises of three parts. The first part is the global 3-D rigid motion of the head, the second part is non-rigid translation motion in jaw area, and the third part consists of local non-rigid expression motion in eyes and mouth areas. The feature points are automatically selected by a function of edges, brightness and end-node outside the blocks of eyes and mouth. The numbers of feature point are adjusted adaptively. The jaw translation motion is tracked by the changes of the feature point position of jaw. The areas of non-rigid expression motion can be rebuilt by using block-pasting method. The estimation approach of motion parameter error based on the quality of reconstructed image is suggested, and area error function and the error function of contour transition-turn rate are used to be quality criteria. The criteria reflect the image geometric distortion caused by the error of estimated motion parameters properly.

Calibration of a subcutaneous amperometric glucose sensor implanted for 7 days in diabetic patients. Part 2. Superiority of the one-point calibration method.

PubMed

Choleau, C; Klein, J C; Reach, G; Aussedat, B; Demaria-Pesce, V; Wilson, G S; Gifford, R; Ward, W K

2002-08-01

Calibration, i.e. the transformation in real time of the signal I(t) generated by the glucose sensor at time t into an estimation of glucose concentration G(t), represents a key issue for the development of a continuous glucose monitoring system. To compare two calibration procedures. In the one-point calibration, which assumes that I(o) is negligible, S is simply determined as the ratio I/G, and G(t) = I(t)/S. The two-point calibration consists in the determination of a sensor sensitivity S and of a background current I(o) by plotting two values of the sensor signal versus the concomitant blood glucose concentrations. The subsequent estimation of G(t) is given by G(t) = (I(t)-I(o))/S. A glucose sensor was implanted in the abdominal subcutaneous tissue of nine type 1 diabetic patients during 3 (n = 2) and 7 days (n = 7). The one-point calibration was performed a posteriori either once per day before breakfast, or twice per day before breakfast and dinner, or three times per day before each meal. The two-point calibration was performed each morning during breakfast. The percentages of points present in zones A and B of the Clarke Error Grid were significantly higher when the system was calibrated using the one-point calibration. Use of two one-point calibrations per day before meals was virtually as accurate as three one-point calibrations. This study demonstrates the feasibility of a simple method for calibrating a continuous glucose monitoring system.

Robust head pose estimation via supervised manifold learning.

PubMed

Wang, Chao; Song, Xubo

2014-05-01

Head poses can be automatically estimated using manifold learning algorithms, with the assumption that with the pose being the only variable, the face images should lie in a smooth and low-dimensional manifold. However, this estimation approach is challenging due to other appearance variations related to identity, head location in image, background clutter, facial expression, and illumination. To address the problem, we propose to incorporate supervised information (pose angles of training samples) into the process of manifold learning. The process has three stages: neighborhood construction, graph weight computation and projection learning. For the first two stages, we redefine inter-point distance for neighborhood construction as well as graph weight by constraining them with the pose angle information. For Stage 3, we present a supervised neighborhood-based linear feature transformation algorithm to keep the data points with similar pose angles close together but the data points with dissimilar pose angles far apart. The experimental results show that our method has higher estimation accuracy than the other state-of-art algorithms and is robust to identity and illumination variations. Copyright © 2014 Elsevier Ltd. All rights reserved.

Estimating minimally important difference (MID) in PROMIS pediatric measures using the scale-judgment method.

PubMed

Thissen, David; Liu, Yang; Magnus, Brooke; Quinn, Hally; Gipson, Debbie S; Dampier, Carlton; Huang, I-Chan; Hinds, Pamela S; Selewski, David T; Reeve, Bryce B; Gross, Heather E; DeWalt, Darren A

2016-01-01

To assess minimally important differences (MIDs) for several pediatric self-report item banks from the National Institutes of Health Patient-Reported Outcomes Measurement Information System(®) (PROMIS(®)). We presented vignettes comprising sets of two completed PROMIS questionnaires and asked judges to declare whether the individual completing those questionnaires had an important change or not. We enrolled judges (including adolescents, parents, and clinicians) who responded to 24 vignettes (six for each domain of depression, pain interference, fatigue, and mobility). We used item response theory to model responses to the vignettes across different judges and estimated MID as the point at which 50 % of the judges would declare an important change. We enrolled 246 judges (78 adolescents, 85 parents, and 83 clinicians). The MID estimated with clinician data was about 2 points on the PROMIS T-score scale, and the MID estimated with adolescent and parent data was about 3 points on that same scale. The MIDs enhance the value of PROMIS pediatric measures in clinical research studies to identify meaningful changes in health status over time.

Foundations for estimation by the method of least squares

NASA Technical Reports Server (NTRS)

Hauck, W. W., Jr.

1971-01-01

Least squares estimation is discussed from the point of view of a statistician. Much of the emphasis is on problems encountered in application and, more specifically, on questions involving assumptions: what assumptions are needed, when are they needed, what happens if they are not valid, and if they are invalid, how that fact can be detected.

Ice Velocity Mapping of Ross Ice Shelf, Antarctica by Matching Surface Undulations Measured by Icesat Laser Altimetry

NASA Technical Reports Server (NTRS)

Lee, Choon-Ki; Han, Shin-Chan; Yu, Jaehyung; Scambos, Ted A.; Seo, Ki-Weon

2012-01-01

We present a novel method for estimating the surface horizontal velocity on ice shelves using laser altimetrydata from the Ice Cloud and land Elevation Satellite (ICESat; 20032009). The method matches undulations measured at crossover points between successive campaigns.

Critical evaluations of vegetation cover measurement techniques: a response to Thacker et al. (2015)

USDA-ARS?s Scientific Manuscript database

Comparison studies are necessary to reconcile methods that have arisen among disparate rangeland monitoring programs. However, Thacker et al.'s study comparing Daubenmire frame (DF) and line-point intercept (LPI) methods for estimating vegetation cover ignores definitional differences between what t...

Common Clinical Practice versus new PRIM Score in Predicting Coronary Heart Disease Risk

PubMed Central

Frikke-Schmidt, Ruth; Tybjærg-Hansen, Anne; Schnohr, Peter; Jensen, Gorm B.; Nordestgaard, Børge G.

2011-01-01

Objectives To compare the new Patient Rule Induction Method(PRIM) Score and common clinical practice with the Framingham Point Score for classification of individuals with respect to coronary heart disease(CHD) risk. Methods and Results PRIM Score and the Framingham Point Score were estimated for 11,444 participants from the Copenhagen City Heart Study. Gender specific cumulative incidences and 10 year absolute CHD risks were estimated for subsets defined by age, total cholesterol, high-density lipoprotein(HDL) cholesterol, blood pressure, diabetes and smoking categories. PRIM defined seven mutually exclusive subsets in women and men, with cumulative incidences of CHD from 0.01 to 0.22 in women, and from 0.03 to 0.26 in men. PRIM versus Framingham Point Score found 11% versus 4% of all women, and 31% versus 35% of all men to have 10 year CHD risks >20%. Among women ≥65 years with hypertension and/or with diabetes, 10 year CHD risk >20% was found for 100% with PRIM scoring but for only 18% with the Framingham Point Score. Conclusion Compared to the PRIM Score, common clinical practice with the Framingham Point Score underestimates CHD risk in women, especially in women ≥65 years with hypertension and/or with diabetes. PMID:20728887

Registration using natural features for augmented reality systems.

PubMed

Yuan, M L; Ong, S K; Nee, A Y C

2006-01-01

Registration is one of the most difficult problems in augmented reality (AR) systems. In this paper, a simple registration method using natural features based on the projective reconstruction technique is proposed. This method consists of two steps: embedding and rendering. Embedding involves specifying four points to build the world coordinate system on which a virtual object will be superimposed. In rendering, the Kanade-Lucas-Tomasi (KLT) feature tracker is used to track the natural feature correspondences in the live video. The natural features that have been tracked are used to estimate the corresponding projective matrix in the image sequence. Next, the projective reconstruction technique is used to transfer the four specified points to compute the registration matrix for augmentation. This paper also proposes a robust method for estimating the projective matrix, where the natural features that have been tracked are normalized (translation and scaling) and used as the input data. The estimated projective matrix will be used as an initial estimate for a nonlinear optimization method that minimizes the actual residual errors based on the Levenberg-Marquardt (LM) minimization method, thus making the results more robust and stable. The proposed registration method has three major advantages: 1) It is simple, as no predefined fiducials or markers are used for registration for either indoor and outdoor AR applications. 2) It is robust, because it remains effective as long as at least six natural features are tracked during the entire augmentation, and the existence of the corresponding projective matrices in the live video is guaranteed. Meanwhile, the robust method to estimate the projective matrix can obtain stable results even when there are some outliers during the tracking process. 3) Virtual objects can still be superimposed on the specified areas, even if some parts of the areas are occluded during the entire process. Some indoor and outdoor experiments have been conducted to validate the performance of this proposed method.

Integrating spatial and temporal oxygen data to improve the quantification of in situ petroleum biodegradation rates.

PubMed

Davis, Gregory B; Laslett, Dean; Patterson, Bradley M; Johnston, Colin D

2013-03-15

Accurate estimation of biodegradation rates during remediation of petroleum impacted soil and groundwater is critical to avoid excessive costs and to ensure remedial effectiveness. Oxygen depth profiles or oxygen consumption over time are often used separately to estimate the magnitude and timeframe for biodegradation of petroleum hydrocarbons in soil and subsurface environments. Each method has limitations. Here we integrate spatial and temporal oxygen concentration data from a field experiment to develop better estimates and more reliably quantify biodegradation rates. During a nine-month bioremediation trial, 84 sets of respiration rate data (where aeration was halted and oxygen consumption was measured over time) were collected from in situ oxygen sensors at multiple locations and depths across a diesel non-aqueous phase liquid (NAPL) contaminated subsurface. Additionally, detailed vertical soil moisture (air-filled porosity) and NAPL content profiles were determined. The spatial and temporal oxygen concentration (respiration) data were modeled assuming one-dimensional diffusion of oxygen through the soil profile which was open to the atmosphere. Point and vertically averaged biodegradation rates were determined, and compared to modeled data from a previous field trial. Point estimates of biodegradation rates assuming no diffusion ranged up to 58 mg kg(-1) day(-1) while rates accounting for diffusion ranged up to 87 mg kg(-1) day(-1). Typically, accounting for diffusion increased point biodegradation rate estimates by 15-75% and vertically averaged rates by 60-80% depending on the averaging method adopted. Importantly, ignoring diffusion led to overestimation of biodegradation rates where the location of measurement was outside the zone of NAPL contamination. Over or underestimation of biodegradation rate estimates leads to cost implications for successful remediation of petroleum impacted sites. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.

A Comparison of Quantum and Molecular Mechanical Methods to Estimate Strain Energy in Druglike Fragments.

PubMed

Sellers, Benjamin D; James, Natalie C; Gobbi, Alberto

2017-06-26

Reducing internal strain energy in small molecules is critical for designing potent drugs. Quantum mechanical (QM) and molecular mechanical (MM) methods are often used to estimate these energies. In an effort to determine which methods offer an optimal balance in accuracy and performance, we have carried out torsion scan analyses on 62 fragments. We compared nine QM and four MM methods to reference energies calculated at a higher level of theory: CCSD(T)/CBS single point energies (coupled cluster with single, double, and perturbative triple excitations at the complete basis set limit) calculated on optimized geometries using MP2/6-311+G**. The results show that both the more recent MP2.X perturbation method as well as MP2/CBS perform quite well. In addition, combining a Hartree-Fock geometry optimization with a MP2/CBS single point energy calculation offers a fast and accurate compromise when dispersion is not a key energy component. Among MM methods, the OPLS3 force field accurately reproduces CCSD(T)/CBS torsion energies on more test cases than the MMFF94s or Amber12:EHT force fields, which struggle with aryl-amide and aryl-aryl torsions. Using experimental conformations from the Cambridge Structural Database, we highlight three example structures for which OPLS3 significantly overestimates the strain. The energies and conformations presented should enable scientists to estimate the expected error for the methods described and we hope will spur further research into QM and MM methods.

Distribution of basic sediments (bedload transport) on changes in coastal coastline Donggala, Central Sulawesi Province, Indonesia

NASA Astrophysics Data System (ADS)

Amiruddin

2018-03-01

This study entitled "Distribution of Bedload Transport Against Coastline Changes in Donggala Coast", the formulation of the problem (1) how much of the estimated bedload transport in Donggala Bodies; (2) where were the location of erosion and sedimentation strong point based on the estimation of bed load transport; (3) the extent to which the prediction of shoreline change rate of transport of sediments in coastal areas Donggala. This study aims to: (1) the calculation of estimated bed load transport in Donggala waters; (2) determining the location of the point of erosion and sedimentation strong basis of estimated bedload transport; (3) the prediction of shoreline change rate of transport of sediments in coastal areas Donggala.The survey method used in this research to collect primary data include: (1) decision point waypoint coordinates of each location of measurement; (2) measurement of height, period and direction of the waves; (3) a large measurement of sediment transport; (4) The angle measurement coastline, angle of attack and wave direction, and secondary data include: (1) information from the public; (2) the physical condition data field. The results showed that: (1) general estimate sediment transport base in each location data collection is varied. This is due to the different points of the coastline as well as the angle of attack of the shoreline waters broke Donggala; (2) strong abrasion at the study site occurs at the point Ts4 (622.75 m3/yr) and TS11 (755.25 m3/yr) located in the Village Tosale and point Tw7 and Tw17 (649.25 m3/yr) in Village of Towale. As for the strong sedimentation occurs at the point Ts3 (450.50 m3/yr) located in the Village Tosale and Tg3 point (357.75 m3/yr) located in the Village Tolonggano; (3) of the predicted outcome coastline changes based on the input data estimate sediment transport, beaches and waves parameters is seen that the changes in the location prophyl coastline tends toward research into or undergo a process of abrasion.

Muscle parameters estimation based on biplanar radiography.

