A web service system supporting three-dimensional post-processing of medical images based on WADO protocol.

PubMed

He, Longjun; Xu, Lang; Ming, Xing; Liu, Qian

2015-02-01

Three-dimensional post-processing operations on the volume data generated by a series of CT or MR images had important significance on image reading and diagnosis. As a part of the DIOCM standard, WADO service defined how to access DICOM objects on the Web, but it didn't involve three-dimensional post-processing operations on the series images. This paper analyzed the technical features of three-dimensional post-processing operations on the volume data, and then designed and implemented a web service system for three-dimensional post-processing operations of medical images based on the WADO protocol. In order to improve the scalability of the proposed system, the business tasks and calculation operations were separated into two modules. As results, it was proved that the proposed system could support three-dimensional post-processing service of medical images for multiple clients at the same moment, which met the demand of accessing three-dimensional post-processing operations on the volume data on the web.

Folding free energy surfaces of three small proteins under crowding: validation of the postprocessing method by direct simulation

NASA Astrophysics Data System (ADS)

Qin, Sanbo; Mittal, Jeetain; Zhou, Huan-Xiang

2013-08-01

We have developed a ‘postprocessing’ method for modeling biochemical processes such as protein folding under crowded conditions (Qin and Zhou 2009 Biophys. J. 97 12-19). In contrast to the direct simulation approach, in which the protein undergoing folding is simulated along with crowders, the postprocessing method requires only the folding simulation without crowders. The influence of the crowders is then obtained by taking conformations from the crowder-free simulation and calculating the free energies of transferring to the crowders. This postprocessing yields the folding free energy surface of the protein under crowding. Here the postprocessing results for the folding of three small proteins under ‘repulsive’ crowding are validated by those obtained previously by the direct simulation approach (Mittal and Best 2010 Biophys. J. 98 315-20). This validation confirms the accuracy of the postprocessing approach and highlights its distinct advantages in modeling biochemical processes under cell-like crowded conditions, such as enabling an atomistic representation of the test proteins.

Methods of practice and guidelines for using survey-grade global navigation satellite systems (GNSS) to establish vertical datum in the United States Geological Survey

USGS Publications Warehouse

Rydlund, Jr., Paul H.; Densmore, Brenda K.

2012-01-01

Geodetic surveys have evolved through the years to the use of survey-grade (centimeter level) global positioning to perpetuate and post-process vertical datum. The U.S. Geological Survey (USGS) uses Global Navigation Satellite Systems (GNSS) technology to monitor natural hazards, ensure geospatial control for climate and land use change, and gather data necessary for investigative studies related to water, the environment, energy, and ecosystems. Vertical datum is fundamental to a variety of these integrated earth sciences. Essentially GNSS surveys provide a three-dimensional position x, y, and z as a function of the North American Datum of 1983 ellipsoid and the most current hybrid geoid model. A GNSS survey may be approached with post-processed positioning for static observations related to a single point or network, or involve real-time corrections to provide positioning "on-the-fly." Field equipment required to facilitate GNSS surveys range from a single receiver, with a power source for static positioning, to an additional receiver or network communicated by radio or cellular for real-time positioning. A real-time approach in its most common form may be described as a roving receiver augmented by a single-base station receiver, known as a single-base real-time (RT) survey. More efficient real-time methods involving a Real-Time Network (RTN) permit the use of only one roving receiver that is augmented to a network of fixed receivers commonly known as Continually Operating Reference Stations (CORS). A post-processed approach in its most common form involves static data collection at a single point. Data are most commonly post-processed through a universally accepted utility maintained by the National Geodetic Survey (NGS), known as the Online Position User Service (OPUS). More complex post-processed methods involve static observations among a network of additional receivers collecting static data at known benchmarks. Both classifications provide users flexibility regarding efficiency and quality of data collection. Quality assurance of survey-grade global positioning is often overlooked or not understood and perceived uncertainties can be misleading. GNSS users can benefit from a blueprint of data collection standards used to ensure consistency among USGS mission areas. A classification of GNSS survey qualities provide the user with the ability to choose from the highest quality survey used to establish objective points with low uncertainties, identified as a Level I, to a GNSS survey for general topographic control without quality assurance, identified as a Level IV. A Level I survey is strictly limited to post-processed methods, whereas Level II, Level III, and Level IV surveys integrate variations of a RT approach. Among these classifications, techniques involving blunder checks and redundancy are important, and planning that involves the assessment of the overall satellite configuration, as well as terrestrial and space weather, are necessary to ensure an efficient and quality campaign. Although quality indicators and uncertainties are identified in post-processed methods using CORS, the accuracy of a GNSS survey is most effectively expressed as a comparison to a local benchmark that has a high degree of confidence. Real-time and post-processed methods should incorporate these "trusted" benchmarks as a check during any campaign. Global positioning surveys are expected to change rapidly in the future. The expansion of continuously operating reference stations, combined with newly available satellite signals, and enhancements to the conterminous geoid, are all sufficient indicators for substantial growth in real-time positioning and quality thereof.

A stochastic post-processing method for solar irradiance forecasts derived from NWPs models

NASA Astrophysics Data System (ADS)

Lara-Fanego, V.; Pozo-Vazquez, D.; Ruiz-Arias, J. A.; Santos-Alamillos, F. J.; Tovar-Pescador, J.

2010-09-01

Solar irradiance forecast is an important area of research for the future of the solar-based renewable energy systems. Numerical Weather Prediction models (NWPs) have proved to be a valuable tool for solar irradiance forecasting with lead time up to a few days. Nevertheless, these models show low skill in forecasting the solar irradiance under cloudy conditions. Additionally, climatic (averaged over seasons) aerosol loading are usually considered in these models, leading to considerable errors for the Direct Normal Irradiance (DNI) forecasts during high aerosols load conditions. In this work we propose a post-processing method for the Global Irradiance (GHI) and DNI forecasts derived from NWPs. Particularly, the methods is based on the use of Autoregressive Moving Average with External Explanatory Variables (ARMAX) stochastic models. These models are applied to the residuals of the NWPs forecasts and uses as external variables the measured cloud fraction and aerosol loading of the day previous to the forecast. The method is evaluated for a set one-moth length three-days-ahead forecast of the GHI and DNI, obtained based on the WRF mesoscale atmospheric model, for several locations in Andalusia (Southern Spain). The Cloud fraction is derived from MSG satellite estimates and the aerosol loading from the MODIS platform estimates. Both sources of information are readily available at the time of the forecast. Results showed a considerable improvement of the forecasting skill of the WRF model using the proposed post-processing method. Particularly, relative improvement (in terms of the RMSE) for the DNI during summer is about 20%. A similar value is obtained for the GHI during the winter.

Post processing of protein-compound docking for fragment-based drug discovery (FBDD): in-silico structure-based drug screening and ligand-binding pose prediction.

PubMed

Fukunishi, Yoshifumi

2010-01-01

For fragment-based drug development, both hit (active) compound prediction and docking-pose (protein-ligand complex structure) prediction of the hit compound are important, since chemical modification (fragment linking, fragment evolution) subsequent to the hit discovery must be performed based on the protein-ligand complex structure. However, the naïve protein-compound docking calculation shows poor accuracy in terms of docking-pose prediction. Thus, post-processing of the protein-compound docking is necessary. Recently, several methods for the post-processing of protein-compound docking have been proposed. In FBDD, the compounds are smaller than those for conventional drug screening. This makes it difficult to perform the protein-compound docking calculation. A method to avoid this problem has been reported. Protein-ligand binding free energy estimation is useful to reduce the procedures involved in the chemical modification of the hit fragment. Several prediction methods have been proposed for high-accuracy estimation of protein-ligand binding free energy. This paper summarizes the various computational methods proposed for docking-pose prediction and their usefulness in FBDD.

A comparison of performance of automatic cloud coverage assessment algorithm for Formosat-2 image using clustering-based and spatial thresholding methods

NASA Astrophysics Data System (ADS)

Hsu, Kuo-Hsien

2012-11-01

Formosat-2 image is a kind of high-spatial-resolution (2 meters GSD) remote sensing satellite data, which includes one panchromatic band and four multispectral bands (Blue, Green, Red, near-infrared). An essential sector in the daily processing of received Formosat-2 image is to estimate the cloud statistic of image using Automatic Cloud Coverage Assessment (ACCA) algorithm. The information of cloud statistic of image is subsequently recorded as an important metadata for image product catalog. In this paper, we propose an ACCA method with two consecutive stages: preprocessing and post-processing analysis. For pre-processing analysis, the un-supervised K-means classification, Sobel's method, thresholding method, non-cloudy pixels reexamination, and cross-band filter method are implemented in sequence for cloud statistic determination. For post-processing analysis, Box-Counting fractal method is implemented. In other words, the cloud statistic is firstly determined via pre-processing analysis, the correctness of cloud statistic of image of different spectral band is eventually cross-examined qualitatively and quantitatively via post-processing analysis. The selection of an appropriate thresholding method is very critical to the result of ACCA method. Therefore, in this work, We firstly conduct a series of experiments of the clustering-based and spatial thresholding methods that include Otsu's, Local Entropy(LE), Joint Entropy(JE), Global Entropy(GE), and Global Relative Entropy(GRE) method, for performance comparison. The result shows that Otsu's and GE methods both perform better than others for Formosat-2 image. Additionally, our proposed ACCA method by selecting Otsu's method as the threshoding method has successfully extracted the cloudy pixels of Formosat-2 image for accurate cloud statistic estimation.

On Fast Post-Processing of Global Positioning System Simulator Truth Data and Receiver Measurements and Solutions Data

NASA Technical Reports Server (NTRS)

Kizhner, Semion; Day, John H. (Technical Monitor)

2000-01-01

Post-processing of data, related to a GPS receiver test in a GPS simulator and test facility, is an important step towards qualifying a receiver for space flight. Although the GPS simulator provides all the parameters needed to analyze a simulation, as well as excellent analysis tools on the simulator workstation, post-processing is not a GPS simulator or receiver function alone, and it must be planned as a separate pre-flight test program requirement. A GPS simulator is a critical resource, and it is desirable to move off the pertinent test data from the simulator as soon as a test is completed. The receiver and simulator databases are used to extract the test data files for postprocessing. These files are then usually moved from the simulator and receiver systems to a personal computer (PC) platform, where post-processing is done typically using PC-based commercial software languages and tools. Because of commercial software systems generality their functions are notoriously slow and more than often are the bottleneck even for short duration simulator-based tests. There is a need to do post-processing faster and within an hour after test completion, including all required operations on the simulator and receiver to prepare and move off the post-processing files. This is especially significant in order to use the previous test feedback for the next simulation setup or to run near back-to-back simulation scenarios. Solving the post-processing timing problem is critical for a pre-flight test program success. Towards this goal an approach was developed that allows to speed-up post-processing by an order of a magnitude. It is based on improving the post-processing bottleneck function algorithm using a priory information that is specific to a GPS simulation application and using only the necessary volume of truth data. The presented postprocessing scheme was used in support of a few successful space flight missions carrying GPS receivers.

Post-processing techniques to enhance reliability of assignment algorithm based performance measures.

DOT National Transportation Integrated Search

2011-01-01

This study develops an enhanced transportation planning framework by augmenting the sequential four-step : planning process with post-processing techniques. The post-processing techniques are incorporated through a feedback : mechanism and aim to imp...

Towards an improved ensemble precipitation forecast: A probabilistic post-processing approach

NASA Astrophysics Data System (ADS)

Khajehei, Sepideh; Moradkhani, Hamid

2017-03-01

Recently, ensemble post-processing (EPP) has become a commonly used approach for reducing the uncertainty in forcing data and hence hydrologic simulation. The procedure was introduced to build ensemble precipitation forecasts based on the statistical relationship between observations and forecasts. More specifically, the approach relies on a transfer function that is developed based on a bivariate joint distribution between the observations and the simulations in the historical period. The transfer function is used to post-process the forecast. In this study, we propose a Bayesian EPP approach based on copula functions (COP-EPP) to improve the reliability of the precipitation ensemble forecast. Evaluation of the copula-based method is carried out by comparing the performance of the generated ensemble precipitation with the outputs from an existing procedure, i.e. mixed type meta-Gaussian distribution. Monthly precipitation from Climate Forecast System Reanalysis (CFS) and gridded observation from Parameter-Elevation Relationships on Independent Slopes Model (PRISM) have been employed to generate the post-processed ensemble precipitation. Deterministic and probabilistic verification frameworks are utilized in order to evaluate the outputs from the proposed technique. Distribution of seasonal precipitation for the generated ensemble from the copula-based technique is compared to the observation and raw forecasts for three sub-basins located in the Western United States. Results show that both techniques are successful in producing reliable and unbiased ensemble forecast, however, the COP-EPP demonstrates considerable improvement in the ensemble forecast in both deterministic and probabilistic verification, in particular in characterizing the extreme events in wet seasons.

On Fast Post-Processing of Global Positioning System Simulator Truth Data and Receiver Measurements and Solutions Data

NASA Technical Reports Server (NTRS)

Kizhner, Semion; Day, John H. (Technical Monitor)

2000-01-01

Post-Processing of data related to a Global Positioning System (GPS) simulation is an important activity in qualification of a GPS receiver for space flight. Because a GPS simulator is a critical resource it is desirable to move off the pertinent simulation data from the simulator as soon as a test is completed. The simulator data files are usually moved to a Personal Computer (PC), where the post-processing of the receiver logged measurements and solutions data and simulated data is performed. Typically post-processing is accomplished using PC-based commercial software languages and tools. Because of commercial software systems generality their general-purpose functions are notoriously slow and more than often are the bottleneck problem even for short duration experiments. For example, it may take 8 hours to post-process data from a 6-hour simulation. There is a need to do post-processing faster, especially in order to use the previous test results as feedback for a next simulation setup. This paper demonstrates that a fast software linear interpolation algorithm is applicable to a large class of engineering problems, like GPS simulation data post-processing, where computational time is a critical resource and is one of the most important considerations. An approach is developed that allows to speed-up post-processing by an order of magnitude. It is based on improving the post-processing bottleneck interpolation algorithm using apriori information that is specific to the GPS simulation application. The presented post-processing scheme was used in support of a few successful space flight missions carrying GPS receivers. A future approach to solving the post-processing performance problem using Field Programmable Gate Array (FPGA) technology is described.

Additive manufacturing of reflective optics: evaluating finishing methods

NASA Astrophysics Data System (ADS)

Leuteritz, G.; Lachmayer, R.

2018-02-01

Individually shaped light distributions become more and more important in lighting technologies and thus the importance of additively manufactured reflectors increases significantly. The vast field of applications ranges from automotive lighting to medical imaging and bolsters the statement. However, the surfaces of additively manufactured reflectors suffer from insufficient optical properties even when manufactured using optimized process parameters for the Selective Laser Melting (SLM) process. Therefore post-process treatments of reflectors are necessary in order to further enhance their optical quality. This work concentrates on the effectiveness of post-process procedures for reflective optics. Based on already optimized aluminum reflectors, which are manufactured with a SLM machine, the parts are differently machined after the SLM process. Selected finishing methods like laser polishing, sputtering or sand blasting are applied and their effects quantified and compared. The post-process procedures are investigated on their impact on surface roughness and reflectance as well as geometrical precision. For each finishing method a demonstrator will be created and compared to a fully milled sample and among themselves. Ultimately, guidelines are developed in order to figure out the optimal treatment of additively manufactured reflectors regarding their optical and geometrical properties. Simulations of the light distributions will be validated with the developed demonstrators.

Investigating different filter and rescaling methods on simulated GRACE-like TWS variations for hydrological applications

NASA Astrophysics Data System (ADS)

Zhang, Liangjing; Dobslaw, Henryk; Dahle, Christoph; Thomas, Maik; Neumayer, Karl-Hans; Flechtner, Frank

2017-04-01

By operating for more than one decade now, the GRACE satellite provides valuable information on the total water storage (TWS) for hydrological and hydro-meteorological applications. The increasing interest in use of the GRACE-based TWS requires an in-depth assessment of the reliability of the outputs and also its uncertainties. Through years of development, different post-processing methods have been suggested for TWS estimation. However, since GRACE offers an unique way to provide high spatial and temporal scale TWS, there is no global ground truth data available to fully validate the results. In this contribution, we re-assess a number of commonly used post-processing methods using a simulated GRACE-type gravity field time-series based on realistic orbits and instrument error assumptions as well as background error assumptions out of the updated ESA Earth System Model. Three non-isotropic filter methods from Kusche (2007) and a combined filter from DDK1 and DDK3 based on the ground tracks are tested. Rescaling factors estimated from five different hydrological models and the ensemble median are applied to the post-processed simulated GRACE-type TWS estimates to correct the bias and leakage. Time variant rescaling factors as monthly scaling factors and scaling factors for seasonal and long-term variations separately are investigated as well. Since TWS anomalies out of the post-processed simulation results can be readily compared to the time-variable Earth System Model initially used as "truth" during the forward simulation step, we are able to thoroughly check the plausibility of our error estimation assessment (Zhang et al., 2016) and will subsequently recommend a processing strategy that shall also be applied for planned GRACE and GRACE-FO Level-3 products for terrestrial applications provided by GFZ. Kusche, J., 2007:Approximate decorrelation and non-isotropic smoothing of time-variable GRACE-type gravity field models. J. Geodesy, 81 (11), 733-749, doi:10.1007/s00190-007-0143-3. Zhang L, Dobslaw H, Thomas M (2016) Globally gridded terrestrial water storage variations from GRACE satellite gravimetry for hydrometeorological applications. Geophysical Journal International 206(1):368-378, DOI 10.1093/gji/ggw153.

Post-processing of adaptive optics images based on frame selection and multi-frame blind deconvolution

NASA Astrophysics Data System (ADS)

Tian, Yu; Rao, Changhui; Wei, Kai

2008-07-01

The adaptive optics can only partially compensate the image blurred by atmospheric turbulence due to the observing condition and hardware restriction. A post-processing method based on frame selection and multi-frames blind deconvolution to improve images partially corrected by adaptive optics is proposed. The appropriate frames which are suitable for blind deconvolution from the recorded AO close-loop frames series are selected by the frame selection technique and then do the multi-frame blind deconvolution. There is no priori knowledge except for the positive constraint in blind deconvolution. It is benefit for the use of multi-frame images to improve the stability and convergence of the blind deconvolution algorithm. The method had been applied in the image restoration of celestial bodies which were observed by 1.2m telescope equipped with 61-element adaptive optical system at Yunnan Observatory. The results show that the method can effectively improve the images partially corrected by adaptive optics.

Comparison of ensemble post-processing approaches, based on empirical and dynamical error modelisation of rainfall-runoff model forecasts

NASA Astrophysics Data System (ADS)

Chardon, J.; Mathevet, T.; Le Lay, M.; Gailhard, J.

2012-04-01

In the context of a national energy company (EDF : Electricité de France), hydro-meteorological forecasts are necessary to ensure safety and security of installations, meet environmental standards and improve water ressources management and decision making. Hydrological ensemble forecasts allow a better representation of meteorological and hydrological forecasts uncertainties and improve human expertise of hydrological forecasts, which is essential to synthesize available informations, coming from different meteorological and hydrological models and human experience. An operational hydrological ensemble forecasting chain has been developed at EDF since 2008 and is being used since 2010 on more than 30 watersheds in France. This ensemble forecasting chain is characterized ensemble pre-processing (rainfall and temperature) and post-processing (streamflow), where a large human expertise is solicited. The aim of this paper is to compare 2 hydrological ensemble post-processing methods developed at EDF in order improve ensemble forecasts reliability (similar to Monatanari &Brath, 2004; Schaefli et al., 2007). The aim of the post-processing methods is to dress hydrological ensemble forecasts with hydrological model uncertainties, based on perfect forecasts. The first method (called empirical approach) is based on a statistical modelisation of empirical error of perfect forecasts, by streamflow sub-samples of quantile class and lead-time. The second method (called dynamical approach) is based on streamflow sub-samples of quantile class and streamflow variation, and lead-time. On a set of 20 watersheds used for operational forecasts, results show that both approaches are necessary to ensure a good post-processing of hydrological ensemble, allowing a good improvement of reliability, skill and sharpness of ensemble forecasts. The comparison of the empirical and dynamical approaches shows the limits of the empirical approach which is not able to take into account hydrological dynamic and processes, i. e. sample heterogeneity. For a same streamflow range corresponds different processes such as rising limbs or recession, where uncertainties are different. The dynamical approach improves reliability, skills and sharpness of forecasts and globally reduces confidence intervals width. When compared in details, the dynamical approach allows a noticeable reduction of confidence intervals during recessions where uncertainty is relatively lower and a slight increase of confidence intervals during rising limbs or snowmelt where uncertainty is greater. The dynamic approach, validated by forecaster's experience that considered the empirical approach not discriminative enough, improved forecaster's confidence and communication of uncertainties. Montanari, A. and Brath, A., (2004). A stochastic approach for assessing the uncertainty of rainfall-runoff simulations. Water Resources Research, 40, W01106, doi:10.1029/2003WR002540. Schaefli, B., Balin Talamba, D. and Musy, A., (2007). Quantifying hydrological modeling errors through a mixture of normal distributions. Journal of Hydrology, 332, 303-315.

Nowcasting Cloud Fields for U.S. Air Force Special Operations

DTIC Science & Technology

2017-03-01

application of Bayes’ Rule offers many advantages over Kernel Density Estimation (KDE) and other commonly used statistical post-processing methods...reflectance and probability of cloud. A statistical post-processing technique is applied using Bayesian estimation to train the system from a set of past...nowcasting, low cloud forecasting, cloud reflectance, ISR, Bayesian estimation, statistical post-processing, machine learning 15. NUMBER OF PAGES

Optimization of IVF pregnancy outcomes with donor spermatozoa.

PubMed

Wang, Jeff G; Douglas, Nataki C; Prosser, Robert; Kort, Daniel; Choi, Janet M; Sauer, Mark V

2009-03-01

To identify risk factors for suboptimal IVF outcomes using insemination with donor spermatozoa and to define a lower threshold that may signal a conversion to fertilization by ICSI rather than insemination. Retrospective, age-matched, case-control study of women undergoing non-donor oocyte IVF cycles using either freshly ejaculated (N=138) or cryopreserved donor spermatozoa (N=69). Associations between method of fertilization, semen sample parameters, and pregnancy rates were analyzed. In vitro fertilization of oocytes with donor spermatozoa by insemination results in equivalent fertilization and pregnancy rates compared to those of freshly ejaculated spermatozoa from men with normal semen analyses when the post-processing motility is greater than or equal to 88%. IVF by insemination with donor spermatozoa when the post-processing motility is less than 88% is associated with a 5-fold reduction in pregnancy rates when compared to those of donor spermatozoa above this motility threshold. When the post-processing donor spermatozoa motility is low, fertilization by ICSI is associated with significantly higher pregnancy rates compared to those of insemination. While ICSI does not need to be categorically instituted when using donor spermatozoa in IVF, patients should be counseled that conversion from insemination to ICSI may be recommended based on low post-processing motility.

Postprocessing of Voxel-Based Topologies for Additive Manufacturing Using the Computational Geometry Algorithms Library (CGAL)

DTIC Science & Technology

2015-06-01

10-2014 to 00-11-2014 4. TITLE AND SUBTITLE Postprocessing of Voxel-Based Topologies for Additive Manufacturing Using the Computational Geometry...ABSTRACT Postprocessing of 3-dimensional (3-D) topologies that are defined as a set of voxels using the Computational Geometry Algorithms Library (CGAL... computational geometry algorithms, several of which are suited to the task. The work flow described in this report involves first defining a set of

A Hierarchical Multivariate Bayesian Approach to Ensemble Model output Statistics in Atmospheric Prediction

DTIC Science & Technology

2017-09-01

efficacy of statistical post-processing methods downstream of these dynamical model components with a hierarchical multivariate Bayesian approach to...Bayesian hierarchical modeling, Markov chain Monte Carlo methods , Metropolis algorithm, machine learning, atmospheric prediction 15. NUMBER OF PAGES...scale processes. However, this dissertation explores the efficacy of statistical post-processing methods downstream of these dynamical model components

Total probabilities of ensemble runoff forecasts

NASA Astrophysics Data System (ADS)

Olav Skøien, Jon; Bogner, Konrad; Salamon, Peter; Smith, Paul; Pappenberger, Florian

2017-04-01

Ensemble forecasting has a long history from meteorological modelling, as an indication of the uncertainty of the forecasts. However, it is necessary to calibrate and post-process the ensembles as the they often exhibit both bias and dispersion errors. Two of the most common methods for this are Bayesian Model Averaging (Raftery et al., 2005) and Ensemble Model Output Statistics (EMOS) (Gneiting et al., 2005). There are also methods for regionalizing these methods (Berrocal et al., 2007) and for incorporating the correlation between lead times (Hemri et al., 2013). Engeland and Steinsland Engeland and Steinsland (2014) developed a framework which can estimate post-processing parameters varying in space and time, while giving a spatially and temporally consistent output. However, their method is computationally complex for our larger number of stations, which makes it unsuitable for our purpose. Our post-processing method of the ensembles is developed in the framework of the European Flood Awareness System (EFAS - http://www.efas.eu), where we are making forecasts for whole Europe, and based on observations from around 700 catchments. As the target is flood forecasting, we are also more interested in improving the forecast skill for high-flows rather than in a good prediction of the entire flow regime. EFAS uses a combination of ensemble forecasts and deterministic forecasts from different meteorological forecasters to force a distributed hydrologic model and to compute runoff ensembles for each river pixel within the model domain. Instead of showing the mean and the variability of each forecast ensemble individually, we will now post-process all model outputs to estimate the total probability, the post-processed mean and uncertainty of all ensembles. The post-processing parameters are first calibrated for each calibration location, but we are adding a spatial penalty in the calibration process to force a spatial correlation of the parameters. The penalty takes distance, stream-connectivity and size of the catchment areas into account. This can in some cases have a slight negative impact on the calibration error, but avoids large differences between parameters of nearby locations, whether stream connected or not. The spatial calibration also makes it easier to interpolate the post-processing parameters to uncalibrated locations. We also look into different methods for handling the non-normal distributions of runoff data and the effect of different data transformations on forecasts skills in general and for floods in particular. Berrocal, V. J., Raftery, A. E. and Gneiting, T.: Combining Spatial Statistical and Ensemble Information in Probabilistic Weather Forecasts, Mon. Weather Rev., 135(4), 1386-1402, doi:10.1175/MWR3341.1, 2007. Engeland, K. and Steinsland, I.: Probabilistic postprocessing models for flow forecasts for a system of catchments and several lead times, Water Resour. Res., 50(1), 182-197, doi:10.1002/2012WR012757, 2014. Gneiting, T., Raftery, A. E., Westveld, A. H. and Goldman, T.: Calibrated Probabilistic Forecasting Using Ensemble Model Output Statistics and Minimum CRPS Estimation, Mon. Weather Rev., 133(5), 1098-1118, doi:10.1175/MWR2904.1, 2005. Hemri, S., Fundel, F. and Zappa, M.: Simultaneous calibration of ensemble river flow predictions over an entire range of lead times, Water Resour. Res., 49(10), 6744-6755, doi:10.1002/wrcr.20542, 2013. Raftery, A. E., Gneiting, T., Balabdaoui, F. and Polakowski, M.: Using Bayesian Model Averaging to Calibrate Forecast Ensembles, Mon. Weather Rev., 133(5), 1155-1174, doi:10.1175/MWR2906.1, 2005.

Free energy reconstruction from steered dynamics without post-processing

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

Athenes, Manuel, E-mail: Manuel.Athenes@cea.f; Condensed Matter and Materials Division, Physics and Life Sciences Directorate, LLNL, Livermore, CA 94551; Marinica, Mihai-Cosmin

2010-09-20

Various methods achieving importance sampling in ensembles of nonequilibrium trajectories enable one to estimate free energy differences and, by maximum-likelihood post-processing, to reconstruct free energy landscapes. Here, based on Bayes theorem, we propose a more direct method in which a posterior likelihood function is used both to construct the steered dynamics and to infer the contribution to equilibrium of all the sampled states. The method is implemented with two steering schedules. First, using non-autonomous steering, we calculate the migration barrier of the vacancy in Fe-{alpha}. Second, using an autonomous scheduling related to metadynamics and equivalent to temperature-accelerated molecular dynamics, wemore » accurately reconstruct the two-dimensional free energy landscape of the 38-atom Lennard-Jones cluster as a function of an orientational bond-order parameter and energy, down to the solid-solid structural transition temperature of the cluster and without maximum-likelihood post-processing.« less

Skill of Global Raw and Postprocessed Ensemble Predictions of Rainfall over Northern Tropical Africa

NASA Astrophysics Data System (ADS)

Vogel, Peter; Knippertz, Peter; Fink, Andreas H.; Schlueter, Andreas; Gneiting, Tilmann

2018-04-01

Accumulated precipitation forecasts are of high socioeconomic importance for agriculturally dominated societies in northern tropical Africa. In this study, we analyze the performance of nine operational global ensemble prediction systems (EPSs) relative to climatology-based forecasts for 1 to 5-day accumulated precipitation based on the monsoon seasons 2007-2014 for three regions within northern tropical Africa. To assess the full potential of raw ensemble forecasts across spatial scales, we apply state-of-the-art statistical postprocessing methods in form of Bayesian Model Averaging (BMA) and Ensemble Model Output Statistics (EMOS), and verify against station and spatially aggregated, satellite-based gridded observations. Raw ensemble forecasts are uncalibrated, unreliable, and underperform relative to climatology, independently of region, accumulation time, monsoon season, and ensemble. Differences between raw ensemble and climatological forecasts are large, and partly stem from poor prediction for low precipitation amounts. BMA and EMOS postprocessed forecasts are calibrated, reliable, and strongly improve on the raw ensembles, but - somewhat disappointingly - typically do not outperform climatology. Most EPSs exhibit slight improvements over the period 2007-2014, but overall have little added value compared to climatology. We suspect that the parametrization of convection is a potential cause for the sobering lack of ensemble forecast skill in a region dominated by mesoscale convective systems.

MRI Post-processing in Pre-surgical Evaluation

PubMed Central

Wang, Z. Irene; Alexopoulos, Andreas V.

2016-01-01

Purpose of Review Advanced MRI post-processing techniques are increasingly used to complement visual analysis and elucidate structural epileptogenic lesions. This review summarizes recent developments in MRI post-processing in the context of epilepsy pre-surgical evaluation, with the focus on patients with unremarkable MRI by visual analysis (i.e., “nonlesional” MRI). Recent Findings Various methods of MRI post-processing have been reported to show additional clinical values in the following areas: (1) lesion detection on an individual level; (2) lesion confirmation for reducing the risk of over reading the MRI; (3) detection of sulcal/gyral morphologic changes that are particularly difficult for visual analysis; and (4) delineation of cortical abnormalities extending beyond the visible lesion. Future directions to improve performance of MRI post-processing include using higher magnetic field strength for better signal and contrast to noise ratio, adopting a multi-contrast frame work, and integration with other noninvasive modalities. Summary MRI post-processing can provide essential value to increase the yield of structural MRI and should be included as part of the presurgical evaluation of nonlesional epilepsies. MRI post-processing allows for more accurate identification/delineation of cortical abnormalities, which should then be more confidently targeted and mapped. PMID:26900745

Neuroimaging in epilepsy.