PubMed

Dubois, G; Rouch, P; Bonneau, D; Gennisson, J L; Skalli, W

2016-11-01

The evaluation of muscle and joint forces in vivo is still a challenge. Musculo-Skeletal (musculo-skeletal) models are used to compute forces based on movement analysis. Most of them are built from a scaled-generic model based on cadaver measurements, which provides a low level of personalization, or from Magnetic Resonance Images, which provide a personalized model in lying position. This study proposed an original two steps method to access a subject-specific musculo-skeletal model in 30 min, which is based solely on biplanar X-Rays. First, the subject-specific 3D geometry of bones and skin envelopes were reconstructed from biplanar X-Rays radiography. Then, 2200 corresponding control points were identified between a reference model and the subject-specific X-Rays model. Finally, the shape of 21 lower limb muscles was estimated using a non-linear transformation between the control points in order to fit the muscle shape of the reference model to the X-Rays model. Twelfth musculo-skeletal models were reconstructed and compared to their reference. The muscle volume was not accurately estimated with a standard deviation (SD) ranging from 10 to 68%. However, this method provided an accurate estimation the muscle line of action with a SD of the length difference lower than 2% and a positioning error lower than 20 mm. The moment arm was also well estimated with SD lower than 15% for most muscle, which was significantly better than scaled-generic model for most muscle. This method open the way to a quick modeling method for gait analysis based on biplanar radiography.

3D depth-to-basement and density contrast estimates using gravity and borehole data

NASA Astrophysics Data System (ADS)

Barbosa, V. C.; Martins, C. M.; Silva, J. B.

2009-05-01

We present a gravity inversion method for simultaneously estimating the 3D basement relief of a sedimentary basin and the parameters defining the parabolic decay of the density contrast with depth in a sedimentary pack assuming the prior knowledge about the basement depth at a few points. The sedimentary pack is approximated by a grid of 3D vertical prisms juxtaposed in both horizontal directions, x and y, of a right-handed coordinate system. The prisms' thicknesses represent the depths to the basement and are the parameters to be estimated from the gravity data. To produce stable depth-to-basement estimates we impose smoothness on the basement depths through minimization of the spatial derivatives of the parameters in the x and y directions. To estimate the parameters defining the parabolic decay of the density contrast with depth we mapped a functional containing prior information about the basement depths at a few points. We apply our method to synthetic data from a simulated complex 3D basement relief with two sedimentary sections having distinct parabolic laws describing the density contrast variation with depth. Our method retrieves the true parameters of the parabolic law of density contrast decay with depth and produces good estimates of the basement relief if the number and the distribution of boreholes are sufficient. We also applied our method to real gravity data from the onshore and part of the shallow offshore Almada Basin, on Brazil's northeastern coast. The estimated 3D Almada's basement shows geologic structures that cannot be easily inferred just from the inspection of the gravity anomaly. The estimated Almada relief presents steep borders evidencing the presence of gravity faults. Also, we note the existence of three terraces separating two local subbasins. These geologic features are consistent with Almada's geodynamic origin (the Mesozoic breakup of Gondwana and the opening of the South Atlantic Ocean) and they are important in understanding the basin evolution and in detecting structural oil traps.

Analysis of methods to assess frontal sinus extent in osteoplastic flap surgery: transillumination versus 6-ft Caldwell versus image guidance.

PubMed

Melroy, Christopher T; Dubin, Marc G; Hardy, Stuart M; Senior, Brent A

2006-01-01

The aim of this study was to compare three common methods (transillumination, plain radiographs, and computerized tomography [CT] image guidance) for estimating the position and extent of pneumatization of the frontal sinus in osteoplastic flap surgery. Axial CT scans and 6-ft Caldwell radiographs were performed on 10 cadaver heads. For each head, soft tissue overlying the frontal bone was raised and the anticipated position and extent of the frontal sinus at four points was marked using three common methods. The silhouette of the frontal sinus from the Caldwell plain radiograph was excised and placed in position. Four points at the periphery also were made using information obtained from a passive optically guided image-guided surgery device, and transillumination via a frontal trephination also was used to estimate sinus extent. The true sinus size was measured at each point and compared with experimental values. The use of CT image guidance generated the least difference between measured and actual values (mean = 1.91 mm; SEM = 0.29); this method was found statistically superior to Caldwell (p = 0.040) and transillumination (p = 0.007). Image guidance did not overestimate the size of the sinus (0/36) and was quicker than the Caldwell approach (8.5 versus 11.5 minutes). There was no learning curve appreciated with image guidance. Accurate and precise estimation of the position and extent of the frontal sinus is crucial when performing osteoplastic flap surgery. Use of CT image guidance was statistically superior to Caldwell and transillumination methods and proved to be safe, reproducible, economic, and easy to learn.

Confidence intervals for the first crossing point of two hazard functions.

PubMed

Cheng, Ming-Yen; Qiu, Peihua; Tan, Xianming; Tu, Dongsheng

2009-12-01

The phenomenon of crossing hazard rates is common in clinical trials with time to event endpoints. Many methods have been proposed for testing equality of hazard functions against a crossing hazards alternative. However, there has been relatively few approaches available in the literature for point or interval estimation of the crossing time point. The problem of constructing confidence intervals for the first crossing time point of two hazard functions is considered in this paper. After reviewing a recent procedure based on Cox proportional hazard modeling with Box-Cox transformation of the time to event, a nonparametric procedure using the kernel smoothing estimate of the hazard ratio is proposed. The proposed procedure and the one based on Cox proportional hazard modeling with Box-Cox transformation of the time to event are both evaluated by Monte-Carlo simulations and applied to two clinical trial datasets.

Robust gaze-steering of an active vision system against errors in the estimated parameters

NASA Astrophysics Data System (ADS)

Han, Youngmo

2015-01-01

Gaze-steering is often used to broaden the viewing range of an active vision system. Gaze-steering procedures are usually based on estimated parameters such as image position, image velocity, depth and camera calibration parameters. However, there may be uncertainties in these estimated parameters because of measurement noise and estimation errors. In this case, robust gaze-steering cannot be guaranteed. To compensate for such problems, this paper proposes a gaze-steering method based on a linear matrix inequality (LMI). In this method, we first propose a proportional derivative (PD) control scheme on the unit sphere that does not use depth parameters. This proposed PD control scheme can avoid uncertainties in the estimated depth and camera calibration parameters, as well as inconveniences in their estimation process, including the use of auxiliary feature points and highly non-linear computation. Furthermore, the control gain of the proposed PD control scheme on the unit sphere is designed using LMI such that the designed control is robust in the presence of uncertainties in the other estimated parameters, such as image position and velocity. Simulation results demonstrate that the proposed method provides a better compensation for uncertainties in the estimated parameters than the contemporary linear method and steers the gaze of the camera more steadily over time than the contemporary non-linear method.

Vanishing points detection using combination of fast Hough transform and deep learning

NASA Astrophysics Data System (ADS)

Sheshkus, Alexander; Ingacheva, Anastasia; Nikolaev, Dmitry

2018-04-01

In this paper we propose a novel method for vanishing points detection based on convolutional neural network (CNN) approach and fast Hough transform algorithm. We show how to determine fast Hough transform neural network layer and how to use it in order to increase usability of the neural network approach to the vanishing point detection task. Our algorithm includes CNN with consequence of convolutional and fast Hough transform layers. We are building estimator for distribution of possible vanishing points in the image. This distribution can be used to find candidates of vanishing point. We provide experimental results from tests of suggested method using images collected from videos of road trips. Our approach shows stable result on test images with different projective distortions and noise. Described approach can be effectively implemented for mobile GPU and CPU.

Curvature computation in volume-of-fluid method based on point-cloud sampling

NASA Astrophysics Data System (ADS)

Kassar, Bruno B. M.; Carneiro, João N. E.; Nieckele, Angela O.

2018-01-01

This work proposes a novel approach to compute interface curvature in multiphase flow simulation based on Volume of Fluid (VOF) method. It is well documented in the literature that curvature and normal vector computation in VOF may lack accuracy mainly due to abrupt changes in the volume fraction field across the interfaces. This may cause deterioration on the interface tension forces estimates, often resulting in inaccurate results for interface tension dominated flows. Many techniques have been presented over the last years in order to enhance accuracy in normal vectors and curvature estimates including height functions, parabolic fitting of the volume fraction, reconstructing distance functions, coupling Level Set method with VOF, convolving the volume fraction field with smoothing kernels among others. We propose a novel technique based on a representation of the interface by a cloud of points. The curvatures and the interface normal vectors are computed geometrically at each point of the cloud and projected onto the Eulerian grid in a Front-Tracking manner. Results are compared to benchmark data and significant reduction on spurious currents as well as improvement in the pressure jump are observed. The method was developed in the open source suite OpenFOAM® extending its standard VOF implementation, the interFoam solver.

3-D Localization Method for a Magnetically Actuated Soft Capsule Endoscope and Its Applications

PubMed Central

Yim, Sehyuk; Sitti, Metin

2014-01-01

In this paper, we present a 3-D localization method for a magnetically actuated soft capsule endoscope (MASCE). The proposed localization scheme consists of three steps. First, MASCE is oriented to be coaxially aligned with an external permanent magnet (EPM). Second, MASCE is axially contracted by the enhanced magnetic attraction of the approaching EPM. Third, MASCE recovers its initial shape by the retracting EPM as the magnetic attraction weakens. The combination of the estimated direction in the coaxial alignment step and the estimated distance in the shape deformation (recovery) step provides the position of MASCE in 3-D. It is experimentally shown that the proposed localization method could provide 2.0–3.7 mm of distance error in 3-D. This study also introduces two new applications of the proposed localization method. First, based on the trace of contact points between the MASCE and the surface of the stomach, the 3-D geometrical model of a synthetic stomach was reconstructed. Next, the relative tissue compliance at each local contact point in the stomach was characterized by measuring the local tissue deformation at each point due to the preloading force. Finally, the characterized relative tissue compliance parameter was mapped onto the geometrical model of the stomach toward future use in disease diagnosis. PMID:25383064

Model-based registration of multi-rigid-body for augmented reality

NASA Astrophysics Data System (ADS)

Ikeda, Sei; Hori, Hajime; Imura, Masataka; Manabe, Yoshitsugu; Chihara, Kunihiro

2009-02-01

Geometric registration between a virtual object and the real space is the most basic problem in augmented reality. Model-based tracking methods allow us to estimate three-dimensional (3-D) position and orientation of a real object by using a textured 3-D model instead of visual marker. However, it is difficult to apply existing model-based tracking methods to the objects that have movable parts such as a display of a mobile phone, because these methods suppose a single, rigid-body model. In this research, we propose a novel model-based registration method for multi rigid-body objects. For each frame, the 3-D models of each rigid part of the object are first rendered according to estimated motion and transformation from the previous frame. Second, control points are determined by detecting the edges of the rendered image and sampling pixels on these edges. Motion and transformation are then simultaneously calculated from distances between the edges and the control points. The validity of the proposed method is demonstrated through experiments using synthetic videos.

Future PMPs Estimation in Korea under AR5 RCP 8.5 Climate Change Scenario: Focus on Dew Point Temperature Change

NASA Astrophysics Data System (ADS)

Okjeong, Lee; Sangdan, Kim

2016-04-01

According to future climate change scenarios, future temperature is expected to increase gradually. Therefore, it is necessary to reflect the effects of these climate changes to predict Probable Maximum Precipitations (PMPs). In this presentation, PMPs will be estimated with future dew point temperature change. After selecting 174 major storm events from 1981 to 2005, new PMPs will be proposed with respect to storm areas (25, 100, 225, 400, 900, 2,025, 4,900, 10,000 and 19,600 km2) and storm durations (1, 2, 4, 6, 8, 12, 18, 24, 48 and 72 hours) using the Korea hydro-meteorological method. Also, orographic transposition factor will be applied in place of the conventional terrain impact factor which has been used in previous Korean PMPs estimation reports. After estimating dew point temperature using future temperature and representative humidity information under the Korea Meteorological Administration AR5 RCP 8.5, changes in the PMPs under dew point temperature change will be investigated by comparison with present and future PMPs. This research was supported by a grant(14AWMP-B082564-01) from Advanced Water Management Research Program funded by Ministry of Land, Infrastructure and Transport of Korean government.

A removal model for estimating detection probabilities from point-count surveys

USGS Publications Warehouse

Farnsworth, G.L.; Pollock, K.H.; Nichols, J.D.; Simons, T.R.; Hines, J.E.; Sauer, J.R.

2000-01-01

We adapted a removal model to estimate detection probability during point count surveys. The model assumes one factor influencing detection during point counts is the singing frequency of birds. This may be true for surveys recording forest songbirds when most detections are by sound. The model requires counts to be divided into several time intervals. We used time intervals of 2, 5, and 10 min to develop a maximum-likelihood estimator for the detectability of birds during such surveys. We applied this technique to data from bird surveys conducted in Great Smoky Mountains National Park. We used model selection criteria to identify whether detection probabilities varied among species, throughout the morning, throughout the season, and among different observers. The overall detection probability for all birds was 75%. We found differences in detection probability among species. Species that sing frequently such as Winter Wren and Acadian Flycatcher had high detection probabilities (about 90%) and species that call infrequently such as Pileated Woodpecker had low detection probability (36%). We also found detection probabilities varied with the time of day for some species (e.g. thrushes) and between observers for other species. This method of estimating detectability during point count surveys offers a promising new approach to using count data to address questions of the bird abundance, density, and population trends.

Nondestructive detection of decay in living trees

Treesearch

Bertil Larsson; Bengt Bengtsson; Mats Gustaffson

2004-01-01

We used a four-point resistivity method to detect wood decay in living trees. low-frequency alternating current was applied to the stem and the induced voltage measured between two points along the stem. The effective resistivity of the stem was estimated based on stem cross-sectional area. A comparison within a group of trees showed that trees with butt rot had an...

Improved image decompression for reduced transform coding artifacts

NASA Technical Reports Server (NTRS)

Orourke, Thomas P.; Stevenson, Robert L.

1994-01-01

The perceived quality of images reconstructed from low bit rate compression is severely degraded by the appearance of transform coding artifacts. This paper proposes a method for producing higher quality reconstructed images based on a stochastic model for the image data. Quantization (scalar or vector) partitions the transform coefficient space and maps all points in a partition cell to a representative reconstruction point, usually taken as the centroid of the cell. The proposed image estimation technique selects the reconstruction point within the quantization partition cell which results in a reconstructed image which best fits a non-Gaussian Markov random field (MRF) image model. This approach results in a convex constrained optimization problem which can be solved iteratively. At each iteration, the gradient projection method is used to update the estimate based on the image model. In the transform domain, the resulting coefficient reconstruction points are projected to the particular quantization partition cells defined by the compressed image. Experimental results will be shown for images compressed using scalar quantization of block DCT and using vector quantization of subband wavelet transform. The proposed image decompression provides a reconstructed image with reduced visibility of transform coding artifacts and superior perceived quality.

A principal component analysis of the relationship between the external body shape and internal skeleton for the upper body.

PubMed

Nerot, A; Skalli, W; Wang, X

2016-10-03

Recent progress in 3D scanning technologies allows easy access to 3D human body envelope. To create personalized human models with an articulated linkage for realistic re-posturing and motion analyses, an accurate estimation of internal skeleton points, including joint centers, from the external envelope is required. For this research project, 3D reconstructions of both internal skeleton and external envelope from low dose biplanar X-rays of 40 male adults were obtained. Using principal component analysis technique (PCA), a low-dimensional dataset was used to predict internal points of the upper body from the trunk envelope. A least squares method was used to find PC scores that fit the PCA-based model to the envelope of a new subject. To validate the proposed approach, estimated internal points were evaluated using a leave-one-out (LOO) procedure, i.e. successively considering each individual from our dataset as an extra-subject. In addition, different methods were proposed to reduce the variability in data and improve the performance of the PCA-based prediction. The best method was considered as the one providing the smallest errors between estimated and reference internal points with an average error of 8.3mm anterior-posteriorly, 6.7mm laterally and 6.5mm vertically. As the proposed approach relies on few or no bony landmarks, it could be easily applicable and generalizable to surface scans from any devices. Combined with automatic body scanning techniques, this study could potentially constitute a new step towards automatic generation of external/internal subject-specific manikins. Copyright © 2016 Elsevier Ltd. All rights reserved.

Having a Whale of a Time

ERIC Educational Resources Information Center

du Feu, Chris

2009-01-01

A classroom practical exercise exploring the reliability of a basic capture-mark-recapture method of population estimation is described using great whale conservation as a starting point. Various teaching resources are made available.

Comparison of two stand-alone CADe systems at multiple operating points

NASA Astrophysics Data System (ADS)

Sahiner, Berkman; Chen, Weijie; Pezeshk, Aria; Petrick, Nicholas

2015-03-01

Computer-aided detection (CADe) systems are typically designed to work at a given operating point: The device displays a mark if and only if the level of suspiciousness of a region of interest is above a fixed threshold. To compare the standalone performances of two systems, one approach is to select the parameters of the systems to yield a target false-positive rate that defines the operating point, and to compare the sensitivities at that operating point. Increasingly, CADe developers offer multiple operating points, which necessitates the comparison of two CADe systems involving multiple comparisons. To control the Type I error, multiple-comparison correction is needed for keeping the family-wise error rate (FWER) less than a given alpha-level. The sensitivities of a single modality at different operating points are correlated. In addition, the sensitivities of the two modalities at the same or different operating points are also likely to be correlated. It has been shown in the literature that when test statistics are correlated, well-known methods for controlling the FWER are conservative. In this study, we compared the FWER and power of three methods, namely the Bonferroni, step-up, and adjusted step-up methods in comparing the sensitivities of two CADe systems at multiple operating points, where the adjusted step-up method uses the estimated correlations. Our results indicate that the adjusted step-up method has a substantial advantage over other the two methods both in terms of the FWER and power.

An investigation of new methods for estimating parameter sensitivities

NASA Technical Reports Server (NTRS)

Beltracchi, Todd J.; Gabriele, Gary A.

1988-01-01

Parameter sensitivity is defined as the estimation of changes in the modeling functions and the design variables due to small changes in the fixed parameters of the formulation. There are currently several methods for estimating parameter sensitivities requiring either difficult to obtain second order information, or do not return reliable estimates for the derivatives. Additionally, all the methods assume that the set of active constraints does not change in a neighborhood of the estimation point. If the active set does in fact change, than any extrapolations based on these derivatives may be in error. The objective here is to investigate more efficient new methods for estimating parameter sensitivities when the active set changes. The new method is based on the recursive quadratic programming (RQP) method and in conjunction a differencing formula to produce estimates of the sensitivities. This is compared to existing methods and is shown to be very competitive in terms of the number of function evaluations required. In terms of accuracy, the method is shown to be equivalent to a modified version of the Kuhn-Tucker method, where the Hessian of the Lagrangian is estimated using the BFS method employed by the RPQ algorithm. Inital testing on a test set with known sensitivities demonstrates that the method can accurately calculate the parameter sensitivity. To handle changes in the active set, a deflection algorithm is proposed for those cases where the new set of active constraints remains linearly independent. For those cases where dependencies occur, a directional derivative is proposed. A few simple examples are included for the algorithm, but extensive testing has not yet been performed.

A Monocular Vision Sensor-Based Obstacle Detection Algorithm for Autonomous Robots.

PubMed

Lee, Tae-Jae; Yi, Dong-Hoon; Cho, Dong-Il Dan

2016-03-01

This paper presents a monocular vision sensor-based obstacle detection algorithm for autonomous robots. Each individual image pixel at the bottom region of interest is labeled as belonging either to an obstacle or the floor. While conventional methods depend on point tracking for geometric cues for obstacle detection, the proposed algorithm uses the inverse perspective mapping (IPM) method. This method is much more advantageous when the camera is not high off the floor, which makes point tracking near the floor difficult. Markov random field-based obstacle segmentation is then performed using the IPM results and a floor appearance model. Next, the shortest distance between the robot and the obstacle is calculated. The algorithm is tested by applying it to 70 datasets, 20 of which include nonobstacle images where considerable changes in floor appearance occur. The obstacle segmentation accuracies and the distance estimation error are quantitatively analyzed. For obstacle datasets, the segmentation precision and the average distance estimation error of the proposed method are 81.4% and 1.6 cm, respectively, whereas those for a conventional method are 57.5% and 9.9 cm, respectively. For nonobstacle datasets, the proposed method gives 0.0% false positive rates, while the conventional method gives 17.6%.

Alternative Methods for Estimating Plane Parameters Based on a Point Cloud

NASA Astrophysics Data System (ADS)

Stryczek, Roman

2017-12-01

Non-contact measurement techniques carried out using triangulation optical sensors are increasingly popular in measurements with the use of industrial robots directly on production lines. The result of such measurements is often a cloud of measurement points that is characterized by considerable measuring noise, presence of a number of points that differ from the reference model, and excessive errors that must be eliminated from the analysis. To obtain vector information points contained in the cloud that describe reference models, the data obtained during a measurement should be subjected to appropriate processing operations. The present paperwork presents an analysis of suitability of methods known as RANdom Sample Consensus (RANSAC), Monte Carlo Method (MCM), and Particle Swarm Optimization (PSO) for the extraction of the reference model. The effectiveness of the tested methods is illustrated by examples of measurement of the height of an object and the angle of a plane, which were made on the basis of experiments carried out at workshop conditions.

Collaborative Indoor Access Point Localization Using Autonomous Mobile Robot Swarm.

PubMed

Awad, Fahed; Naserllah, Muhammad; Omar, Ammar; Abu-Hantash, Alaa; Al-Taj, Abrar

2018-01-31

Localization of access points has become an important research problem due to the wide range of applications it addresses such as dismantling critical security threats caused by rogue access points or optimizing wireless coverage of access points within a service area. Existing proposed solutions have mostly relied on theoretical hypotheses or computer simulation to demonstrate the efficiency of their methods. The techniques that rely on estimating the distance using samples of the received signal strength usually assume prior knowledge of the signal propagation characteristics of the indoor environment in hand and tend to take a relatively large number of uniformly distributed random samples. This paper presents an efficient and practical collaborative approach to detect the location of an access point in an indoor environment without any prior knowledge of the environment. The proposed approach comprises a swarm of wirelessly connected mobile robots that collaboratively and autonomously collect a relatively small number of non-uniformly distributed random samples of the access point's received signal strength. These samples are used to efficiently and accurately estimate the location of the access point. The experimental testing verified that the proposed approach can identify the location of the access point in an accurate and efficient manner.

Application of a laser scanner to three dimensional visual sensing tasks

NASA Technical Reports Server (NTRS)

Ryan, Arthur M.

1992-01-01

The issues are described which are associated with using a laser scanner for visual sensing and the methods developed by the author to address them. A laser scanner is a device that controls the direction of a laser beam by deflecting it through a pair of orthogonal mirrors, the orientations of which are specified by a computer. If a calibrated laser scanner is combined with a calibrated camera, it is possible to perform three dimensional sensing by directing the laser at objects within the field of view of the camera. There are several issues associated with using a laser scanner for three dimensional visual sensing that must be addressed in order to use the laser scanner effectively. First, methods are needed to calibrate the laser scanner and estimate three dimensional points. Second, methods to estimate three dimensional points using a calibrated camera and laser scanner are required. Third, methods are required for locating the laser spot in a cluttered image. Fourth, mathematical models that predict the laser scanner's performance and provide structure for three dimensional data points are necessary. Several methods were developed to address each of these and has evaluated them to determine how and when they should be applied. The theoretical development, implementation, and results when used in a dual arm eighteen degree of freedom robotic system for space assembly is described.

An Assessment of Common Approaches to Estimating Peak Skin Dose Resulting From Fluoroscopically Guided Interventions

NASA Astrophysics Data System (ADS)

Smith, Caleb Martin

Fluoroscopy guided procedures are increasing in complexity, and with that, Peak Skin Doses (PSD) that produce cutaneous radiation injury are a growing concern. Direct measurement of PSD is possible, but the decision to do so must be made in advance. PSD estimates and correctly monitoring their possible deterministic skin injuries are important to patient care. Three methods of indirect PSD estimation are examined for nine cases at MedStar Georgetown University Hospital. The aim of the study is to determine the magnitude of variation between these three methods for estimating the PSD. Method 1 (Fluoroscopy Time and Maximum Entrance Skin Exposure) was used at MedStar Georgetown University Hospital up until 2016. Methods 2 and 3 incorporate procedure information (Reference Point Air Kerma, Source-to-Patent distance, and Backscatter Factor) from DICOM (Digital Imaging and Communications in Medicine) tags into PSD estimates. Method 1 PSD estimates are vastly different, by as much as 136%, than those from Methods 2 and 3. Method 2 and 3 PSD estimates differ very little, 7.3% or less. Governing bodies have discounted Method 1 as a reliable dose metric because of its poor correlation with PSD. The accuracy of Method 2 is suitable to determine PSD and which dose band a patient fits so their injuries can be accurately monitored. Method 3, the most time intensive approach, should only be used in the case of a sentinel event where a full investigation is warranted.

Point prevalence and incidence of Mycobacterium tuberculosis complex in captive elephants in the United States of America.

PubMed

Feldman, Melissa; Isaza, Ramiro; Prins, Cindy; Hernandez, Jorge

2013-01-01

Captive elephants infected with tuberculosis are implicated as an occupational source of zoonotic tuberculosis. However, accurate estimates of prevalence and incidence of elephant tuberculosis from well-defined captive populations are lacking in the literature. Studies published in recent years contain a wide range of prevalence estimates calculated from summary data. Incidence estimates of elephant tuberculosis in captive elephants are not available. This study estimated the annual point prevalence, annual incidence, cumulative incidence, and incidence density of tuberculosis in captive elephants within the USA during the past 52 years. We combined existing elephant census records from captive elephants in the USA with tuberculosis culture results obtained from trunk washes or at necropsy. This data set included 15 years where each elephant was screened annually. Between 1960 and 1996, the annual point prevalence of tuberculosis complex mycobacteria for both species was 0. From 1997 through 2011, the median point prevalence within the Asian elephant population was 5.1%, with a range from 0.3% to 6.7%. The incidence density was 9.7 cases/1000 elephant years (95% CI: 7.0-13.4). In contrast, the annual point prevalence during the same time period within the African elephant population remained 0 and the incidence density was 1.5 cases/1000 elephant years (95% CI: 0.7-4.0). The apparent increase in new cases noted after 1996 resulted from a combination of both index cases and the initiation of mandatory annual tuberculosis screening in 1997 for all the elephants. This study found lower annual point prevalence estimates than previously reported in the literature. These discrepancies in prevalence estimates are primarily due to differences in terminology and calculation methods. Using the same intensive testing regime, the incidence of tuberculosis differed significantly between Asian and African elephants. Accurate and species specific knowledge of prevalence and incidence will inform our efforts to mitigate occupational risks associated with captive elephants in the USA.

a Robust Method for Stereo Visual Odometry Based on Multiple Euclidean Distance Constraint and Ransac Algorithm

NASA Astrophysics Data System (ADS)

Zhou, Q.; Tong, X.; Liu, S.; Lu, X.; Liu, S.; Chen, P.; Jin, Y.; Xie, H.

2017-07-01

Visual Odometry (VO) is a critical component for planetary robot navigation and safety. It estimates the ego-motion using stereo images frame by frame. Feature points extraction and matching is one of the key steps for robotic motion estimation which largely influences the precision and robustness. In this work, we choose the Oriented FAST and Rotated BRIEF (ORB) features by considering both accuracy and speed issues. For more robustness in challenging environment e.g., rough terrain or planetary surface, this paper presents a robust outliers elimination method based on Euclidean Distance Constraint (EDC) and Random Sample Consensus (RANSAC) algorithm. In the matching process, a set of ORB feature points are extracted from the current left and right synchronous images and the Brute Force (BF) matcher is used to find the correspondences between the two images for the Space Intersection. Then the EDC and RANSAC algorithms are carried out to eliminate mismatches whose distances are beyond a predefined threshold. Similarly, when the left image of the next time matches the feature points with the current left images, the EDC and RANSAC are iteratively performed. After the above mentioned, there are exceptional remaining mismatched points in some cases, for which the third time RANSAC is applied to eliminate the effects of those outliers in the estimation of the ego-motion parameters (Interior Orientation and Exterior Orientation). The proposed approach has been tested on a real-world vehicle dataset and the result benefits from its high robustness.

Application of geostatistics to risk assessment.