PubMed

Sidhu, Meneka Kaur; Duncan, John S; Sander, Josemir W

2018-05-17

Epilepsy neuroimaging is important for detecting the seizure onset zone, predicting and preventing deficits from surgery and illuminating mechanisms of epileptogenesis. An aspiration is to integrate imaging and genetic biomarkers to enable personalized epilepsy treatments. The ability to detect lesions, particularly focal cortical dysplasia and hippocampal sclerosis, is increased using ultra high-field imaging and postprocessing techniques such as automated volumetry, T2 relaxometry, voxel-based morphometry and surface-based techniques. Statistical analysis of PET and single photon emission computer tomography (STATISCOM) are superior to qualitative analysis alone in identifying focal abnormalities in MRI-negative patients. These methods have also been used to study mechanisms of epileptogenesis and pharmacoresistance.Recent language fMRI studies aim to localize, and also lateralize language functions. Memory fMRI has been recommended to lateralize mnemonic function and predict outcome after surgery in temporal lobe epilepsy. Combinations of structural, functional and post-processing methods have been used in multimodal and machine learning models to improve the identification of the seizure onset zone and increase understanding of mechanisms underlying structural and functional aberrations in epilepsy.

MGmapper: Reference based mapping and taxonomy annotation of metagenomics sequence reads

PubMed Central

Lukjancenko, Oksana; Thomsen, Martin Christen Frølund; Maddalena Sperotto, Maria; Lund, Ole; Møller Aarestrup, Frank; Sicheritz-Pontén, Thomas

2017-01-01

An increasing amount of species and gene identification studies rely on the use of next generation sequence analysis of either single isolate or metagenomics samples. Several methods are available to perform taxonomic annotations and a previous metagenomics benchmark study has shown that a vast number of false positive species annotations are a problem unless thresholds or post-processing are applied to differentiate between correct and false annotations. MGmapper is a package to process raw next generation sequence data and perform reference based sequence assignment, followed by a post-processing analysis to produce reliable taxonomy annotation at species and strain level resolution. An in-vitro bacterial mock community sample comprised of 8 genuses, 11 species and 12 strains was previously used to benchmark metagenomics classification methods. After applying a post-processing filter, we obtained 100% correct taxonomy assignments at species and genus level. A sensitivity and precision at 75% was obtained for strain level annotations. A comparison between MGmapper and Kraken at species level, shows MGmapper assigns taxonomy at species level using 84.8% of the sequence reads, compared to 70.5% for Kraken and both methods identified all species with no false positives. Extensive read count statistics are provided in plain text and excel sheets for both rejected and accepted taxonomy annotations. The use of custom databases is possible for the command-line version of MGmapper, and the complete pipeline is freely available as a bitbucked package (https://bitbucket.org/genomicepidemiology/mgmapper). A web-version (https://cge.cbs.dtu.dk/services/MGmapper) provides the basic functionality for analysis of small fastq datasets. PMID:28467460

MGmapper: Reference based mapping and taxonomy annotation of metagenomics sequence reads.

PubMed

Petersen, Thomas Nordahl; Lukjancenko, Oksana; Thomsen, Martin Christen Frølund; Maddalena Sperotto, Maria; Lund, Ole; Møller Aarestrup, Frank; Sicheritz-Pontén, Thomas

2017-01-01

An increasing amount of species and gene identification studies rely on the use of next generation sequence analysis of either single isolate or metagenomics samples. Several methods are available to perform taxonomic annotations and a previous metagenomics benchmark study has shown that a vast number of false positive species annotations are a problem unless thresholds or post-processing are applied to differentiate between correct and false annotations. MGmapper is a package to process raw next generation sequence data and perform reference based sequence assignment, followed by a post-processing analysis to produce reliable taxonomy annotation at species and strain level resolution. An in-vitro bacterial mock community sample comprised of 8 genuses, 11 species and 12 strains was previously used to benchmark metagenomics classification methods. After applying a post-processing filter, we obtained 100% correct taxonomy assignments at species and genus level. A sensitivity and precision at 75% was obtained for strain level annotations. A comparison between MGmapper and Kraken at species level, shows MGmapper assigns taxonomy at species level using 84.8% of the sequence reads, compared to 70.5% for Kraken and both methods identified all species with no false positives. Extensive read count statistics are provided in plain text and excel sheets for both rejected and accepted taxonomy annotations. The use of custom databases is possible for the command-line version of MGmapper, and the complete pipeline is freely available as a bitbucked package (https://bitbucket.org/genomicepidemiology/mgmapper). A web-version (https://cge.cbs.dtu.dk/services/MGmapper) provides the basic functionality for analysis of small fastq datasets.

Global gene expression analysis by combinatorial optimization.

PubMed

Ameur, Adam; Aurell, Erik; Carlsson, Mats; Westholm, Jakub Orzechowski

2004-01-01

Generally, there is a trade-off between methods of gene expression analysis that are precise but labor-intensive, e.g. RT-PCR, and methods that scale up to global coverage but are not quite as quantitative, e.g. microarrays. In the present paper, we show how how a known method of gene expression profiling (K. Kato, Nucleic Acids Res. 23, 3685-3690 (1995)), which relies on a fairly small number of steps, can be turned into a global gene expression measurement by advanced data post-processing, with potentially little loss of accuracy. Post-processing here entails solving an ancillary combinatorial optimization problem. Validation is performed on in silico experiments generated from the FANTOM data base of full-length mouse cDNA. We present two variants of the method. One uses state-of-the-art commercial software for solving problems of this kind, the other a code developed by us specifically for this purpose, released in the public domain under GPL license.

UCXp camera imaging principle and key technologies of data post-processing

NASA Astrophysics Data System (ADS)

Yuan, Fangyan; Li, Guoqing; Zuo, Zhengli; Liu, Jianmin; Wu, Liang; Yu, Xiaoping; Zhao, Haitao

2014-03-01

The large format digital aerial camera product UCXp was introduced into the Chinese market in 2008, the image consists of 17310 columns and 11310 rows with a pixel size of 6 mm. The UCXp camera has many advantages compared with the same generation camera, with multiple lenses exposed almost at the same time and no oblique lens. The camera has a complex imaging process whose principle will be detailed in this paper. On the other hand, the UCXp image post-processing method, including data pre-processing and orthophoto production, will be emphasized in this article. Based on the data of new Beichuan County, this paper will describe the data processing and effects.

Unsupervised Approaches for Post-Processing in Computationally Efficient Waveform-Similarity-Based Earthquake Detection

NASA Astrophysics Data System (ADS)

Bergen, K.; Yoon, C. E.; OReilly, O. J.; Beroza, G. C.

2015-12-01

Recent improvements in computational efficiency for waveform correlation-based detections achieved by new methods such as Fingerprint and Similarity Thresholding (FAST) promise to allow large-scale blind search for similar waveforms in long-duration continuous seismic data. Waveform similarity search applied to datasets of months to years of continuous seismic data will identify significantly more events than traditional detection methods. With the anticipated increase in number of detections and associated increase in false positives, manual inspection of the detection results will become infeasible. This motivates the need for new approaches to process the output of similarity-based detection. We explore data mining techniques for improved detection post-processing. We approach this by considering similarity-detector output as a sparse similarity graph with candidate events as vertices and similarities as weighted edges. Image processing techniques are leveraged to define candidate events and combine results individually processed at multiple stations. Clustering and graph analysis methods are used to identify groups of similar waveforms and assign a confidence score to candidate detections. Anomaly detection and classification are applied to waveform data for additional false detection removal. A comparison of methods will be presented and their performance will be demonstrated on a suspected induced and non-induced earthquake sequence.

Active non-volatile memory post-processing

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

Kannan, Sudarsun; Milojicic, Dejan S.; Talwar, Vanish

A computing node includes an active Non-Volatile Random Access Memory (NVRAM) component which includes memory and a sub-processor component. The memory is to store data chunks received from a processor core, the data chunks comprising metadata indicating a type of post-processing to be performed on data within the data chunks. The sub-processor component is to perform post-processing of said data chunks based on said metadata.

Possible world based consistency learning model for clustering and classifying uncertain data.

PubMed

Liu, Han; Zhang, Xianchao; Zhang, Xiaotong

2018-06-01

Possible world has shown to be effective for handling various types of data uncertainty in uncertain data management. However, few uncertain data clustering and classification algorithms are proposed based on possible world. Moreover, existing possible world based algorithms suffer from the following issues: (1) they deal with each possible world independently and ignore the consistency principle across different possible worlds; (2) they require the extra post-processing procedure to obtain the final result, which causes that the effectiveness highly relies on the post-processing method and the efficiency is also not very good. In this paper, we propose a novel possible world based consistency learning model for uncertain data, which can be extended both for clustering and classifying uncertain data. This model utilizes the consistency principle to learn a consensus affinity matrix for uncertain data, which can make full use of the information across different possible worlds and then improve the clustering and classification performance. Meanwhile, this model imposes a new rank constraint on the Laplacian matrix of the consensus affinity matrix, thereby ensuring that the number of connected components in the consensus affinity matrix is exactly equal to the number of classes. This also means that the clustering and classification results can be directly obtained without any post-processing procedure. Furthermore, for the clustering and classification tasks, we respectively derive the efficient optimization methods to solve the proposed model. Experimental results on real benchmark datasets and real world uncertain datasets show that the proposed model outperforms the state-of-the-art uncertain data clustering and classification algorithms in effectiveness and performs competitively in efficiency. Copyright © 2018 Elsevier Ltd. All rights reserved.

Comparison of breast percent density estimation from raw versus processed digital mammograms

NASA Astrophysics Data System (ADS)

Li, Diane; Gavenonis, Sara; Conant, Emily; Kontos, Despina

2011-03-01

We compared breast percent density (PD%) measures obtained from raw and post-processed digital mammographic (DM) images. Bilateral raw and post-processed medio-lateral oblique (MLO) images from 81 screening studies were retrospectively analyzed. Image acquisition was performed with a GE Healthcare DS full-field DM system. Image post-processing was performed using the PremiumViewTM algorithm (GE Healthcare). Area-based breast PD% was estimated by a radiologist using a semi-automated image thresholding technique (Cumulus, Univ. Toronto). Comparison of breast PD% between raw and post-processed DM images was performed using the Pearson correlation (r), linear regression, and Student's t-test. Intra-reader variability was assessed with a repeat read on the same data-set. Our results show that breast PD% measurements from raw and post-processed DM images have a high correlation (r=0.98, R2=0.95, p<0.001). Paired t-test comparison of breast PD% between the raw and the post-processed images showed a statistically significant difference equal to 1.2% (p = 0.006). Our results suggest that the relatively small magnitude of the absolute difference in PD% between raw and post-processed DM images is unlikely to be clinically significant in breast cancer risk stratification. Therefore, it may be feasible to use post-processed DM images for breast PD% estimation in clinical settings. Since most breast imaging clinics routinely use and store only the post-processed DM images, breast PD% estimation from post-processed data may accelerate the integration of breast density in breast cancer risk assessment models used in clinical practice.

Microstructure and Mechanical Properties of Microwave Post-processed Ni Coating

NASA Astrophysics Data System (ADS)

Zafar, Sunny; Sharma, Apurbba Kumar

2017-03-01

Flame-sprayed coatings are widely used in the industries attributed to their low cost and simple processing. However, the presence of porosity and poor adhesion with the substrate requires suitable post-processing of the as-sprayed deposits. In the present work, post-processing of the flame-sprayed Ni-based coating has been successfully attempted using microwave hybrid heating. Microwave post-processing of the flame-sprayed coatings was carried out at 2.45 GHz in a 1 kW multimode industrial microwave applicator. The microwave-processed and as-sprayed deposits were characterized for their microstructure, porosity, fracture toughness and surface roughness. The properties of the coatings were correlated with their abrasive wear behavior using a sliding abrasion test on a pin-on-disk tribometer. Microwave post-processing led to healed micropores and microcracks, thus causing homogenization of the microstructure in the coating layer. Therefore, microwave post-processed coating layer exhibits improved mechanical and tribological properties compared to the as-sprayed coating layer.

Postprocessing for character recognition using pattern features and linguistic information

NASA Astrophysics Data System (ADS)

Yoshikawa, Takatoshi; Okamoto, Masayosi; Horii, Hiroshi

1993-04-01

We propose a new method of post-processing for character recognition using pattern features and linguistic information. This method corrects errors in the recognition of handwritten Japanese sentences containing Kanji characters. This post-process method is characterized by having two types of character recognition. Improving the accuracy of the character recognition rate of Japanese characters is made difficult by the large number of characters, and the existence of characters with similar patterns. Therefore, it is not practical for a character recognition system to recognize all characters in detail. First, this post-processing method generates a candidate character table by recognizing the simplest features of characters. Then, it selects words corresponding to the character from the candidate character table by referring to a word and grammar dictionary before selecting suitable words. If the correct character is included in the candidate character table, this process can correct an error, however, if the character is not included, it cannot correct an error. Therefore, if this method can presume a character does not exist in a candidate character table by using linguistic information (word and grammar dictionary). It then can verify a presumed character by character recognition using complex features. When this method is applied to an online character recognition system, the accuracy of character recognition improves 93.5% to 94.7%. This proved to be the case when it was used for the editorials of a Japanese newspaper (Asahi Shinbun).

Commercialisation of CMOS integrated circuit technology in multi-electrode arrays for neuroscience and cell-based biosensors.

PubMed

Graham, Anthony H D; Robbins, Jon; Bowen, Chris R; Taylor, John

2011-01-01

The adaptation of standard integrated circuit (IC) technology as a transducer in cell-based biosensors in drug discovery pharmacology, neural interface systems and electrophysiology requires electrodes that are electrochemically stable, biocompatible and affordable. Unfortunately, the ubiquitous Complementary Metal Oxide Semiconductor (CMOS) IC technology does not meet the first of these requirements. For devices intended only for research, modification of CMOS by post-processing using cleanroom facilities has been achieved. However, to enable adoption of CMOS as a basis for commercial biosensors, the economies of scale of CMOS fabrication must be maintained by using only low-cost post-processing techniques. This review highlights the methodologies employed in cell-based biosensor design where CMOS-based integrated circuits (ICs) form an integral part of the transducer system. Particular emphasis will be placed on the application of multi-electrode arrays for in vitro neuroscience applications. Identifying suitable IC packaging methods presents further significant challenges when considering specific applications. The various challenges and difficulties are reviewed and some potential solutions are presented.

Obtaining Accurate Probabilities Using Classifier Calibration

ERIC Educational Resources Information Center

Pakdaman Naeini, Mahdi

2016-01-01

Learning probabilistic classification and prediction models that generate accurate probabilities is essential in many prediction and decision-making tasks in machine learning and data mining. One way to achieve this goal is to post-process the output of classification models to obtain more accurate probabilities. These post-processing methods are…

Optimization of diffusion-weighted single-refocused spin-echo EPI by reducing eddy-current artifacts and shortening the echo time.

PubMed

Shrestha, Manoj; Hok, Pavel; Nöth, Ulrike; Lienerth, Bianca; Deichmann, Ralf

2018-03-30

The purpose of this work was to optimize the acquisition of diffusion-weighted (DW) single-refocused spin-echo (srSE) data without intrinsic eddy-current compensation (ECC) for an improved performance of ECC postprocessing. The rationale is that srSE sequences without ECC may yield shorter echo times (TE) and thus higher signal-to-noise ratios (SNR) than srSE or twice-refocused spin-echo (trSE) schemes with intrinsic ECC. The proposed method employs dummy scans with DW gradients to drive eddy currents into a steady state before data acquisition. Parameters of the ECC postprocessing algorithm were also optimized. Simulations were performed to obtain minimum TE values for the proposed sequence and sequences with intrinsic ECC. Experimentally, the proposed method was compared with standard DW-trSE imaging, both in vitro and in vivo. Simulations showed substantially shorter TE for the proposed method than for methods with intrinsic ECC when using shortened echo readouts. Data of the proposed method showed a marked increase in SNR. A dummy scan duration of at least 1.5 s improved performance of the ECC postprocessing algorithm. Changes proposed for the DW-srSE sequence and for the parameter setting of the postprocessing ECC algorithm considerably reduced eddy-current artifacts and provided a higher SNR.

Post-processing optimization of electrospun submicron poly(3-hydroxybutyrate) fibers to obtain continuous films of interest in food packaging applications.

PubMed

Cherpinski, Adriane; Torres-Giner, Sergio; Cabedo, Luis; Lagaron, Jose M

2017-10-01

Polyhydroxyalkanoates (PHAs) are one of the most researched family of biodegradable polymers based on renewable materials due to their thermoplastic nature and moisture resistance. The present study was targeted to investigate the preparation and characterization of poly(3-hydroxybutyrate) (PHB) films obtained through the electrospinning technique. To convert them into continuous films and then to increase their application interest in packaging, the electrospun fiber mats were subsequently post-processed by different physical treatments. Thus, the effect of annealing time and cooling method on morphology, molecular order, thermal, optical, mechanical, and barrier properties of the electrospun submicron PHB fibers was studied. Annealing at 160°C, well below the homopolyester melting point, was found to be the minimum temperature at which homogeneous transparent films were produced. The film samples that were cooled slowly after annealing showed the lowest permeability to oxygen, water vapor, and limonene. The optimally post-processed electrospun PHB fibers exhibited similar rigidity to conventional compression-molded PHA films, but with enhanced elongation at break and toughness. Films made by this electrospinning technique have many potential applications, such as in the design of barrier layers, adhesive interlayers, and coatings for fiber- and plastic-based food packaging materials.

3D freeform printing of silk fibroin.

PubMed

Rodriguez, Maria J; Dixon, Thomas A; Cohen, Eliad; Huang, Wenwen; Omenetto, Fiorenzo G; Kaplan, David L

2018-04-15

Freeform fabrication has emerged as a key direction in printing biologically-relevant materials and structures. With this emerging technology, complex structures with microscale resolution can be created in arbitrary geometries and without the limitations found in traditional bottom-up or top-down additive manufacturing methods. Recent advances in freeform printing have used the physical properties of microparticle-based granular gels as a medium for the submerged extrusion of bioinks. However, most of these techniques require post-processing or crosslinking for the removal of the printed structures (Miller et al., 2015; Jin et al., 2016) [1,2]. In this communication, we introduce a novel method for the one-step gelation of silk fibroin within a suspension of synthetic nanoclay (Laponite) and polyethylene glycol (PEG). Silk fibroin has been used as a biopolymer for bioprinting in several contexts, but chemical or enzymatic additives or bulking agents are needed to stabilize 3D structures. Our method requires no post-processing of printed structures and allows for in situ physical crosslinking of pure aqueous silk fibroin into arbitrary geometries produced through freeform 3D printing. 3D bioprinting has emerged as a technology that can produce biologically relevant structures in defined geometries with microscale resolution. Techniques for fabrication of free-standing structures by printing into granular gel media has been demonstrated previously, however, these methods require crosslinking agents and post-processing steps on printed structures. Our method utilizes one-step gelation of silk fibroin within a suspension of synthetic nanoclay (Laponite), with no need for additional crosslinking compounds or post processing of the material. This new method allows for in situ physical crosslinking of pure aqueous silk fibroin into defined geometries produced through freeform 3D printing. Copyright © 2018 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Comparison of ring artifact removal methods using flat panel detector based CT images

PubMed Central

2011-01-01

Background Ring artifacts are the concentric rings superimposed on the tomographic images often caused by the defective and insufficient calibrated detector elements as well as by the damaged scintillator crystals of the flat panel detector. It may be also generated by objects attenuating X-rays very differently in different projection direction. Ring artifact reduction techniques so far reported in the literature can be broadly classified into two groups. One category of the approaches is based on the sinogram processing also known as the pre-processing techniques and the other category of techniques perform processing on the 2-D reconstructed images, recognized as the post-processing techniques in the literature. The strength and weakness of these categories of approaches are yet to be explored from a common platform. Method In this paper, a comparative study of the two categories of ring artifact reduction techniques basically designed for the multi-slice CT instruments is presented from a common platform. For comparison, two representative algorithms from each of the two categories are selected from the published literature. A very recently reported state-of-the-art sinogram domain ring artifact correction method that classifies the ring artifacts according to their strength and then corrects the artifacts using class adaptive correction schemes is also included in this comparative study. The first sinogram domain correction method uses a wavelet based technique to detect the corrupted pixels and then using a simple linear interpolation technique estimates the responses of the bad pixels. The second sinogram based correction method performs all the filtering operations in the transform domain, i.e., in the wavelet and Fourier domain. On the other hand, the two post-processing based correction techniques actually operate on the polar transform domain of the reconstructed CT images. The first method extracts the ring artifact template vector using a homogeneity test and then corrects the CT images by subtracting the artifact template vector from the uncorrected images. The second post-processing based correction technique performs median and mean filtering on the reconstructed images to produce the corrected images. Results The performances of the comparing algorithms have been tested by using both quantitative and perceptual measures. For quantitative analysis, two different numerical performance indices are chosen. On the other hand, different types of artifact patterns, e.g., single/band ring, artifacts from defective and mis-calibrated detector elements, rings in highly structural object and also in hard object, rings from different flat-panel detectors are analyzed to perceptually investigate the strength and weakness of the five methods. An investigation has been also carried out to compare the efficacy of these algorithms in correcting the volume images from a cone beam CT with the parameters determined from one particular slice. Finally, the capability of each correction technique in retaining the image information (e.g., small object at the iso-center) accurately in the corrected CT image has been also tested. Conclusions The results show that the performances of the algorithms are limited and none is fully suitable for correcting different types of ring artifacts without introducing processing distortion to the image structure. To achieve the diagnostic quality of the corrected slices a combination of the two approaches (sinogram- and post-processing) can be used. Also the comparing methods are not suitable for correcting the volume images from a cone beam flat-panel detector based CT. PMID:21846411

POSTPROCESSING MIXED FINITE ELEMENT METHODS FOR SOLVING CAHN-HILLIARD EQUATION: METHODS AND ERROR ANALYSIS

PubMed Central

Wang, Wansheng; Chen, Long; Zhou, Jie

2015-01-01

A postprocessing technique for mixed finite element methods for the Cahn-Hilliard equation is developed and analyzed. Once the mixed finite element approximations have been computed at a fixed time on the coarser mesh, the approximations are postprocessed by solving two decoupled Poisson equations in an enriched finite element space (either on a finer grid or a higher-order space) for which many fast Poisson solvers can be applied. The nonlinear iteration is only applied to a much smaller size problem and the computational cost using Newton and direct solvers is negligible compared with the cost of the linear problem. The analysis presented here shows that this technique remains the optimal rate of convergence for both the concentration and the chemical potential approximations. The corresponding error estimate obtained in our paper, especially the negative norm error estimates, are non-trivial and different with the existing results in the literatures. PMID:27110063

A novel post-processing scheme for two-dimensional electrical impedance tomography based on artificial neural networks

PubMed Central

2017-01-01

Objective Electrical Impedance Tomography (EIT) is a powerful non-invasive technique for imaging applications. The goal is to estimate the electrical properties of living tissues by measuring the potential at the boundary of the domain. Being safe with respect to patient health, non-invasive, and having no known hazards, EIT is an attractive and promising technology. However, it suffers from a particular technical difficulty, which consists of solving a nonlinear inverse problem in real time. Several nonlinear approaches have been proposed as a replacement for the linear solver, but in practice very few are capable of stable, high-quality, and real-time EIT imaging because of their very low robustness to errors and inaccurate modeling, or because they require considerable computational effort. Methods In this paper, a post-processing technique based on an artificial neural network (ANN) is proposed to obtain a nonlinear solution to the inverse problem, starting from a linear solution. While common reconstruction methods based on ANNs estimate the solution directly from the measured data, the method proposed here enhances the solution obtained from a linear solver. Conclusion Applying a linear reconstruction algorithm before applying an ANN reduces the effects of noise and modeling errors. Hence, this approach significantly reduces the error associated with solving 2D inverse problems using machine-learning-based algorithms. Significance This work presents radical enhancements in the stability of nonlinear methods for biomedical EIT applications. PMID:29206856

Time-Resolved Influences of Functional DAT1 and COMT Variants on Visual Perception and Post-Processing

PubMed Central

Bender, Stephan; Rellum, Thomas; Freitag, Christine; Resch, Franz; Rietschel, Marcella; Treutlein, Jens; Jennen-Steinmetz, Christine; Brandeis, Daniel; Banaschewski, Tobias; Laucht, Manfred

2012-01-01

Background Dopamine plays an important role in orienting and the regulation of selective attention to relevant stimulus characteristics. Thus, we examined the influences of functional variants related to dopamine inactivation in the dopamine transporter (DAT1) and catechol-O-methyltransferase genes (COMT) on the time-course of visual processing in a contingent negative variation (CNV) task. Methods 64-channel EEG recordings were obtained from 195 healthy adolescents of a community-based sample during a continuous performance task (A-X version). Early and late CNV as well as preceding visual evoked potential components were assessed. Results Significant additive main effects of DAT1 and COMT on the occipito-temporal early CNV were observed. In addition, there was a trend towards an interaction between the two polymorphisms. Source analysis showed early CNV generators in the ventral visual stream and in frontal regions. There was a strong negative correlation between occipito-temporal visual post-processing and the frontal early CNV component. The early CNV time interval 500–1000 ms after the visual cue was specifically affected while the preceding visual perception stages were not influenced. Conclusions Late visual potentials allow the genomic imaging of dopamine inactivation effects on visual post-processing. The same specific time-interval has been found to be affected by DAT1 and COMT during motor post-processing but not motor preparation. We propose the hypothesis that similar dopaminergic mechanisms modulate working memory encoding in both the visual and motor and perhaps other systems. PMID:22844499

Commercialisation of CMOS Integrated Circuit Technology in Multi-Electrode Arrays for Neuroscience and Cell-Based Biosensors

PubMed Central

Graham, Anthony H. D.; Robbins, Jon; Bowen, Chris R.; Taylor, John

2011-01-01

The adaptation of standard integrated circuit (IC) technology as a transducer in cell-based biosensors in drug discovery pharmacology, neural interface systems and electrophysiology requires electrodes that are electrochemically stable, biocompatible and affordable. Unfortunately, the ubiquitous Complementary Metal Oxide Semiconductor (CMOS) IC technology does not meet the first of these requirements. For devices intended only for research, modification of CMOS by post-processing using cleanroom facilities has been achieved. However, to enable adoption of CMOS as a basis for commercial biosensors, the economies of scale of CMOS fabrication must be maintained by using only low-cost post-processing techniques. This review highlights the methodologies employed in cell-based biosensor design where CMOS-based integrated circuits (ICs) form an integral part of the transducer system. Particular emphasis will be placed on the application of multi-electrode arrays for in vitro neuroscience applications. Identifying suitable IC packaging methods presents further significant challenges when considering specific applications. The various challenges and difficulties are reviewed and some potential solutions are presented. PMID:22163884

Video enhancement method with color-protection post-processing

NASA Astrophysics Data System (ADS)

Kim, Youn Jin; Kwak, Youngshin

2015-01-01

The current study is aimed to propose a post-processing method for video enhancement by adopting a color-protection technique. The color-protection intends to attenuate perceptible artifacts due to over-enhancements in visually sensitive image regions such as low-chroma colors, including skin and gray objects. In addition, reducing the loss in color texture caused by the out-of-color-gamut signals is also taken into account. Consequently, color reproducibility of video sequences could be remarkably enhanced while the undesirable visual exaggerations are minimized.

STAMPS: Software Tool for Automated MRI Post-processing on a supercomputer.

PubMed

Bigler, Don C; Aksu, Yaman; Miller, David J; Yang, Qing X

2009-08-01

This paper describes a Software Tool for Automated MRI Post-processing (STAMP) of multiple types of brain MRIs on a workstation and for parallel processing on a supercomputer (STAMPS). This software tool enables the automation of nonlinear registration for a large image set and for multiple MR image types. The tool uses standard brain MRI post-processing tools (such as SPM, FSL, and HAMMER) for multiple MR image types in a pipeline fashion. It also contains novel MRI post-processing features. The STAMP image outputs can be used to perform brain analysis using Statistical Parametric Mapping (SPM) or single-/multi-image modality brain analysis using Support Vector Machines (SVMs). Since STAMPS is PBS-based, the supercomputer may be a multi-node computer cluster or one of the latest multi-core computers.

Border-oriented post-processing refinement on detected vehicle bounding box for ADAS

NASA Astrophysics Data System (ADS)

Chen, Xinyuan; Zhang, Zhaoning; Li, Minne; Li, Dongsheng

2018-04-01

We investigate a new approach for improving localization accuracy of detected vehicles for object detection in advanced driver assistance systems(ADAS). Specifically, we implement a bounding box refinement as a post-processing of the state-of-the-art object detectors (Faster R-CNN, YOLOv2, etc.). The bounding box refinement is achieved by individually adjusting each border of the detected bounding box to its target location using a regression method. We use HOG features which perform well on the edge detection of vehicles to train the regressor and the regressor is independent of the CNN-based object detectors. Experiment results on the KITTI 2012 benchmark show that we can achieve up to 6% improvements over YOLOv2 and Faster R-CNN object detectors on the IoU threshold of 0.8. Also, the proposed refinement framework is computationally light, allowing for processing one bounding box within a few milliseconds on CPU. Further, this refinement method can be added to any object detectors, especially those with high speed but less accuracy.

Micromechanics Analysis Code Post-Processing (MACPOST) User Guide. 1.0

NASA Technical Reports Server (NTRS)

Goldberg, Robert K.; Comiskey, Michele D.; Bednarcyk, Brett A.

1999-01-01

As advanced composite materials have gained wider usage. the need for analytical models and computer codes to predict the thermomechanical deformation response of these materials has increased significantly. Recently, a micromechanics technique called the generalized method of cells (GMC) has been developed, which has the capability to fulfill this -oal. Tc provide a framework for GMC, the Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC) has been developed. As MAC/GMC has been updated, significant improvements have been made to the post-processing capabilities of the code. Through the MACPOST program, which operates directly within the MSC/PATRAN graphical pre- and post-processing package, a direct link between the analysis capabilities of MAC/GMC and the post-processing capabilities of MSC/PATRAN has been established. MACPOST has simplified the production, printing. and exportation of results for unit cells analyzed by MAC/GMC. MACPOST allows different micro-level quantities to be plotted quickly and easily in contour plots. In addition, meaningful data for X-Y plots can be examined. MACPOST thus serves as an important analysis and visualization tool for the macro- and micro-level data generated by MAC/GMC. This report serves as the user's manual for the MACPOST program.

A Rotor Tip Vortex Tracing Algorithm for Image Post-Processing

NASA Technical Reports Server (NTRS)

Overmeyer, Austin D.

2015-01-01

A neurite tracing algorithm, originally developed for medical image processing, was used to trace the location of the rotor tip vortex in density gradient flow visualization images. The tracing algorithm was applied to several representative test images to form case studies. The accuracy of the tracing algorithm was compared to two current methods including a manual point and click method and a cross-correlation template method. It is shown that the neurite tracing algorithm can reduce the post-processing time to trace the vortex by a factor of 10 to 15 without compromising the accuracy of the tip vortex location compared to other methods presented in literature.