PubMed

Thayer, William C; Griffith, Daniel A; Goodrum, Philip E; Diamond, Gary L; Hassett, James M

2003-10-01

Geostatistics offers two fundamental contributions to environmental contaminant exposure assessment: (1) a group of methods to quantitatively describe the spatial distribution of a pollutant and (2) the ability to improve estimates of the exposure point concentration by exploiting the geospatial information present in the data. The second contribution is particularly valuable when exposure estimates must be derived from small data sets, which is often the case in environmental risk assessment. This article addresses two topics related to the use of geostatistics in human and ecological risk assessments performed at hazardous waste sites: (1) the importance of assessing model assumptions when using geostatistics and (2) the use of geostatistics to improve estimates of the exposure point concentration (EPC) in the limited data scenario. The latter topic is approached here by comparing design-based estimators that are familiar to environmental risk assessors (e.g., Land's method) with geostatistics, a model-based estimator. In this report, we summarize the basics of spatial weighting of sample data, kriging, and geostatistical simulation. We then explore the two topics identified above in a case study, using soil lead concentration data from a Superfund site (a skeet and trap range). We also describe several areas where research is needed to advance the use of geostatistics in environmental risk assessment.

Development of method for experimental determination of wheel-rail contact forces and contact point position by using instrumented wheelset

NASA Astrophysics Data System (ADS)

Bižić, Milan B.; Petrović, Dragan Z.; Tomić, Miloš C.; Djinović, Zoran V.

2017-07-01

This paper presents the development of a unique method for experimental determination of wheel-rail contact forces and contact point position by using the instrumented wheelset (IWS). Solutions of key problems in the development of IWS are proposed, such as the determination of optimal locations, layout, number and way of connecting strain gauges as well as the development of an inverse identification algorithm (IIA). The base for the solution of these problems is the wheel model and results of FEM calculations, while IIA is based on the method of blind source separation using independent component analysis. In the first phase, the developed method was tested on a wheel model and a high accuracy was obtained (deviations of parameters obtained with IIA and really applied parameters in the model are less than 2%). In the second phase, experimental tests on the real object or IWS were carried out. The signal-to-noise ratio was identified as the main influential parameter on the measurement accuracy. Тhе obtained results have shown that the developed method enables measurement of vertical and lateral wheel-rail contact forces Q and Y and their ratio Y/Q with estimated errors of less than 10%, while the estimated measurement error of contact point position is less than 15%. At flange contact and higher values of ratio Y/Q or Y force, the measurement errors are reduced, which is extremely important for the reliability and quality of experimental tests of safety against derailment of railway vehicles according to the standards UIC 518 and EN 14363. The obtained results have shown that the proposed method can be successfully applied in solving the problem of high accuracy measurement of wheel-rail contact forces and contact point position using IWS.

A method for analyzing clustered interval-censored data based on Cox's model.

PubMed

Kor, Chew-Teng; Cheng, Kuang-Fu; Chen, Yi-Hau

2013-02-28

Methods for analyzing interval-censored data are well established. Unfortunately, these methods are inappropriate for the studies with correlated data. In this paper, we focus on developing a method for analyzing clustered interval-censored data. Our method is based on Cox's proportional hazard model with piecewise-constant baseline hazard function. The correlation structure of the data can be modeled by using Clayton's copula or independence model with proper adjustment in the covariance estimation. We establish estimating equations for the regression parameters and baseline hazards (and a parameter in copula) simultaneously. Simulation results confirm that the point estimators follow a multivariate normal distribution, and our proposed variance estimations are reliable. In particular, we found that the approach with independence model worked well even when the true correlation model was derived from Clayton's copula. We applied our method to a family-based cohort study of pandemic H1N1 influenza in Taiwan during 2009-2010. Using the proposed method, we investigate the impact of vaccination and family contacts on the incidence of pH1N1 influenza. Copyright © 2012 John Wiley & Sons, Ltd.

Dual ant colony operational modal analysis parameter estimation method

NASA Astrophysics Data System (ADS)

Sitarz, Piotr; Powałka, Bartosz

2018-01-01

Operational Modal Analysis (OMA) is a common technique used to examine the dynamic properties of a system. Contrary to experimental modal analysis, the input signal is generated in object ambient environment. Operational modal analysis mainly aims at determining the number of pole pairs and at estimating modal parameters. Many methods are used for parameter identification. Some methods operate in time while others in frequency domain. The former use correlation functions, the latter - spectral density functions. However, while some methods require the user to select poles from a stabilisation diagram, others try to automate the selection process. Dual ant colony operational modal analysis parameter estimation method (DAC-OMA) presents a new approach to the problem, avoiding issues involved in the stabilisation diagram. The presented algorithm is fully automated. It uses deterministic methods to define the interval of estimated parameters, thus reducing the problem to optimisation task which is conducted with dedicated software based on ant colony optimisation algorithm. The combination of deterministic methods restricting parameter intervals and artificial intelligence yields very good results, also for closely spaced modes and significantly varied mode shapes within one measurement point.

Camera pose estimation for augmented reality in a small indoor dynamic scene

NASA Astrophysics Data System (ADS)

Frikha, Rawia; Ejbali, Ridha; Zaied, Mourad

2017-09-01

Camera pose estimation remains a challenging task for augmented reality (AR) applications. Simultaneous localization and mapping (SLAM)-based methods are able to estimate the six degrees of freedom camera motion while constructing a map of an unknown environment. However, these methods do not provide any reference for where to insert virtual objects since they do not have any information about scene structure and may fail in cases of occlusion of three-dimensional (3-D) map points or dynamic objects. This paper presents a real-time monocular piece wise planar SLAM method using the planar scene assumption. Using planar structures in the mapping process allows rendering virtual objects in a meaningful way on the one hand and improving the precision of the camera pose and the quality of 3-D reconstruction of the environment by adding constraints on 3-D points and poses in the optimization process on the other hand. We proposed to benefit from the 3-D planes rigidity motion in the tracking process to enhance the system robustness in the case of dynamic scenes. Experimental results show that using a constrained planar scene improves our system accuracy and robustness compared with the classical SLAM systems.

New results on the relation between tyre-road longitudinal stiffness and maximum available grip for motor car

NASA Astrophysics Data System (ADS)

Andrieux, A.; Vandanjon, P. O.; Lengelle, R.; Chabanon, C.

2010-12-01

Tyre-road estimation methods have been the objective of many research programmes throughout the world. Most of these methods aim at estimating the friction components such as tyre longitudinal slip rate κ and friction coefficient μ in the contact patch area. In order to estimate the maximum available friction coefficient μmax, these methods generally use a probabilistic relationship between the grip obtained for low tyre excitations (such as constant speed driving) and the grip obtained for high tyre excitations (such as emergency braking manoeuvre). Confirmation or invalidation of this relationship from experimental results is the purpose of this paper. Experiments have been carried out on a reference track including several test boards corresponding to a wide textural spectrum. The main advantage of these experiments lies in the use of a vehicle allowing us to accurately build point-by-point relationship between κ and μ. This relationship has been determined for different tyres and pavement textures. Finally, the curves obtained are analysed to check the validity of the relationship between the current friction coefficient used by the car during normal driving conditions and μmax.

Bottom Pressure Tides Along a Line in the Southeast Atlantic Ocean and Comparisons with Satellite Altimetry

NASA Technical Reports Server (NTRS)

Ray, Richard D.; Byrne, Deidre A.

2010-01-01

Seafloor pressure records, collected at 11 stations aligned along a single ground track of the Topex/Poseidon and Jason satellites, are analyzed for their tidal content. With very low background noise levels and approximately 27 months of high-quality records, tidal constituents can be estimated with unusually high precision. This includes many high-frequency lines up through the seventh-diurnal band. The station deployment provides a unique opportunity to compare with tides estimated from satellite altimetry, point by point along the satellite track, in a region of moderately high mesoscale variability. That variability can significantly corrupt altimeter-based tide estimates, even with 17 years of data. A method to improve the along-track altimeter estimates by correcting the data for nontidal variability is found to yield much better agreement with the bottom-pressure data. The technique should prove useful in certain demanding applications, such as altimetric studies of internal tides.

Improved remote gaze estimation using corneal reflection-adaptive geometric transforms

NASA Astrophysics Data System (ADS)

Ma, Chunfei; Baek, Seung-Jin; Choi, Kang-A.; Ko, Sung-Jea

2014-05-01

Recently, the remote gaze estimation (RGE) technique has been widely applied to consumer devices as a more natural interface. In general, the conventional RGE method estimates a user's point of gaze using a geometric transform, which represents the relationship between several infrared (IR) light sources and their corresponding corneal reflections (CRs) in the eye image. Among various methods, the homography normalization (HN) method achieves state-of-the-art performance. However, the geometric transform of the HN method requiring four CRs is infeasible for the case when fewer than four CRs are available. To solve this problem, this paper proposes a new RGE method based on three alternative geometric transforms, which are adaptive to the number of CRs. Unlike the HN method, the proposed method not only can operate with two or three CRs, but can also provide superior accuracy. To further enhance the performance, an effective error correction method is also proposed. By combining the introduced transforms with the error-correction method, the proposed method not only provides high accuracy and robustness for gaze estimation, but also allows for a more flexible system setup with a different number of IR light sources. Experimental results demonstrate the effectiveness of the proposed method.

Solid oxide fuel cell anode image segmentation based on a novel quantum-inspired fuzzy clustering

NASA Astrophysics Data System (ADS)

Fu, Xiaowei; Xiang, Yuhan; Chen, Li; Xu, Xin; Li, Xi

2015-12-01

High quality microstructure modeling can optimize the design of fuel cells. For three-phase accurate identification of Solid Oxide Fuel Cell (SOFC) microstructure, this paper proposes a novel image segmentation method on YSZ/Ni anode Optical Microscopic (OM) images. According to Quantum Signal Processing (QSP), the proposed approach exploits a quantum-inspired adaptive fuzziness factor to adaptively estimate the energy function in the fuzzy system based on Markov Random Filed (MRF). Before defuzzification, a quantum-inspired probability distribution based on distance and gray correction is proposed, which can adaptively adjust the inaccurate probability estimation of uncertain points caused by noises and edge points. In this study, the proposed method improves accuracy and effectiveness of three-phase identification on the micro-investigation. It provides firm foundation to investigate the microstructural evolution and its related properties.

A simple, remote, video based breathing monitor.

PubMed

Regev, Nir; Wulich, Dov

2017-07-01

Breathing monitors have become the all-important cornerstone of a wide variety of commercial and personal safety applications, ranging from elderly care to baby monitoring. Many such monitors exist in the market, some, with vital signs monitoring capabilities, but none remote. This paper presents a simple, yet efficient, real time method of extracting the subject's breathing sinus rhythm. Points of interest are detected on the subject's body, and the corresponding optical flow is estimated and tracked using the well known Lucas-Kanade algorithm on a frame by frame basis. A generalized likelihood ratio test is then utilized on each of the many interest points to detect which is moving in harmonic fashion. Finally, a spectral estimation algorithm based on Pisarenko harmonic decomposition tracks the harmonic frequency in real time, and a fusion maximum likelihood algorithm optimally estimates the breathing rate using all points considered. The results show a maximal error of 1 BPM between the true breathing rate and the algorithm's calculated rate, based on experiments on two babies and three adults.

Identification of the release history of a groundwater contaminant in non-uniform flow field through the minimum relative entropy method

NASA Astrophysics Data System (ADS)

Cupola, F.; Tanda, M. G.; Zanini, A.

2014-12-01

The interest in approaches that allow the estimation of pollutant source release in groundwater has increased exponentially over the last decades. This is due to the large number of groundwater reclamation procedures that have been carried out: the remediation is expensive and the costs can be easily shared among the different actors if the release history is known. Moreover, a reliable release history can be a useful tool for predicting the plume evolution and for minimizing the harmful effects of the contamination. In this framework, Woodbury and Ulrych (1993, 1996) adopted and improved the minimum relative entropy (MRE) method to solve linear inverse problems for the recovery of the pollutant release history in an aquifer. In this work, the MRE method has been improved to detect the source release history in 2-D aquifer characterized by a non-uniform flow-field. The approach has been tested on two cases: a 2-D homogeneous conductivity field and a strong heterogeneous one (the hydraulic conductivity presents three orders of magnitude in terms of variability). In the latter case the transfer function could not be described with an analytical formulation, thus, the transfer functions were estimated by means of the method developed by Butera et al. (2006). In order to demonstrate its scope, this method was applied with two different datasets: observations collected at the same time at 20 different monitoring points, and observations collected at 2 monitoring points at different times (15-25 monitoring points). The data observed were considered affected by a random error. These study cases have been carried out considering a Boxcar and a Gaussian function as expected value of the prior distribution of the release history. The agreement between the true and the estimated release history has been evaluated through the calculation of the normalized Root Mean Square (nRMSE) error: this has shown the ability of the method of recovering the release history even in the most severe cases. Finally, the forward simulation has been carried out by using the estimated release history in order to compare the true data with the estimated one: the best agreement has been obtained in the homogeneous case, even if also in the heterogenous one the nRMSE is acceptable.

A Doppler centroid estimation algorithm for SAR systems optimized for the quasi-homogeneous source

NASA Technical Reports Server (NTRS)

Jin, Michael Y.

1989-01-01

Radar signal processing applications frequently require an estimate of the Doppler centroid of a received signal. The Doppler centroid estimate is required for synthetic aperture radar (SAR) processing. It is also required for some applications involving target motion estimation and antenna pointing direction estimation. In some cases, the Doppler centroid can be accurately estimated based on available information regarding the terrain topography, the relative motion between the sensor and the terrain, and the antenna pointing direction. Often, the accuracy of the Doppler centroid estimate can be improved by analyzing the characteristics of the received SAR signal. This kind of signal processing is also referred to as clutterlock processing. A Doppler centroid estimation (DCE) algorithm is described which contains a linear estimator optimized for the type of terrain surface that can be modeled by a quasi-homogeneous source (QHS). Information on the following topics is presented: (1) an introduction to the theory of Doppler centroid estimation; (2) analysis of the performance characteristics of previously reported DCE algorithms; (3) comparison of these analysis results with experimental results; (4) a description and performance analysis of a Doppler centroid estimator which is optimized for a QHS; and (5) comparison of the performance of the optimal QHS Doppler centroid estimator with that of previously reported methods.

Inter-comparison of interpolated background nitrogen dioxide concentrations across Greater Manchester, UK

NASA Astrophysics Data System (ADS)

Lindley, S. J.; Walsh, T.