Post-processing through linear regression

NASA Astrophysics Data System (ADS)

van Schaeybroeck, B.; Vannitsem, S.

2011-03-01

Various post-processing techniques are compared for both deterministic and ensemble forecasts, all based on linear regression between forecast data and observations. In order to evaluate the quality of the regression methods, three criteria are proposed, related to the effective correction of forecast error, the optimal variability of the corrected forecast and multicollinearity. The regression schemes under consideration include the ordinary least-square (OLS) method, a new time-dependent Tikhonov regularization (TDTR) method, the total least-square method, a new geometric-mean regression (GM), a recently introduced error-in-variables (EVMOS) method and, finally, a "best member" OLS method. The advantages and drawbacks of each method are clarified. These techniques are applied in the context of the 63 Lorenz system, whose model version is affected by both initial condition and model errors. For short forecast lead times, the number and choice of predictors plays an important role. Contrarily to the other techniques, GM degrades when the number of predictors increases. At intermediate lead times, linear regression is unable to provide corrections to the forecast and can sometimes degrade the performance (GM and the best member OLS with noise). At long lead times the regression schemes (EVMOS, TDTR) which yield the correct variability and the largest correlation between ensemble error and spread, should be preferred.

Statistical post-processing of seasonal multi-model forecasts: Why is it so hard to beat the multi-model mean?

NASA Astrophysics Data System (ADS)

Siegert, Stefan

2017-04-01

Initialised climate forecasts on seasonal time scales, run several months or even years ahead, are now an integral part of the battery of products offered by climate services world-wide. The availability of seasonal climate forecasts from various modeling centres gives rise to multi-model ensemble forecasts. Post-processing such seasonal-to-decadal multi-model forecasts is challenging 1) because the cross-correlation structure between multiple models and observations can be complicated, 2) because the amount of training data to fit the post-processing parameters is very limited, and 3) because the forecast skill of numerical models tends to be low on seasonal time scales. In this talk I will review new statistical post-processing frameworks for multi-model ensembles. I will focus particularly on Bayesian hierarchical modelling approaches, which are flexible enough to capture commonly made assumptions about collective and model-specific biases of multi-model ensembles. Despite the advances in statistical methodology, it turns out to be very difficult to out-perform the simplest post-processing method, which just recalibrates the multi-model ensemble mean by linear regression. I will discuss reasons for this, which are closely linked to the specific characteristics of seasonal multi-model forecasts. I explore possible directions for improvements, for example using informative priors on the post-processing parameters, and jointly modelling forecasts and observations.

Statistical Post-Processing of Wind Speed Forecasts to Estimate Relative Economic Value

NASA Astrophysics Data System (ADS)

Courtney, Jennifer; Lynch, Peter; Sweeney, Conor

2013-04-01

The objective of this research is to get the best possible wind speed forecasts for the wind energy industry by using an optimal combination of well-established forecasting and post-processing methods. We start with the ECMWF 51 member ensemble prediction system (EPS) which is underdispersive and hence uncalibrated. We aim to produce wind speed forecasts that are more accurate and calibrated than the EPS. The 51 members of the EPS are clustered to 8 weighted representative members (RMs), chosen to minimize the within-cluster spread, while maximizing the inter-cluster spread. The forecasts are then downscaled using two limited area models, WRF and COSMO, at two resolutions, 14km and 3km. This process creates four distinguishable ensembles which are used as input to statistical post-processes requiring multi-model forecasts. Two such processes are presented here. The first, Bayesian Model Averaging, has been proven to provide more calibrated and accurate wind speed forecasts than the ECMWF EPS using this multi-model input data. The second, heteroscedastic censored regression is indicating positive results also. We compare the two post-processing methods, applied to a year of hindcast wind speed data around Ireland, using an array of deterministic and probabilistic verification techniques, such as MAE, CRPS, probability transform integrals and verification rank histograms, to show which method provides the most accurate and calibrated forecasts. However, the value of a forecast to an end-user cannot be fully quantified by just the accuracy and calibration measurements mentioned, as the relationship between skill and value is complex. Capturing the full potential of the forecast benefits also requires detailed knowledge of the end-users' weather sensitive decision-making processes and most importantly the economic impact it will have on their income. Finally, we present the continuous relative economic value of both post-processing methods to identify which is more beneficial to the wind energy industry of Ireland.

Super-Resolution for "Jilin-1" Satellite Video Imagery via a Convolutional Network.

PubMed

Xiao, Aoran; Wang, Zhongyuan; Wang, Lei; Ren, Yexian

2018-04-13

Super-resolution for satellite video attaches much significance to earth observation accuracy, and the special imaging and transmission conditions on the video satellite pose great challenges to this task. The existing deep convolutional neural-network-based methods require pre-processing or post-processing to be adapted to a high-resolution size or pixel format, leading to reduced performance and extra complexity. To this end, this paper proposes a five-layer end-to-end network structure without any pre-processing and post-processing, but imposes a reshape or deconvolution layer at the end of the network to retain the distribution of ground objects within the image. Meanwhile, we formulate a joint loss function by combining the output and high-dimensional features of a non-linear mapping network to precisely learn the desirable mapping relationship between low-resolution images and their high-resolution counterparts. Also, we use satellite video data itself as a training set, which favors consistency between training and testing images and promotes the method's practicality. Experimental results on "Jilin-1" satellite video imagery show that this method demonstrates a superior performance in terms of both visual effects and measure metrics over competing methods.

Automated detection of focal cortical dysplasia type II with surface-based magnetic resonance imaging postprocessing and machine learning.

PubMed

Jin, Bo; Krishnan, Balu; Adler, Sophie; Wagstyl, Konrad; Hu, Wenhan; Jones, Stephen; Najm, Imad; Alexopoulos, Andreas; Zhang, Kai; Zhang, Jianguo; Ding, Meiping; Wang, Shuang; Wang, Zhong Irene

2018-05-01

Focal cortical dysplasia (FCD) is a major pathology in patients undergoing surgical resection to treat pharmacoresistant epilepsy. Magnetic resonance imaging (MRI) postprocessing methods may provide essential help for detection of FCD. In this study, we utilized surface-based MRI morphometry and machine learning for automated lesion detection in a mixed cohort of patients with FCD type II from 3 different epilepsy centers. Sixty-one patients with pharmacoresistant epilepsy and histologically proven FCD type II were included in the study. The patients had been evaluated at 3 different epilepsy centers using 3 different MRI scanners. T1-volumetric sequence was used for postprocessing. A normal database was constructed with 120 healthy controls. We also included 35 healthy test controls and 15 disease test controls with histologically confirmed hippocampal sclerosis to assess specificity. Features were calculated and incorporated into a nonlinear neural network classifier, which was trained to identify lesional cluster. We optimized the threshold of the output probability map from the classifier by performing receiver operating characteristic (ROC) analyses. Success of detection was defined by overlap between the final cluster and the manual labeling. Performance was evaluated using k-fold cross-validation. The threshold of 0.9 showed optimal sensitivity of 73.7% and specificity of 90.0%. The area under the curve for the ROC analysis was 0.75, which suggests a discriminative classifier. Sensitivity and specificity were not significantly different for patients from different centers, suggesting robustness of performance. Correct detection rate was significantly lower in patients with initially normal MRI than patients with unequivocally positive MRI. Subgroup analysis showed the size of the training group and normal control database impacted classifier performance. Automated surface-based MRI morphometry equipped with machine learning showed robust performance across cohorts from different centers and scanners. The proposed method may be a valuable tool to improve FCD detection in presurgical evaluation for patients with pharmacoresistant epilepsy. Wiley Periodicals, Inc. © 2018 International League Against Epilepsy.

Adaptive target binarization method based on a dual-camera system

NASA Astrophysics Data System (ADS)

Lei, Jing; Zhang, Ping; Xu, Jiangtao; Gao, Zhiyuan; Gao, Jing

2018-01-01

An adaptive target binarization method based on a dual-camera system that contains two dynamic vision sensors was proposed. First, a preprocessing procedure of denoising is introduced to remove the noise events generated by the sensors. Then, the complete edge of the target is retrieved and represented by events based on an event mosaicking method. Third, the region of the target is confirmed by an event-to-event method. Finally, a postprocessing procedure of image open and close operations of morphology methods is adopted to remove the artifacts caused by event-to-event mismatching. The proposed binarization method has been extensively tested on numerous degraded images with nonuniform illumination, low contrast, noise, or light spots and successfully compared with other well-known binarization methods. The experimental results, which are based on visual and misclassification error criteria, show that the proposed method performs well and has better robustness on the binarization of degraded images.

Precise GPS orbits for geodesy

NASA Technical Reports Server (NTRS)

Colombo, Oscar L.

1994-01-01

The Global Positioning System (GPS) has become, in recent years, the main space-based system for surveying and navigation in many military, commercial, cadastral, mapping, and scientific applications. Better receivers, interferometric techniques (DGPS), and advances in post-processing methods have made possible to position fixed or moving receivers with sub-decimeter accuracies in a global reference frame. Improved methods for obtaining the orbits of the GPS satellites have played a major role in these achievements; this paper gives a personal view of the main developments in GPS orbit determination.

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

DTIC Science & Technology

2012-01-01

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

Application of EOF/PCA-based methods in the post-processing of GRACE derived water variations

NASA Astrophysics Data System (ADS)

Forootan, Ehsan; Kusche, Jürgen

2010-05-01

Two problems that users of monthly GRACE gravity field solutions face are 1) the presence of correlated noise in the Stokes coefficients that increases with harmonic degree and causes ‘striping', and 2) the fact that different physical signals are overlaid and difficult to separate from each other in the data. These problems are termed the signal-noise separation problem and the signal-signal separation problem. Methods that are based on principal component analysis and empirical orthogonal functions (PCA/EOF) have been frequently proposed to deal with these problems for GRACE. However, different strategies have been applied to different (spatial: global/regional, spectral: global/order-wise, geoid/equivalent water height) representations of the GRACE level 2 data products, leading to differing results and a general feeling that PCA/EOF-based methods are to be applied ‘with care'. In addition, it is known that conventional EOF/PCA methods force separated modes to be orthogonal, and that, on the other hand, to either EOFs or PCs an arbitrary orthogonal rotation can be applied. The aim of this paper is to provide a common theoretical framework and to study the application of PCA/EOF-based methods as a signal separation tool due to post-process GRACE data products. In order to investigate and illustrate the applicability of PCA/EOF-based methods, we have employed them on GRACE level 2 monthly solutions based on the Center for Space Research, University of Texas (CSR/UT) RL04 products and on the ITG-GRACE03 solutions from the University of Bonn, and on various representations of them. Our results show that EOF modes do reveal the dominating annual, semiannual and also long-periodic signals in the global water storage variations, but they also show how choosing different strategies changes the outcome and may lead to unexpected results.

A fast automatic target detection method for detecting ships in infrared scenes

NASA Astrophysics Data System (ADS)

Özertem, Kemal Arda

2016-05-01

Automatic target detection in infrared scenes is a vital task for many application areas like defense, security and border surveillance. For anti-ship missiles, having a fast and robust ship detection algorithm is crucial for overall system performance. In this paper, a straight-forward yet effective ship detection method for infrared scenes is introduced. First, morphological grayscale reconstruction is applied to the input image, followed by an automatic thresholding onto the suppressed image. For the segmentation step, connected component analysis is employed to obtain target candidate regions. At this point, it can be realized that the detection is defenseless to outliers like small objects with relatively high intensity values or the clouds. To deal with this drawback, a post-processing stage is introduced. For the post-processing stage, two different methods are used. First, noisy detection results are rejected with respect to target size. Second, the waterline is detected by using Hough transform and the detection results that are located above the waterline with a small margin are rejected. After post-processing stage, there are still undesired holes remaining, which cause to detect one object as multi objects or not to detect an object as a whole. To improve the detection performance, another automatic thresholding is implemented only to target candidate regions. Finally, two detection results are fused and post-processing stage is repeated to obtain final detection result. The performance of overall methodology is tested with real world infrared test data.

A deblocking algorithm based on color psychology for display quality enhancement

NASA Astrophysics Data System (ADS)

Yeh, Chia-Hung; Tseng, Wen-Yu; Huang, Kai-Lin

2012-12-01

This article proposes a post-processing deblocking filter to reduce blocking effects. The proposed algorithm detects blocking effects by fusing the results of Sobel edge detector and wavelet-based edge detector. The filtering stage provides four filter modes to eliminate blocking effects at different color regions according to human color vision and color psychology analysis. Experimental results show that the proposed algorithm has better subjective and objective qualities for H.264/AVC reconstructed videos when compared to several existing methods.

Super-Resolution for “Jilin-1” Satellite Video Imagery via a Convolutional Network

PubMed Central

Wang, Zhongyuan; Wang, Lei; Ren, Yexian

2018-01-01

Super-resolution for satellite video attaches much significance to earth observation accuracy, and the special imaging and transmission conditions on the video satellite pose great challenges to this task. The existing deep convolutional neural-network-based methods require pre-processing or post-processing to be adapted to a high-resolution size or pixel format, leading to reduced performance and extra complexity. To this end, this paper proposes a five-layer end-to-end network structure without any pre-processing and post-processing, but imposes a reshape or deconvolution layer at the end of the network to retain the distribution of ground objects within the image. Meanwhile, we formulate a joint loss function by combining the output and high-dimensional features of a non-linear mapping network to precisely learn the desirable mapping relationship between low-resolution images and their high-resolution counterparts. Also, we use satellite video data itself as a training set, which favors consistency between training and testing images and promotes the method’s practicality. Experimental results on “Jilin-1” satellite video imagery show that this method demonstrates a superior performance in terms of both visual effects and measure metrics over competing methods. PMID:29652838

The role of ensemble post-processing for modeling the ensemble tail

NASA Astrophysics Data System (ADS)

Van De Vyver, Hans; Van Schaeybroeck, Bert; Vannitsem, Stéphane

2016-04-01

The past decades the numerical weather prediction community has witnessed a paradigm shift from deterministic to probabilistic forecast and state estimation (Buizza and Leutbecher, 2015; Buizza et al., 2008), in an attempt to quantify the uncertainties associated with initial-condition and model errors. An important benefit of a probabilistic framework is the improved prediction of extreme events. However, one may ask to what extent such model estimates contain information on the occurrence probability of extreme events and how this information can be optimally extracted. Different approaches have been proposed and applied on real-world systems which, based on extreme value theory, allow the estimation of extreme-event probabilities conditional on forecasts and state estimates (Ferro, 2007; Friederichs, 2010). Using ensemble predictions generated with a model of low dimensionality, a thorough investigation is presented quantifying the change of predictability of extreme events associated with ensemble post-processing and other influencing factors including the finite ensemble size, lead time and model assumption and the use of different covariates (ensemble mean, maximum, spread...) for modeling the tail distribution. Tail modeling is performed by deriving extreme-quantile estimates using peak-over-threshold representation (generalized Pareto distribution) or quantile regression. Common ensemble post-processing methods aim to improve mostly the ensemble mean and spread of a raw forecast (Van Schaeybroeck and Vannitsem, 2015). Conditional tail modeling, on the other hand, is a post-processing in itself, focusing on the tails only. Therefore, it is unclear how applying ensemble post-processing prior to conditional tail modeling impacts the skill of extreme-event predictions. This work is investigating this question in details. Buizza, Leutbecher, and Isaksen, 2008: Potential use of an ensemble of analyses in the ECMWF Ensemble Prediction System, Q. J. R. Meteorol. Soc. 134: 2051-2066.Buizza and Leutbecher, 2015: The forecast skill horizon, Q. J. R. Meteorol. Soc. 141: 3366-3382.Ferro, 2007: A probability model for verifying deterministic forecasts of extreme events. Weather and Forecasting 22 (5), 1089-1100.Friederichs, 2010: Statistical downscaling of extreme precipitation events using extreme value theory. Extremes 13, 109-132.Van Schaeybroeck and Vannitsem, 2015: Ensemble post-processing using member-by-member approaches: theoretical aspects. Q.J.R. Meteorol. Soc., 141: 807-818.

Image enhancement in positron emission mammography

NASA Astrophysics Data System (ADS)

Slavine, Nikolai V.; Seiler, Stephen; McColl, Roderick W.; Lenkinski, Robert E.

2017-02-01

Purpose: To evaluate an efficient iterative deconvolution method (RSEMD) for improving the quantitative accuracy of previously reconstructed breast images by commercial positron emission mammography (PEM) scanner. Materials and Methods: The RSEMD method was tested on breast phantom data and clinical PEM imaging data. Data acquisition was performed on a commercial Naviscan Flex Solo II PEM camera. This method was applied to patient breast images previously reconstructed with Naviscan software (MLEM) to determine improvements in resolution, signal to noise ratio (SNR) and contrast to noise ratio (CNR.) Results: In all of the patients' breast studies the post-processed images proved to have higher resolution and lower noise as compared with images reconstructed by conventional methods. In general, the values of SNR reached a plateau at around 6 iterations with an improvement factor of about 2 for post-processed Flex Solo II PEM images. Improvements in image resolution after the application of RSEMD have also been demonstrated. Conclusions: A rapidly converging, iterative deconvolution algorithm with a novel resolution subsets-based approach RSEMD that operates on patient DICOM images has been used for quantitative improvement in breast imaging. The RSEMD method can be applied to clinical PEM images to improve image quality to diagnostically acceptable levels and will be crucial in order to facilitate diagnosis of tumor progression at the earliest stages. The RSEMD method can be considered as an extended Richardson-Lucy algorithm with multiple resolution levels (resolution subsets).

Automatic cloud coverage assessment of Formosat-2 image

NASA Astrophysics Data System (ADS)

Hsu, Kuo-Hsien

2011-11-01

Formosat-2 satellite equips with the high-spatial-resolution (2m ground sampling distance) remote sensing instrument. It has been being operated on the daily-revisiting mission orbit by National Space organization (NSPO) of Taiwan since May 21 2004. NSPO has also serving as one of the ground receiving stations for daily processing the received Formosat- 2 images. The current cloud coverage assessment of Formosat-2 image for NSPO Image Processing System generally consists of two major steps. Firstly, an un-supervised K-means method is used for automatically estimating the cloud statistic of Formosat-2 image. Secondly, manual estimation of cloud coverage from Formosat-2 image is processed by manual examination. Apparently, a more accurate Automatic Cloud Coverage Assessment (ACCA) method certainly increases the efficiency of processing step 2 with a good prediction of cloud statistic. In this paper, mainly based on the research results from Chang et al, Irish, and Gotoh, we propose a modified Formosat-2 ACCA method which considered pre-processing and post-processing analysis. For pre-processing analysis, cloud statistic is determined by using un-supervised K-means classification, Sobel's method, Otsu's method, non-cloudy pixels reexamination, and cross-band filter method. Box-Counting fractal method is considered as a post-processing tool to double check the results of pre-processing analysis for increasing the efficiency of manual examination.

A Novel Approach to Enhance the Mechanical Strength and Electrical and Thermal Conductivity of Cu-GNP Nanocomposites

NASA Astrophysics Data System (ADS)

Saboori, Abdollah; Pavese, Matteo; Badini, Claudio; Fino, Paolo

2018-01-01

Copper/graphene nanoplatelet (GNP) nanocomposites were produced by a wet mixing method followed by a classical powder metallurgy technique. A qualitative evaluation of the structure of graphene after mixing indicated that wet mixing is an appropriate dispersion method. Thereafter, the effects of two post-processing techniques such as repressing-annealing and hot isostatic pressing (HIP) on density, interfacial bonding, hardness, and thermal and electrical conductivity of the nanocomposites were analyzed. Density evaluations showed that the relative density of specimens increased after the post-processing steps so that after HIPing almost full densification was achieved. The Vickers hardness of specimens increased considerably after the post-processing techniques. The thermal conductivity of pure copper was very low in the case of the as-sintered samples containing 2 to 3 pct porosity and increased considerably to a maximum value in the case of HIPed samples which contained only 0.1 to 0.2 pct porosity. Electrical conductivity measurements showed that by increasing the graphene content electrical conductivity decreased.

Adaptive optics images restoration based on frame selection and multi-framd blind deconvolution

NASA Astrophysics Data System (ADS)

Tian, Y.; Rao, C. H.; Wei, K.

2008-10-01

The adaptive optics can only partially compensate the image blurred by atmospheric turbulent due to the observing condition and hardware restriction. A post-processing method based on frame selection and multi-frame blind deconvolution to improve images partially corrected by adaptive optics is proposed. The appropriate frames which are picked out by frame selection technique is deconvolved. There is no priori knowledge except the positive constraint. The method has been applied in the image restoration of celestial bodies which were observed by 1.2m telescope equipped with 61-element adaptive optical system in Yunnan Observatory. The results showed that the method can effectively improve the images partially corrected by adaptive optics.

A New Strategy for Fast MRI-Based Quantification of the Myelin Water Fraction: Application to Brain Imaging in Infants

PubMed Central

Kulikova, Sofya; Hertz-Pannier, Lucie; Dehaene-Lambertz, Ghislaine

2016-01-01

The volume fraction of water related to myelin (fmy) is a promising MRI index for in vivo assessment of brain myelination, that can be derived from multi-component analysis of T1 and T2 relaxometry signals. However, existing quantification methods require rather long acquisition and/or post-processing times, making implementation difficult both in research studies on healthy unsedated children and in clinical examinations. The goal of this work was to propose a novel strategy for fmy quantification within acceptable acquisition and post-processing times. Our approach is based on a 3-compartment model (myelin-related water, intra/extra-cellular water and unrestricted water), and uses calibrated values of inherent relaxation times (T1c and T2c) for each compartment c. Calibration was first performed on adult relaxometry datasets (N = 3) acquired with large numbers of inversion times (TI) and echo times (TE), using an original combination of a region contraction approach and a non-negative least-square (NNLS) algorithm. This strategy was compared with voxel-wise fitting, and showed robust estimation of T1c and T2c. The accuracy of fmy calculations depending on multiple factors was investigated using simulated data. In the testing stage, our strategy enabled fast fmy mapping, based on relaxometry datasets acquired with reduced TI and TE numbers (acquisition <6 min), and analyzed with NNLS algorithm (post-processing <5min). In adults (N = 13, mean age 22.4±1.6 years), fmy maps showed variability across white matter regions, in agreement with previous studies. In healthy infants (N = 18, aged 3 to 34 weeks), asynchronous changes in fmy values were demonstrated across bundles, confirming the well-known progression of myelination. PMID:27736872

Feasibility and availability of ⁶⁸Ga-labelled peptides.

PubMed

Decristoforo, Clemens; Pickett, Roger D; Verbruggen, Alfons

2012-02-01

(68)Ga has attracted tremendous interest as a radionuclide for PET based on its suitable half-life of 68 min, high positron emission yield and ready availability from (68)Ge/(68)Ga generators, making it independent of cyclotron production. (68)Ga-labelled DOTA-conjugated somatostatin analogues, including DOTA-TOC, DOTA-TATE and DOTA-NOC, have driven the development of technologies to provide such radiopharmaceuticals for clinical applications mainly in the diagnosis of somatostatin receptor-expressing tumours. We summarize the issues determining the feasibility and availability of (68)Ga-labelled peptides, including generator technology, (68)Ga generator eluate postprocessing methods, radiolabelling, automation and peptide developments, and also quality assurance and regulatory aspects. (68)Ge/(68)Ga generators based on SnO(2), TiO(2) or organic matrices are today routinely supplied to nuclear medicine departments, and a variety of automated systems for postprocessing and radiolabelling have been developed. New developments include improved chelators for (68)Ga that could open new ways to utilize this technology. Challenges and limitations in the on-site preparation and use of (68)Ga-labelled peptides outside the marketing authorization track are also discussed.

Knowledge-guided golf course detection using a convolutional neural network fine-tuned on temporally augmented data

NASA Astrophysics Data System (ADS)

Chen, Jingbo; Wang, Chengyi; Yue, Anzhi; Chen, Jiansheng; He, Dongxu; Zhang, Xiuyan

2017-10-01

The tremendous success of deep learning models such as convolutional neural networks (CNNs) in computer vision provides a method for similar problems in the field of remote sensing. Although research on repurposing pretrained CNN to remote sensing tasks is emerging, the scarcity of labeled samples and the complexity of remote sensing imagery still pose challenges. We developed a knowledge-guided golf course detection approach using a CNN fine-tuned on temporally augmented data. The proposed approach is a combination of knowledge-driven region proposal, data-driven detection based on CNN, and knowledge-driven postprocessing. To confront data complexity, knowledge-derived cooccurrence, composition, and area-based rules are applied sequentially to propose candidate golf regions. To confront sample scarcity, we employed data augmentation in the temporal domain, which extracts samples from multitemporal images. The augmented samples were then used to fine-tune a pretrained CNN for golf detection. Finally, commission error was further suppressed by postprocessing. Experiments conducted on GF-1 imagery prove the effectiveness of the proposed approach.

Retina lesion and microaneurysm segmentation using morphological reconstruction methods with ground-truth data.

PubMed

Karnowski, Thomas P; Govindasamy, V; Tobin, Kenneth W; Chaum, Edward; Abramoff, M D

2008-01-01

In this work we report on a method for lesion segmentation based on the morphological reconstruction methods of Sbeh et. al. We adapt the method to include segmentation of dark lesions with a given vasculature segmentation. The segmentation is performed at a variety of scales determined using ground-truth data. Since the method tends to over-segment imagery, ground-truth data was used to create post-processing filters to separate nuisance blobs from true lesions. A sensitivity and specificity of 90% of classification of blobs into nuisance and actual lesion was achieved on two data sets of 86 images and 1296 images.

Spot restoration for GPR image post-processing

DOEpatents

Paglieroni, David W; Beer, N. Reginald

2014-05-20

A method and system for detecting the presence of subsurface objects within a medium is provided. In some embodiments, the imaging and detection system operates in a multistatic mode to collect radar return signals generated by an array of transceiver antenna pairs that is positioned across the surface and that travels down the surface. The imaging and detection system pre-processes the return signal to suppress certain undesirable effects. The imaging and detection system then generates synthetic aperture radar images from real aperture radar images generated from the pre-processed return signal. The imaging and detection system then post-processes the synthetic aperture radar images to improve detection of subsurface objects. The imaging and detection system identifies peaks in the energy levels of the post-processed image frame, which indicates the presence of a subsurface object.

Spectroscopic optical coherence tomography based on wavelength de-multiplexing and smart pixel array detection

NASA Astrophysics Data System (ADS)

Laubscher, Markus; Bourquin, Stéphane; Froehly, Luc; Karamata, Boris; Lasser, Theo

2004-07-01

Current spectroscopic optical coherence tomography (OCT) methods rely on a posteriori numerical calculation. We present an experimental alternative for accessing spectroscopic information in OCT without post-processing based on wavelength de-multiplexing and parallel detection using a diffraction grating and a smart pixel detector array. Both a conventional A-scan with high axial resolution and the spectrally resolved measurement are acquired simultaneously. A proof-of-principle demonstration is given on a dynamically changing absorbing sample. The method's potential for fast spectroscopic OCT imaging is discussed. The spectral measurements obtained with this approach are insensitive to scan non-linearities or sample movements.

Collaborative WiFi Fingerprinting Using Sensor-Based Navigation on Smartphones.

PubMed

Zhang, Peng; Zhao, Qile; Li, You; Niu, Xiaoji; Zhuang, Yuan; Liu, Jingnan

2015-07-20

This paper presents a method that trains the WiFi fingerprint database using sensor-based navigation solutions. Since micro-electromechanical systems (MEMS) sensors provide only a short-term accuracy but suffer from the accuracy degradation with time, we restrict the time length of available indoor navigation trajectories, and conduct post-processing to improve the sensor-based navigation solution. Different middle-term navigation trajectories that move in and out of an indoor area are combined to make up the database. Furthermore, we evaluate the effect of WiFi database shifts on WiFi fingerprinting using the database generated by the proposed method. Results show that the fingerprinting errors will not increase linearly according to database (DB) errors in smartphone-based WiFi fingerprinting applications.

Collaborative WiFi Fingerprinting Using Sensor-Based Navigation on Smartphones

PubMed Central

Zhang, Peng; Zhao, Qile; Li, You; Niu, Xiaoji; Zhuang, Yuan; Liu, Jingnan

2015-01-01

This paper presents a method that trains the WiFi fingerprint database using sensor-based navigation solutions. Since micro-electromechanical systems (MEMS) sensors provide only a short-term accuracy but suffer from the accuracy degradation with time, we restrict the time length of available indoor navigation trajectories, and conduct post-processing to improve the sensor-based navigation solution. Different middle-term navigation trajectories that move in and out of an indoor area are combined to make up the database. Furthermore, we evaluate the effect of WiFi database shifts on WiFi fingerprinting using the database generated by the proposed method. Results show that the fingerprinting errors will not increase linearly according to database (DB) errors in smartphone-based WiFi fingerprinting applications. PMID:26205269

4D flow mri post-processing strategies for neuropathologies

NASA Astrophysics Data System (ADS)

Schrauben, Eric Mathew

4D flow MRI allows for the measurement of a dynamic 3D velocity vector field. Blood flow velocities in large vascular territories can be qualitatively visualized with the added benefit of quantitative probing. Within cranial pathologies theorized to have vascular-based contributions or effects, 4D flow MRI provides a unique platform for comprehensive assessment of hemodynamic parameters. Targeted blood flow derived measurements, such as flow rate, pulsatility, retrograde flow, or wall shear stress may provide insight into the onset or characterization of more complex neuropathologies. Therefore, the thorough assessment of each parameter within the context of a given disease has important medical implications. Not surprisingly, the last decade has seen rapid growth in the use of 4D flow MRI. Data acquisition sequences are available to researchers on all major scanner platforms. However, the use has been limited mostly to small research trials. One major reason that has hindered the more widespread use and application in larger clinical trials is the complexity of the post-processing tasks and the lack of adequate tools for these tasks. Post-processing of 4D flow MRI must be semi-automated, fast, user-independent, robust, and reliably consistent for use in a clinical setting, within large patient studies, or across a multicenter trial. Development of proper post-processing methods coupled with systematic investigation in normal and patient populations pushes 4D flow MRI closer to clinical realization while elucidating potential underlying neuropathological origins. Within this framework, the work in this thesis assesses venous flow reproducibility and internal consistency in a healthy population. A preliminary analysis of venous flow parameters in healthy controls and multiple sclerosis patients is performed in a large study employing 4D flow MRI. These studies are performed in the context of the chronic cerebrospinal venous insufficiency hypothesis. Additionally, a double-gated flow acquisition and reconstruction scheme demonstrates respiratory-induced changes in internal jugular vein flow. Finally, a semi-automated intracranial vessel segmentation and flow parameter measurement software tool for fast and consistent 4D flow post-processing analysis is developed, validated, and exhibited an in-vivo.

Contingency Analysis Post-Processing With Advanced Computing and Visualization

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

Chen, Yousu; Glaesemann, Kurt; Fitzhenry, Erin

Contingency analysis is a critical function widely used in energy management systems to assess the impact of power system component failures. Its outputs are important for power system operation for improved situational awareness, power system planning studies, and power market operations. With the increased complexity of power system modeling and simulation caused by increased energy production and demand, the penetration of renewable energy and fast deployment of smart grid devices, and the trend of operating grids closer to their capacity for better efficiency, more and more contingencies must be executed and analyzed quickly in order to ensure grid reliability andmore » accuracy for the power market. Currently, many researchers have proposed different techniques to accelerate the computational speed of contingency analysis, but not much work has been published on how to post-process the large amount of contingency outputs quickly. This paper proposes a parallel post-processing function that can analyze contingency analysis outputs faster and display them in a web-based visualization tool to help power engineers improve their work efficiency by fast information digestion. Case studies using an ESCA-60 bus system and a WECC planning system are presented to demonstrate the functionality of the parallel post-processing technique and the web-based visualization tool.« less

Total probabilities of ensemble runoff forecasts

NASA Astrophysics Data System (ADS)

Olav Skøien, Jon; Bogner, Konrad; Salamon, Peter; Smith, Paul; Pappenberger, Florian

2016-04-01

Ensemble forecasting has for a long time been used as a method in meteorological modelling to indicate the uncertainty of the forecasts. However, as the ensembles often exhibit both bias and dispersion errors, it is necessary to calibrate and post-process them. Two of the most common methods for this are Bayesian Model Averaging (Raftery et al., 2005) and Ensemble Model Output Statistics (EMOS) (Gneiting et al., 2005). There are also methods for regionalizing these methods (Berrocal et al., 2007) and for incorporating the correlation between lead times (Hemri et al., 2013). Engeland and Steinsland Engeland and Steinsland (2014) developed a framework which can estimate post-processing parameters which are different in space and time, but still can give a spatially and temporally consistent output. However, their method is computationally complex for our larger number of stations, and cannot directly be regionalized in the way we would like, so we suggest a different path below. The target of our work is to create a mean forecast with uncertainty bounds for a large number of locations in the framework of the European Flood Awareness System (EFAS - http://www.efas.eu) We are therefore more interested in improving the forecast skill for high-flows rather than the forecast skill of lower runoff levels. EFAS uses a combination of ensemble forecasts and deterministic forecasts from different forecasters to force a distributed hydrologic model and to compute runoff ensembles for each river pixel within the model domain. Instead of showing the mean and the variability of each forecast ensemble individually, we will now post-process all model outputs to find a total probability, the post-processed mean and uncertainty of all ensembles. The post-processing parameters are first calibrated for each calibration location, but assuring that they have some spatial correlation, by adding a spatial penalty in the calibration process. This can in some cases have a slight negative impact on the calibration error, but makes it easier to interpolate the post-processing parameters to uncalibrated locations. We also look into different methods for handling the non-normal distributions of runoff data and the effect of different data transformations on forecasts skills in general and for floods in particular. Berrocal, V. J., Raftery, A. E. and Gneiting, T.: Combining Spatial Statistical and Ensemble Information in Probabilistic Weather Forecasts, Mon. Weather Rev., 135(4), 1386-1402, doi:10.1175/MWR3341.1, 2007. Engeland, K. and Steinsland, I.: Probabilistic postprocessing models for flow forecasts for a system of catchments and several lead times, Water Resour. Res., 50(1), 182-197, doi:10.1002/2012WR012757, 2014. Gneiting, T., Raftery, A. E., Westveld, A. H. and Goldman, T.: Calibrated Probabilistic Forecasting Using Ensemble Model Output Statistics and Minimum CRPS Estimation, Mon. Weather Rev., 133(5), 1098-1118, doi:10.1175/MWR2904.1, 2005. Hemri, S., Fundel, F. and Zappa, M.: Simultaneous calibration of ensemble river flow predictions over an entire range of lead times, Water Resour. Res., 49(10), 6744-6755, doi:10.1002/wrcr.20542, 2013. Raftery, A. E., Gneiting, T., Balabdaoui, F. and Polakowski, M.: Using Bayesian Model Averaging to Calibrate Forecast Ensembles, Mon. Weather Rev., 133(5), 1155-1174, doi:10.1175/MWR2906.1, 2005.

In-Vivo Imaging of Cell Migration Using Contrast Enhanced MRI and SVM Based Post-Processing.

PubMed

Weis, Christian; Hess, Andreas; Budinsky, Lubos; Fabry, Ben

2015-01-01

The migration of cells within a living organism can be observed with magnetic resonance imaging (MRI) in combination with iron oxide nanoparticles as an intracellular contrast agent. This method, however, suffers from low sensitivity and specificty. Here, we developed a quantitative non-invasive in-vivo cell localization method using contrast enhanced multiparametric MRI and support vector machines (SVM) based post-processing. Imaging phantoms consisting of agarose with compartments containing different concentrations of cancer cells labeled with iron oxide nanoparticles were used to train and evaluate the SVM for cell localization. From the magnitude and phase data acquired with a series of T2*-weighted gradient-echo scans at different echo-times, we extracted features that are characteristic for the presence of superparamagnetic nanoparticles, in particular hyper- and hypointensities, relaxation rates, short-range phase perturbations, and perturbation dynamics. High detection quality was achieved by SVM analysis of the multiparametric feature-space. The in-vivo applicability was validated in animal studies. The SVM detected the presence of iron oxide nanoparticles in the imaging phantoms with high specificity and sensitivity with a detection limit of 30 labeled cells per mm3, corresponding to 19 μM of iron oxide. As proof-of-concept, we applied the method to follow the migration of labeled cancer cells injected in rats. The combination of iron oxide labeled cells, multiparametric MRI and a SVM based post processing provides high spatial resolution, specificity, and sensitivity, and is therefore suitable for non-invasive in-vivo cell detection and cell migration studies over prolonged time periods.

Considering Time in Orthophotography Production: from a General Workflow to a Shortened Workflow for a Faster Disaster Response

NASA Astrophysics Data System (ADS)

Lucas, G.

2015-08-01

This article overall deals with production time with orthophoto imagery with medium size digital frame camera. The workflow examination follows two main parts: data acquisition and post-processing. The objectives of the research are fourfold: 1/ gathering time references for the most important steps of orthophoto production (it turned out that literature is missing on this topic); these figures are used later for total production time estimation; 2/ identifying levers for reducing orthophoto production time; 3/ building a simplified production workflow for emergency response: less exigent with accuracy and faster; and compare it to a classical workflow; 4/ providing methodical elements for the estimation of production time with a custom project. In the data acquisition part a comprehensive review lists and describes all the factors that may affect the acquisition efficiency. Using a simulation with different variables (average line length, time of the turns, flight speed) their effect on acquisition efficiency is quantitatively examined. Regarding post-processing, the time references figures were collected from the processing of a 1000 frames case study with 15 cm GSD covering a rectangular area of 447 km2; the time required to achieve each step during the production is written down. When several technical options are possible, each one is tested and time documented so as all alternatives are available. Based on a technical choice with the workflow and using the compiled time reference of the elementary steps, a total time is calculated for the post-processing of the 1000 frames. Two scenarios are compared as regards to time and accuracy. The first one follows the "normal" practices, comprising triangulation, orthorectification and advanced mosaicking methods (feature detection, seam line editing and seam applicator); the second is simplified and make compromise over positional accuracy (using direct geo-referencing) and seamlines preparation in order to achieve orthophoto production faster. The shortened workflow reduces the production time by more than three whereas the positional error increases from 1 GSD to 1.5 GSD. The examination of time allocation through the production process shows that it is worth sparing time in the post-processing phase.

Acquisition, preprocessing, and reconstruction of ultralow dose volumetric CT scout for organ-based CT scan planning

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

Yin, Zhye, E-mail: yin@ge.com; De Man, Bruno; Yao, Yangyang

Purpose: Traditionally, 2D radiographic preparatory scan images (scout scans) are used to plan diagnostic CT scans. However, a 3D CT volume with a full 3D organ segmentation map could provide superior information for customized scan planning and other purposes. A practical challenge is to design the volumetric scout acquisition and processing steps to provide good image quality (at least good enough to enable 3D organ segmentation) while delivering a radiation dose similar to that of the conventional 2D scout. Methods: The authors explored various acquisition methods, scan parameters, postprocessing methods, and reconstruction methods through simulation and cadaver data studies tomore » achieve an ultralow dose 3D scout while simultaneously reducing the noise and maintaining the edge strength around the target organ. Results: In a simulation study, the 3D scout with the proposed acquisition, preprocessing, and reconstruction strategy provided a similar level of organ segmentation capability as a traditional 240 mAs diagnostic scan, based on noise and normalized edge strength metrics. At the same time, the proposed approach delivers only 1.25% of the dose of a traditional scan. In a cadaver study, the authors’ pictorial-structures based organ localization algorithm successfully located the major abdominal-thoracic organs from the ultralow dose 3D scout obtained with the proposed strategy. Conclusions: The authors demonstrated that images with a similar degree of segmentation capability (interpretability) as conventional dose CT scans can be achieved with an ultralow dose 3D scout acquisition and suitable postprocessing. Furthermore, the authors applied these techniques to real cadaver CT scans with a CTDI dose level of less than 0.1 mGy and successfully generated a 3D organ localization map.« less

Spatially assisted down-track median filter for GPR image post-processing

DOEpatents

Paglieroni, David W; Beer, N Reginald

2014-10-07

A method and system for detecting the presence of subsurface objects within a medium is provided. In some embodiments, the imaging and detection system operates in a multistatic mode to collect radar return signals generated by an array of transceiver antenna pairs that is positioned across the surface and that travels down the surface. The imaging and detection system pre-processes the return signal to suppress certain undesirable effects. The imaging and detection system then generates synthetic aperture radar images from real aperture radar images generated from the pre-processed return signal. The imaging and detection system then post-processes the synthetic aperture radar images to improve detection of subsurface objects. The imaging and detection system identifies peaks in the energy levels of the post-processed image frame, which indicates the presence of a subsurface object.

Tools for 3D scientific visualization in computational aerodynamics at NASA Ames Research Center

NASA Technical Reports Server (NTRS)

Bancroft, Gordon; Plessel, Todd; Merritt, Fergus; Watson, Val

1989-01-01

Hardware, software, and techniques used by the Fluid Dynamics Division (NASA) for performing visualization of computational aerodynamics, which can be applied to the visualization of flow fields from computer simulations of fluid dynamics about the Space Shuttle, are discussed. Three visualization techniques applied, post-processing, tracking, and steering, are described, as well as the post-processing software packages used, PLOT3D, SURF (Surface Modeller), GAS (Graphical Animation System), and FAST (Flow Analysis software Toolkit). Using post-processing methods a flow simulation was executed on a supercomputer and, after the simulation was complete, the results were processed for viewing. It is shown that the high-resolution, high-performance three-dimensional workstation combined with specially developed display and animation software provides a good tool for analyzing flow field solutions obtained from supercomputers.

Practical issues in quantum-key-distribution postprocessing

NASA Astrophysics Data System (ADS)

Fung, Chi-Hang Fred; Ma, Xiongfeng; Chau, H. F.

2010-01-01

Quantum key distribution (QKD) is a secure key generation method between two distant parties by wisely exploiting properties of quantum mechanics. In QKD, experimental measurement outcomes on quantum states are transformed by the two parties to a secret key. This transformation is composed of many logical steps (as guided by security proofs), which together will ultimately determine the length of the final secret key and its security. We detail the procedure for performing such classical postprocessing taking into account practical concerns (including the finite-size effect and authentication and encryption for classical communications). This procedure is directly applicable to realistic QKD experiments and thus serves as a recipe that specifies what postprocessing operations are needed and what the security level is for certain lengths of the keys. Our result is applicable to the BB84 protocol with a single or entangled photon source.

The total probabilities from high-resolution ensemble forecasting of floods

NASA Astrophysics Data System (ADS)

Olav Skøien, Jon; Bogner, Konrad; Salamon, Peter; Smith, Paul; Pappenberger, Florian

2015-04-01

Ensemble forecasting has for a long time been used in meteorological modelling, to give an indication of the uncertainty of the forecasts. As meteorological ensemble forecasts often show some bias and dispersion errors, there is a need for calibration and post-processing of the ensembles. Typical methods for this are Bayesian Model Averaging (Raftery et al., 2005) and Ensemble Model Output Statistics (EMOS) (Gneiting et al., 2005). There are also methods for regionalizing these methods (Berrocal et al., 2007) and for incorporating the correlation between lead times (Hemri et al., 2013). To make optimal predictions of floods along the stream network in hydrology, we can easily use the ensemble members as input to the hydrological models. However, some of the post-processing methods will need modifications when regionalizing the forecasts outside the calibration locations, as done by Hemri et al. (2013). We present a method for spatial regionalization of the post-processed forecasts based on EMOS and top-kriging (Skøien et al., 2006). We will also look into different methods for handling the non-normality of runoff and the effect on forecasts skills in general and for floods in particular. Berrocal, V. J., Raftery, A. E. and Gneiting, T.: Combining Spatial Statistical and Ensemble Information in Probabilistic Weather Forecasts, Mon. Weather Rev., 135(4), 1386-1402, doi:10.1175/MWR3341.1, 2007. Gneiting, T., Raftery, A. E., Westveld, A. H. and Goldman, T.: Calibrated Probabilistic Forecasting Using Ensemble Model Output Statistics and Minimum CRPS Estimation, Mon. Weather Rev., 133(5), 1098-1118, doi:10.1175/MWR2904.1, 2005. Hemri, S., Fundel, F. and Zappa, M.: Simultaneous calibration of ensemble river flow predictions over an entire range of lead times, Water Resour. Res., 49(10), 6744-6755, doi:10.1002/wrcr.20542, 2013. Raftery, A. E., Gneiting, T., Balabdaoui, F. and Polakowski, M.: Using Bayesian Model Averaging to Calibrate Forecast Ensembles, Mon. Weather Rev., 133(5), 1155-1174, doi:10.1175/MWR2906.1, 2005. Skøien, J. O., Merz, R. and Blöschl, G.: Top-kriging - Geostatistics on stream networks, Hydrol. Earth Syst. Sci., 10(2), 277-287, 2006.

Improvement of Storm Forecasts Using Gridded Bayesian Linear Regression for Northeast United States

NASA Astrophysics Data System (ADS)

Yang, J.; Astitha, M.; Schwartz, C. S.

2017-12-01

Bayesian linear regression (BLR) is a post-processing technique in which regression coefficients are derived and used to correct raw forecasts based on pairs of observation-model values. This study presents the development and application of a gridded Bayesian linear regression (GBLR) as a new post-processing technique to improve numerical weather prediction (NWP) of rain and wind storm forecasts over northeast United States. Ten controlled variables produced from ten ensemble members of the National Center for Atmospheric Research (NCAR) real-time prediction system are used for a GBLR model. In the GBLR framework, leave-one-storm-out cross-validation is utilized to study the performances of the post-processing technique in a database composed of 92 storms. To estimate the regression coefficients of the GBLR, optimization procedures that minimize the systematic and random error of predicted atmospheric variables (wind speed, precipitation, etc.) are implemented for the modeled-observed pairs of training storms. The regression coefficients calculated for meteorological stations of the National Weather Service are interpolated back to the model domain. An analysis of forecast improvements based on error reductions during the storms will demonstrate the value of GBLR approach. This presentation will also illustrate how the variances are optimized for the training partition in GBLR and discuss the verification strategy for grid points where no observations are available. The new post-processing technique is successful in improving wind speed and precipitation storm forecasts using past event-based data and has the potential to be implemented in real-time.

Local finite element enrichment strategies for 2D contact computations and a corresponding post-processing scheme

NASA Astrophysics Data System (ADS)

Sauer, Roger A.

2013-08-01

Recently an enriched contact finite element formulation has been developed that substantially increases the accuracy of contact computations while keeping the additional numerical effort at a minimum reported by Sauer (Int J Numer Meth Eng, 87: 593-616, 2011). Two enrich-ment strategies were proposed, one based on local p-refinement using Lagrange interpolation and one based on Hermite interpolation that produces C 1-smoothness on the contact surface. Both classes, which were initially considered for the frictionless Signorini problem, are extended here to friction and contact between deformable bodies. For this, a symmetric contact formulation is used that allows the unbiased treatment of both contact partners. This paper also proposes a post-processing scheme for contact quantities like the contact pressure. The scheme, which provides a more accurate representation than the raw data, is based on an averaging procedure that is inspired by mortar formulations. The properties of the enrichment strategies and the corresponding post-processing scheme are illustrated by several numerical examples considering sliding and peeling contact in the presence of large deformations.

Finger Vein Segmentation from Infrared Images Based on a Modified Separable Mumford Shah Model and Local Entropy Thresholding

PubMed Central

Dermatas, Evangelos

2015-01-01

A novel method for finger vein pattern extraction from infrared images is presented. This method involves four steps: preprocessing which performs local normalization of the image intensity, image enhancement, image segmentation, and finally postprocessing for image cleaning. In the image enhancement step, an image which will be both smooth and similar to the original is sought. The enhanced image is obtained by minimizing the objective function of a modified separable Mumford Shah Model. Since, this minimization procedure is computationally intensive for large images, a local application of the Mumford Shah Model in small window neighborhoods is proposed. The finger veins are located in concave nonsmooth regions and, so, in order to distinct them from the other tissue parts, all the differences between the smooth neighborhoods, obtained by the local application of the model, and the corresponding windows of the original image are added. After that, veins in the enhanced image have been sufficiently emphasized. Thus, after image enhancement, an accurate segmentation can be obtained readily by a local entropy thresholding method. Finally, the resulted binary image may suffer from some misclassifications and, so, a postprocessing step is performed in order to extract a robust finger vein pattern. PMID:26120357

Postprocessing of docked protein-ligand complexes using implicit solvation models.

PubMed

Lindström, Anton; Edvinsson, Lotta; Johansson, Andreas; Andersson, C David; Andersson, Ida E; Raubacher, Florian; Linusson, Anna

2011-02-28

Molecular docking plays an important role in drug discovery as a tool for the structure-based design of small organic ligands for macromolecules. Possible applications of docking are identification of the bioactive conformation of a protein-ligand complex and the ranking of different ligands with respect to their strength of binding to a particular target. We have investigated the effect of implicit water on the postprocessing of binding poses generated by molecular docking using MM-PB/GB-SA (molecular mechanics Poisson-Boltzmann and generalized Born surface area) methodology. The investigation was divided into three parts: geometry optimization, pose selection, and estimation of the relative binding energies of docked protein-ligand complexes. Appropriate geometry optimization afforded more accurate binding poses for 20% of the complexes investigated. The time required for this step was greatly reduced by minimizing the energy of the binding site using GB solvation models rather than minimizing the entire complex using the PB model. By optimizing the geometries of docking poses using the GB(HCT+SA) model then calculating their free energies of binding using the PB implicit solvent model, binding poses similar to those observed in crystal structures were obtained. Rescoring of these poses according to their calculated binding energies resulted in improved correlations with experimental binding data. These correlations could be further improved by applying the postprocessing to several of the most highly ranked poses rather than focusing exclusively on the top-scored pose. The postprocessing protocol was successfully applied to the analysis of a set of Factor Xa inhibitors and a set of glycopeptide ligands for the class II major histocompatibility complex (MHC) A(q) protein. These results indicate that the protocol for the postprocessing of docked protein-ligand complexes developed in this paper may be generally useful for structure-based design in drug discovery.

A post-processing algorithm for time domain pitch trackers

NASA Astrophysics Data System (ADS)

Specker, P.

1983-01-01

This paper describes a powerful post-processing algorithm for time-domain pitch trackers. On two successive passes, the post-processing algorithm eliminates errors produced during a first pass by a time-domain pitch tracker. During the second pass, incorrect pitch values are detected as outliers by computing the distribution of values over a sliding 80 msec window. During the third pass (based on artificial intelligence techniques), remaining pitch pulses are used as anchor points to reconstruct the pitch train from the original waveform. The algorithm produced a decrease in the error rate from 21% obtained with the original time domain pitch tracker to 2% for isolated words and sentences produced in an office environment by 3 male and 3 female talkers. In a noisy computer room errors decreased from 52% to 2.9% for the same stimuli produced by 2 male talkers. The algorithm is efficient, accurate, and resistant to noise. The fundamental frequency micro-structure is tracked sufficiently well to be used in extracting phonetic features in a feature-based recognition system.

A TRACER METHOD FOR COMPUTING TYPE IA SUPERNOVA YIELDS: BURNING MODEL CALIBRATION, RECONSTRUCTION OF THICKENED FLAMES, AND VERIFICATION FOR PLANAR DETONATIONS

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

Townsley, Dean M.; Miles, Broxton J.; Timmes, F. X.

2016-07-01

We refine our previously introduced parameterized model for explosive carbon–oxygen fusion during thermonuclear Type Ia supernovae (SNe Ia) by adding corrections to post-processing of recorded Lagrangian fluid-element histories to obtain more accurate isotopic yields. Deflagration and detonation products are verified for propagation in a medium of uniform density. A new method is introduced for reconstructing the temperature–density history within the artificially thick model deflagration front. We obtain better than 5% consistency between the electron capture computed by the burning model and yields from post-processing. For detonations, we compare to a benchmark calculation of the structure of driven steady-state planar detonationsmore » performed with a large nuclear reaction network and error-controlled integration. We verify that, for steady-state planar detonations down to a density of 5 × 10{sup 6} g cm{sup −3}, our post-processing matches the major abundances in the benchmark solution typically to better than 10% for times greater than 0.01 s after the passage of the shock front. As a test case to demonstrate the method, presented here with post-processing for the first time, we perform a two-dimensional simulation of a SN Ia in the scenario of a Chandrasekhar-mass deflagration–detonation transition (DDT). We find that reconstruction of deflagration tracks leads to slightly more complete silicon burning than without reconstruction. The resulting abundance structure of the ejecta is consistent with inferences from spectroscopic studies of observed SNe Ia. We confirm the absence of a central region of stable Fe-group material for the multi-dimensional DDT scenario. Detailed isotopic yields are tabulated and change only modestly when using deflagration reconstruction.« less

On the construction of a ground truth framework for evaluating voxel-based diffusion tensor MRI analysis methods.

PubMed

Van Hecke, Wim; Sijbers, Jan; De Backer, Steve; Poot, Dirk; Parizel, Paul M; Leemans, Alexander

2009-07-01

Although many studies are starting to use voxel-based analysis (VBA) methods to compare diffusion tensor images between healthy and diseased subjects, it has been demonstrated that VBA results depend heavily on parameter settings and implementation strategies, such as the applied coregistration technique, smoothing kernel width, statistical analysis, etc. In order to investigate the effect of different parameter settings and implementations on the accuracy and precision of the VBA results quantitatively, ground truth knowledge regarding the underlying microstructural alterations is required. To address the lack of such a gold standard, simulated diffusion tensor data sets are developed, which can model an array of anomalies in the diffusion properties of a predefined location. These data sets can be employed to evaluate the numerous parameters that characterize the pipeline of a VBA algorithm and to compare the accuracy, precision, and reproducibility of different post-processing approaches quantitatively. We are convinced that the use of these simulated data sets can improve the understanding of how different diffusion tensor image post-processing techniques affect the outcome of VBA. In turn, this may possibly lead to a more standardized and reliable evaluation of diffusion tensor data sets of large study groups with a wide range of white matter altering pathologies. The simulated DTI data sets will be made available online (http://www.dti.ua.ac.be).

Echocardiographic strain and strain-rate imaging: a new tool to study regional myocardial function.

PubMed

D'hooge, Jan; Bijnens, Bart; Thoen, Jan; Van de Werf, Frans; Sutherland, George R; Suetens, Paul

2002-09-01

Ultrasonic imaging is the noninvasive clinical imaging modality of choice for diagnosing heart disease. At present, two-dimensional ultrasonic grayscale images provide a relatively cheap, fast, bedside method to study the morphology of the heart. Several methods have been proposed to assess myocardial function. These have been based on either grayscale or motion (velocity) information measured in real-time. However, the quantitative assessment of regional myocardial function remains an important goal in clinical cardiology. To do this, ultrasonic strain and strain-rate imaging have been introduced. In the clinical setting, these techniques currently only allow one component of the true three-dimensional deformation to be measured. Clinical, multidimensional strain (rate) information can currently thus only be obtained by combining data acquired using different transducer positions. Nevertheless, given the appropriate postprocessing, the clinical value of these techniques has already been shown. Moreover, multidimensional strain and strain-rate estimation of the heart in vivo by means of a single ultrasound acquisition has been shown to be feasible. In this paper, the new techniques of ultrasonic strain rate and strain imaging of the heart are reviewed in terms of definitions, data acquisition, strain-rate estimation, postprocessing, and parameter extraction. Their clinical validation and relevance will be discussed using clinical examples on relevant cardiac pathology. Based on these examples, suggestions are made for future developments of these techniques.

Quantifying model uncertainty in seasonal Arctic sea-ice forecasts

NASA Astrophysics Data System (ADS)

Blanchard-Wrigglesworth, Edward; Barthélemy, Antoine; Chevallier, Matthieu; Cullather, Richard; Fučkar, Neven; Massonnet, François; Posey, Pamela; Wang, Wanqiu; Zhang, Jinlun; Ardilouze, Constantin; Bitz, Cecilia; Vernieres, Guillaume; Wallcraft, Alan; Wang, Muyin

2017-04-01

Dynamical model forecasts in the Sea Ice Outlook (SIO) of September Arctic sea-ice extent over the last decade have shown lower skill than that found in both idealized model experiments and hindcasts of previous decades. Additionally, it is unclear how different model physics, initial conditions or post-processing techniques contribute to SIO forecast uncertainty. In this work, we have produced a seasonal forecast of 2015 Arctic summer sea ice using SIO dynamical models initialized with identical sea-ice thickness in the central Arctic. Our goals are to calculate the relative contribution of model uncertainty and irreducible error growth to forecast uncertainty and assess the importance of post-processing, and to contrast pan-Arctic forecast uncertainty with regional forecast uncertainty. We find that prior to forecast post-processing, model uncertainty is the main contributor to forecast uncertainty, whereas after forecast post-processing forecast uncertainty is reduced overall, model uncertainty is reduced by an order of magnitude, and irreducible error growth becomes the main contributor to forecast uncertainty. While all models generally agree in their post-processed forecasts of September sea-ice volume and extent, this is not the case for sea-ice concentration. Additionally, forecast uncertainty of sea-ice thickness grows at a much higher rate along Arctic coastlines relative to the central Arctic ocean. Potential ways of offering spatial forecast information based on the timescale over which the forecast signal beats the noise are also explored.

MRO DKF Post-Processing Tool

NASA Technical Reports Server (NTRS)

Ayap, Shanti; Fisher, Forest; Gladden, Roy; Khanampompan, Teerapat

2008-01-01

This software tool saves time and reduces risk by automating two labor-intensive and error-prone post-processing steps required for every DKF [DSN (Deep Space Network) Keyword File] that MRO (Mars Reconnaissance Orbiter) produces, and is being extended to post-process the corresponding TSOE (Text Sequence Of Events) as well. The need for this post-processing step stems from limitations in the seq-gen modeling resulting in incorrect DKF generation that is then cleaned up in post-processing.

Multiple approaches to fine-grained indexing of the biomedical literature.

PubMed

Neveol, Aurelie; Shooshan, Sonya E; Humphrey, Susanne M; Rindflesh, Thomas C; Aronson, Alan R

2007-01-01

The number of articles in the MEDLINE database is expected to increase tremendously in the coming years. To ensure that all these documents are indexed with continuing high quality, it is necessary to develop tools and methods that help the indexers in their daily task. We present three methods addressing a novel aspect of automatic indexing of the biomedical literature, namely producing MeSH main heading/subheading pair recommendations. The methods, (dictionary-based, post- processing rules and Natural Language Processing rules) are described and evaluated on a genetics-related corpus. The best overall performance is obtained for the subheading genetics (70% precision and 17% recall with post-processing rules, 48% precision and 37% recall with the dictionary-based method). Future work will address extending this work to all MeSH subheadings and a more thorough study of method combination.

Thirteenth NASTRAN (R) Users' Colloquium

NASA Technical Reports Server (NTRS)

1985-01-01

The application of finite element methods in engineering is discussed and the use of NASTRAN is compared with other approaches. Specific applications, pre- and post-processing or auxiliary programs, and additional methods of analysis with NASTRAN are covered.

Development and Evaluation of a Spectral Analysis Method to Eliminate Organic Interference with Cavity Ring-Down Measurements of Water Isotope Ratios.

NASA Astrophysics Data System (ADS)

Lin, Z.; Kim-Hak, D.; Popp, B. N.; Wallsgrove, N.; Kagawa-Viviani, A.; Johnson, J.

2017-12-01

Cavity ring-down spectroscopy (CRDS) is a technology based on the spectral absorption of gas molecules of interest at specific spectral regions. The CRDS technique enables the analysis of hydrogen and oxygen stable isotope ratios of water by directly measuring individual isotopologue absorption peaks such as H16OH, H18OH, and D16OH. Early work demonstrated that the accuracy of isotope analysis by CRDS and other laser-based absorption techniques could be compromised by spectral interference from organic compounds, in particular methanol and ethanol, which can be prevalent in ecologically-derived waters. There have been several methods developed by various research groups including Picarro to address the organic interference challenge. Here, we describe an organic fitter and a post-processing algorithm designed to improve the accuracy of the isotopic analysis of the "organic contaminated" water specifically for Picarro models L2130-i and L2140-i. To create the organic fitter, the absorption features of methanol around 7200 cm-1 were characterized and incorporated into spectral analysis. Since there was residual interference remaining after applying the organic fitter, a statistical model was also developed for post-processing correction. To evaluate the performance of the organic fitter and the postprocessing correction, we conducted controlled experiments on the L2130-i for two water samples with different isotope ratios blended with varying amounts of methanol (0-0.5%) and ethanol (0-5%). When the original fitter was not used for spectral analysis, the addition of 0.5% methanol changed the apparent isotopic composition of the water samples by +62‰ for δ18O values and +97‰ for δ2H values, and the addition of 5% ethanol changed the apparent isotopic composition by -0.5‰ for δ18O values and -3‰ for δ2H values. When the organic fitter was used for spectral analysis, the maximum methanol-induced errors were reduced to +4‰ for δ18O values and +5‰ for δ2H values, and the maximum ethanol-induced errors were unchanged. When the organic fitter was combined with the post-processing correction, up to 99.8% of the total methanol-induced errors and 96% of the total ethanol-induced errors could be corrected. The applicability of the algorithm to natural samples such as plant and soil waters will be investigated.

Force measurement-based discontinuity detection during friction stir welding

DOE PAGES

Shrivastava, Amber; Zinn, Michael; Duffie, Neil A.; ...