There are many modelling methods dedicated to the estimation of spatial patterns in pollutant concentrations, each with their distinctive advantages and disadvantages. The derivation of a surface of air quality values from monitoring data alone requires the conversion of point-based data from a limited number of monitoring stations to a continuous surface using interpolation. Since interpolation techniques involve the estimation of data at un-sampled points based on calculated relationships between data measured at a number of known sample points, they are subject to some uncertainty, both in terms of the values estimated and their spatial distribution. These uncertainties, which are incorporated into many empirical and semi-empirical mapping methodologies, could be recognised in any further usage of the data and also in the assessment of the extent of an exceedence of an air quality standard and the degree of exposure this may represent. There is a wide range of available interpolation techniques and the differences in the characteristics of these result in variations in the output surfaces estimated from the same set of input points. The work presented in this paper provides an examination of uncertainties through the application of a number of interpolation techniques available in standard GIS packages to a case study nitrogen dioxide data set for the Greater Manchester conurbation in northern England. The implications of the use of different techniques are discussed through application to hourly concentrations during an air quality episode and annual average concentrations in 2001. Patterns of concentrations demonstrate considerable differences in the estimated spatial pattern of maxima as the combined effects of chemical processes, topography and meteorology. In the case of air quality episodes, the considerable spatial variability of concentrations results in large uncertainties in the surfaces produced but these uncertainties vary widely from area to area. In view of the uncertainties with classical techniques research is ongoing to develop alternative methods which should in time help improve the suite of tools available to air quality managers.

Comparison of bipolar vs. tripolar concentric ring electrode Laplacian estimates.

PubMed

Besio, W; Aakula, R; Dai, W

2004-01-01

Potentials on the body surface from the heart are of a spatial and temporal function. The 12-lead electrocardiogram (ECG) provides useful global temporal assessment, but it yields limited spatial information due to the smoothing effect caused by the volume conductor. The smoothing complicates identification of multiple simultaneous bioelectrical events. In an attempt to circumvent the smoothing problem, some researchers used a five-point method (FPM) to numerically estimate the analytical solution of the Laplacian with an array of monopolar electrodes. The FPM is generalized to develop a bi-polar concentric ring electrode system. We have developed a new Laplacian ECG sensor, a trielectrode sensor, based on a nine-point method (NPM) numerical approximation of the analytical Laplacian. For a comparison, the NPM, FPM and compact NPM were calculated over a 400 x 400 mesh with 1/400 spacing. Tri and bi-electrode sensors were also simulated and their Laplacian estimates were compared against the analytical Laplacian. We found that tri-electrode sensors have a much-improved accuracy with significantly less relative and maximum errors in estimating the Laplacian operator. Apart from the higher accuracy, our new electrode configuration will allow better localization of the electrical activity of the heart than bi-electrode configurations.

A model-based approach to wildland fire reconstruction using sediment charcoal records

USGS Publications Warehouse

Itter, Malcolm S.; Finley, Andrew O.; Hooten, Mevin B.; Higuera, Philip E.; Marlon, Jennifer R.; Kelly, Ryan; McLachlan, Jason S.

2017-01-01

Lake sediment charcoal records are used in paleoecological analyses to reconstruct fire history, including the identification of past wildland fires. One challenge of applying sediment charcoal records to infer fire history is the separation of charcoal associated with local fire occurrence and charcoal originating from regional fire activity. Despite a variety of methods to identify local fires from sediment charcoal records, an integrated statistical framework for fire reconstruction is lacking. We develop a Bayesian point process model to estimate the probability of fire associated with charcoal counts from individual-lake sediments and estimate mean fire return intervals. A multivariate extension of the model combines records from multiple lakes to reduce uncertainty in local fire identification and estimate a regional mean fire return interval. The univariate and multivariate models are applied to 13 lakes in the Yukon Flats region of Alaska. Both models resulted in similar mean fire return intervals (100–350 years) with reduced uncertainty under the multivariate model due to improved estimation of regional charcoal deposition. The point process model offers an integrated statistical framework for paleofire reconstruction and extends existing methods to infer regional fire history from multiple lake records with uncertainty following directly from posterior distributions.

Imputation of a true endpoint from a surrogate: application to a cluster randomized controlled trial with partial information on the true endpoint.

PubMed

Nixon, Richard M; Duffy, Stephen W; Fender, Guy R K

2003-09-24

The Anglia Menorrhagia Education Study (AMES) is a randomized controlled trial testing the effectiveness of an education package applied to general practices. Binary data are available from two sources; general practitioner reported referrals to hospital, and referrals to hospital determined by independent audit of the general practices. The former may be regarded as a surrogate for the latter, which is regarded as the true endpoint. Data are only available for the true end point on a sub set of the practices, but there are surrogate data for almost all of the audited practices and for most of the remaining practices. The aim of this paper was to estimate the treatment effect using data from every practice in the study. Where the true endpoint was not available, it was estimated by three approaches, a regression method, multiple imputation and a full likelihood model. Including the surrogate data in the analysis yielded an estimate of the treatment effect which was more precise than an estimate gained from using the true end point data alone. The full likelihood method provides a new imputation tool at the disposal of trials with surrogate data.

Estimating the vibration level of an L-shaped beam using power flow techniques

NASA Technical Reports Server (NTRS)

Cuschieri, J. M.; Mccollum, M.; Rassineux, J. L.; Gilbert, T.

1986-01-01

The response of one component of an L-shaped beam, with point force excitation on the other component, is estimated using the power flow method. The transmitted power from the source component to the receiver component is expressed in terms of the transfer and input mobilities at the excitation point and the joint. The response is estimated both in narrow frequency bands, using the exact geometry of the beams, and as a frequency averaged response using infinite beam models. The results using this power flow technique are compared to the results obtained using finite element analysis (FEA) of the L-shaped beam for the low frequency response and to results obtained using statistical energy analysis (SEA) for the high frequencies. The agreement between the FEA results and the power flow method results at low frequencies is very good. SEA results are in terms of frequency averaged levels and these are in perfect agreement with the results obtained using the infinite beam models in the power flow method. The narrow frequency band results from the power flow method also converge to the SEA results at high frequencies. The advantage of the power flow method is that detail of the response can be retained while reducing computation time, which will allow the narrow frequency band analysis of the response to be extended to higher frequencies.

Directional MTF measurement using sphere phantoms for a digital breast tomosynthesis system

NASA Astrophysics Data System (ADS)

Lee, Changwoo; Baek, Jongduk

2015-03-01

The digital breast tomosynthesis (DBT) has been widely used as a diagnosis imaging modality of breast cancer because of potential for structure noise reduction, better detectability, and less breast compression. Since 3D modulation transfer function (MTF) is one of the quantitative metrics to assess the spatial resolution of medical imaging systems, it is very important to measure 3D MTF of the DBT system to evaluate the resolution performance. In order to do that, Samei et al. used sphere phantoms and applied Thornton's method to the DBT system. However, due to the limitation of Thornton's method, the low frequency drop, caused by the limited data acquisition angle and reconstruction filters, was not measured correctly. To overcome this limitation, we propose a Richardson-Lucy (RL) deconvolution based estimation method to measure the directional MTF. We reconstructed point and sphere objects using FDK algorithm within a 40⁰ data acquisition angle. The ideal 3D MTF is obtained by taking Fourier transform of the reconstructed point object, and three directions (i.e., fx-direction, fy-direction, and fxy-direction) of the ideal 3D MTF are used as a reference. To estimate the directional MTF, the plane integrals of the reconstructed and ideal sphere object were calculated and used to estimate the directional PSF using RL deconvolution technique. Finally, the directional MTF was calculated by taking Fourier transform of the estimated PSF. Compared to the previous method, the proposed method showed a good agreement with the ideal directional MTF, especially at low frequency regions.

A comparison of moment-based methods of estimation for the log Pearson type 3 distribution

NASA Astrophysics Data System (ADS)

Koutrouvelis, I. A.; Canavos, G. C.

2000-06-01

The log Pearson type 3 distribution is a very important model in statistical hydrology, especially for modeling annual flood series. In this paper we compare the various methods based on moments for estimating quantiles of this distribution. Besides the methods of direct and mixed moments which were found most successful in previous studies and the well-known indirect method of moments, we develop generalized direct moments and generalized mixed moments methods and a new method of adaptive mixed moments. The last method chooses the orders of two moments for the original observations by utilizing information contained in the sample itself. The results of Monte Carlo experiments demonstrated the superiority of this method in estimating flood events of high return periods when a large sample is available and in estimating flood events of low return periods regardless of the sample size. In addition, a comparison of simulation and asymptotic results shows that the adaptive method may be used for the construction of meaningful confidence intervals for design events based on the asymptotic theory even with small samples. The simulation results also point to the specific members of the class of generalized moments estimates which maintain small values for bias and/or mean square error.

Control-enhanced multiparameter quantum estimation

NASA Astrophysics Data System (ADS)

Liu, Jing; Yuan, Haidong

2017-10-01

Most studies in multiparameter estimation assume the dynamics is fixed and focus on identifying the optimal probe state and the optimal measurements. In practice, however, controls are usually available to alter the dynamics, which provides another degree of freedom. In this paper we employ optimal control methods, particularly the gradient ascent pulse engineering (GRAPE), to design optimal controls for the improvement of the precision limit in multiparameter estimation. We show that the controlled schemes are not only capable to provide a higher precision limit, but also have a higher stability to the inaccuracy of the time point performing the measurements. This high time stability will benefit the practical metrology, where it is hard to perform the measurement at a very accurate time point due to the response time of the measurement apparatus.

Near-station terrain corrections for gravity data by a surface-integral technique

USGS Publications Warehouse

Gettings, M.E.

1982-01-01

A new method of computing gravity terrain corrections by use of a digitizer and digital computer can result in substantial savings in the time and manual labor required to perform such corrections by conventional manual ring-chart techniques. The method is typically applied to estimate terrain effects for topography near the station, for example within 3 km of the station, although it has been used successfully to a radius of 15 km to estimate corrections in areas where topographic mapping is poor. Points (about 20) that define topographic maxima, minima, and changes in the slope gradient are picked on the topographic map, within the desired radius of correction about the station. Particular attention must be paid to the area immediately surrounding the station to ensure a good topographic representation. The horizontal and vertical coordinates of these points are entered into the computer, usually by means of a digitizer. The computer then fits a multiquadric surface to the input points to form an analytic representation of the surface. By means of the divergence theorem, the gravity effect of an interior closed solid can be expressed as a surface integral, and the terrain correction is calculated by numerical evaluation of the integral over the surfaces of a cylinder, The vertical sides of which are at the correction radius about the station, the flat bottom surface at the topographic minimum, and the upper surface given by the multiquadric equation. The method has been tested with favorable results against models for which an exact result is available and against manually computed field-station locations in areas of rugged topography. By increasing the number of points defining the topographic surface, any desired degree of accuracy can be obtained. The method is more objective than manual ring-chart techniques because no average compartment elevations need be estimated ?

Comparison of anchor-based and distributional approaches in estimating important difference in common cold.

PubMed

Barrett, Bruce; Brown, Roger; Mundt, Marlon

2008-02-01

Evaluative health-related quality-of-life instruments used in clinical trials should be able to detect small but important changes in health status. Several approaches to minimal important difference (MID) and responsiveness have been developed. To compare anchor-based and distributional approaches to important difference and responsiveness for the Wisconsin Upper Respiratory Symptom Survey (WURSS), an illness-specific quality of life outcomes instrument. Participants with community-acquired colds self-reported daily using the WURSS-44. Distribution-based methods calculated standardized effect size (ES) and standard error of measurement (SEM). Anchor-based methods compared daily interval changes to global ratings of change, using: (1) standard MID methods based on correspondence to ratings of "a little better" or "somewhat better," and (2) two-level multivariate regression models. About 150 adults were monitored throughout their colds (1,681 sick days.): 88% were white, 69% were women, and 50% had completed college. The mean age was 35.5 years (SD = 14.7). WURSS scores increased 2.2 points from the first to second day, and then dropped by an average of 8.2 points per day from days 2 to 7. The SEM averaged 9.1 during these 7 days. Standard methods yielded a between day MID of 22 points. Regression models of MID projected 11.3-point daily changes. Dividing these estimates of small-but-important-difference by pooled SDs yielded coefficients of .425 for standard MID, .218 for regression model, .177 for SEM, and .157 for ES. These imply per-group sample sizes of 870 using ES, 616 for SEM, 302 for regression model, and 89 for standard MID, assuming alpha = .05, beta = .20 (80% power), and two-tailed testing. Distribution and anchor-based approaches provide somewhat different estimates of small but important difference, which in turn can have substantial impact on trial design.

Simultaneous Detection and Tracking of Pedestrian from Panoramic Laser Scanning Data

NASA Astrophysics Data System (ADS)

Xiao, Wen; Vallet, Bruno; Schindler, Konrad; Paparoditis, Nicolas

2016-06-01

Pedestrian traffic flow estimation is essential for public place design and construction planning. Traditional data collection by human investigation is tedious, inefficient and expensive. Panoramic laser scanners, e.g. Velodyne HDL-64E, which scan surroundings repetitively at a high frequency, have been increasingly used for 3D object tracking. In this paper, a simultaneous detection and tracking (SDAT) method is proposed for precise and automatic pedestrian trajectory recovery. First, the dynamic environment is detected using two different methods, Nearest-point and Max-distance. Then, all the points on moving objects are transferred into a space-time (x, y, t) coordinate system. The pedestrian detection and tracking amounts to assign the points belonging to pedestrians into continuous trajectories in space-time. We formulate the point assignment task as an energy function which incorporates the point evidence, trajectory number, pedestrian shape and motion. A low energy trajectory will well explain the point observations, and have plausible trajectory trend and length. The method inherently filters out points from other moving objects and false detections. The energy function is solved by a two-step optimization process: tracklet detection in a short temporal window; and global tracklet association through the whole time span. Results demonstrate that the proposed method can automatically recover the pedestrians trajectories with accurate positions and low false detections and mismatches.

Estimating IMU heading error from SAR images.

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

Doerry, Armin Walter

Angular orientation errors of the real antenna for Synthetic Aperture Radar (SAR) will manifest as undesired illumination gradients in SAR images. These gradients can be measured, and the pointing error can be calculated. This can be done for single images, but done more robustly using multi-image methods. Several methods are provided in this report. The pointing error can then be fed back to the navigation Kalman filter to correct for problematic heading (yaw) error drift. This can mitigate the need for uncomfortable and undesired IMU alignment maneuvers such as S-turns.

Performance of quantitative vegetation sampling methods across gradients of cover in Great Basin plant communities

USGS Publications Warehouse

Pilliod, David S.; Arkle, Robert S.