2017-02-23

Here, the objective of this work is to develop a method for detecting the creation of discontinuities ( i.e., voids, volume defects) during friction stir welding. Friction stir welding is inherently cost effective, however, the need for significant weld inspection can make the process cost prohibitive. A new approach to weld inspection is required in which an in situ characterization of weld quality can be obtained, reducing the need for postprocess inspection. To this end, friction stir welds with subsurface voids and without voids were created. The subsurface voids were generated by reducing the friction stir tool rotation frequency andmore » increasing the tool traverse speed in order to create “colder” welds. Process forces were measured during welding, and the void sizes were measured postprocess by computerized tomography ( i.e., 3D X-ray imaging). Two parameters, based on frequency domain content and time-domain average of the force signals, were found to be correlated with void size. Criteria for subsurface void detection and size prediction were developed and shown to be in good agreement with experimental observations. Furthermore, with the proper choice of data acquisition system and frequency analyzer the occurrence of subsurface voids can be detected in real time.« less

Force measurement-based discontinuity detection during friction stir welding

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

Shrivastava, Amber; Zinn, Michael; Duffie, Neil A.

Here, the objective of this work is to develop a method for detecting the creation of discontinuities ( i.e., voids, volume defects) during friction stir welding. Friction stir welding is inherently cost effective, however, the need for significant weld inspection can make the process cost prohibitive. A new approach to weld inspection is required in which an in situ characterization of weld quality can be obtained, reducing the need for postprocess inspection. To this end, friction stir welds with subsurface voids and without voids were created. The subsurface voids were generated by reducing the friction stir tool rotation frequency andmore » increasing the tool traverse speed in order to create “colder” welds. Process forces were measured during welding, and the void sizes were measured postprocess by computerized tomography ( i.e., 3D X-ray imaging). Two parameters, based on frequency domain content and time-domain average of the force signals, were found to be correlated with void size. Criteria for subsurface void detection and size prediction were developed and shown to be in good agreement with experimental observations. Furthermore, with the proper choice of data acquisition system and frequency analyzer the occurrence of subsurface voids can be detected in real time.« less

A postprocessing method in the HMC framework for predicting gene function based on biological instrumental data

NASA Astrophysics Data System (ADS)

Feng, Shou; Fu, Ping; Zheng, Wenbin

2018-03-01

Predicting gene function based on biological instrumental data is a complicated and challenging hierarchical multi-label classification (HMC) problem. When using local approach methods to solve this problem, a preliminary results processing method is usually needed. This paper proposed a novel preliminary results processing method called the nodes interaction method. The nodes interaction method revises the preliminary results and guarantees that the predictions are consistent with the hierarchy constraint. This method exploits the label dependency and considers the hierarchical interaction between nodes when making decisions based on the Bayesian network in its first phase. In the second phase, this method further adjusts the results according to the hierarchy constraint. Implementing the nodes interaction method in the HMC framework also enhances the HMC performance for solving the gene function prediction problem based on the Gene Ontology (GO), the hierarchy of which is a directed acyclic graph that is more difficult to tackle. The experimental results validate the promising performance of the proposed method compared to state-of-the-art methods on eight benchmark yeast data sets annotated by the GO.

Pre-operative Simulation of the Appropriate C-arm Position Using Computed Tomography Post-processing Software Reduces Radiation and Contrast Medium Exposure During EVAR Procedures.

PubMed

Stahlberg, E; Planert, M; Panagiotopoulos, N; Horn, M; Wiedner, M; Kleemann, M; Barkhausen, J; Goltz, J P

2017-02-01

The aim was to evaluate the feasibility and efficacy of a new method for pre-operative calculation of an appropriate C-arm position for iliac bifurcation visualisation during endovascular aortic repair (EVAR) procedures by using three dimensional computed tomography angiography (CTA) post-processing software. Post-processing software was used to simulate C-arm angulations in two dimensions (oblique, cranial/caudal) for appropriate visualisation of distal landing zones at the iliac bifurcation during EVAR. Retrospectively, 27 consecutive EVAR patients (25 men, mean ± SD age 73 ± 7 years) were identified; one group of patients (NEW; n = 12 [23 iliac bifurcations]) was compared after implementation of the new method with a group of patients who received a historic method (OLD; n = 15 [23 iliac bifurcations]), treated with EVAR before the method was applied. In the OLD group, a median of 2.0 (interquartile range [IQR] 1-3) digital subtraction angiography runs were needed per iliac bifurcation versus 1.0 (IQR 1-1) runs in the NEW group (p = .007). The median dose area products per iliac bifurcation were 11951 mGy*cm 2 (IQR 7308-16663 mGy*cm 2 ) for the NEW, and 39394 mGy*cm 2 (IQR 19066-53702 mGy*cm 2 ) for the OLD group, respectively (p = .001). The median volume of contrast per iliac bifurcation was 13.0 mL (IQR: 13-13 mL) in the NEW and 26 mL (IQR 13-39 mL) in the OLD group (p = .007). Pre-operative simulation of the appropriate C-arm angulation in two dimensions using dedicated computed tomography angiography post-processing software is feasible and significantly reduces radiation and contrast medium exposure. Copyright © 2016 European Society for Vascular Surgery. Published by Elsevier Ltd. All rights reserved.

Process and Post-Process: A Discursive History.

ERIC Educational Resources Information Center

Matsuda, Paul Kei

2003-01-01

Examines the history of process and post-process in composition studies, focusing on ways in which terms, such as "current-traditional rhetoric,""process," and "post-process" have contributed to the discursive construction of reality. Argues that use of the term post-process in the context of second language writing needs to be guided by a…

Detecting false positive sequence homology: a machine learning approach.

PubMed

Fujimoto, M Stanley; Suvorov, Anton; Jensen, Nicholas O; Clement, Mark J; Bybee, Seth M

2016-02-24

Accurate detection of homologous relationships of biological sequences (DNA or amino acid) amongst organisms is an important and often difficult task that is essential to various evolutionary studies, ranging from building phylogenies to predicting functional gene annotations. There are many existing heuristic tools, most commonly based on bidirectional BLAST searches that are used to identify homologous genes and combine them into two fundamentally distinct classes: orthologs and paralogs. Due to only using heuristic filtering based on significance score cutoffs and having no cluster post-processing tools available, these methods can often produce multiple clusters constituting unrelated (non-homologous) sequences. Therefore sequencing data extracted from incomplete genome/transcriptome assemblies originated from low coverage sequencing or produced by de novo processes without a reference genome are susceptible to high false positive rates of homology detection. In this paper we develop biologically informative features that can be extracted from multiple sequence alignments of putative homologous genes (orthologs and paralogs) and further utilized in context of guided experimentation to verify false positive outcomes. We demonstrate that our machine learning method trained on both known homology clusters obtained from OrthoDB and randomly generated sequence alignments (non-homologs), successfully determines apparent false positives inferred by heuristic algorithms especially among proteomes recovered from low-coverage RNA-seq data. Almost ~42 % and ~25 % of predicted putative homologies by InParanoid and HaMStR respectively were classified as false positives on experimental data set. Our process increases the quality of output from other clustering algorithms by providing a novel post-processing method that is both fast and efficient at removing low quality clusters of putative homologous genes recovered by heuristic-based approaches.

Evaluation of TIGGE Ensemble Forecasts of Precipitation in Distinct Climate Regions in Iran

NASA Astrophysics Data System (ADS)

Aminyavari, Saleh; Saghafian, Bahram; Delavar, Majid

2018-04-01

The application of numerical weather prediction (NWP) products is increasing dramatically. Existing reports indicate that ensemble predictions have better skill than deterministic forecasts. In this study, numerical ensemble precipitation forecasts in the TIGGE database were evaluated using deterministic, dichotomous (yes/no), and probabilistic techniques over Iran for the period 2008-16. Thirteen rain gauges spread over eight homogeneous precipitation regimes were selected for evaluation. The Inverse Distance Weighting and Kriging methods were adopted for interpolation of the prediction values, downscaled to the stations at lead times of one to three days. To enhance the forecast quality, NWP values were post-processed via Bayesian Model Averaging. The results showed that ECMWF had better scores than other products. However, products of all centers underestimated precipitation in high precipitation regions while overestimating precipitation in other regions. This points to a systematic bias in forecasts and demands application of bias correction techniques. Based on dichotomous evaluation, NCEP did better at most stations, although all centers overpredicted the number of precipitation events. Compared to those of ECMWF and NCEP, UKMO yielded higher scores in mountainous regions, but performed poorly at other selected stations. Furthermore, the evaluations showed that all centers had better skill in wet than in dry seasons. The quality of post-processed predictions was better than those of the raw predictions. In conclusion, the accuracy of the NWP predictions made by the selected centers could be classified as medium over Iran, while post-processing of predictions is recommended to improve the quality.

Dopamine Inactivation Efficacy Related to Functional DAT1 and COMT Variants Influences Motor Response Evaluation

PubMed Central

Bender, Stephan; Rellum, Thomas; Freitag, Christine; Resch, Franz; Rietschel, Marcella; Treutlein, Jens; Jennen-Steinmetz, Christine; Brandeis, Daniel; Banaschewski, Tobias; Laucht, Manfred

2012-01-01

Background Dopamine plays an important role in orienting, response anticipation and movement evaluation. Thus, we examined the influence of functional variants related to dopamine inactivation in the dopamine transporter (DAT1) and catechol-O-methyltransferase genes (COMT) on the time-course of motor processing in a contingent negative variation (CNV) task. Methods 64-channel EEG recordings were obtained from 195 healthy adolescents of a community-based sample during a continuous performance task (A-X version). Early and late CNV as well as motor postimperative negative variation were assessed. Adolescents were genotyped for the COMT Val158Met and two DAT1 polymorphisms (variable number tandem repeats in the 3′-untranslated region and in intron 8). Results The results revealed a significant interaction between COMT and DAT1, indicating that COMT exerted stronger effects on lateralized motor post-processing (centro-parietal motor postimperative negative variation) in homozygous carriers of a DAT1 haplotype increasing DAT1 expression. Source analysis showed that the time interval 500–1000 ms after the motor response was specifically affected in contrast to preceding movement anticipation and programming stages, which were not altered. Conclusions Motor slow negative waves allow the genomic imaging of dopamine inactivation effects on cortical motor post-processing during response evaluation. This is the first report to point towards epistatic effects in the motor system during response evaluation, i.e. during the post-processing of an already executed movement rather than during movement programming. PMID:22649558

Computational method for multi-modal microscopy based on transport of intensity equation

NASA Astrophysics Data System (ADS)

Li, Jiaji; Chen, Qian; Sun, Jiasong; Zhang, Jialin; Zuo, Chao

2017-02-01

In this paper, we develop the requisite theory to describe a hybrid virtual-physical multi-modal imaging system which yields quantitative phase, Zernike phase contrast, differential interference contrast (DIC), and light field moment imaging simultaneously based on transport of intensity equation(TIE). We then give the experimental demonstration of these ideas by time-lapse imaging of live HeLa cell mitosis. Experimental results verify that a tunable lens based TIE system, combined with the appropriate post-processing algorithm, can achieve a variety of promising imaging modalities in parallel with the quantitative phase images for the dynamic study of cellular processes.

Trends in the predictive performance of raw ensemble weather forecasts

NASA Astrophysics Data System (ADS)

Hemri, Stephan; Scheuerer, Michael; Pappenberger, Florian; Bogner, Konrad; Haiden, Thomas

2015-04-01

Over the last two decades the paradigm in weather forecasting has shifted from being deterministic to probabilistic. Accordingly, numerical weather prediction (NWP) models have been run increasingly as ensemble forecasting systems. The goal of such ensemble forecasts is to approximate the forecast probability distribution by a finite sample of scenarios. Global ensemble forecast systems, like the European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble, are prone to probabilistic biases, and are therefore not reliable. They particularly tend to be underdispersive for surface weather parameters. Hence, statistical post-processing is required in order to obtain reliable and sharp forecasts. In this study we apply statistical post-processing to ensemble forecasts of near-surface temperature, 24-hour precipitation totals, and near-surface wind speed from the global ECMWF model. Our main objective is to evaluate the evolution of the difference in skill between the raw ensemble and the post-processed forecasts. The ECMWF ensemble is under continuous development, and hence its forecast skill improves over time. Parts of these improvements may be due to a reduction of probabilistic bias. Thus, we first hypothesize that the gain by post-processing decreases over time. Based on ECMWF forecasts from January 2002 to March 2014 and corresponding observations from globally distributed stations we generate post-processed forecasts by ensemble model output statistics (EMOS) for each station and variable. Parameter estimates are obtained by minimizing the Continuous Ranked Probability Score (CRPS) over rolling training periods that consist of the n days preceding the initialization dates. Given the higher average skill in terms of CRPS of the post-processed forecasts for all three variables, we analyze the evolution of the difference in skill between raw ensemble and EMOS forecasts. The fact that the gap in skill remains almost constant over time, especially for near-surface wind speed, suggests that improvements to the atmospheric model have an effect quite different from what calibration by statistical post-processing is doing. That is, they are increasing potential skill. Thus this study indicates that (a) further model development is important even if one is just interested in point forecasts, and (b) statistical post-processing is important because it will keep adding skill in the foreseeable future.

Estimation Methods for Non-Homogeneous Regression - Minimum CRPS vs Maximum Likelihood

NASA Astrophysics Data System (ADS)

Gebetsberger, Manuel; Messner, Jakob W.; Mayr, Georg J.; Zeileis, Achim

2017-04-01

Non-homogeneous regression models are widely used to statistically post-process numerical weather prediction models. Such regression models correct for errors in mean and variance and are capable to forecast a full probability distribution. In order to estimate the corresponding regression coefficients, CRPS minimization is performed in many meteorological post-processing studies since the last decade. In contrast to maximum likelihood estimation, CRPS minimization is claimed to yield more calibrated forecasts. Theoretically, both scoring rules used as an optimization score should be able to locate a similar and unknown optimum. Discrepancies might result from a wrong distributional assumption of the observed quantity. To address this theoretical concept, this study compares maximum likelihood and minimum CRPS estimation for different distributional assumptions. First, a synthetic case study shows that, for an appropriate distributional assumption, both estimation methods yield to similar regression coefficients. The log-likelihood estimator is slightly more efficient. A real world case study for surface temperature forecasts at different sites in Europe confirms these results but shows that surface temperature does not always follow the classical assumption of a Gaussian distribution. KEYWORDS: ensemble post-processing, maximum likelihood estimation, CRPS minimization, probabilistic temperature forecasting, distributional regression models

Using Meteorological Analogues for Reordering Postprocessed Precipitation Ensembles in Hydrological Forecasting

NASA Astrophysics Data System (ADS)

Bellier, Joseph; Bontron, Guillaume; Zin, Isabella

2017-12-01

Meteorological ensemble forecasts are nowadays widely used as input of hydrological models for probabilistic streamflow forecasting. These forcings are frequently biased and have to be statistically postprocessed, using most of the time univariate techniques that apply independently to individual locations, lead times and weather variables. Postprocessed ensemble forecasts therefore need to be reordered so as to reconstruct suitable multivariate dependence structures. The Schaake shuffle and ensemble copula coupling are the two most popular methods for this purpose. This paper proposes two adaptations of them that make use of meteorological analogues for reconstructing spatiotemporal dependence structures of precipitation forecasts. Performances of the original and adapted techniques are compared through a multistep verification experiment using real forecasts from the European Centre for Medium-Range Weather Forecasts. This experiment evaluates not only multivariate precipitation forecasts but also the corresponding streamflow forecasts that derive from hydrological modeling. Results show that the relative performances of the different reordering methods vary depending on the verification step. In particular, the standard Schaake shuffle is found to perform poorly when evaluated on streamflow. This emphasizes the crucial role of the precipitation spatiotemporal dependence structure in hydrological ensemble forecasting.

Postprocessing Algorithm for Driving Conventional Scanning Tunneling Microscope at Fast Scan Rates.

PubMed

Zhang, Hao; Li, Xianqi; Chen, Yunmei; Park, Jewook; Li, An-Ping; Zhang, X-G

2017-01-01

We present an image postprocessing framework for Scanning Tunneling Microscope (STM) to reduce the strong spurious oscillations and scan line noise at fast scan rates and preserve the features, allowing an order of magnitude increase in the scan rate without upgrading the hardware. The proposed method consists of two steps for large scale images and four steps for atomic scale images. For large scale images, we first apply for each line an image registration method to align the forward and backward scans of the same line. In the second step we apply a "rubber band" model which is solved by a novel Constrained Adaptive and Iterative Filtering Algorithm (CIAFA). The numerical results on measurement from copper(111) surface indicate the processed images are comparable in accuracy to data obtained with a slow scan rate, but are free of the scan drift error commonly seen in slow scan data. For atomic scale images, an additional first step to remove line-by-line strong background fluctuations and a fourth step of replacing the postprocessed image by its ranking map as the final atomic resolution image are required. The resulting image restores the lattice image that is nearly undetectable in the original fast scan data.

Multi-model seasonal forecast of Arctic sea-ice: forecast uncertainty at pan-Arctic and regional scales

NASA Astrophysics Data System (ADS)

Blanchard-Wrigglesworth, E.; Barthélemy, A.; Chevallier, M.; Cullather, R.; Fučkar, N.; Massonnet, F.; Posey, P.; Wang, W.; Zhang, J.; Ardilouze, C.; Bitz, C. M.; Vernieres, G.; Wallcraft, A.; Wang, M.

2017-08-01

Dynamical model forecasts in the Sea Ice Outlook (SIO) of September Arctic sea-ice extent over the last decade have shown lower skill than that found in both idealized model experiments and hindcasts of previous decades. Additionally, it is unclear how different model physics, initial conditions or forecast post-processing (bias correction) techniques contribute to SIO forecast uncertainty. In this work, we have produced a seasonal forecast of 2015 Arctic summer sea ice using SIO dynamical models initialized with identical sea-ice thickness in the central Arctic. Our goals are to calculate the relative contribution of model uncertainty and irreducible error growth to forecast uncertainty and assess the importance of post-processing, and to contrast pan-Arctic forecast uncertainty with regional forecast uncertainty. We find that prior to forecast post-processing, model uncertainty is the main contributor to forecast uncertainty, whereas after forecast post-processing forecast uncertainty is reduced overall, model uncertainty is reduced by an order of magnitude, and irreducible error growth becomes the main contributor to forecast uncertainty. While all models generally agree in their post-processed forecasts of September sea-ice volume and extent, this is not the case for sea-ice concentration. Additionally, forecast uncertainty of sea-ice thickness grows at a much higher rate along Arctic coastlines relative to the central Arctic ocean. Potential ways of offering spatial forecast information based on the timescale over which the forecast signal beats the noise are also explored.

An unsupervised classification scheme for improving predictions of prokaryotic TIS.

PubMed

Tech, Maike; Meinicke, Peter

2006-03-09

Although it is not difficult for state-of-the-art gene finders to identify coding regions in prokaryotic genomes, exact prediction of the corresponding translation initiation sites (TIS) is still a challenging problem. Recently a number of post-processing tools have been proposed for improving the annotation of prokaryotic TIS. However, inherent difficulties of these approaches arise from the considerable variation of TIS characteristics across different species. Therefore prior assumptions about the properties of prokaryotic gene starts may cause suboptimal predictions for newly sequenced genomes with TIS signals differing from those of well-investigated genomes. We introduce a clustering algorithm for completely unsupervised scoring of potential TIS, based on positionally smoothed probability matrices. The algorithm requires an initial gene prediction and the genomic sequence of the organism to perform the reannotation. As compared with other methods for improving predictions of gene starts in bacterial genomes, our approach is not based on any specific assumptions about prokaryotic TIS. Despite the generality of the underlying algorithm, the prediction rate of our method is competitive on experimentally verified test data from E. coli and B. subtilis. Regarding genomes with high G+C content, in contrast to some previously proposed methods, our algorithm also provides good performance on P. aeruginosa, B. pseudomallei and R. solanacearum. On reliable test data we showed that our method provides good results in post-processing the predictions of the widely-used program GLIMMER. The underlying clustering algorithm is robust with respect to variations in the initial TIS annotation and does not require specific assumptions about prokaryotic gene starts. These features are particularly useful on genomes with high G+C content. The algorithm has been implemented in the tool "TICO" (TIs COrrector) which is publicly available from our web site.

An accuracy assessment of realtime GNSS time series toward semi- real time seafloor geodetic observation

NASA Astrophysics Data System (ADS)

Osada, Y.; Ohta, Y.; Demachi, T.; Kido, M.; Fujimoto, H.; Azuma, R.; Hino, R.

2013-12-01

Large interplate earthquake repeatedly occurred in Japan Trench. Recently, the detail crustal deformation revealed by the nation-wide inland GPS network called as GEONET by GSI. However, the maximum displacement region for interplate earthquake is mainly located offshore region. GPS/Acoustic seafloor geodetic observation (hereafter GPS/A) is quite important and useful for understanding of shallower part of the interplate coupling between subducting and overriding plates. We typically conduct GPS/A in specific ocean area based on repeated campaign style using research vessel or buoy. Therefore, we cannot monitor the temporal variation of seafloor crustal deformation in real time. The one of technical issue on real time observation is kinematic GPS analysis because kinematic GPS analysis based on reference and rover data. If the precise kinematic GPS analysis will be possible in the offshore region, it should be promising method for real time GPS/A with USV (Unmanned Surface Vehicle) and a moored buoy. We assessed stability, precision and accuracy of StarFireTM global satellites based augmentation system. We primarily tested for StarFire in the static condition. In order to assess coordinate precision and accuracy, we compared 1Hz StarFire time series and post-processed precise point positioning (PPP) 1Hz time series by GIPSY-OASIS II processing software Ver. 6.1.2 with three difference product types (ultra-rapid, rapid, and final orbits). We also used difference interval clock information (30 and 300 seconds) for the post-processed PPP processing. The standard deviation of real time StarFire time series is less than 30 mm (horizontal components) and 60 mm (vertical component) based on 1 month continuous processing. We also assessed noise spectrum of the estimated time series by StarFire and post-processed GIPSY PPP results. We found that the noise spectrum of StarFire time series is similar pattern with GIPSY-OASIS II processing result based on JPL rapid orbit products with 300 seconds interval clock information. And we report stability, precision and accuracy of StarFire in the moving conditon.

Modified dixon‐based renal dynamic contrast‐enhanced MRI facilitates automated registration and perfusion analysis

PubMed Central

Leiner, Tim; Vink, Eva E.; Blankestijn, Peter J.; van den Berg, Cornelis A.T.

2017-01-01

Purpose Renal dynamic contrast‐enhanced (DCE) MRI provides information on renal perfusion and filtration. However, clinical implementation is hampered by challenges in postprocessing as a result of misalignment of the kidneys due to respiration. We propose to perform automated image registration using the fat‐only images derived from a modified Dixon reconstruction of a dual‐echo acquisition because these provide consistent contrast over the dynamic series. Methods DCE data of 10 hypertensive patients was used. Dual‐echo images were acquired at 1.5 T with temporal resolution of 3.9 s during contrast agent injection. Dixon fat, water, and in‐phase and opposed‐phase (OP) images were reconstructed. Postprocessing was automated. Registration was performed both to fat images and OP images for comparison. Perfusion and filtration values were extracted from a two‐compartment model fit. Results Automatic registration to fat images performed better than automatic registration to OP images with visible contrast enhancement. Median vertical misalignment of the kidneys was 14 mm prior to registration, compared to 3 mm and 5 mm with registration to fat images and OP images, respectively (P = 0.03). Mean perfusion values and MR‐based glomerular filtration rates (GFR) were 233 ± 64 mL/100 mL/min and 60 ± 36 mL/minute, respectively, based on fat‐registered images. MR‐based GFR correlated with creatinine‐based GFR (P = 0.04) for fat‐registered images. For unregistered and OP‐registered images, this correlation was not significant. Conclusion Absence of contrast changes on Dixon fat images improves registration in renal DCE MRI and enables automated postprocessing, resulting in a more accurate estimation of GFR. Magn Reson Med 80:66–76, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. PMID:29134673

Research on detection method of UAV obstruction based on binocular vision

NASA Astrophysics Data System (ADS)

Zhu, Xiongwei; Lei, Xusheng; Sui, Zhehao

2018-04-01

For the autonomous obstacle positioning and ranging in the process of UAV (unmanned aerial vehicle) flight, a system based on binocular vision is constructed. A three-stage image preprocessing method is proposed to solve the problem of the noise and brightness difference in the actual captured image. The distance of the nearest obstacle is calculated by using the disparity map that generated by binocular vision. Then the contour of the obstacle is extracted by post-processing of the disparity map, and a color-based adaptive parameter adjustment algorithm is designed to extract contours of obstacle automatically. Finally, the safety distance measurement and obstacle positioning during the UAV flight process are achieved. Based on a series of tests, the error of distance measurement can keep within 2.24% of the measuring range from 5 m to 20 m.

Postprocessing for Air Quality Predictions

NASA Astrophysics Data System (ADS)

Delle Monache, L.

2017-12-01

In recent year, air quality (AQ) forecasting has made significant progress towards better predictions with the goal of protecting the public from harmful pollutants. This progress is the results of improvements in weather and chemical transport models, their coupling, and more accurate emission inventories (e.g., with the development of new algorithms to account in near real-time for fires). Nevertheless, AQ predictions are still affected at times by significant biases which stem from limitations in both weather and chemistry transport models. Those are the result of numerical approximations and the poor representation (and understanding) of important physical and chemical process. Moreover, although the quality of emission inventories has been significantly improved, they are still one of the main sources of uncertainties in AQ predictions. For operational real-time AQ forecasting, a significant portion of these biases can be reduced with the implementation of postprocessing methods. We will review some of the techniques that have been proposed to reduce both systematic and random errors of AQ predictions, and improve the correlation between predictions and observations of ground-level ozone and surface particulate matter less than 2.5 µm in diameter (PM2.5). These methods, which can be applied to both deterministic and probabilistic predictions, include simple bias-correction techniques, corrections inspired by the Kalman filter, regression methods, and the more recently developed analog-based algorithms. These approaches will be compared and contrasted, and strength and weaknesses of each will be discussed.

Efficiency of the spectral-spatial classification of hyperspectral imaging data

NASA Astrophysics Data System (ADS)

Borzov, S. M.; Potaturkin, O. I.

2017-01-01

The efficiency of methods of the spectral-spatial classification of similarly looking types of vegetation on the basis of hyperspectral data of remote sensing of the Earth, which take into account local neighborhoods of analyzed image pixels, is experimentally studied. Algorithms that involve spatial pre-processing of the raw data and post-processing of pixel-based spectral classification maps are considered. Results obtained both for a large-size hyperspectral image and for its test fragment with different methods of training set construction are reported. The classification accuracy in all cases is estimated through comparisons of ground-truth data and classification maps formed by using the compared methods. The reasons for the differences in these estimates are discussed.

The design and implementation of postprocessing for depth map on real-time extraction system.

PubMed

Tang, Zhiwei; Li, Bin; Li, Huosheng; Xu, Zheng

2014-01-01

Depth estimation becomes the key technology to resolve the communications of the stereo vision. We can get the real-time depth map based on hardware, which cannot implement complicated algorithm as software, because there are some restrictions in the hardware structure. Eventually, some wrong stereo matching will inevitably exist in the process of depth estimation by hardware, such as FPGA. In order to solve the problem a postprocessing function is designed in this paper. After matching cost unique test, the both left-right and right-left consistency check solutions are implemented, respectively; then, the cavities in depth maps can be filled by right depth values on the basis of right-left consistency check solution. The results in the experiments have shown that the depth map extraction and postprocessing function can be implemented in real time in the same system; what is more, the quality of the depth maps is satisfactory.

A post-processing method to simulate the generalized RF sheath boundary condition

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

Myra, James R.; Kohno, Haruhiko

For applications of ICRF power in fusion devices, control of RF sheath interactions is of great importance. A sheath boundary condition (SBC) was previously developed to provide an effective surface impedance for the interaction of the RF sheath with the waves. The SBC enables the surface power flux and rectified potential energy available for sputtering to be calculated. For legacy codes which cannot easily implement the SBC, or to speed convergence in codes which do implement it, we consider here an approximate method to simulate SBCs by post-processing results obtained using other, e.g. conducting wall, boundary conditions. The basic approximationmore » is that the modifications resulting from the generalized SBC are driven by a fixed incoming wave which could be either a fast wave or a slow wave. Finally, the method is illustrated in slab geometry and compared with exact numerical solutions; it is shown to work very well.« less

A post-processing method to simulate the generalized RF sheath boundary condition

DOE PAGES

Myra, James R.; Kohno, Haruhiko

2017-10-23

For applications of ICRF power in fusion devices, control of RF sheath interactions is of great importance. A sheath boundary condition (SBC) was previously developed to provide an effective surface impedance for the interaction of the RF sheath with the waves. The SBC enables the surface power flux and rectified potential energy available for sputtering to be calculated. For legacy codes which cannot easily implement the SBC, or to speed convergence in codes which do implement it, we consider here an approximate method to simulate SBCs by post-processing results obtained using other, e.g. conducting wall, boundary conditions. The basic approximationmore » is that the modifications resulting from the generalized SBC are driven by a fixed incoming wave which could be either a fast wave or a slow wave. Finally, the method is illustrated in slab geometry and compared with exact numerical solutions; it is shown to work very well.« less

Wavelet Filter Banks for Super-Resolution SAR Imaging

NASA Technical Reports Server (NTRS)

Sheybani, Ehsan O.; Deshpande, Manohar; Memarsadeghi, Nargess

2011-01-01

This paper discusses Innovative wavelet-based filter banks designed to enhance the analysis of super resolution Synthetic Aperture Radar (SAR) images using parametric spectral methods and signal classification algorithms, SAR finds applications In many of NASA's earth science fields such as deformation, ecosystem structure, and dynamics of Ice, snow and cold land processes, and surface water and ocean topography. Traditionally, standard methods such as Fast-Fourier Transform (FFT) and Inverse Fast-Fourier Transform (IFFT) have been used to extract Images from SAR radar data, Due to non-parametric features of these methods and their resolution limitations and observation time dependence, use of spectral estimation and signal pre- and post-processing techniques based on wavelets to process SAR radar data has been proposed. Multi-resolution wavelet transforms and advanced spectral estimation techniques have proven to offer efficient solutions to this problem.

Multivariate postprocessing techniques for probabilistic hydrological forecasting

NASA Astrophysics Data System (ADS)

Hemri, Stephan; Lisniak, Dmytro; Klein, Bastian

2016-04-01

Hydrologic ensemble forecasts driven by atmospheric ensemble prediction systems need statistical postprocessing in order to account for systematic errors in terms of both mean and spread. Runoff is an inherently multivariate process with typical events lasting from hours in case of floods to weeks or even months in case of droughts. This calls for multivariate postprocessing techniques that yield well calibrated forecasts in univariate terms and ensure a realistic temporal dependence structure at the same time. To this end, the univariate ensemble model output statistics (EMOS; Gneiting et al., 2005) postprocessing method is combined with two different copula approaches that ensure multivariate calibration throughout the entire forecast horizon. These approaches comprise ensemble copula coupling (ECC; Schefzik et al., 2013), which preserves the dependence structure of the raw ensemble, and a Gaussian copula approach (GCA; Pinson and Girard, 2012), which estimates the temporal correlations from training observations. Both methods are tested in a case study covering three subcatchments of the river Rhine that represent different sizes and hydrological regimes: the Upper Rhine up to the gauge Maxau, the river Moselle up to the gauge Trier, and the river Lahn up to the gauge Kalkofen. The results indicate that both ECC and GCA are suitable for modelling the temporal dependences of probabilistic hydrologic forecasts (Hemri et al., 2015). References Gneiting, T., A. E. Raftery, A. H. Westveld, and T. Goldman (2005), Calibrated probabilistic forecasting using ensemble model output statistics and minimum CRPS estimation, Monthly Weather Review, 133(5), 1098-1118, DOI: 10.1175/MWR2904.1. Hemri, S., D. Lisniak, and B. Klein, Multivariate postprocessing techniques for probabilistic hydrological forecasting, Water Resources Research, 51(9), 7436-7451, DOI: 10.1002/2014WR016473. Pinson, P., and R. Girard (2012), Evaluating the quality of scenarios of short-term wind power generation, Applied Energy, 96, 12-20, DOI: 10.1016/j.apenergy.2011.11.004. Schefzik, R., T. L. Thorarinsdottir, and T. Gneiting (2013), Uncertainty quantification in complex simulation models using ensemble copula coupling, Statistical Science, 28, 616-640, DOI: 10.1214/13-STS443.

Free-breathing diffusion tensor imaging and tractography of the human heart in healthy volunteers using wavelet-based image fusion.

PubMed

Wei, Hongjiang; Viallon, Magalie; Delattre, Benedicte M A; Moulin, Kevin; Yang, Feng; Croisille, Pierre; Zhu, Yuemin

2015-01-01

Free-breathing cardiac diffusion tensor imaging (DTI) is a promising but challenging technique for the study of fiber structures of the human heart in vivo. This work proposes a clinically compatible and robust technique to provide three-dimensional (3-D) fiber architecture properties of the human heart. To this end, 10 short-axis slices were acquired across the entire heart using a multiple shifted trigger delay (TD) strategy under free breathing conditions. Interscan motion was first corrected automatically using a nonrigid registration method. Then, two post-processing schemes were optimized and compared: an algorithm based on principal component analysis (PCA) filtering and temporal maximum intensity projection (TMIP), and an algorithm that uses the wavelet-based image fusion (WIF) method. The two methods were applied to the registered diffusion-weighted (DW) images to cope with intrascan motion-induced signal loss. The tensor fields were finally calculated, from which fractional anisotropy (FA), mean diffusivity (MD), and 3-D fiber tracts were derived and compared. The results show that the comparison of the FA values (FA(PCATMIP) = 0.45 ±0.10, FA(WIF) = 0.42 ±0.05, P=0.06) showed no significant difference, while the MD values ( MD(PCATMIP)=0.83 ±0.12×10(-3) mm (2)/s, MD(WIF)=0.74±0.05×10(-3) mm (2)/s, P=0.028) were significantly different. Improved helix angle variations through the myocardium wall reflecting the rotation characteristic of cardiac fibers were observed with WIF. This study demonstrates that the combination of multiple shifted TD acquisitions and dedicated post-processing makes it feasible to retrieve in vivo cardiac tractographies from free-breathing DTI acquisitions. The substantial improvements were observed using the WIF method instead of the previously published PCATMIP technique.

A grid-based tropospheric product for China using a GNSS network

NASA Astrophysics Data System (ADS)

Zhang, Hongxing; Yuan, Yunbin; Li, Wei; Zhang, Baocheng; Ou, Jikun

2017-11-01

Tropospheric delay accounts for one source of error in global navigation satellite systems (GNSS). To better characterize the tropospheric delays in the temporal and spatial domain and facilitate the safety-critical use of GNSS across China, a method is proposed to generate a grid-based tropospheric product (GTP) using the GNSS network with an empirical tropospheric model, known as IGGtrop. The prototype system generates the GTPs in post-processing and real-time modes and is based on the undifferenced and uncombined precise point positioning (UU-PPP) technique. GTPs are constructed for a grid form (2.0{°}× 2.5{°} latitude-longitude) over China with a time resolution of 5 min. The real-time GTP messages are encoded in a self-defined RTCM3 format and broadcast to users using NTRIP (networked transport of RTCM via internet protocol), which enables efficient and safe transmission to real-time users. Our approach for GTP generation consists of three sequential steps. In the first step, GNSS-derived zenith tropospheric delays (ZTDs) for a network of GNSS stations are estimated using UU-PPP. In the second step, vertical adjustments for the GNSS-derived ZTDs are applied to address the height differences between the GNSS stations and grid points. The ZTD height corrections are provided by the IGGtrop model. Finally, an inverse distance weighting method is used to interpolate the GNSS-derived ZTDs from the surrounding GNSS stations to the location of the grid point. A total of 210 global positioning system (GPS) stations from the crustal movement observation network of China are used to generate the GTPs in both post-processing and real-time modes. The accuracies of the GTPs are assessed against with ERA-Interim-derived ZTDs and the GPS-derived ZTDs at 12 test GPS stations, respectively. The results show that the post-processing and real-time GTPs can provide the ZTDs with accuracies of 1.4 and 1.8 cm, respectively. We also apply the GTPs in real-time kinematic GPS PPP, and the results show that the convergence time of the PPP solutions is shortened. These results confirm that the GTPs can act as an efficient information source to augment GNSS positioning over China.

Reducing the Requirements and Cost of Astronomical Telescopes

NASA Technical Reports Server (NTRS)

Smith, W. Scott; Whitakter, Ann F. (Technical Monitor)

2002-01-01

Limits on astronomical telescope apertures are being rapidly approached. These limits result from logistics, increasing complexity, and finally budgetary constraints. In an historical perspective, great strides have been made in the area of aperture, adaptive optics, wavefront sensors, detectors, stellar interferometers and image reconstruction. What will be the next advances? Emerging data analysis techniques based on communication theory holds the promise of yielding more information from observational data based on significant computer post-processing. This paper explores some of the current telescope limitations and ponders the possibilities increasing the yield of scientific data based on the migration computer post-processing techniques to higher dimensions. Some of these processes hold the promise of reducing the requirements on the basic telescope hardware making the next generation of instruments more affordable.

Raman spectral post-processing for oral tissue discrimination – a step for an automatized diagnostic system

PubMed Central

Carvalho, Luis Felipe C. S.; Nogueira, Marcelo Saito; Neto, Lázaro P. M.; Bhattacharjee, Tanmoy T.; Martin, Airton A.

2017-01-01

Most oral injuries are diagnosed by histopathological analysis of a biopsy, which is an invasive procedure and does not give immediate results. On the other hand, Raman spectroscopy is a real time and minimally invasive analytical tool with potential for the diagnosis of diseases. The potential for diagnostics can be improved by data post-processing. Hence, this study aims to evaluate the performance of preprocessing steps and multivariate analysis methods for the classification of normal tissues and pathological oral lesion spectra. A total of 80 spectra acquired from normal and abnormal tissues using optical fiber Raman-based spectroscopy (OFRS) were subjected to PCA preprocessing in the z-scored data set, and the KNN (K-nearest neighbors), J48 (unpruned C4.5 decision tree), RBF (radial basis function), RF (random forest), and MLP (multilayer perceptron) classifiers at WEKA software (Waikato environment for knowledge analysis), after area normalization or maximum intensity normalization. Our results suggest the best classification was achieved by using maximum intensity normalization followed by MLP. Based on these results, software for automated analysis can be generated and validated using larger data sets. This would aid quick comprehension of spectroscopic data and easy diagnosis by medical practitioners in clinical settings. PMID:29188115

Raman spectral post-processing for oral tissue discrimination - a step for an automatized diagnostic system.

PubMed

Carvalho, Luis Felipe C S; Nogueira, Marcelo Saito; Neto, Lázaro P M; Bhattacharjee, Tanmoy T; Martin, Airton A

2017-11-01

Most oral injuries are diagnosed by histopathological analysis of a biopsy, which is an invasive procedure and does not give immediate results. On the other hand, Raman spectroscopy is a real time and minimally invasive analytical tool with potential for the diagnosis of diseases. The potential for diagnostics can be improved by data post-processing. Hence, this study aims to evaluate the performance of preprocessing steps and multivariate analysis methods for the classification of normal tissues and pathological oral lesion spectra. A total of 80 spectra acquired from normal and abnormal tissues using optical fiber Raman-based spectroscopy (OFRS) were subjected to PCA preprocessing in the z-scored data set, and the KNN (K-nearest neighbors), J48 (unpruned C4.5 decision tree), RBF (radial basis function), RF (random forest), and MLP (multilayer perceptron) classifiers at WEKA software (Waikato environment for knowledge analysis), after area normalization or maximum intensity normalization. Our results suggest the best classification was achieved by using maximum intensity normalization followed by MLP. Based on these results, software for automated analysis can be generated and validated using larger data sets. This would aid quick comprehension of spectroscopic data and easy diagnosis by medical practitioners in clinical settings.

Noise reduction in single time frame optical DNA maps

PubMed Central

Müller, Vilhelm; Westerlund, Fredrik

2017-01-01

In optical DNA mapping technologies sequence-specific intensity variations (DNA barcodes) along stretched and stained DNA molecules are produced. These “fingerprints” of the underlying DNA sequence have a resolution of the order one kilobasepairs and the stretching of the DNA molecules are performed by surface adsorption or nano-channel setups. A post-processing challenge for nano-channel based methods, due to local and global random movement of the DNA molecule during imaging, is how to align different time frames in order to produce reproducible time-averaged DNA barcodes. The current solutions to this challenge are computationally rather slow. With high-throughput applications in mind, we here introduce a parameter-free method for filtering a single time frame noisy barcode (snap-shot optical map), measured in a fraction of a second. By using only a single time frame barcode we circumvent the need for post-processing alignment. We demonstrate that our method is successful at providing filtered barcodes which are less noisy and more similar to time averaged barcodes. The method is based on the application of a low-pass filter on a single noisy barcode using the width of the Point Spread Function of the system as a unique, and known, filtering parameter. We find that after applying our method, the Pearson correlation coefficient (a real number in the range from -1 to 1) between the single time-frame barcode and the time average of the aligned kymograph increases significantly, roughly by 0.2 on average. By comparing to a database of more than 3000 theoretical plasmid barcodes we show that the capabilities to identify plasmids is improved by filtering single time-frame barcodes compared to the unfiltered analogues. Since snap-shot experiments and computational time using our method both are less than a second, this study opens up for high throughput optical DNA mapping with improved reproducibility. PMID:28640821

TU-FG-BRB-03: Basis Vector Model Based Method for Proton Stopping Power Estimation From Experimental Dual Energy CT Data

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

Zhang, S; Politte, D; O’Sullivan, J

2016-06-15

Purpose: This work aims at reducing the uncertainty in proton stopping power (SP) estimation by a novel combination of a linear, separable basis vector model (BVM) for stopping power calculation (Med Phys 43:600) and a statistical, model-based dual-energy CT (DECT) image reconstruction algorithm (TMI 35:685). The method was applied to experimental data. Methods: BVM assumes the photon attenuation coefficients, electron densities, and mean excitation energies (I-values) of unknown materials can be approximated by a combination of the corresponding quantities of two reference materials. The DECT projection data for a phantom with 5 different known materials was collected on a Philipsmore » Brilliance scanner using two scans at 90 kVp and 140 kVp. The line integral alternating minimization (LIAM) algorithm was used to recover the two BVM coefficient images using the measured source spectra. The proton stopping powers are then estimated from the Bethe-Bloch equation using electron densities and I-values derived from the BVM coefficients. The proton stopping powers and proton ranges for the phantom materials estimated via our BVM based DECT method are compared to ICRU reference values and a post-processing DECT analysis (Yang PMB 55:1343) applied to vendorreconstructed images using the Torikoshi parametric fit model (tPFM). Results: For the phantom materials, the average stopping power estimations for 175 MeV protons derived from our method are within 1% of the ICRU reference values (except for Teflon with a 1.48% error), with an average standard deviation of 0.46% over pixels. The resultant proton ranges agree with the reference values within 2 mm. Conclusion: Our principled DECT iterative reconstruction algorithm, incorporating optimal beam hardening and scatter corrections, in conjunction with a simple linear BVM model, achieves more accurate and robust proton stopping power maps than the post-processing, nonlinear tPFM based DECT analysis applied to conventional reconstructions of low and high energy scans. Funding Support: NIH R01CA 75371; NCI grant R01 CA 149305.« less

Postprocessing Algorithm for Driving Conventional Scanning Tunneling Microscope at Fast Scan Rates

PubMed Central

Zhang, Hao; Li, Xianqi; Park, Jewook; Li, An-Ping

2017-01-01

We present an image postprocessing framework for Scanning Tunneling Microscope (STM) to reduce the strong spurious oscillations and scan line noise at fast scan rates and preserve the features, allowing an order of magnitude increase in the scan rate without upgrading the hardware. The proposed method consists of two steps for large scale images and four steps for atomic scale images. For large scale images, we first apply for each line an image registration method to align the forward and backward scans of the same line. In the second step we apply a “rubber band” model which is solved by a novel Constrained Adaptive and Iterative Filtering Algorithm (CIAFA). The numerical results on measurement from copper(111) surface indicate the processed images are comparable in accuracy to data obtained with a slow scan rate, but are free of the scan drift error commonly seen in slow scan data. For atomic scale images, an additional first step to remove line-by-line strong background fluctuations and a fourth step of replacing the postprocessed image by its ranking map as the final atomic resolution image are required. The resulting image restores the lattice image that is nearly undetectable in the original fast scan data. PMID:29362664

Optical vector network analyzer based on double-sideband modulation.

PubMed

Jun, Wen; Wang, Ling; Yang, Chengwu; Li, Ming; Zhu, Ning Hua; Guo, Jinjin; Xiong, Liangming; Li, Wei

2017-11-01

We report an optical vector network analyzer (OVNA) based on double-sideband (DSB) modulation using a dual-parallel Mach-Zehnder modulator. The device under test (DUT) is measured twice with different modulation schemes. By post-processing the measurement results, the response of the DUT can be obtained accurately. Since DSB modulation is used in our approach, the measurement range is doubled compared with conventional single-sideband (SSB) modulation-based OVNA. Moreover, the measurement accuracy is improved by eliminating the even-order sidebands. The key advantage of the proposed scheme is that the measurement of a DUT with bandpass response can also be simply realized, which is a big challenge for the SSB-based OVNA. The proposed method is theoretically and experimentally demonstrated.

Quantification of Human Cortical Bone Bound and Free Water in Vivo with Ultrashort Echo Time MR Imaging: A Model-based Approach.

PubMed

Abbasi-Rad, Shahrokh; Saligheh Rad, Hamidreza

2017-06-01

Purpose To quantify free and bound water components of cortical bone with a model-based numeric approach with use of ultrashort echo time (UTE) magnetic resonance (MR) imaging in vivo in order to introduce a new predictor for age-related deterioration of cortical bone structure. Materials and Methods Human studies were compliant with HIPAA and approved by the institutional review board. Dual-repetition time three-dimensional hybrid-radial UTE imaging was performed, followed by the application of postprocessing algorithms, to quantify free and bound water parameters (concentration [ρ] and longitudinal relaxation time [T1]) of human cortical bone in vivo. The postprocessing algorithms included the decomposition of bulk equations into free- and bound-associated equations and solving resulted inverse problem by using evolutionary strategy methods. To test the validity of the introduced biomarker, it was measured in 40 healthy women by using the proposed method, and associations among parameters were evaluated with the Pearson correlation coefficient. Results The mean free water concentration, bound water concentration, free water T1, and bound water T1 in the recruited population were 5.9%, 19.6%, 306.79 msec, and 162.47 msec, respectively. All reported values were in good agreement with those in the literature. Cortical bone free water T1 (R 2 = 0.72) and cortical bone free water concentration (R 2 = 0.62) showed strong positive correlations with age. Conclusion The cortical bone free water concentration and free water T1 derived with UTE imaging are good predictors of age-related deterioration of cortical bone structure and are potentially superior to previously introduced measures such as bone water concentration and suppression ratio. © RSNA, 2017.

a Method for the Positioning and Orientation of Rail-Bound Vehicles in Gnss-Free Environments

NASA Astrophysics Data System (ADS)

Hung, R.; King, B. A.; Chen, W.

2016-06-01

Mobile Mapping System (MMS) are increasingly applied for spatial data collection to support different fields because of their efficiencies and the levels of detail they can provide. The Position and Orientation System (POS), which is conventionally employed for locating and orienting MMS, allows direct georeferencing of spatial data in real-time. Since the performance of a POS depends on both the Inertial Navigation System (INS) and the Global Navigation Satellite System (GNSS), poor GNSS conditions, such as in long tunnels and underground, introduce the necessity for post-processing. In above-ground railways, mobile mapping technology is employed with high performance sensors for finite usage, which has considerable potential for enhancing railway safety and management in real-time. In contrast, underground railways present a challenge for a conventional POS thus alternative configurations are necessary to maintain data accuracy and alleviate the need for post-processing. This paper introduces a method of rail-bound navigation to replace the role of GNSS for railway applications. The proposed method integrates INS and track alignment data for environment-independent navigation and reduces the demand of post-processing. The principle of rail-bound navigation is presented and its performance is verified by an experiment using a consumer-grade Inertial Measurement Unit (IMU) and a small-scale railway model. The method produced a substantial improvement in position and orientation for a poorly initialised system in centimetre positional accuracy. The potential improvements indicated by, and limitations of rail-bound navigation are also considered for further development in existing railway systems.

Red lesion detection using background estimation and lesions characteristics in diabetic retinal image

NASA Astrophysics Data System (ADS)

Zhang, Dongbo; Peng, Yinghui; Yi, Yao; Shang, Xingyu

2013-10-01

Detection of red lesions [hemorrhages (HRs) and microaneurysms (MAs)] is crucial for the diagnosis of early diabetic retinopathy. A method based on background estimation and adapted to specific characteristics of HRs and MAs is proposed. Candidate red lesions are located by background estimation and Mahalanobis distance measure and then some adaptive postprocessing techniques, which include vessel detection, nonvessel exclusion based on shape analysis, and noise points exclusion by double-ring filter (only used for MAs detection), are conducted to remove nonlesion pixels. The method is evaluated on our collected image dataset, and experimental results show that it is better than or approximate to other previous approaches. It is effective to reduce the false-positive and false-negative results that arise from incomplete and inaccurate vessel structure.

Spatial Ensemble Postprocessing of Precipitation Forecasts Using High Resolution Analyses

NASA Astrophysics Data System (ADS)

Lang, Moritz N.; Schicker, Irene; Kann, Alexander; Wang, Yong

2017-04-01

Ensemble prediction systems are designed to account for errors or uncertainties in the initial and boundary conditions, imperfect parameterizations, etc. However, due to sampling errors and underestimation of the model errors, these ensemble forecasts tend to be underdispersive, and to lack both reliability and sharpness. To overcome such limitations, statistical postprocessing methods are commonly applied to these forecasts. In this study, a full-distributional spatial post-processing method is applied to short-range precipitation forecasts over Austria using Standardized Anomaly Model Output Statistics (SAMOS). Following Stauffer et al. (2016), observation and forecast fields are transformed into standardized anomalies by subtracting a site-specific climatological mean and dividing by the climatological standard deviation. Due to the need of fitting only a single regression model for the whole domain, the SAMOS framework provides a computationally inexpensive method to create operationally calibrated probabilistic forecasts for any arbitrary location or for all grid points in the domain simultaneously. Taking advantage of the INCA system (Integrated Nowcasting through Comprehensive Analysis), high resolution analyses are used for the computation of the observed climatology and for model training. The INCA system operationally combines station measurements and remote sensing data into real-time objective analysis fields at 1 km-horizontal resolution and 1 h-temporal resolution. The precipitation forecast used in this study is obtained from a limited area model ensemble prediction system also operated by ZAMG. The so called ALADIN-LAEF provides, by applying a multi-physics approach, a 17-member forecast at a horizontal resolution of 10.9 km and a temporal resolution of 1 hour. The performed SAMOS approach statistically combines the in-house developed high resolution analysis and ensemble prediction system. The station-based validation of 6 hour precipitation sums shows a mean improvement of more than 40% in CRPS when compared to bilinearly interpolated uncalibrated ensemble forecasts. The validation on randomly selected grid points, representing the true height distribution over Austria, still indicates a mean improvement of 35%. The applied statistical model is currently set up for 6-hourly and daily accumulation periods, but will be extended to a temporal resolution of 1-3 hours within a new probabilistic nowcasting system operated by ZAMG.

TH-CD-209-01: A Greedy Reassignment Algorithm for the PBS Minimum Monitor Unit Constraint

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

Lin, Y; Kooy, H; Craft, D

2016-06-15

Purpose: To investigate a Greedy Reassignment algorithm in order to mitigate the effects of low weight spots in proton pencil beam scanning (PBS) treatment plans. Methods: To convert a plan from the treatment planning system’s (TPS) to a deliverable plan, post processing methods can be used to adjust the spot maps to meets the minimum MU constraint. Existing methods include: deleting low weight spots (Cut method), or rounding spots with weight above/below half the limit up/down to the limit/zero (Round method). An alternative method called Greedy Reassignment was developed in this work in which the lowest weight spot in themore » field was removed and its weight reassigned equally among its nearest neighbors. The process was repeated with the next lowest weight spot until all spots in the field were above the MU constraint. The algorithm performance was evaluated using plans collected from 190 patients (496 fields) treated at our facility. The evaluation criteria were the γ-index pass rate comparing the pre-processed and post-processed dose distributions. A planning metric was further developed to predict the impact of post-processing on treatment plans for various treatment planning, machine, and dose tolerance parameters. Results: For fields with a gamma pass rate of 90±1%, the metric has a standard deviation equal to 18% of the centroid value. This showed that the metric and γ-index pass rate are correlated for the Greedy Reassignment algorithm. Using a 3rd order polynomial fit to the data, the Greedy Reassignment method had 1.8 times better metric at 90% pass rate compared to other post-processing methods. Conclusion: We showed that the Greedy Reassignment method yields deliverable plans that are closest to the optimized-without-MU-constraint plan from the TPS. The metric developed in this work could help design the minimum MU threshold with the goal of keeping the γ-index pass rate above an acceptable value.« less

HIPS: A new hippocampus subfield segmentation method.

PubMed

Romero, José E; Coupé, Pierrick; Manjón, José V

2017-12-01

The importance of the hippocampus in the study of several neurodegenerative diseases such as Alzheimer's disease makes it a structure of great interest in neuroimaging. However, few segmentation methods have been proposed to measure its subfields due to its complex structure and the lack of high resolution magnetic resonance (MR) data. In this work, we present a new pipeline for automatic hippocampus subfield segmentation using two available hippocampus subfield delineation protocols that can work with both high and standard resolution data. The proposed method is based on multi-atlas label fusion technology that benefits from a novel multi-contrast patch match search process (using high resolution T1-weighted and T2-weighted images). The proposed method also includes as post-processing a new neural network-based error correction step to minimize systematic segmentation errors. The method has been evaluated on both high and standard resolution images and compared to other state-of-the-art methods showing better results in terms of accuracy and execution time. Copyright © 2017 Elsevier Inc. All rights reserved.

Development of a Post-Processing Algorithm for Accurate Human Skull Profile Extraction via Ultrasonic Phased Arrays

NASA Astrophysics Data System (ADS)

Al-Ansary, Mariam Luay Y.

Ultrasound Imaging has been favored by clinicians for its safety, affordability, accessibility, and speed compared to other imaging modalities. However, the trade-offs to these benefits are a relatively lower image quality and interpretability, which can be addressed by, for example, post-processing methods. One particularly difficult imaging case is associated with the presence of a barrier, such as a human skull, with significantly different acoustical properties than the brain tissue as the target medium. Some methods were proposed in the literature to account for this structure if the skull's geometry is known. Measuring the skull's geometry is therefore an important task that requires attention. In this work, a new edge detection method for accurate human skull profile extraction via post-processing of ultrasonic A-Scans is introduced. This method, referred to as the Selective Echo Extraction algorithm, SEE, processes each A-Scan separately and determines the outermost and innermost boundaries of the skull by means of adaptive filtering. The method can also be used to determine the average attenuation coefficient of the skull. When applied to simulated B-Mode images of the skull profile, promising results were obtained. The profiles obtained from the proposed process in simulations were found to be within 0.15lambda +/- 0.11lambda or 0.09 +/- 0.07mm from the actual profiles. Experiments were also performed to test SEE on skull mimicking phantoms with major acoustical properties similar to those of the actual human skull. With experimental data, the profiles obtained with the proposed process were within 0.32lambda +/- 0.25lambda or 0.19 +/- 0.15mm from the actual profile.

On Aethalometer measurement uncertainties and an instrument correction factor for the Arctic

NASA Astrophysics Data System (ADS)

Backman, John; Schmeisser, Lauren; Virkkula, Aki; Ogren, John A.; Asmi, Eija; Starkweather, Sandra; Sharma, Sangeeta; Eleftheriadis, Konstantinos; Uttal, Taneil; Jefferson, Anne; Bergin, Michael; Makshtas, Alexander; Tunved, Peter; Fiebig, Markus

2017-12-01

Several types of filter-based instruments are used to estimate aerosol light absorption coefficients. Two significant results are presented based on Aethalometer measurements at six Arctic stations from 2012 to 2014. First, an alternative method of post-processing the Aethalometer data is presented, which reduces measurement noise and lowers the detection limit of the instrument more effectively than boxcar averaging. The biggest benefit of this approach can be achieved if instrument drift is minimised. Moreover, by using an attenuation threshold criterion for data post-processing, the relative uncertainty from the electronic noise of the instrument is kept constant. This approach results in a time series with a variable collection time (Δt) but with a constant relative uncertainty with regard to electronic noise in the instrument. An additional advantage of this method is that the detection limit of the instrument will be lowered at small aerosol concentrations at the expense of temporal resolution, whereas there is little to no loss in temporal resolution at high aerosol concentrations ( > 2.1-6.7 Mm-1 as measured by the Aethalometers). At high aerosol concentrations, minimising the detection limit of the instrument is less critical. Additionally, utilising co-located filter-based absorption photometers, a correction factor is presented for the Arctic that can be used in Aethalometer corrections available in literature. The correction factor of 3.45 was calculated for low-elevation Arctic stations. This correction factor harmonises Aethalometer attenuation coefficients with light absorption coefficients as measured by the co-located light absorption photometers. Using one correction factor for Arctic Aethalometers has the advantage that measurements between stations become more inter-comparable.

An in vitro test bench reproducing coronary blood flow signals.

PubMed

Chodzyński, Kamil Jerzy; Boudjeltia, Karim Zouaoui; Lalmand, Jacques; Aminian, Adel; Vanhamme, Luc; de Sousa, Daniel Ribeiro; Gremmo, Simone; Bricteux, Laurent; Renotte, Christine; Courbebaisse, Guy; Coussement, Grégory

2015-08-07

It is a known fact that blood flow pattern and more specifically the pulsatile time variation of shear stress on the vascular wall play a key role in atherogenesis. The paper presents the conception, the building and the control of a new in vitro test bench that mimics the pulsatile flows behavior based on in vivo measurements. An in vitro cardiovascular simulator is alimented with in vivo constraints upstream and provided with further post-processing analysis downstream in order to mimic the pulsatile in vivo blood flow quantities. This real-time controlled system is designed to perform real pulsatile in vivo blood flow signals to study endothelial cells' behavior under near physiological environment. The system is based on an internal model controller and a proportional-integral controller that controls a linear motor with customized piston pump, two proportional-integral controllers that control the mean flow rate and temperature of the medium. This configuration enables to mimic any resulting blood flow rate patterns between 40 and 700 ml/min. In order to feed the system with reliable periodic flow quantities in vivo measurements were performed. Data from five patients (1 female, 4 males; ages 44-63) were filtered and post-processed using the Newtonian Womersley's solution. These resulting flow signals were compared with 2D axisymmetric, numerical simulation using a Carreau non-Newtonian model to validate the approximation of a Newtonian behavior. This in vitro test bench reproduces the measured flow rate time evolution and the complexity of in vivo hemodynamic signals within the accuracy of the relative error below 5%. This post-processing method is compatible with any real complex in vivo signal and demonstrates the heterogeneity of pulsatile patterns in coronary arteries among of different patients. The comparison between analytical and numerical solution demonstrate the fair quality of the Newtonian Womersley's approximation. Therefore, Womersley's solution was used to calculate input flow rate for the in vitro test bench.

Voxel-based Gaussian naïve Bayes classification of ischemic stroke lesions in individual T1-weighted MRI scans.

PubMed

Griffis, Joseph C; Allendorfer, Jane B; Szaflarski, Jerzy P

2016-01-15

Manual lesion delineation by an expert is the standard for lesion identification in MRI scans, but it is time-consuming and can introduce subjective bias. Alternative methods often require multi-modal MRI data, user interaction, scans from a control population, and/or arbitrary statistical thresholding. We present an approach for automatically identifying stroke lesions in individual T1-weighted MRI scans using naïve Bayes classification. Probabilistic tissue segmentation and image algebra were used to create feature maps encoding information about missing and abnormal tissue. Leave-one-case-out training and cross-validation was used to obtain out-of-sample predictions for each of 30 cases with left hemisphere stroke lesions. Our method correctly predicted lesion locations for 30/30 un-trained cases. Post-processing with smoothing (8mm FWHM) and cluster-extent thresholding (100 voxels) was found to improve performance. Quantitative evaluations of post-processed out-of-sample predictions on 30 cases revealed high spatial overlap (mean Dice similarity coefficient=0.66) and volume agreement (mean percent volume difference=28.91; Pearson's r=0.97) with manual lesion delineations. Our automated approach agrees with manual tracing. It provides an alternative to automated methods that require multi-modal MRI data, additional control scans, or user interaction to achieve optimal performance. Our fully trained classifier has applications in neuroimaging and clinical contexts. Copyright © 2015 Elsevier B.V. All rights reserved.

A three-image algorithm for hard x-ray grating interferometry.

PubMed

Pelliccia, Daniele; Rigon, Luigi; Arfelli, Fulvia; Menk, Ralf-Hendrik; Bukreeva, Inna; Cedola, Alessia

2013-08-12

A three-image method to extract absorption, refraction and scattering information for hard x-ray grating interferometry is presented. The method comprises a post-processing approach alternative to the conventional phase stepping procedure and is inspired by a similar three-image technique developed for analyzer-based x-ray imaging. Results obtained with this algorithm are quantitatively comparable with phase-stepping. This method can be further extended to samples with negligible scattering, where only two images are needed to separate absorption and refraction signal. Thanks to the limited number of images required, this technique is a viable route to bio-compatible imaging with x-ray grating interferometer. In addition our method elucidates and strengthens the formal and practical analogies between grating interferometry and the (non-interferometric) diffraction enhanced imaging technique.