2013-01-01

Resource managers and scientists need efficient, reliable methods for quantifying vegetation to conduct basic research, evaluate land management actions, and monitor trends in habitat conditions. We examined three methods for quantifying vegetation in 1-ha plots among different plant communities in the northern Great Basin: photography-based grid-point intercept (GPI), line-point intercept (LPI), and point-quarter (PQ). We also evaluated each method for within-plot subsampling adequacy and effort requirements relative to information gain. We found that, for most functional groups, percent cover measurements collected with the use of LPI, GPI, and PQ methods were strongly correlated. These correlations were even stronger when we used data from the upper canopy only (i.e., top “hit” of pin flags) in LPI to estimate cover. PQ was best at quantifying cover of sparse plants such as shrubs in early successional habitats. As cover of a given functional group decreased within plots, the variance of the cover estimate increased substantially, which required more subsamples per plot (i.e., transect lines, quadrats) to achieve reliable precision. For GPI, we found that that six–nine quadrats per hectare were sufficient to characterize the vegetation in most of the plant communities sampled. All three methods reasonably characterized the vegetation in our plots, and each has advantages depending on characteristics of the vegetation, such as cover or heterogeneity, study goals, precision of measurements required, and efficiency needed.

A method of PSF generation for 3D brightfield deconvolution.

PubMed

Tadrous, P J

2010-02-01

This paper addresses the problem of 3D deconvolution of through focus widefield microscope datasets (Z-stacks). One of the most difficult stages in brightfield deconvolution is finding the point spread function. A theoretically calculated point spread function (called a 'synthetic PSF' in this paper) requires foreknowledge of many system parameters and still gives only approximate results. A point spread function measured from a sub-resolution bead suffers from low signal-to-noise ratio, compounded in the brightfield setting (by contrast to fluorescence) by absorptive, refractive and dispersal effects. This paper describes a method of point spread function estimation based on measurements of a Z-stack through a thin sample. This Z-stack is deconvolved by an idealized point spread function derived from the same Z-stack to yield a point spread function of high signal-to-noise ratio that is also inherently tailored to the imaging system. The theory is validated by a practical experiment comparing the non-blind 3D deconvolution of the yeast Saccharomyces cerevisiae with the point spread function generated using the method presented in this paper (called the 'extracted PSF') to a synthetic point spread function. Restoration of both high- and low-contrast brightfield structures is achieved with fewer artefacts using the extracted point spread function obtained with this method. Furthermore the deconvolution progresses further (more iterations are allowed before the error function reaches its nadir) with the extracted point spread function compared to the synthetic point spread function indicating that the extracted point spread function is a better fit to the brightfield deconvolution model than the synthetic point spread function.

Campground users... a computerized method for summarizing where they come from and how long they stay

Treesearch

Gary H. Elsner

1971-01-01

A computerized method for gathering market area information from campground permits has been developed. Point-of-origin and length-of-stay of campground users can be estimated and summarized quickly and inexpensively. The method should be equally useful for public as well as private campgrounds-provided basic registration data are available and can be processed...

An Empirical Method for Deriving Grade Equivalence for University Entrance Qualifications: An Application to A Levels and the International Baccalaureate

ERIC Educational Resources Information Center

Green, Francis; Vignoles, Anna

2012-01-01

We present a method to compare different qualifications for entry to higher education by studying students' subsequent performance. Using this method for students holding either the International Baccalaureate (IB) or A-levels gaining their degrees in 2010, we estimate an "empirical" equivalence scale between IB grade points and UCAS…

How large must a treatment effect be before it matters to practitioners? An estimation method and demonstration.

PubMed

Miller, William R; Manuel, Jennifer Knapp

2008-09-01

Treatment research is sometimes criticised as lacking in clinical relevance, and one potential source of this friction is a disconnection between statistical significance and what clinicians regard to be a meaningful difference in outcomes. This report demonstrates a novel methodology for estimating what substance abuse practitioners regard to be clinically important differences. To illustrate the estimation method, we surveyed 50 substance abuse treatment providers participating in the National Institute on Drug Abuse (NIDA) Clinical Trials Network. Practitioners identified thresholds for clinically meaningful differences on nine common outcome variables, indicated the size of effect that would justify their learning a new treatment method and estimated current outcomes from their services. Clinicians judged a difference between two treatments to be meaningful if outcomes were improved by about 10 - 12 points on the percentage of patients totally abstaining, arrested for driving while intoxicated, employed or having abnormal liver enzymes. A 5 percentage-point reduction in patient mortality was regarded as clinically significant. On continuous outcome measures (such as percentage of days abstinent or drinks per drinking day), practitioners judged an outcome to be significant when it doubled or halved the base rate. When a new treatment meets such criteria, practitioners were interested in learning it. Effects that are statistically significant in clinical trials may be unimpressive to practitioners. Clinicians' judgements of meaningful differences can inform the powering of clinical trials.

Micropulsed Plasma Thrusters for Attitude Control of a Low-Earth-Orbiting CubeSat

NASA Technical Reports Server (NTRS)

Gatsonis, Nikolaos A.; Lu, Ye; Blandino, John; Demetriou, Michael A.; Paschalidis, Nicholas

2016-01-01

This study presents a 3-Unit CubeSat design with commercial-off-the-shelf hardware, Teflon-fueled micropulsed plasma thrusters, and an attitude determination and control approach. The micropulsed plasma thruster is sized by the impulse bit and pulse frequency required for continuous compensation of expected maximum disturbance torques at altitudes between 400 and 1000 km, as well as to perform stabilization of up to 20 deg /s and slew maneuvers of up to 180 deg. The study involves realistic power constraints anticipated on the 3-Unit CubeSat. Attitude estimation is implemented using the q method for static attitude determination of the quaternion using pairs of the spacecraft-sun and magnetic-field vectors. The quaternion estimate and the gyroscope measurements are used with an extended Kalman filter to obtain the attitude estimates. Proportional-derivative control algorithms use the static attitude estimates in order to calculate the torque required to compensate for the disturbance torques and to achieve specified stabilization and slewing maneuvers or combinations. The controller includes a thruster-allocation method, which determines the optimal utilization of the available thrusters and introduces redundancy in case of failure. Simulation results are presented for a 3-Unit CubeSat under detumbling, pointing, and pointing and spinning scenarios, as well as comparisons between the thruster-allocation and the paired-firing methods under thruster failure.

An optical flow-based method for velocity field of fluid flow estimation

NASA Astrophysics Data System (ADS)

Głomb, Grzegorz; Świrniak, Grzegorz; Mroczka, Janusz

2017-06-01

The aim of this paper is to present a method for estimating flow-velocity vector fields using the Lucas-Kanade algorithm. The optical flow measurements are based on the Particle Image Velocimetry (PIV) technique, which is commonly used in fluid mechanics laboratories in both research institutes and industry. Common approaches for an optical characterization of velocity fields base on computation of partial derivatives of the image intensity using finite differences. Nevertheless, the accuracy of velocity field computations is low due to the fact that an exact estimation of spatial derivatives is very difficult in presence of rapid intensity changes in the PIV images, caused by particles having small diameters. The method discussed in this paper solves this problem by interpolating the PIV images using Gaussian radial basis functions. This provides a significant improvement in the accuracy of the velocity estimation but, more importantly, allows for the evaluation of the derivatives in intermediate points between pixels. Numerical analysis proves that the method is able to estimate even a separate vector for each particle with a 5× 5 px2 window, whereas a classical correlation-based method needs at least 4 particle images. With the use of a specialized multi-step hybrid approach to data analysis the method improves the estimation of the particle displacement far above 1 px.

Use of personalized Dynamic Treatment Regimes (DTRs) and Sequential Multiple Assignment Randomized Trials (SMARTs) in mental health studies

PubMed Central

Liu, Ying; ZENG, Donglin; WANG, Yuanjia

2014-01-01

Summary Dynamic treatment regimens (DTRs) are sequential decision rules tailored at each point where a clinical decision is made based on each patient’s time-varying characteristics and intermediate outcomes observed at earlier points in time. The complexity, patient heterogeneity, and chronicity of mental disorders call for learning optimal DTRs to dynamically adapt treatment to an individual’s response over time. The Sequential Multiple Assignment Randomized Trial (SMARTs) design allows for estimating causal effects of DTRs. Modern statistical tools have been developed to optimize DTRs based on personalized variables and intermediate outcomes using rich data collected from SMARTs; these statistical methods can also be used to recommend tailoring variables for designing future SMART studies. This paper introduces DTRs and SMARTs using two examples in mental health studies, discusses two machine learning methods for estimating optimal DTR from SMARTs data, and demonstrates the performance of the statistical methods using simulated data. PMID:25642116

Theoretical study of the accuracy of the elution by characteristic points method for bi-langmuir isotherms.

PubMed

Ravald, L; Fornstedt, T

2001-01-26

The bi-Langmuir equation has recently been proven essential to describe chiral chromatographic surfaces and we therefore investigated the accuracy of the elution by characteristic points method (ECP) for estimation of bi-Langmuir isotherm parameters. The ECP calculations was done on elution profiles generated by the equilibrium-dispersive model of chromatography for five different sets of bi-Langmuir parameters. The ECP method generates two different errors; (i) the error of the ECP calculated isotherm and (ii) the model error of the fitting to the ECP isotherm. Both errors decreased with increasing column efficiency. Moreover, the model error was strongly affected by the weight of the bi-Langmuir function fitted. For some bi-Langmuir compositions the error of the ECP calculated isotherm is too large even at high column efficiencies. Guidelines will be given on surface types to be avoided and on column efficiencies and loading factors required for adequate parameter estimations with ECP.

A real-time ionospheric model based on GNSS Precise Point Positioning

NASA Astrophysics Data System (ADS)

Tu, Rui; Zhang, Hongping; Ge, Maorong; Huang, Guanwen

2013-09-01

This paper proposes a method of real-time monitoring and modeling the ionospheric Total Electron Content (TEC) by Precise Point Positioning (PPP). Firstly, the ionospheric TEC and receiver’s Differential Code Biases (DCB) are estimated with the undifferenced raw observation in real-time, then the ionospheric TEC model is established based on the Single Layer Model (SLM) assumption and the recovered ionospheric TEC. In this study, phase observations with high precision are directly used instead of phase smoothed code observations. In addition, the DCB estimation is separated from the establishment of the ionospheric model which will limit the impacts of the SLM assumption impacts. The ionospheric model is established at every epoch for real time application. The method is validated with three different GNSS networks on a local, regional, and global basis. The results show that the method is feasible and effective, the real-time ionosphere and DCB results are very consistent with the IGS final products, with a bias of 1-2 TECU and 0.4 ns respectively.

A Comparison of Methods for Estimating Relationships in the Change between Two Time Points for Latent Variables

ERIC Educational Resources Information Center

Finch, W. Holmes; Shim, Sungok Serena

2018-01-01

Collection and analysis of longitudinal data is an important tool in understanding growth and development over time in a whole range of human endeavors. Ideally, researchers working in the longitudinal framework are able to collect data at more than two points in time, as this will provide them with the potential for a deeper understanding of the…

Three-Dimensional Object Recognition and Registration for Robotic Grasping Systems Using a Modified Viewpoint Feature Histogram

PubMed Central

Chen, Chin-Sheng; Chen, Po-Chun; Hsu, Chih-Ming

2016-01-01

This paper presents a novel 3D feature descriptor for object recognition and to identify poses when there are six-degrees-of-freedom for mobile manipulation and grasping applications. Firstly, a Microsoft Kinect sensor is used to capture 3D point cloud data. A viewpoint feature histogram (VFH) descriptor for the 3D point cloud data then encodes the geometry and viewpoint, so an object can be simultaneously recognized and registered in a stable pose and the information is stored in a database. The VFH is robust to a large degree of surface noise and missing depth information so it is reliable for stereo data. However, the pose estimation for an object fails when the object is placed symmetrically to the viewpoint. To overcome this problem, this study proposes a modified viewpoint feature histogram (MVFH) descriptor that consists of two parts: a surface shape component that comprises an extended fast point feature histogram and an extended viewpoint direction component. The MVFH descriptor characterizes an object’s pose and enhances the system’s ability to identify objects with mirrored poses. Finally, the refined pose is further estimated using an iterative closest point when the object has been recognized and the pose roughly estimated by the MVFH descriptor and it has been registered on a database. The estimation results demonstrate that the MVFH feature descriptor allows more accurate pose estimation. The experiments also show that the proposed method can be applied in vision-guided robotic grasping systems. PMID:27886080

Anatomy guided automated SPECT renal seed point estimation

NASA Astrophysics Data System (ADS)

Dwivedi, Shekhar; Kumar, Sailendra

2010-04-01

Quantification of SPECT(Single Photon Emission Computed Tomography) images can be more accurate if correct segmentation of region of interest (ROI) is achieved. Segmenting ROI from SPECT images is challenging due to poor image resolution. SPECT is utilized to study the kidney function, though the challenge involved is to accurately locate the kidneys and bladder for analysis. This paper presents an automated method for generating seed point location of both kidneys using anatomical location of kidneys and bladder. The motivation for this work is based on the premise that the anatomical location of the bladder relative to the kidneys will not differ much. A model is generated based on manual segmentation of the bladder and both the kidneys on 10 patient datasets (including sum and max images). Centroid is estimated for manually segmented bladder and kidneys. Relatively easier bladder segmentation is followed by feeding bladder centroid coordinates into the model to generate seed point for kidneys. Percentage error observed in centroid coordinates of organs from ground truth to estimated values from our approach are acceptable. Percentage error of approximately 1%, 6% and 2% is observed in X coordinates and approximately 2%, 5% and 8% is observed in Y coordinates of bladder, left kidney and right kidney respectively. Using a regression model and the location of the bladder, the ROI generation for kidneys is facilitated. The model based seed point estimation will enhance the robustness of kidney ROI estimation for noisy cases.

Memory persistency and nonlinearity in daily mean dew point across India

NASA Astrophysics Data System (ADS)

Ray, Rajdeep; Khondekar, Mofazzal Hossain; Ghosh, Koushik; Bhattacharjee, Anup Kumar

2016-04-01

Enterprising endeavour has been taken in this work to realize and estimate the persistence in memory of the daily mean dew point time series obtained from seven different weather stations viz. Kolkata, Chennai (Madras), New Delhi, Mumbai (Bombay), Bhopal, Agartala and Ahmedabad representing different geographical zones in India. Hurst exponent values reveal an anti-persistent behaviour of these dew point series. To affirm the Hurst exponent values, five different scaling methods have been used and the corresponding results are compared to synthesize a finer and reliable conclusion out of it. The present analysis also bespeaks that the variation in daily mean dew point is governed by a non-stationary process with stationary increments. The delay vector variance (DVV) method has been exploited to investigate nonlinearity, and the present calculation confirms the presence of deterministic nonlinear profile in the daily mean dew point time series of the seven stations.

Comparison among methods of effective energy evaluation of corn silage for beef cattle.

PubMed

Wei, Ming; Chen, Zhiqiang; Wei, Shengjuan; Geng, Guangduo; Yan, Peishi

2018-06-01

This study was conducted to compare different methods on effective energy evaluation of corn silage for beef cattle. Twenty Wandong bulls (Chinese indigenous yellow cattle) with initial body weight of 281±15.6 kg, were assigned to 1 of 5 dietary treatments with 4 animals per treatment in a randomized complete block design. Five dietary treatments included group 1 with corn silage only diet, group 2 with corn silage-concentrate basal diet (BD) and 3 groups with 3 test diets, which were the BD partly substituted by corn silage at 10%, 30%, and 60%. The total collection digestion trial was conducted for 5 d for each block after a 10-d adaptation period, and then an open-circuit respiratory cage was used to measure the gas exchange of each animal in a consecutive 4-d period. The direct method-derived metabolizable energy and net energy of corn silage were 8.86 and 5.15 MJ/kg dry matter (DM), expressed as net energy requirement for maintenance and gain were 5.28 and 2.90 MJ/kg DM, respectively; the corresponding regression method-derived estimates were 8.96, 5.34, 5.37, and 2.98 MJ/kg DM, respectively. The direct method-derived estimates were not different (p>0.05) from those obtained using the regression method. Using substitution method, the nutrient apparent digestibility and effective energy values of corn silage varied with the increased corn silage substitution ratio (p<0.05). In addition, the corn silage estimates at the substitution ratio of 30% were similar to those estimated by direct and regression methods. In determining the energy value of corn silage using substitution method, there was a discrepancy between different substitution ratios, and the substitution ratio of 30% was more appropriate than 10% or 60% in the current study. The regression method based on multiple point substitution was more appropriate than single point substitution on energy evaluation of feedstuffs for beef cattle.

Error analysis in stereo vision for location measurement of 3D point

NASA Astrophysics Data System (ADS)

Li, Yunting; Zhang, Jun; Tian, Jinwen

2015-12-01

Location measurement of 3D point in stereo vision is subjected to different sources of uncertainty that propagate to the final result. For current methods of error analysis, most of them are based on ideal intersection model to calculate the uncertainty region of point location via intersecting two fields of view of pixel that may produce loose bounds. Besides, only a few of sources of error such as pixel error or camera position are taken into account in the process of analysis. In this paper we present a straightforward and available method to estimate the location error that is taken most of source of error into account. We summed up and simplified all the input errors to five parameters by rotation transformation. Then we use the fast algorithm of midpoint method to deduce the mathematical relationships between target point and the parameters. Thus, the expectations and covariance matrix of 3D point location would be obtained, which can constitute the uncertainty region of point location. Afterwards, we turned back to the error propagation of the primitive input errors in the stereo system and throughout the whole analysis process from primitive input errors to localization error. Our method has the same level of computational complexity as the state-of-the-art method. Finally, extensive experiments are performed to verify the performance of our methods.

Quantitative Analysis of Clopidogrel Bisulphate and Aspirin by First Derivative Spectrophotometric Method in Tablets

PubMed Central

Game, Madhuri D.; Gabhane, K. B.; Sakarkar, D. M.

2010-01-01

A simple, accurate and precise spectrophotometric method has been developed for simultaneous estimation of clopidogrel bisulphate and aspirin by employing first order derivative zero crossing method. The first order derivative absorption at 232.5 nm (zero cross point of aspirin) was used for clopidogrel bisulphate and 211.3 nm (zero cross point of clopidogrel bisulphate) for aspirin.Both the drugs obeyed linearity in the concentration range of 5.0 μg/ml to 25.0 μg/ml (correlation coefficient r2<1). No interference was found between both determined constituents and those of matrix. The method was validated statistically and recovery studies were carried out to confirm the accuracy of the method. PMID:21969765

An analytic data analysis method for oscillatory slug tests.

PubMed

Chen, Chia-Shyun

2006-01-01

An analytical data analysis method is developed for slug tests in partially penetrating wells in confined or unconfined aquifers of high hydraulic conductivity. As adapted from the van der Kamp method, the determination of the hydraulic conductivity is based on the occurrence times and the displacements of the extreme points measured from the oscillatory data and their theoretical counterparts available in the literature. This method is applied to two sets of slug test response data presented by Butler et al.: one set shows slow damping with seven discernable extremities, and the other shows rapid damping with three extreme points. The estimates of the hydraulic conductivity obtained by the analytic method are in good agreement with those determined by an available curve-matching technique.

Change-in-ratio density estimator for feral pigs is less biased than closed mark-recapture estimates

USGS Publications Warehouse

Hanson, L.B.; Grand, J.B.; Mitchell, M.S.; Jolley, D.B.; Sparklin, B.D.; Ditchkoff, S.S.

2008-01-01

Closed-population capture-mark-recapture (CMR) methods can produce biased density estimates for species with low or heterogeneous detection probabilities. In an attempt to address such biases, we developed a density-estimation method based on the change in ratio (CIR) of survival between two populations where survival, calculated using an open-population CMR model, is known to differ. We used our method to estimate density for a feral pig (Sus scrofa) population on Fort Benning, Georgia, USA. To assess its validity, we compared it to an estimate of the minimum density of pigs known to be alive and two estimates based on closed-population CMR models. Comparison of the density estimates revealed that the CIR estimator produced a density estimate with low precision that was reasonable with respect to minimum known density. By contrast, density point estimates using the closed-population CMR models were less than the minimum known density, consistent with biases created by low and heterogeneous capture probabilities for species like feral pigs that may occur in low density or are difficult to capture. Our CIR density estimator may be useful for tracking broad-scale, long-term changes in species, such as large cats, for which closed CMR models are unlikely to work. ?? CSIRO 2008.

Inverse consistent non-rigid image registration based on robust point set matching

PubMed Central

2014-01-01

Background Robust point matching (RPM) has been extensively used in non-rigid registration of images to robustly register two sets of image points. However, except for the location at control points, RPM cannot estimate the consistent correspondence between two images because RPM is a unidirectional image matching approach. Therefore, it is an important issue to make an improvement in image registration based on RPM. Methods In our work, a consistent image registration approach based on the point sets matching is proposed to incorporate the property of inverse consistency and improve registration accuracy. Instead of only estimating the forward transformation between the source point sets and the target point sets in state-of-the-art RPM algorithms, the forward and backward transformations between two point sets are estimated concurrently in our algorithm. The inverse consistency constraints are introduced to the cost function of RPM and the fuzzy correspondences between two point sets are estimated based on both the forward and backward transformations simultaneously. A modified consistent landmark thin-plate spline registration is discussed in detail to find the forward and backward transformations during the optimization of RPM. The similarity of image content is also incorporated into point matching in order to improve image matching. Results Synthetic data sets, medical images are employed to demonstrate and validate the performance of our approach. The inverse consistent errors of our algorithm are smaller than RPM. Especially, the topology of transformations is preserved well for our algorithm for the large deformation between point sets. Moreover, the distance errors of our algorithm are similar to that of RPM, and they maintain a downward trend as whole, which demonstrates the convergence of our algorithm. The registration errors for image registrations are evaluated also. Again, our algorithm achieves the lower registration errors in same iteration number. The determinant of the Jacobian matrix of the deformation field is used to analyse the smoothness of the forward and backward transformations. The forward and backward transformations estimated by our algorithm are smooth for small deformation. For registration of lung slices and individual brain slices, large or small determinant of the Jacobian matrix of the deformation fields are observed. Conclusions Results indicate the improvement of the proposed algorithm in bi-directional image registration and the decrease of the inverse consistent errors of the forward and the reverse transformations between two images. PMID:25559889

Analysis of an optimization-based atomistic-to-continuum coupling method for point defects

DOE PAGES

Olson, Derek; Shapeev, Alexander V.; Bochev, Pavel B.; ...

2015-11-16

Here, we formulate and analyze an optimization-based Atomistic-to-Continuum (AtC) coupling method for problems with point defects. Application of a potential-based atomistic model near the defect core enables accurate simulation of the defect. Away from the core, where site energies become nearly independent of the lattice position, the method switches to a more efficient continuum model. The two models are merged by minimizing the mismatch of their states on an overlap region, subject to the atomistic and continuum force balance equations acting independently in their domains. We prove that the optimization problem is well-posed and establish error estimates.

Numerical method for solving the nonlinear four-point boundary value problems

NASA Astrophysics Data System (ADS)

Lin, Yingzhen; Lin, Jinnan

2010-12-01

In this paper, a new reproducing kernel space is constructed skillfully in order to solve a class of nonlinear four-point boundary value problems. The exact solution of the linear problem can be expressed in the form of series and the approximate solution of the nonlinear problem is given by the iterative formula. Compared with known investigations, the advantages of our method are that the representation of exact solution is obtained in a new reproducing kernel Hilbert space and accuracy of numerical computation is higher. Meanwhile we present the convergent theorem, complexity analysis and error estimation. The performance of the new method is illustrated with several numerical examples.

Fatigue properties of JIS H3300 C1220 copper for strain life prediction

NASA Astrophysics Data System (ADS)

Harun, Muhammad Faiz; Mohammad, Roslina

2018-05-01

The existing methods for estimating strain life parameters are dependent on the material's monotonic tensile properties. However, a few of these methods yield quite complicated expressions for calculating fatigue parameters, and are specific to certain groups of materials only. The Universal Slopes method, Modified Universal Slopes method, Uniform Material Law, the Hardness method, and Medians method are a few existing methods for predicting strain-life fatigue based on monotonic tensile material properties and hardness of material. In the present study, nine methods for estimating fatigue life and properties are applied on JIS H3300 C1220 copper to determine the best methods for strain life estimation of this ductile material. Experimental strain-life curves are compared to estimations obtained using each method. Muralidharan-Manson's Modified Universal Slopes method and Bäumel-Seeger's method for unalloyed and low-alloy steels are found to yield batter accuracy in estimating fatigue life with a deviation of less than 25%. However, the prediction of both methods only yield much better accuracy for a cycle of less than 1000 or for strain amplitudes of more than 1% and less than 6%. Manson's Original Universal Slopes method and Ong's Modified Four-Point Correlation method are found to predict the strain-life fatigue of copper with better accuracy for a high number of cycles of strain amplitudes of less than 1%. The differences between mechanical behavior during monotonic and cyclic loading and the complexity in deciding the coefficient in an equation are probably the reason for the lack of a reliable method for estimating fatigue behavior using the monotonic properties of a group of materials. It is therefore suggested that a differential approach and new expressions be developed to estimate the strain-life fatigue parameters for ductile materials such as copper.

Collaborative Indoor Access Point Localization Using Autonomous Mobile Robot Swarm

PubMed Central

Awad, Fahed; Naserllah, Muhammad; Omar, Ammar; Abu-Hantash, Alaa; Al-Taj, Abrar

2018-01-01

Localization of access points has become an important research problem due to the wide range of applications it addresses such as dismantling critical security threats caused by rogue access points or optimizing wireless coverage of access points within a service area. Existing proposed solutions have mostly relied on theoretical hypotheses or computer simulation to demonstrate the efficiency of their methods. The techniques that rely on estimating the distance using samples of the received signal strength usually assume prior knowledge of the signal propagation characteristics of the indoor environment in hand and tend to take a relatively large number of uniformly distributed random samples. This paper presents an efficient and practical collaborative approach to detect the location of an access point in an indoor environment without any prior knowledge of the environment. The proposed approach comprises a swarm of wirelessly connected mobile robots that collaboratively and autonomously collect a relatively small number of non-uniformly distributed random samples of the access point’s received signal strength. These samples are used to efficiently and accurately estimate the location of the access point. The experimental testing verified that the proposed approach can identify the location of the access point in an accurate and efficient manner. PMID:29385042

Optimal two-stage dynamic treatment regimes from a classification perspective with censored survival data.

PubMed

Hager, Rebecca; Tsiatis, Anastasios A; Davidian, Marie

2018-05-18

Clinicians often make multiple treatment decisions at key points over the course of a patient's disease. A dynamic treatment regime is a sequence of decision rules, each mapping a patient's observed history to the set of available, feasible treatment options at each decision point, and thus formalizes this process. An optimal regime is one leading to the most beneficial outcome on average if used to select treatment for the patient population. We propose a method for estimation of an optimal regime involving two decision points when the outcome of interest is a censored survival time, which is based on maximizing a locally efficient, doubly robust, augmented inverse probability weighted estimator for average outcome over a class of regimes. By casting this optimization as a classification problem, we exploit well-studied classification techniques such as support vector machines to characterize the class of regimes and facilitate implementation via a backward iterative algorithm. Simulation studies of performance and application of the method to data from a sequential, multiple assignment randomized clinical trial in acute leukemia are presented. © 2018, The International Biometric Society.

On-orbit calibration for star sensors without priori information.

PubMed

Zhang, Hao; Niu, Yanxiong; Lu, Jiazhen; Zhang, Chengfen; Yang, Yanqiang

2017-07-24

The star sensor is a prerequisite navigation device for a spacecraft. The on-orbit calibration is an essential guarantee for its operation performance. However, traditional calibration methods rely on ground information and are invalid without priori information. The uncertain on-orbit parameters will eventually influence the performance of guidance navigation and control system. In this paper, a novel calibration method without priori information for on-orbit star sensors is proposed. Firstly, the simplified back propagation neural network is designed for focal length and main point estimation along with system property evaluation, called coarse calibration. Then the unscented Kalman filter is adopted for the precise calibration of all parameters, including focal length, main point and distortion. The proposed method benefits from self-initialization and no attitude or preinstalled sensor parameter is required. Precise star sensor parameter estimation can be achieved without priori information, which is a significant improvement for on-orbit devices. Simulations and experiments results demonstrate that the calibration is easy for operation with high accuracy and robustness. The proposed method can satisfy the stringent requirement for most star sensors.