Adaptive Optics Image Restoration Based on Frame Selection and Multi-frame Blind Deconvolution

NASA Astrophysics Data System (ADS)

Tian, Yu; Rao, Chang-hui; Wei, Kai

Restricted by the observational condition and the hardware, adaptive optics can only make a partial correction of the optical images blurred by atmospheric turbulence. A postprocessing method based on frame selection and multi-frame blind deconvolution is proposed for the restoration of high-resolution adaptive optics images. By frame selection we mean we first make a selection of the degraded (blurred) images for participation in the iterative blind deconvolution calculation, with no need of any a priori knowledge, and with only a positivity constraint. This method has been applied to the restoration of some stellar images observed by the 61-element adaptive optics system installed on the Yunnan Observatory 1.2m telescope. The experimental results indicate that this method can effectively compensate for the residual errors of the adaptive optics system on the image, and the restored image can reach the diffraction-limited quality.

Enhancement of low visibility aerial images using histogram truncation and an explicit Retinex representation for balancing contrast and color consistency

NASA Astrophysics Data System (ADS)

Liu, Changjiang; Cheng, Irene; Zhang, Yi; Basu, Anup

2017-06-01

This paper presents an improved multi-scale Retinex (MSR) based enhancement for ariel images under low visibility. For traditional multi-scale Retinex, three scales are commonly employed, which limits its application scenarios. We extend our research to a general purpose enhanced method, and design an MSR with more than three scales. Based on the mathematical analysis and deductions, an explicit multi-scale representation is proposed that balances image contrast and color consistency. In addition, a histogram truncation technique is introduced as a post-processing strategy to remap the multi-scale Retinex output to the dynamic range of the display. Analysis of experimental results and comparisons with existing algorithms demonstrate the effectiveness and generality of the proposed method. Results on image quality assessment proves the accuracy of the proposed method with respect to both objective and subjective criteria.

Spectral-spatial classification of hyperspectral image using three-dimensional convolution network

NASA Astrophysics Data System (ADS)

Liu, Bing; Yu, Xuchu; Zhang, Pengqiang; Tan, Xiong; Wang, Ruirui; Zhi, Lu

2018-01-01

Recently, hyperspectral image (HSI) classification has become a focus of research. However, the complex structure of an HSI makes feature extraction difficult to achieve. Most current methods build classifiers based on complex handcrafted features computed from the raw inputs. The design of an improved 3-D convolutional neural network (3D-CNN) model for HSI classification is described. This model extracts features from both the spectral and spatial dimensions through the application of 3-D convolutions, thereby capturing the important discrimination information encoded in multiple adjacent bands. The designed model views the HSI cube data altogether without relying on any pre- or postprocessing. In addition, the model is trained in an end-to-end fashion without any handcrafted features. The designed model was applied to three widely used HSI datasets. The experimental results demonstrate that the 3D-CNN-based method outperforms conventional methods even with limited labeled training samples.

Limitations on post-processing assisted quantum programming

NASA Astrophysics Data System (ADS)

Heinosaari, Teiko; Miyadera, Takayuki; Tukiainen, Mikko

2017-03-01

A quantum multimeter is a programmable device that can implement measurements of different observables depending on the programming quantum state inserted into it. The advantage of this arrangement over a single-purpose device is in its versatility: one can realize various measurements simply by changing the programming state. The classical manipulation of measurement output data is known as post-processing. In this work we study the post-processing assisted quantum programming, which is a protocol where quantum programming and classical post-processing are combined. We provide examples showing that these two processes combined can be more efficient than either of them used separately. Furthermore, we derive an inequality relating the programming resources to their corresponding programmed observables, thereby enabling us to study the limitations on post-processing assisted quantum programming.

Post-processing of a low-flow forecasting system in the Thur basin (Switzerland)

NASA Astrophysics Data System (ADS)

Bogner, Konrad; Joerg-Hess, Stefanie; Bernhard, Luzi; Zappa, Massimiliano

2015-04-01

Low-flows and droughts are natural hazards with potentially severe impacts and economic loss or damage in a number of environmental and socio-economic sectors. As droughts develop slowly there is time to prepare and pre-empt some of these impacts. Real-time information and forecasting of a drought situation can therefore be an effective component of drought management. Although Switzerland has traditionally been more concerned with problems related to floods, in recent years some unprecedented low-flow situations have been experienced. Driven by the climate change debate a drought information platform has been developed to guide water resources management during situations where water resources drop below critical low-flow levels characterised by the indices duration (time between onset and offset), severity (cumulative water deficit) and magnitude (severity/duration). However to gain maximum benefit from such an information system it is essential to remove the bias from the meteorological forecast, to derive optimal estimates of the initial conditions, and to post-process the stream-flow forecasts. Quantile mapping methods for pre-processing the meteorological forecasts and improved data assimilation methods of snow measurements, which accounts for much of the seasonal stream-flow predictability for the majority of the basins in Switzerland, have been tested previously. The objective of this study is the testing of post-processing methods in order to remove bias and dispersion errors and to derive the predictive uncertainty of a calibrated low-flow forecast system. Therefore various stream-flow error correction methods with different degrees of complexity have been applied and combined with the Hydrological Uncertainty Processor (HUP) in order to minimise the differences between the observations and model predictions and to derive posterior probabilities. The complexity of the analysed error correction methods ranges from simple AR(1) models to methods including wavelet transformations and support vector machines. These methods have been combined with forecasts driven by Numerical Weather Prediction (NWP) systems with different temporal and spatial resolutions, lead-times and different numbers of ensembles covering short to medium to extended range forecasts (COSMO-LEPS, 10-15 days, monthly and seasonal ENS) as well as climatological forecasts. Additionally the suitability of various skill scores and efficiency measures regarding low-flow predictions will be tested. Amongst others the novel 2afc (2 alternatives forced choices) score and the quantile skill score and its decompositions will be applied to evaluate the probabilistic forecasts and the effects of post-processing. First results of the performance of the low-flow predictions of the hydrological model PREVAH initialised with different NWP's will be shown.

Forensic identification of resampling operators: A semi non-intrusive approach.

PubMed

Cao, Gang; Zhao, Yao; Ni, Rongrong

2012-03-10

Recently, several new resampling operators have been proposed and successfully invalidate the existing resampling detectors. However, the reliability of such anti-forensic techniques is unaware and needs to be investigated. In this paper, we focus on the forensic identification of digital image resampling operators including the traditional type and the anti-forensic type which hides the trace of traditional resampling. Various resampling algorithms involving geometric distortion (GD)-based, dual-path-based and postprocessing-based are investigated. The identification is achieved in the manner of semi non-intrusive, supposing the resampling software could be accessed. Given an input pattern of monotone signal, polarity aberration of GD-based resampled signal's first derivative is analyzed theoretically and measured by effective feature metric. Dual-path-based and postprocessing-based resampling can also be identified by feeding proper test patterns. Experimental results on various parameter settings demonstrate the effectiveness of the proposed approach. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Cobalt Oxide Nanosheet and CNT Micro Carbon Monoxide Sensor Integrated with Readout Circuit on Chip

PubMed Central

Dai, Ching-Liang; Chen, Yen-Chi; Wu, Chyan-Chyi; Kuo, Chin-Fu

2010-01-01

The study presents a micro carbon monoxide (CO) sensor integrated with a readout circuit-on-a-chip manufactured by the commercial 0.35 μm complementary metal oxide semiconductor (CMOS) process and a post-process. The sensing film of the sensor is a composite cobalt oxide nanosheet and carbon nanotube (CoOOH/CNT) film that is prepared by a precipitation-oxidation method. The structure of the CO sensor is composed of a polysilicon resistor and a sensing film. The sensor, which is of a resistive type, changes its resistance when the sensing film adsorbs or desorbs CO gas. The readout circuit is used to convert the sensor resistance into the voltage output. The post-processing of the sensor includes etching the sacrificial layers and coating the sensing film. The advantages of the sensor include room temperature operation, short response/recovery times and easy post-processing. Experimental results show that the sensitivity of the CO sensor is about 0.19 mV/ppm, and the response and recovery times are 23 s and 34 s for 200 ppm CO, respectively. PMID:22294897

Cobalt oxide nanosheet and CNT micro carbon monoxide sensor integrated with readout circuit on chip.

PubMed

Dai, Ching-Liang; Chen, Yen-Chi; Wu, Chyan-Chyi; Kuo, Chin-Fu

2010-01-01

The study presents a micro carbon monoxide (CO) sensor integrated with a readout circuit-on-a-chip manufactured by the commercial 0.35 μm complementary metal oxide semiconductor (CMOS) process and a post-process. The sensing film of the sensor is a composite cobalt oxide nanosheet and carbon nanotube (CoOOH/CNT) film that is prepared by a precipitation-oxidation method. The structure of the CO sensor is composed of a polysilicon resistor and a sensing film. The sensor, which is of a resistive type, changes its resistance when the sensing film adsorbs or desorbs CO gas. The readout circuit is used to convert the sensor resistance into the voltage output. The post-processing of the sensor includes etching the sacrificial layers and coating the sensing film. The advantages of the sensor include room temperature operation, short response/recovery times and easy post-processing. Experimental results show that the sensitivity of the CO sensor is about 0.19 mV/ppm, and the response and recovery times are 23 s and 34 s for 200 ppm CO, respectively.

High resolution probabilistic precipitation forecast over Spain combining the statistical downscaling tool PROMETEO and the AEMET short range EPS system (AEMET/SREPS)

NASA Astrophysics Data System (ADS)

Cofino, A. S.; Santos, C.; Garcia-Moya, J. A.; Gutierrez, J. M.; Orfila, B.

2009-04-01

The Short-Range Ensemble Prediction System (SREPS) is a multi-LAM (UM, HIRLAM, MM5, LM and HRM) multi analysis/boundary conditions (ECMWF, UKMetOffice, DWD and GFS) run twice a day by AEMET (72 hours lead time) over a European domain, with a total of 5 (LAMs) x 4 (GCMs) = 20 members. One of the main goals of this project is analyzing the impact of models and boundary conditions in the short-range high-resolution forecasted precipitation. A previous validation of this method has been done considering a set of climate networks in Spain, France and Germany, by interpolating the prediction to the gauge locations (SREPS, 2008). In this work we compare these results with those obtained by using a statistical downscaling method to post-process the global predictions, obtaining an "advanced interpolation" for the local precipitation using climate network precipitation observations. In particular, we apply the PROMETEO downscaling system based on analogs and compare the SREPS ensemble of 20 members with the PROMETEO statistical ensemble of 5 (analog ensemble) x 4 (GCMs) = 20 members. Moreover, we will also compare the performance of a combined approach post-processing the SREPS outputs using the PROMETEO system. References: SREPS 2008. 2008 EWGLAM-SRNWP Meeting (http://www.aemet.es/documentos/va/divulgacion/conferencias/prediccion/Ewglam/PRED_CSantos.pdf)

SU-G-IeP1-01: A Novel MRI Post-Processing Algorithm for Visualization of the Prostate LDR Brachytherapy Seeds and Calcifications Based On B0 Field Inhomogeneity Correction and Hough Transform

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

Nosrati, R; Sunnybrook Health Sciences Centre, Toronto, Ontario; Soliman, A

Purpose: This study aims at developing an MRI-only workflow for post-implant dosimetry of the prostate LDR brachytherapy seeds. The specific goal here is to develop a post-processing algorithm to produce positive contrast for the seeds and prostatic calcifications and differentiate between them on MR images. Methods: An agar-based phantom incorporating four dummy seeds (I-125) and five calcifications of different sizes (from sheep cortical bone) was constructed. Seeds were placed arbitrarily in the coronal plane. The phantom was scanned with 3T Philips Achieva MR scanner using an 8-channel head coil array. Multi-echo turbo spin echo (ME-TSE) and multi-echo gradient recalled echomore » (ME-GRE) sequences were acquired. Due to minimal susceptibility artifacts around seeds, ME-GRE sequence (flip angle=15; TR/TE=20/2.3/2.3; resolution=0.7×0.7×2mm3) was further processed.The induced field inhomogeneity due to the presence of titaniumencapsulated seeds was corrected using a B0 field map. B0 map was calculated using the ME-GRE sequence by calculating the phase difference at two different echo times. Initially, the product of the first echo and B0 map was calculated. The features corresponding to the seeds were then extracted in three steps: 1) the edge pixels were isolated using “Prewitt” operator; 2) the Hough transform was employed to detect ellipses approximately matching the dimensions of the seeds and 3) at the position and orientation of the detected ellipses an ellipse was drawn on the B0-corrected image. Results: The proposed B0-correction process produced positive contrast for the seeds and calcifications. The Hough transform based on Prewitt edge operator successfully identified all the seeds according to their ellipsoidal shape and dimensions in the edge image. Conclusion: The proposed post-processing algorithm successfully visualized the seeds and calcifications with positive contrast and differentiates between them according to their shapes. Further assessments on more realistic phantoms and patient study are required to validate the outcome.« less

Multiple imputation of rainfall missing data in the Iberian Mediterranean context

NASA Astrophysics Data System (ADS)

Miró, Juan Javier; Caselles, Vicente; Estrela, María José

2017-11-01

Given the increasing need for complete rainfall data networks, in recent years have been proposed diverse methods for filling gaps in observed precipitation series, progressively more advanced that traditional approaches to overcome the problem. The present study has consisted in validate 10 methods (6 linear, 2 non-linear and 2 hybrid) that allow multiple imputation, i.e., fill at the same time missing data of multiple incomplete series in a dense network of neighboring stations. These were applied for daily and monthly rainfall in two sectors in the Júcar River Basin Authority (east Iberian Peninsula), which is characterized by a high spatial irregularity and difficulty of rainfall estimation. A classification of precipitation according to their genetic origin was applied as pre-processing, and a quantile-mapping adjusting as post-processing technique. The results showed in general a better performance for the non-linear and hybrid methods, highlighting that the non-linear PCA (NLPCA) method outperforms considerably the Self Organizing Maps (SOM) method within non-linear approaches. On linear methods, the Regularized Expectation Maximization method (RegEM) was the best, but far from NLPCA. Applying EOF filtering as post-processing of NLPCA (hybrid approach) yielded the best results.

Achieving superresolution with illumination-enhanced sparsity.

PubMed

Yu, Jiun-Yann; Becker, Stephen R; Folberth, James; Wallin, Bruce F; Chen, Simeng; Cogswell, Carol J

2018-04-16

Recent advances in superresolution fluorescence microscopy have been limited by a belief that surpassing two-fold resolution enhancement of the Rayleigh resolution limit requires stimulated emission or the fluorophore to undergo state transitions. Here we demonstrate a new superresolution method that requires only image acquisitions with a focused illumination spot and computational post-processing. The proposed method utilizes the focused illumination spot to effectively reduce the object size and enhance the object sparsity and consequently increases the resolution and accuracy through nonlinear image post-processing. This method clearly resolves 70nm resolution test objects emitting ~530nm light with a 1.4 numerical aperture (NA) objective, and, when imaging through a 0.5NA objective, exhibits high spatial frequencies comparable to a 1.4NA widefield image, both demonstrating a resolution enhancement above two-fold of the Rayleigh resolution limit. More importantly, we examine how the resolution increases with photon numbers, and show that the more-than-two-fold enhancement is achievable with realistic photon budgets.

Streamflow forecasts from WRF precipitation for flood early warning in mountain tropical areas

NASA Astrophysics Data System (ADS)

Rogelis, María Carolina; Werner, Micha

2018-02-01

Numerical weather prediction (NWP) models are fundamental to extend forecast lead times beyond the concentration time of a watershed. Particularly for flash flood forecasting in tropical mountainous watersheds, forecast precipitation is required to provide timely warnings. This paper aims to assess the potential of NWP for flood early warning purposes, and the possible improvement that bias correction can provide, in a tropical mountainous area. The paper focuses on the comparison of streamflows obtained from the post-processed precipitation forecasts, particularly the comparison of ensemble forecasts and their potential in providing skilful flood forecasts. The Weather Research and Forecasting (WRF) model is used to produce precipitation forecasts that are post-processed and used to drive a hydrologic model. Discharge forecasts obtained from the hydrological model are used to assess the skill of the WRF model. The results show that post-processed WRF precipitation adds value to the flood early warning system when compared to zero-precipitation forecasts, although the precipitation forecast used in this analysis showed little added value when compared to climatology. However, the reduction of biases obtained from the post-processed ensembles show the potential of this method and model to provide usable precipitation forecasts in tropical mountainous watersheds. The need for more detailed evaluation of the WRF model in the study area is highlighted, particularly the identification of the most suitable parameterisation, due to the inability of the model to adequately represent the convective precipitation found in the study area.

Using Resin-Based 3D Printing to Build Geometrically Accurate Proxies of Porous Sedimentary Rocks.

PubMed

Ishutov, Sergey; Hasiuk, Franciszek J; Jobe, Dawn; Agar, Susan

2018-05-01

Three-dimensional (3D) printing is capable of transforming intricate digital models into tangible objects, allowing geoscientists to replicate the geometry of 3D pore networks of sedimentary rocks. We provide a refined method for building scalable pore-network models ("proxies") using stereolithography 3D printing that can be used in repeated flow experiments (e.g., core flooding, permeametry, porosimetry). Typically, this workflow involves two steps, model design and 3D printing. In this study, we explore how the addition of post-processing and validation can reduce uncertainty in the 3D-printed proxy accuracy (difference of proxy geometry from the digital model). Post-processing is a multi-step cleaning of porous proxies involving pressurized ethanol flushing and oven drying. Proxies are validated by: (1) helium porosimetry and (2) digital measurements of porosity from thin-section images of 3D-printed proxies. 3D printer resolution was determined by measuring the smallest open channel in 3D-printed "gap test" wafers. This resolution (400 µm) was insufficient to build porosity of Fontainebleau sandstone (∼13%) from computed tomography data at the sample's natural scale, so proxies were printed at 15-, 23-, and 30-fold magnifications to validate the workflow. Helium porosities of the 3D-printed proxies differed from digital calculations by up to 7% points. Results improved after pressurized flushing with ethanol (e.g., porosity difference reduced to ∼1% point), though uncertainties remain regarding the nature of sub-micron "artifact" pores imparted by the 3D printing process. This study shows the benefits of including post-processing and validation in any workflow to produce porous rock proxies. © 2017, National Ground Water Association.

Assessing LiDAR elevation data for KDOT applications.

DOT National Transportation Integrated Search

2013-02-01

LiDAR-based elevation surveys are a cost-effective means for mapping topography over large areas. LiDAR : surveys use an airplane-mounted or ground-based laser radar unit to scan terrain. Post-processing techniques are : applied to remove vegetation ...

Towards effective interactive three-dimensional colour postprocessing

NASA Technical Reports Server (NTRS)

Bailey, B. C.; Hajjar, J. F.; Abel, J. F.

1986-01-01

Recommendations for the development of effective three-dimensional, graphical color postprocessing are made. First, the evaluation of large, complex numerical models demands that a postprocessor be highly interactive. A menu of available functions should be provided and these operations should be performed quickly so that a sense of continuity and spontaneity exists during the post-processing session. Second, an agenda for three-dimensional color postprocessing is proposed. A postprocessor must be versatile with respect to application and basic algorithms must be designed so that they are flexible. A complete selection of tools is necessary to allow arbitrary specification of views, extraction of qualitative information, and access to detailed quantitative and problem information. Finally, full use of advanced display hardware is necessary if interactivity is to be maximized and effective postprocessing of today's numerical simulations is to be achieved.

The application of quasi-steady approximation in atomic kinetics in simulation of hohlraum radiation drive

NASA Astrophysics Data System (ADS)

Ren, Guoli; Pei, Wenbing; Lan, Ke; Gu, Peijun; Li, Xin; Institute of Applied Physics; Computional Mathematics Team

2011-10-01

In current routine 2D simulation of hohlraum physics, we adopt the principal-quantum- number(n-level) average atom model(AAM). However, the experimental frequency-dependant radiative drive differs from our n-level simulated drive, which reminds us the need of a more detailed atomic kinetics description. The orbital-quantum-number(nl-level) AAM is a natural consideration but the in-line calculation consumes much more resources. We use a new method to built up a nl-level bound electron distribution using in-line n-level calculated plasma condition (such as temperature, density, average ionization degree). We name this method ``quasi-steady approximation.'' Using the re-built nl-level bound electron distribution (Pnl) , we acquire a new hohlraum radiative drive by post-processing. Comparison with the n-level post-processed hohlraum drive shows that we get an almost identical radiation flux but with more-detailed frequency-dependant structures.

Post-processing of the HST STIS coronagraphic observations

NASA Astrophysics Data System (ADS)

Ren, Bin; Pueyo, Laurent; Perrin, Marshall D.; Debes, John H.; Choquet, Élodie

2017-09-01

In the past 20 years, the Hubble Space Telescope (HST) STIS coronagraphic instrument has observed more than 100 stars, obtaining more than 4,000 readouts since its installment on HST in 1997 and the numbers are still increasing. We reduce the whole STIS coronagraphic archive at the most commonly observed positions (Wedge A0.6 and A1.0) with new post-processing methods, and present our results here. We are able to recover all of the 32 previously reported circumstellar disks, and obtain better contrast close to the star. For some of the disks, our results are limited by the over subtraction of the methods, and therefore the major regions of the disks can be recovered except the faintest regions. We also explain our efforts in the calibration of its new BAR5 occulting position, enabling STIS to explore inner regions as close as 0.2 00 .

A Format for Phylogenetic Placements

PubMed Central

Matsen, Frederick A.; Hoffman, Noah G.; Gallagher, Aaron; Stamatakis, Alexandros

2012-01-01

We have developed a unified format for phylogenetic placements, that is, mappings of environmental sequence data (e.g., short reads) into a phylogenetic tree. We are motivated to do so by the growing number of tools for computing and post-processing phylogenetic placements, and the lack of an established standard for storing them. The format is lightweight, versatile, extensible, and is based on the JSON format, which can be parsed by most modern programming languages. Our format is already implemented in several tools for computing and post-processing parsimony- and likelihood-based phylogenetic placements and has worked well in practice. We believe that establishing a standard format for analyzing read placements at this early stage will lead to a more efficient development of powerful and portable post-analysis tools for the growing applications of phylogenetic placement. PMID:22383988

A format for phylogenetic placements.

PubMed

Matsen, Frederick A; Hoffman, Noah G; Gallagher, Aaron; Stamatakis, Alexandros

2012-01-01

We have developed a unified format for phylogenetic placements, that is, mappings of environmental sequence data (e.g., short reads) into a phylogenetic tree. We are motivated to do so by the growing number of tools for computing and post-processing phylogenetic placements, and the lack of an established standard for storing them. The format is lightweight, versatile, extensible, and is based on the JSON format, which can be parsed by most modern programming languages. Our format is already implemented in several tools for computing and post-processing parsimony- and likelihood-based phylogenetic placements and has worked well in practice. We believe that establishing a standard format for analyzing read placements at this early stage will lead to a more efficient development of powerful and portable post-analysis tools for the growing applications of phylogenetic placement.

A Knowledge-Based Approach to Automatic Detection of Equipment Alarm Sounds in a Neonatal Intensive Care Unit Environment.

PubMed

Raboshchuk, Ganna; Nadeu, Climent; Jancovic, Peter; Lilja, Alex Peiro; Kokuer, Munevver; Munoz Mahamud, Blanca; Riverola De Veciana, Ana

2018-01-01

A large number of alarm sounds triggered by biomedical equipment occur frequently in the noisy environment of a neonatal intensive care unit (NICU) and play a key role in providing healthcare. In this paper, our work on the development of an automatic system for detection of acoustic alarms in that difficult environment is presented. Such automatic detection system is needed for the investigation of how a preterm infant reacts to auditory stimuli of the NICU environment and for an improved real-time patient monitoring. The approach presented in this paper consists of using the available knowledge about each alarm class in the design of the detection system. The information about the frequency structure is used in the feature extraction stage, and the time structure knowledge is incorporated at the post-processing stage. Several alternative methods are compared for feature extraction, modeling, and post-processing. The detection performance is evaluated with real data recorded in the NICU of the hospital, and by using both frame-level and period-level metrics. The experimental results show that the inclusion of both spectral and temporal information allows to improve the baseline detection performance by more than 60%.

A Knowledge-Based Approach to Automatic Detection of Equipment Alarm Sounds in a Neonatal Intensive Care Unit Environment

PubMed Central

Nadeu, Climent; Jančovič, Peter; Lilja, Alex Peiró; Köküer, Münevver; Muñoz Mahamud, Blanca; Riverola De Veciana, Ana

2018-01-01

A large number of alarm sounds triggered by biomedical equipment occur frequently in the noisy environment of a neonatal intensive care unit (NICU) and play a key role in providing healthcare. In this paper, our work on the development of an automatic system for detection of acoustic alarms in that difficult environment is presented. Such automatic detection system is needed for the investigation of how a preterm infant reacts to auditory stimuli of the NICU environment and for an improved real-time patient monitoring. The approach presented in this paper consists of using the available knowledge about each alarm class in the design of the detection system. The information about the frequency structure is used in the feature extraction stage, and the time structure knowledge is incorporated at the post-processing stage. Several alternative methods are compared for feature extraction, modeling, and post-processing. The detection performance is evaluated with real data recorded in the NICU of the hospital, and by using both frame-level and period-level metrics. The experimental results show that the inclusion of both spectral and temporal information allows to improve the baseline detection performance by more than 60%. PMID:29404227

Affinity Chart Analysis: A Method for Structured Collection, Aggregation, and Response to Customer Needs in Radiology.

PubMed

Boll, Daniel T; Rubin, Geoffrey D; Heye, Tobias; Pierce, Laura J

2017-04-01

The objective of this study is to analyze implementation of the voice-of-the-customer method to assess the current state of image postprocessing and reporting delivered by a radiology department and to plan improvements on the basis of referring physicians' preferences. The voice-of-the-customer method consisted of discovery, analysis, and optimization phases. Fifty referring physicians were invited to be interviewed. Interviews addressed the topics of structure, process, outcome, and support. Interviews were dissected into individual statements categorized as fact or feeling. Statements were grouped to find collective voices. Improvements were compiled from affinity charts and were processed by identifying insights. Ninety-four percent (47/50) of physicians participated, generating 352 statements (81 facts and 271 feelings) that subsequently underwent affinity chart clustering. The resultant affinity charts covered distinct themes: "we need you to know us better," "we need you to consider our workflow," "we need more from your services," "we want to review your data in certain ways," and "we want to do more with you." As a result of the insights gained, the following optimizations were implemented: a software application that improves study requesting, performance tracking, study prioritization, and longitudinal data archiving; six prototype reports containing tabulated data and annotated images; two prototype longitudinal reporting templates assessing aneurysm evolution and treatment-induced changes in organ size over time; and a teaching curriculum for trainees. This study has shown the clinical feasibility to assess the current state of image postprocessing and reporting and to implement improvements of and investments in image postprocessing and reporting infrastructure on the basis of referring physicians' preferences using the voice-of-the-customer method.

Avoiding the ensemble decorrelation problem using member-by-member post-processing

NASA Astrophysics Data System (ADS)

Van Schaeybroeck, Bert; Vannitsem, Stéphane

2014-05-01

Forecast calibration or post-processing has become a standard tool in atmospheric and climatological science due to the presence of systematic initial condition and model errors. For ensemble forecasts the most competitive methods derive from the assumption of a fixed ensemble distribution. However, when independently applying such 'statistical' methods at different locations, lead times or for multiple variables the correlation structure for individual ensemble members is destroyed. Instead of reastablishing the correlation structure as in Schefzik et al. (2013) we instead propose a calibration method that avoids such problem by correcting each ensemble member individually. Moreover, we analyse the fundamental mechanisms by which the probabilistic ensemble skill can be enhanced. In terms of continuous ranked probability score, our member-by-member approach amounts to skill gain that extends for lead times far beyond the error doubling time and which is as good as the one of the most competitive statistical approach, non-homogeneous Gaussian regression (Gneiting et al. 2005). Besides the conservation of correlation structure, additional benefits arise including the fact that higher-order ensemble moments like kurtosis and skewness are inherited from the uncorrected forecasts. Our detailed analysis is performed in the context of the Kuramoto-Sivashinsky equation and different simple models but the results extent succesfully to the ensemble forecast of the European Centre for Medium-Range Weather Forecasts (Van Schaeybroeck and Vannitsem, 2013, 2014) . References [1] Gneiting, T., Raftery, A. E., Westveld, A., Goldman, T., 2005: Calibrated probabilistic forecasting using ensemble model output statistics and minimum CRPS estimation. Mon. Weather Rev. 133, 1098-1118. [2] Schefzik, R., T.L. Thorarinsdottir, and T. Gneiting, 2013: Uncertainty Quantification in Complex Simulation Models Using Ensemble Copula Coupling. To appear in Statistical Science 28. [3] Van Schaeybroeck, B., and S. Vannitsem, 2013: Reliable probabilities through statistical post-processing of ensemble forecasts. Proceedings of the European Conference on Complex Systems 2012, Springer proceedings on complexity, XVI, p. 347-352. [4] Van Schaeybroeck, B., and S. Vannitsem, 2014: Ensemble post-processing using member-by-member approaches: theoretical aspects, under review.

Multivariate Statistical Postprocessing of Ensemble Forcasts of Precipitation and Temperature over four River Basins in California

NASA Astrophysics Data System (ADS)

Scheuerer, Michael; Hamill, Thomas M.; Whitin, Brett; He, Minxue; Henkel, Arthur

2017-04-01

Hydrological forecasts strongly rely on predictions of precipitation amounts and temperature as meteorological inputs to hydrological models. Ensemble weather predictions provide a number of different scenarios that reflect the uncertainty about these meteorological inputs, but are often biased and underdispersive, and therefore require statistical postprocessing. In hydrological applications it is crucial that spatial and temporal (i.e. between different forecast lead times) dependencies as well as dependence between the two weather variables is adequately represented by the recalibrated forecasts. We present a study with temperature and precipitation forecasts over four river basins over California that are postprocessed with a variant of the nonhomogeneous Gaussian regression method (Gneiting et al., 2005) and the censored, shifted gamma distribution approach (Scheuerer and Hamill, 2015) respectively. For modelling spatial, temporal and inter-variable dependence we propose a variant of the Schaake Shuffle (Clark et al., 2005) that uses spatio-temporal trajectories of observed temperture and precipitation as a dependence template, and chooses the historic dates in such a way that the divergence between the marginal distributions of these trajectories and the univariate forecast distributions is minimized. For the four river basins considered in our study, this new multivariate modelling technique consistently improves upon the Schaake Shuffle and yields reliable spatio-temporal forecast trajectories of temperature and precipitation that can be used to force hydrological forecast systems. References: Clark, M., Gangopadhyay, S., Hay, L., Rajagopalan, B., Wilby, R., 2004. The Schaake Shuffle: A method for reconstructing space-time variability in forecasted precipitation and temperature fields. Journal of Hydrometeorology, 5, pp.243-262. Gneiting, T., Raftery, A.E., Westveld, A.H., Goldman, T., 2005. Calibrated probabilistic forecasting using ensemble model output statistics and minimum CRPS. Monthly Weather Review, 133, pp.1098-1118. Scheuerer, M., Hamill, T.M., 2015. Statistical postprocessing of ensemble precipitation forecasts by fitting censored, shifted gamma distributions. Monthly Weather Review, 143, pp.4578-4596. Scheuerer, M., Hamill, T.M., Whitin, B., He, M., and Henkel, A., 2016: A method for preferential selection of dates in the Schaake shuffle approach to constructing spatio-temporal forecast fields of temperature and precipitation. Water Resources Research, submitted.