General constraints on sampling wildlife on FIA plots

USGS Publications Warehouse

Bailey, L.L.; Sauer, J.R.; Nichols, J.D.; Geissler, P.H.; McRoberts, Ronald E.; Reams, Gregory A.; Van Deusen, Paul C.; McWilliams, William H.; Cieszewski, Chris J.

2005-01-01

This paper reviews the constraints to sampling wildlife populations at FIA points. Wildlife sampling programs must have well-defined goals and provide information adequate to meet those goals. Investigators should choose a State variable based on information needs and the spatial sampling scale. We discuss estimation-based methods for three State variables: species richness, abundance, and patch occupancy. All methods incorporate two essential sources of variation: detectability estimation and spatial variation. FIA sampling imposes specific space and time criteria that may need to be adjusted to meet local wildlife objectives.

Unbiased estimation of the calcaneus volume using the Cavalieri principle on computed tomography images.

PubMed

Acer, N; Bayar, B; Basaloglu, H; Oner, E; Bayar, K; Sankur, S

2008-11-20

The size and shape of tarsal bones are especially relevant when considering some orthopedic diseases such as clubfoot. For this reason, the measurements of the tarsal bones have been the subject of many studies, none of which has used stereological methods to estimate the volume. In the present stereological study, we estimated the volume of calcaneal bone of normal feet and dry bones. We used a combination of the Cavalieri principle and computer tomographic scans taken from eight males and nine dry calcanei to estimate the volumes of calcaneal bones. The mean volume of dry calcaneal bones was estimated, producing mean results using the point-counting method and Archimedes principle being 49.11+/-10.7 or 48.22+/-11.92 cm(3), respectively. A positive correlation was found between anthropometric measurements and the volume of calcaneal bones. The findings of the present study using the stereological methods could provide data for the evaluation of normal and pathological volumes of calcaneal bones.

Soil moisture estimation using reflected solar and emitted thermal infrared radiation

NASA Technical Reports Server (NTRS)

Jackson, R. D.; Cihlar, J.; Estes, J. E.; Heilman, J. L.; Kahle, A.; Kanemasu, E. T.; Millard, J.; Price, J. C.; Wiegand, C. L.

1978-01-01

Classical methods of measuring soil moisture such as gravimetric sampling and the use of neutron moisture probes are useful for cases where a point measurement is sufficient to approximate the water content of a small surrounding area. However, there is an increasing need for rapid and repetitive estimations of soil moisture over large areas. Remote sensing techniques potentially have the capability of meeting this need. The use of reflected-solar and emitted thermal-infrared radiation, measured remotely, to estimate soil moisture is examined.

A Study of Alternative Quantile Estimation Methods in Newsboy-Type Problems

DTIC Science & Technology

1980-03-01

decision maker selects to have on hand. The newsboy cost equation may be formulated as a two-piece continuous linear function in the following manner. C(S...number of observations, some approximations may be possible. Three points which are near each other can be assumed to be linear and some estimator using...respectively. Define the value r as: r = [nq + 0.5] , (6) where [X] denotes the largest integer of X. Let us consider an estimate of X as the linear

Using a Mobile Device "App" and Proximal Remote Sensing Technologies to Assess Soil Cover Fractions on Agricultural Fields.

PubMed

Laamrani, Ahmed; Pardo Lara, Renato; Berg, Aaron A; Branson, Dave; Joosse, Pamela

2018-02-27

Quantifying the amount of crop residue left in the field after harvest is a key issue for sustainability. Conventional assessment approaches (e.g., line-transect) are labor intensive, time-consuming and costly. Many proximal remote sensing devices and systems have been developed for agricultural applications such as cover crop and residue mapping. For instance, current mobile devices (smartphones & tablets) are usually equipped with digital cameras and global positioning systems and use applications (apps) for in-field data collection and analysis. In this study, we assess the feasibility and strength of a mobile device app developed to estimate crop residue cover. The performance of this novel technique (from here on referred to as "app" method) was compared against two point counting approaches: an established digital photograph-grid method and a new automated residue counting script developed in MATLAB at the University of Guelph. Both photograph-grid and script methods were used to count residue under 100 grid points. Residue percent cover was estimated using the app, script and photograph-grid methods on 54 vertical digital photographs (images of the ground taken from above at a height of 1.5 m) collected from eighteen fields (9 corn and 9 soybean, 3 samples each) located in southern Ontario. Results showed that residue estimates from the app method were in good agreement with those obtained from both photograph-grid and script methods (R² = 0.86 and 0.84, respectively). This study has found that the app underestimates the residue coverage by -6.3% and -10.8% when compared to the photograph-grid and script methods, respectively. With regards to residue type, soybean has a slightly lower bias than corn (i.e., -5.3% vs. -7.4%). For photos with residue <30%, the app derived residue measurements are within ±5% difference (bias) of both photograph-grid- and script-derived residue measurements. These methods could therefore be used to track the recommended minimum soil residue cover of 30%, implemented to reduce farmland topsoil and nutrient losses that impact water quality. Overall, the app method was found to be a good alternative to the point counting methods, which are more time-consuming.

A new adaptive algorithm for automated feature extraction in exponentially damped signals for health monitoring of smart structures

NASA Astrophysics Data System (ADS)

Qarib, Hossein; Adeli, Hojjat

2015-12-01

In this paper authors introduce a new adaptive signal processing technique for feature extraction and parameter estimation in noisy exponentially damped signals. The iterative 3-stage method is based on the adroit integration of the strengths of parametric and nonparametric methods such as multiple signal categorization, matrix pencil, and empirical mode decomposition algorithms. The first stage is a new adaptive filtration or noise removal scheme. The second stage is a hybrid parametric-nonparametric signal parameter estimation technique based on an output-only system identification technique. The third stage is optimization of estimated parameters using a combination of the primal-dual path-following interior point algorithm and genetic algorithm. The methodology is evaluated using a synthetic signal and a signal obtained experimentally from transverse vibrations of a steel cantilever beam. The method is successful in estimating the frequencies accurately. Further, it estimates the damping exponents. The proposed adaptive filtration method does not include any frequency domain manipulation. Consequently, the time domain signal is not affected as a result of frequency domain and inverse transformations.

Application of a Threshold Method to Airborne-Spaceborne Attenuating-Wavelength Radars for the Estimation of Space-Time Rain-Rate Statistics.

NASA Astrophysics Data System (ADS)

Meneghini, Robert

1998-09-01

A method is proposed for estimating the area-average rain-rate distribution from attenuating-wavelength spaceborne or airborne radar data. Because highly attenuated radar returns yield unreliable estimates of the rain rate, these are eliminated by means of a proxy variable, Q, derived from the apparent radar reflectivity factors and a power law relating the attenuation coefficient and the reflectivity factor. In determining the probability distribution function of areawide rain rates, the elimination of attenuated measurements at high rain rates and the loss of data at light rain rates, because of low signal-to-noise ratios, leads to truncation of the distribution at the low and high ends. To estimate it over all rain rates, a lognormal distribution is assumed, the parameters of which are obtained from a nonlinear least squares fit to the truncated distribution. Implementation of this type of threshold method depends on the method used in estimating the high-resolution rain-rate estimates (e.g., either the standard Z-R or the Hitschfeld-Bordan estimate) and on the type of rain-rate estimate (either point or path averaged). To test the method, measured drop size distributions are used to characterize the rain along the radar beam. Comparisons with the standard single-threshold method or with the sample mean, taken over the high-resolution estimates, show that the present method usually provides more accurate determinations of the area-averaged rain rate if the values of the threshold parameter, QT, are chosen in the range from 0.2 to 0.4.

Genetic Algorithm for Initial Orbit Determination with Too Short Arc (Continued)

NASA Astrophysics Data System (ADS)

Li, Xin-ran; Wang, Xin

2017-04-01

When the genetic algorithm is used to solve the problem of too short-arc (TSA) orbit determination, due to the difference of computing process between the genetic algorithm and the classical method, the original method for outlier deletion is no longer applicable. In the genetic algorithm, the robust estimation is realized by introducing different loss functions for the fitness function, then the outlier problem of the TSA orbit determination is solved. Compared with the classical method, the genetic algorithm is greatly simplified by introducing in different loss functions. Through the comparison on the calculations of multiple loss functions, it is found that the least median square (LMS) estimation and least trimmed square (LTS) estimation can greatly improve the robustness of the TSA orbit determination, and have a high breakdown point.

The influence of sampling interval on the accuracy of trail impact assessment

USGS Publications Warehouse

Leung, Y.-F.; Marion, J.L.

1999-01-01

Trail impact assessment and monitoring (IA&M) programs have been growing in importance and application in recreation resource management at protected areas. Census-based and sampling-based approaches have been developed in such programs, with systematic point sampling being the most common survey design. This paper examines the influence of sampling interval on the accuracy of estimates for selected trail impact problems. A complete census of four impact types on 70 trails in Great Smoky Mountains National Park was utilized as the base data set for the analyses. The census data were resampled at increasing intervals to create a series of simulated point data sets. Estimates of frequency of occurrence and lineal extent for the four impact types were compared with the census data set. The responses of accuracy loss on lineal extent estimates to increasing sampling intervals varied across different impact types, while the responses on frequency of occurrence estimates were consistent, approximating an inverse asymptotic curve. These findings suggest that systematic point sampling may be an appropriate method for estimating the lineal extent but not the frequency of trail impacts. Sample intervals of less than 100 m appear to yield an excellent level of accuracy for the four impact types evaluated. Multiple regression analysis results suggest that appropriate sampling intervals are more likely to be determined by the type of impact in question rather than the length of trail. The census-based trail survey and the resampling-simulation method developed in this study can be a valuable first step in establishing long-term trail IA&M programs, in which an optimal sampling interval range with acceptable accuracy is determined before investing efforts in data collection.

Measuring Crack Length in Coarse Grain Ceramics

NASA Technical Reports Server (NTRS)

Salem, Jonathan A.; Ghosn, Louis J.

2010-01-01

Due to a coarse grain structure, crack lengths in precracked spinel specimens could not be measured optically, so the crack lengths and fracture toughness were estimated by strain gage measurements. An expression was developed via finite element analysis to correlate the measured strain with crack length in four-point flexure. The fracture toughness estimated by the strain gaged samples and another standardized method were in agreement.

Estimation of the lower flammability limit of organic compounds as a function of temperature.

PubMed

Rowley, J R; Rowley, R L; Wilding, W V

2011-02-15

A new method of estimating the lower flammability limit (LFL) of general organic compounds is presented. The LFL is predicted at 298 K for gases and the lower temperature limit for solids and liquids from structural contributions and the ideal gas heat of formation of the fuel. The average absolute deviation from more than 500 experimental data points is 10.7%. In a previous study, the widely used modified Burgess-Wheeler law was shown to underestimate the effect of temperature on the lower flammability limit when determined in a large-diameter vessel. An improved version of the modified Burgess-Wheeler law is presented that represents the temperature dependence of LFL data determined in large-diameter vessels more accurately. When the LFL is estimated at increased temperatures using a combination of this model and the proposed structural-contribution method, an average absolute deviation of 3.3% is returned when compared with 65 data points for 17 organic compounds determined in an ASHRAE-style apparatus. Copyright © 2010 Elsevier B.V. All rights reserved.

A Multilevel AR(1) Model: Allowing for Inter-Individual Differences in Trait-Scores, Inertia, and Innovation Variance.

PubMed

Jongerling, Joran; Laurenceau, Jean-Philippe; Hamaker, Ellen L

2015-01-01

In this article we consider a multilevel first-order autoregressive [AR(1)] model with random intercepts, random autoregression, and random innovation variance (i.e., the level 1 residual variance). Including random innovation variance is an important extension of the multilevel AR(1) model for two reasons. First, between-person differences in innovation variance are important from a substantive point of view, in that they capture differences in sensitivity and/or exposure to unmeasured internal and external factors that influence the process. Second, using simulation methods we show that modeling the innovation variance as fixed across individuals, when it should be modeled as a random effect, leads to biased parameter estimates. Additionally, we use simulation methods to compare maximum likelihood estimation to Bayesian estimation of the multilevel AR(1) model and investigate the trade-off between the number of individuals and the number of time points. We provide an empirical illustration by applying the extended multilevel AR(1) model to daily positive affect ratings from 89 married women over the course of 42 consecutive days.

5-Aminouracil treatment. A method for estimating G2.

PubMed

Socher, S H; Davidson, D

1971-02-01

Treatment of Vicia faba lateral roots with a range of concentrations of 5-aminouracil (5-AU) indicate that cells are stopped at a particular point in interphase. The timing of the fall in mitotic index suggests that cells are held at the S - G(2) transition. When cells are held at this point, treatments with 5-AU can be used to estimate the duration of G(2) + mitosis/2 of proliferating cells. Treatment with 5-AU can also be used to demonstrate the presence of subpopulations of dividing cells that differ in their G(2) duration. Using this method, 5-AU-induced inhibition, we have confirmed that in V. faba lateral roots there are two populations of dividing cells: (a) a fast-dividing population, which makes up approximately 85% of the proliferating cell population and has a G(2) + mitosis/2 duration of 3.3 hr, and (b) a slow-dividing population, which makes up approximately 15% of dividing cells and has a G(2) duration in excess of 12 hr. These estimates are similar to those obtained from percentage labeled mitosis (PLM) curves after incorporation of thymidine-(3)H.

Two cloud-based cues for estimating scene structure and camera calibration.

PubMed

Jacobs, Nathan; Abrams, Austin; Pless, Robert

2013-10-01

We describe algorithms that use cloud shadows as a form of stochastically structured light to support 3D scene geometry estimation. Taking video captured from a static outdoor camera as input, we use the relationship of the time series of intensity values between pairs of pixels as the primary input to our algorithms. We describe two cues that relate the 3D distance between a pair of points to the pair of intensity time series. The first cue results from the fact that two pixels that are nearby in the world are more likely to be under a cloud at the same time than two distant points. We describe methods for using this cue to estimate focal length and scene structure. The second cue is based on the motion of cloud shadows across the scene; this cue results in a set of linear constraints on scene structure. These constraints have an inherent ambiguity, which we show how to overcome by combining the cloud motion cue with the spatial cue. We evaluate our method on several time lapses of real outdoor scenes.