Infrared vehicle recognition using unsupervised feature learning based on K-feature

NASA Astrophysics Data System (ADS)

Lin, Jin; Tan, Yihua; Xia, Haijiao; Tian, Jinwen

2018-02-01

Subject to the complex battlefield environment, it is difficult to establish a complete knowledge base in practical application of vehicle recognition algorithms. The infrared vehicle recognition is always difficult and challenging, which plays an important role in remote sensing. In this paper we propose a new unsupervised feature learning method based on K-feature to recognize vehicle in infrared images. First, we use the target detection algorithm which is based on the saliency to detect the initial image. Then, the unsupervised feature learning based on K-feature, which is generated by Kmeans clustering algorithm that extracted features by learning a visual dictionary from a large number of samples without label, is calculated to suppress the false alarm and improve the accuracy. Finally, the vehicle target recognition image is finished by some post-processing. Large numbers of experiments demonstrate that the proposed method has satisfy recognition effectiveness and robustness for vehicle recognition in infrared images under complex backgrounds, and it also improve the reliability of it.

Hierarchical graph-based segmentation for extracting road networks from high-resolution satellite images

NASA Astrophysics Data System (ADS)

Alshehhi, Rasha; Marpu, Prashanth Reddy

2017-04-01

Extraction of road networks in urban areas from remotely sensed imagery plays an important role in many urban applications (e.g. road navigation, geometric correction of urban remote sensing images, updating geographic information systems, etc.). It is normally difficult to accurately differentiate road from its background due to the complex geometry of the buildings and the acquisition geometry of the sensor. In this paper, we present a new method for extracting roads from high-resolution imagery based on hierarchical graph-based image segmentation. The proposed method consists of: 1. Extracting features (e.g., using Gabor and morphological filtering) to enhance the contrast between road and non-road pixels, 2. Graph-based segmentation consisting of (i) Constructing a graph representation of the image based on initial segmentation and (ii) Hierarchical merging and splitting of image segments based on color and shape features, and 3. Post-processing to remove irregularities in the extracted road segments. Experiments are conducted on three challenging datasets of high-resolution images to demonstrate the proposed method and compare with other similar approaches. The results demonstrate the validity and superior performance of the proposed method for road extraction in urban areas.

Evaluation of computed tomography post-processing images in postoperative assessment of Lisfranc injuries compared with plain radiographs.

PubMed

Li, Haobo; Chen, Yanxi; Qiang, Minfei; Zhang, Kun; Jiang, Yuchen; Zhang, Yijie; Jia, Xiaoyang

2017-06-14

The objective of this study is to evaluate the value of computed tomography (CT) post-processing images in postoperative assessment of Lisfranc injuries compared with plain radiographs. A total of 79 cases with closed Lisfranc injuries that were treated with conventional open reduction and internal fixation from January 2010 to June 2016 were analyzed. Postoperative assessment was performed by two independent orthopedic surgeons with both plain radiographs and CT post-processing images. Inter- and intra-observer agreement were analyzed by kappa statistics while the differences between the two postoperative imaging assessments were assessed using the χ 2 test (McNemar's test). Significance was assumed when p < 0.05. Inter- and intra-observer agreement of CT post-processing images was much higher than that of plain radiographs. Non-anatomic reduction was more easily identified in patients with injuries of Myerson classifications A, B1, B2, and C1 using CT post-processing images with overall groups (p < 0.05), and poor internal fixation was also more easily detected in patients with injuries of Myerson classifications A, B1, B2, and C2 using CT post-processing images with overall groups (p < 0.05). CT post-processing images can be more reliable than plain radiographs in the postoperative assessment of reduction and implant placement for Lisfranc injuries.

Automatic prediction of protein domains from sequence information using a hybrid learning system.

PubMed

Nagarajan, Niranjan; Yona, Golan

2004-06-12

We describe a novel method for detecting the domain structure of a protein from sequence information alone. The method is based on analyzing multiple sequence alignments that are derived from a database search. Multiple measures are defined to quantify the domain information content of each position along the sequence and are combined into a single predictor using a neural network. The output is further smoothed and post-processed using a probabilistic model to predict the most likely transition positions between domains. The method was assessed using the domain definitions in SCOP and CATH for proteins of known structure and was compared with several other existing methods. Our method performs well both in terms of accuracy and sensitivity. It improves significantly over the best methods available, even some of the semi-manual ones, while being fully automatic. Our method can also be used to suggest and verify domain partitions based on structural data. A few examples of predicted domain definitions and alternative partitions, as suggested by our method, are also discussed. An online domain-prediction server is available at http://biozon.org/tools/domains/

Real-Time and Post-Processed Orbit Determination and Positioning

NASA Technical Reports Server (NTRS)

Harvey, Nathaniel E. (Inventor); Lu, Wenwen (Inventor); Miller, Mark A. (Inventor); Bar-Sever, Yoaz E. (Inventor); Miller, Kevin J. (Inventor); Romans, Larry J. (Inventor); Dorsey, Angela R. (Inventor); Sibthorpe, Anthony J. (Inventor); Weiss, Jan P. (Inventor); Bertiger, William I. (Inventor);

Real-Time and Post-Processed Orbit Determination and Positioning

NASA Technical Reports Server (NTRS)

Bar-Sever, Yoaz E. (Inventor); Romans, Larry J. (Inventor); Weiss, Jan P. (Inventor); Gross, Jason (Inventor); Harvey, Nathaniel E. (Inventor); Lu, Wenwen (Inventor); Dorsey, Angela R. (Inventor); Miller, Mark A. (Inventor); Sibthorpe, Anthony J. (Inventor); Bertiger, William I. (Inventor);

Volumetric calibration of a plenoptic camera.

PubMed

Hall, Elise Munz; Fahringer, Timothy W; Guildenbecher, Daniel R; Thurow, Brian S

2018-02-01

The volumetric calibration of a plenoptic camera is explored to correct for inaccuracies due to real-world lens distortions and thin-lens assumptions in current processing methods. Two methods of volumetric calibration based on a polynomial mapping function that does not require knowledge of specific lens parameters are presented and compared to a calibration based on thin-lens assumptions. The first method, volumetric dewarping, is executed by creation of a volumetric representation of a scene using the thin-lens assumptions, which is then corrected in post-processing using a polynomial mapping function. The second method, direct light-field calibration, uses the polynomial mapping in creation of the initial volumetric representation to relate locations in object space directly to image sensor locations. The accuracy and feasibility of these methods is examined experimentally by capturing images of a known dot card at a variety of depths. Results suggest that use of a 3D polynomial mapping function provides a significant increase in reconstruction accuracy and that the achievable accuracy is similar using either polynomial-mapping-based method. Additionally, direct light-field calibration provides significant computational benefits by eliminating some intermediate processing steps found in other methods. Finally, the flexibility of this method is shown for a nonplanar calibration.

Development of a short-term irradiance prediction system using post-processing tools on WRF-ARW meteorological forecasts in Spain

NASA Astrophysics Data System (ADS)

Rincón, A.; Jorba, O.; Baldasano, J. M.

2010-09-01

The increased contribution of solar energy in power generation sources requires an accurate estimation of surface solar irradiance conditioned by geographical, temporal and meteorological conditions. The knowledge of the variability of these factors is essential to estimate the expected energy production and therefore help stabilizing the electricity grid and increase the reliability of available solar energy. The use of numerical meteorological models in combination with statistical post-processing tools may have the potential to satisfy the requirements for short-term forecasting of solar irradiance for up to several days ahead and its application in solar devices. In this contribution, we present an assessment of a short-term irradiance prediction system based on the WRF-ARW mesoscale meteorological model (Skamarock et al., 2005) and several post-processing tools in order to improve the overall skills of the system in an annual simulation of the year 2004 in Spain. The WRF-ARW model is applied with 4 km x 4 km horizontal resolution and 38 vertical layers over the Iberian Peninsula. The hourly model irradiance is evaluated against more than 90 surface stations. The stations are used to assess the temporal and spatial fluctuations and trends of the system evaluating three different post-processes: Model Output Statistics technique (MOS; Glahn and Lowry, 1972), Recursive statistical method (REC; Boi, 2004) and Kalman Filter Predictor (KFP, Bozic, 1994; Roeger et al., 2003). A first evaluation of the system without post-processing tools shows an overestimation of the surface irradiance, due to the lack of atmospheric absorbers attenuation different than clouds not included in the meteorological model. This produces an annual BIAS of 16 W m-2 h-1, annual RMSE of 106 W m-2 h-1 and annual NMAE of 42%. The largest errors are observed in spring and summer, reaching RMSE of 350 W m-2 h-1. Results using Kalman Filter Predictor show a reduction of 8% of RMSE, 83% of BIAS, and NMAE decreases down to 32%. The REC method shows a reduction of 6% of RMSE, 79% of BIAS, and NMAE decreases down to 28%. When comparing stations at different altitudes, the overestimation is enhanced at coastal stations (less than 200m) up to 900 W m-2 h-1. The results allow us to analyze strengths and drawbacks of the irradiance prediction system and its application in the estimation of energy production from photovoltaic system cells. References Boi, P.: A statistical method for forecasting extreme daily temperatures using ECMWF 2-m temperatures and ground station measurements, Meteorol. Appl., 11, 245-251, 2004. Bozic, S.: Digital and Kalman filtering, John Wiley, Hoboken, New Jersey, 2nd edn., 1994. Glahn, H. and Lowry, D.: The use of Model Output Statistics (MOS) in Objective Weather Forecasting, Applied Meteorology, 11, 1203-1211, 1972. Roeger, C., Stull, R., McClung, D., Hacker, J., Deng, X., and Modzelewski, H.: Verification of Mesoscale Numerical Weather Forecasts in Mountainous Terrain for Application to Avalanche Prediction, Weather and forecasting, 18, 1140-1160, 2003. Skamarock, W., Klemp, J., Dudhia, J., Gill, D., Barker, D. M., Wang, W., and Powers, J. G.: A Description of the Advanced Research WRF Version 2, Tech. Rep. NCAR/TN-468+STR, NCAR Technical note, 2005.

Retooling Laser Speckle Contrast Analysis Algorithm to Enhance Non-Invasive High Resolution Laser Speckle Functional Imaging of Cutaneous Microcirculation

NASA Astrophysics Data System (ADS)

Gnyawali, Surya C.; Blum, Kevin; Pal, Durba; Ghatak, Subhadip; Khanna, Savita; Roy, Sashwati; Sen, Chandan K.

2017-01-01

Cutaneous microvasculopathy complicates wound healing. Functional assessment of gated individual dermal microvessels is therefore of outstanding interest. Functional performance of laser speckle contrast imaging (LSCI) systems is compromised by motion artefacts. To address such weakness, post-processing of stacked images is reported. We report the first post-processing of binary raw data from a high-resolution LSCI camera. Sharp images of low-flowing microvessels were enabled by introducing inverse variance in conjunction with speckle contrast in Matlab-based program code. Extended moving window averaging enhanced signal-to-noise ratio. Functional quantitative study of blood flow kinetics was performed on single gated microvessels using a free hand tool. Based on detection of flow in low-flow microvessels, a new sharp contrast image was derived. Thus, this work presents the first distinct image with quantitative microperfusion data from gated human foot microvasculature. This versatile platform is applicable to study a wide range of tissue systems including fine vascular network in murine brain without craniotomy as well as that in the murine dorsal skin. Importantly, the algorithm reported herein is hardware agnostic and is capable of post-processing binary raw data from any camera source to improve the sensitivity of functional flow data above and beyond standard limits of the optical system.

Retooling Laser Speckle Contrast Analysis Algorithm to Enhance Non-Invasive High Resolution Laser Speckle Functional Imaging of Cutaneous Microcirculation

PubMed Central

Gnyawali, Surya C.; Blum, Kevin; Pal, Durba; Ghatak, Subhadip; Khanna, Savita; Roy, Sashwati; Sen, Chandan K.

2017-01-01

Cutaneous microvasculopathy complicates wound healing. Functional assessment of gated individual dermal microvessels is therefore of outstanding interest. Functional performance of laser speckle contrast imaging (LSCI) systems is compromised by motion artefacts. To address such weakness, post-processing of stacked images is reported. We report the first post-processing of binary raw data from a high-resolution LSCI camera. Sharp images of low-flowing microvessels were enabled by introducing inverse variance in conjunction with speckle contrast in Matlab-based program code. Extended moving window averaging enhanced signal-to-noise ratio. Functional quantitative study of blood flow kinetics was performed on single gated microvessels using a free hand tool. Based on detection of flow in low-flow microvessels, a new sharp contrast image was derived. Thus, this work presents the first distinct image with quantitative microperfusion data from gated human foot microvasculature. This versatile platform is applicable to study a wide range of tissue systems including fine vascular network in murine brain without craniotomy as well as that in the murine dorsal skin. Importantly, the algorithm reported herein is hardware agnostic and is capable of post-processing binary raw data from any camera source to improve the sensitivity of functional flow data above and beyond standard limits of the optical system. PMID:28106129

MO-FG-CAMPUS-TeP3-04: Deliverable Robust Optimization in IMPT Using Quadratic Objective Function

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

Shan, J; Liu, W; Bues, M

Purpose: To find and evaluate the way of applying deliverable MU constraints into robust spot intensity optimization in Intensity-Modulated- Proton-Therapy (IMPT) to prevent plan quality and robustness from degrading due to machine deliverable MU-constraints. Methods: Currently, the influence of the deliverable MU-constraints is retrospectively evaluated by post-processing immediately following optimization. In this study, we propose a new method based on the quasi-Newton-like L-BFGS-B algorithm with which we turn deliverable MU-constraints on and off alternatively during optimization. Seven patients with two different machine settings (small and large spot size) were planned with both conventional and new methods. For each patient, threemore » kinds of plans were generated — conventional non-deliverable plan (plan A), conventional deliverable plan with post-processing (plan B), and new deliverable plan (plan C). We performed this study with both realistic (small) and artificial (large) deliverable MU-constraints. Results: With small minimum MU-constraints considered, new method achieved a slightly better plan quality than conventional method (D95% CTV normalized to the prescription dose: 0.994[0.992∼0.996] (Plan C) vs 0.992[0.986∼0.996] (Plan B)). With large minimum MU constraints considered, results show that the new method maintains plan quality while plan quality from the conventional method is degraded greatly (D95% CTV normalized to the prescription dose: 0.987[0.978∼0.994] (Plan C) vs 0.797[0.641∼1.000] (Plan B)). Meanwhile, plan robustness of these two method’s results is comparable. (For all 7 patients, CTV DVH band gap at D95% normalized to the prescription dose: 0.015[0.005∼0.043] (Plan C) vs 0.012[0.006∼0.038] (Plan B) with small MU-constraints and 0.019[0.009∼0.039] (Plan C) vs 0.030[0.015∼0.041] (Plan B) with large MU-constraints) Conclusion: Positive correlation has been found between plan quality degeneration and magnitude of deliverable minimal MU. Compared to conventional post-processing method, our new method of incorporating deliverable minimal MU-constraints directly into plan optimization, can produce machine-deliverable plans with better plan qualities and non-compromised plan robustness. This research was supported by the National Cancer Institute Career Developmental Award K25CA168984, by the Fraternal Order of Eagles Cancer Research Fund Career Development Award, by The Lawrence W. and Marilyn W. Matteson Fund for Cancer Research, by Mayo Arizona State University Seed Grant and by The Kemper Marley Foundation.« less

Novel Overhang Support Designs for Powder-Based Electron Beam Additive Manufacturing (EBAM)

NASA Technical Reports Server (NTRS)

Nabors, Sammy A.

2014-01-01

NASA Marshall Space Flight Center, in collaboration with the University of Alabama, has developed a contact-free support structure used to fabricate overhang-type geometries via EBAM. The support structure is used for 3-D metal-printed components for the aerospace, automotive, biomedical and other industries. Current techniques use support structures to address deformation challenges inherent in 3-D metal printing. However, these structures (overhangs) are bonded to the component and need to be removed in post-processing using a mechanical tool. This new technology improves the overhang support structure design for components by eliminating associated geometric defects and post-processing requirements.

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

A. Alfonsi; C. Rabiti; D. Mandelli

The Reactor Analysis and Virtual control ENviroment (RAVEN) code is a software tool that acts as the control logic driver and post-processing engine for the newly developed Thermal-Hydraulic code RELAP-7. RAVEN is now a multi-purpose Probabilistic Risk Assessment (PRA) software framework that allows dispatching different functionalities: Derive and actuate the control logic required to simulate the plant control system and operator actions (guided procedures), allowing on-line monitoring/controlling in the Phase Space Perform both Monte-Carlo sampling of random distributed events and Dynamic Event Tree based analysis Facilitate the input/output handling through a Graphical User Interface (GUI) and a post-processing data miningmore » module« less

Comparison of tissue equalization, and premium view post-processing methods in full field digital mammography.

PubMed

Chen, Baoying; Wang, Wei; Huang, Jin; Zhao, Ming; Cui, Guangbin; Xu, Jing; Guo, Wei; Du, Pang; Li, Pei; Yu, Jun

2010-10-01

To retrospectively evaluate the diagnostic abilities of 2 post-processing methods provided by GE Senographe DS system, tissue equalization (TE) and premium view (PV) in full field digital mammography (FFDM). In accordance with the ethical standards of the World Medical Association, this study was approved by regional ethics committee and signed informed patient consents were obtained. We retrospectively reviewed digital mammograms from 101 women (mean age, 47 years; range, 23-81 years) in the modes of TE and PV, respectively. Three radiologists, fully blinded to the post-processing methods, all patient clinical information and histologic results, read images by using objective image interpretation criteria for diagnostic information end points such as lesion border delineation, definition of disease extent, visualization of internal and surrounding morphologic features of the lesions. Also, overall diagnostic impression in terms of lesion conspicuity, detectability and diagnostic confidence was assessed. Between-group comparisons were performed with Wilcoxon signed rank test. Readers 1, 2, and 3 demonstrated significant overall better impression of PV in 29, 27, and 24 patients, compared with that for TE in 12, 13, and 11 patients, respectively (p<0.05). Significant (p<0.05) better impression of PV was also demonstrated for diagnostic information end points. Importantly, PV proved to be more sensitive than TE while detecting malignant lesions in dense breast rather than benign lesions and malignancy in non-dense breast (p<0.01). PV compared with TE provides marked better diagnostic information in FFDM, particularly for patients with malignancy in dense breast. Copyright © 2009 Elsevier Ireland Ltd. All rights reserved.

Verification of a Finite Element Model for Pyrolyzing Ablative Materials

NASA Technical Reports Server (NTRS)

Risch, Timothy K.

2017-01-01

Ablating thermal protection system (TPS) materials have been used in many reentering spacecraft and in other applications such as rocket nozzle linings, fire protection materials, and as countermeasures for directed energy weapons. The introduction of the finite element model to the analysis of ablation has arguably resulted in improved computational capabilities due the flexibility and extended applicability of the method, especially to complex geometries. Commercial finite element codes often provide enhanced capability compared to custom, specially written programs based on versatility, usability, pre- and post-processing, grid generation, total life-cycle costs, and speed.

A Robust Post-Processing Workflow for Datasets with Motion Artifacts in Diffusion Kurtosis Imaging

PubMed Central

Li, Xianjun; Yang, Jian; Gao, Jie; Luo, Xue; Zhou, Zhenyu; Hu, Yajie; Wu, Ed X.; Wan, Mingxi

2014-01-01

Purpose The aim of this study was to develop a robust post-processing workflow for motion-corrupted datasets in diffusion kurtosis imaging (DKI). Materials and methods The proposed workflow consisted of brain extraction, rigid registration, distortion correction, artifacts rejection, spatial smoothing and tensor estimation. Rigid registration was utilized to correct misalignments. Motion artifacts were rejected by using local Pearson correlation coefficient (LPCC). The performance of LPCC in characterizing relative differences between artifacts and artifact-free images was compared with that of the conventional correlation coefficient in 10 randomly selected DKI datasets. The influence of rejected artifacts with information of gradient directions and b values for the parameter estimation was investigated by using mean square error (MSE). The variance of noise was used as the criterion for MSEs. The clinical practicality of the proposed workflow was evaluated by the image quality and measurements in regions of interest on 36 DKI datasets, including 18 artifact-free (18 pediatric subjects) and 18 motion-corrupted datasets (15 pediatric subjects and 3 essential tremor patients). Results The relative difference between artifacts and artifact-free images calculated by LPCC was larger than that of the conventional correlation coefficient (p<0.05). It indicated that LPCC was more sensitive in detecting motion artifacts. MSEs of all derived parameters from the reserved data after the artifacts rejection were smaller than the variance of the noise. It suggested that influence of rejected artifacts was less than influence of noise on the precision of derived parameters. The proposed workflow improved the image quality and reduced the measurement biases significantly on motion-corrupted datasets (p<0.05). Conclusion The proposed post-processing workflow was reliable to improve the image quality and the measurement precision of the derived parameters on motion-corrupted DKI datasets. The workflow provided an effective post-processing method for clinical applications of DKI in subjects with involuntary movements. PMID:24727862

Assessing LiDAR elevation data for KDOT applications : [technical summary].

DOT National Transportation Integrated Search

2013-02-01

LiDAR-based elevation surveys : are a cost-effective means for : mapping topography over large : areas. LiDAR surveys use an : airplane-mounted or ground-based : laser radar unit to scan terrain. : Post-processing techniques are : applied to remove v...

Verification of Eulerian-Eulerian and Eulerian-Lagrangian simulations for turbulent fluid-particle flows

DOE PAGES

Patel, Ravi G.; Desjardins, Olivier; Kong, Bo; ...

2017-09-01

Here, we present a verification study of three simulation techniques for fluid–particle flows, including an Euler–Lagrange approach (EL) inspired by Jackson's seminal work on fluidized particles, a quadrature–based moment method based on the anisotropic Gaussian closure (AG), and the traditional two-fluid model. We perform simulations of two problems: particles in frozen homogeneous isotropic turbulence (HIT) and cluster-induced turbulence (CIT). For verification, we evaluate various techniques for extracting statistics from EL and study the convergence properties of the three methods under grid refinement. The convergence is found to depend on the simulation method and on the problem, with CIT simulations posingmore » fewer difficulties than HIT. Specifically, EL converges under refinement for both HIT and CIT, but statistics exhibit dependence on the postprocessing parameters. For CIT, AG produces similar results to EL. For HIT, converging both TFM and AG poses challenges. Overall, extracting converged, parameter-independent Eulerian statistics remains a challenge for all methods.« less

Verification of Eulerian-Eulerian and Eulerian-Lagrangian simulations for turbulent fluid-particle flows

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

Patel, Ravi G.; Desjardins, Olivier; Kong, Bo

Here, we present a verification study of three simulation techniques for fluid–particle flows, including an Euler–Lagrange approach (EL) inspired by Jackson's seminal work on fluidized particles, a quadrature–based moment method based on the anisotropic Gaussian closure (AG), and the traditional two-fluid model. We perform simulations of two problems: particles in frozen homogeneous isotropic turbulence (HIT) and cluster-induced turbulence (CIT). For verification, we evaluate various techniques for extracting statistics from EL and study the convergence properties of the three methods under grid refinement. The convergence is found to depend on the simulation method and on the problem, with CIT simulations posingmore » fewer difficulties than HIT. Specifically, EL converges under refinement for both HIT and CIT, but statistics exhibit dependence on the postprocessing parameters. For CIT, AG produces similar results to EL. For HIT, converging both TFM and AG poses challenges. Overall, extracting converged, parameter-independent Eulerian statistics remains a challenge for all methods.« less

IR-based spot weld NDT in automotive applications

NASA Astrophysics Data System (ADS)

Chen, Jian; Feng, Zhili

2015-05-01

Today's auto industry primarily relies on destructive teardown evaluation to ensure the quality of the resistance spot welds (RSWs) due to their criticality in crash resistance and performance of vehicles. The destructive teardown evaluation is labor intensive and costly. The very nature of the destructive test means only a few selected welds will be sampled for quality. Most of the welds in a car are never checked. There are significant costs and risks associated with reworking and scrapping the defective welded parts made between the teardown tests. IR thermography as a non-destructive testing (NDT) tool has its distinct advantage — its non-intrusive and non-contact nature. This makes the IR based NDT especially attractive for the highly automated assembly lines. IR for weld quality inspection has been explored in the past, mostly limited to the offline post-processing manner in a laboratory environment. No online real-time RSW inspection using IR thermography has been reported. Typically for postprocessing inspection, a short-pulse heating via xenon flash lamp light (in a few milliseconds) is applied to the surface of a spot weld. However, applications in the auto industry have been unsuccessful, largely due to a critical drawback that cannot be implemented in the high-volume production line - the prerequisite of painting the weld surface to eliminate surface reflection and other environmental interference. This is due to the low signal-to-noise ratio resulting from the low/unknown surface emissivity and the very small temperature changes (typically on the order of 0.1°C) induced by the flash lamp method. An integrated approach consisting of innovations in both data analysis algorithms and hardware apparatus that effectively solved the key technical barriers for IR NDT. The system can be used for both real-time (during welding) and post-processing inspections (after welds have been made). First, we developed a special IR thermal image processing method that utilizes the relative IR intensity change, so that the influence of surface reflection and environment interference can be reduced. Second, for the post-processing inspection, a special induction heater is used to replace the flash lamp, resulting in temperature changes on the order of 10°C. As a result, the signal-to-noise ratio increased by several orders of magnitudes with no surface painting needed, and the inspection results are more accurate and reliable. For real-time inspection, the heat from welding (with temperature exceeding 1000°C) was utilized. Third, "thermal signatures" were identified to uniquely correlate to different weld quality attributes through computational modeling of heat transfer and extensive testing of specially designed ranges of welding conditions. Novel IR image analysis algorithms that automatically and intelligently identify the "thermal signatures" from the IR images and positively determine the weld quality in less than a second were developed.

Virus Particle Detection by Convolutional Neural Network in Transmission Electron Microscopy Images.

PubMed

Ito, Eisuke; Sato, Takaaki; Sano, Daisuke; Utagawa, Etsuko; Kato, Tsuyoshi

2018-06-01

A new computational method for the detection of virus particles in transmission electron microscopy (TEM) images is presented. Our approach is to use a convolutional neural network that transforms a TEM image to a probabilistic map that indicates where virus particles exist in the image. Our proposed approach automatically and simultaneously learns both discriminative features and classifier for virus particle detection by machine learning, in contrast to existing methods that are based on handcrafted features that yield many false positives and require several postprocessing steps. The detection performance of the proposed method was assessed against a dataset of TEM images containing feline calicivirus particles and compared with several existing detection methods, and the state-of-the-art performance of the developed method for detecting virus was demonstrated. Since our method is based on supervised learning that requires both the input images and their corresponding annotations, it is basically used for detection of already-known viruses. However, the method is highly flexible, and the convolutional networks can adapt themselves to any virus particles by learning automatically from an annotated dataset.

Restoration of solar and star images with phase diversity-based blind deconvolution

NASA Astrophysics Data System (ADS)

Li, Qiang; Liao, Sheng; Wei, Honggang; Shen, Mangzuo

2007-04-01

The images recorded by a ground-based telescope are often degraded by atmospheric turbulence and the aberration of the optical system. Phase diversity-based blind deconvolution is an effective post-processing method that can be used to overcome the turbulence-induced degradation. The method uses an ensemble of short-exposure images obtained simultaneously from multiple cameras to jointly estimate the object and the wavefront distribution on pupil. Based on signal estimation theory and optimization theory, we derive the cost function and solve the large-scale optimization problem using a limited memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) method. We apply the method to the turbulence-degraded images generated with computer, the solar images acquired with the swedish vacuum solar telescope (SVST, 0.475 m) in La Palma and the star images collected with 1.2-m telescope in Yunnan Observatory. In order to avoid edge effect in the restoration of the solar images, a modified Hanning apodized window is adopted. The star image still can be restored when the defocus distance is measured inaccurately. The restored results demonstrate that the method is efficient for removing the effect of turbulence and reconstructing the point-like or extended objects.

Comparison of Absolute Apparent Diffusion Coefficient (ADC) Values in ADC Maps Generated Across Different Postprocessing Software: Reproducibility in Endometrial Carcinoma.

PubMed

Ghosh, Adarsh; Singh, Tulika; Singla, Veenu; Bagga, Rashmi; Khandelwal, Niranjan

2017-12-01

Apparent diffusion coefficient (ADC) maps are usually generated by builtin software provided by the MRI scanner vendors; however, various open-source postprocessing software packages are available for image manipulation and parametric map generation. The purpose of this study is to establish the reproducibility of absolute ADC values obtained using different postprocessing software programs. DW images with three b values were obtained with a 1.5-T MRI scanner, and the trace images were obtained. ADC maps were automatically generated by the in-line software provided by the vendor during image generation and were also separately generated on postprocessing software. These ADC maps were compared on the basis of ROIs using paired t test, Bland-Altman plot, mountain plot, and Passing-Bablok regression plot. There was a statistically significant difference in the mean ADC values obtained from the different postprocessing software programs when the same baseline trace DW images were used for the ADC map generation. For using ADC values as a quantitative cutoff for histologic characterization of tissues, standardization of the postprocessing algorithm is essential across processing software packages, especially in view of the implementation of vendor-neutral archiving.

A stable and high-order accurate discontinuous Galerkin based splitting method for the incompressible Navier-Stokes equations

NASA Astrophysics Data System (ADS)

Piatkowski, Marian; Müthing, Steffen; Bastian, Peter

2018-03-01

In this paper we consider discontinuous Galerkin (DG) methods for the incompressible Navier-Stokes equations in the framework of projection methods. In particular we employ symmetric interior penalty DG methods within the second-order rotational incremental pressure correction scheme. The major focus of the paper is threefold: i) We propose a modified upwind scheme based on the Vijayasundaram numerical flux that has favourable properties in the context of DG. ii) We present a novel postprocessing technique in the Helmholtz projection step based on H (div) reconstruction of the pressure correction that is computed locally, is a projection in the discrete setting and ensures that the projected velocity satisfies the discrete continuity equation exactly. As a consequence it also provides local mass conservation of the projected velocity. iii) Numerical results demonstrate the properties of the scheme for different polynomial degrees applied to two-dimensional problems with known solution as well as large-scale three-dimensional problems. In particular we address second-order convergence in time of the splitting scheme as well as its long-time stability.

TH-E-17A-07: Improved Cine Four-Dimensional Computed Tomography (4D CT) Acquisition and Processing Method

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

Castillo, S; Castillo, R; Castillo, E

2014-06-15

Purpose: Artifacts arising from the 4D CT acquisition and post-processing methods add systematic uncertainty to the treatment planning process. We propose an alternate cine 4D CT acquisition and post-processing method to consistently reduce artifacts, and explore patient parameters indicative of image quality. Methods: In an IRB-approved protocol, 18 patients with primary thoracic malignancies received a standard cine 4D CT acquisition followed by an oversampling 4D CT that doubled the number of images acquired. A second cohort of 10 patients received the clinical 4D CT plus 3 oversampling scans for intra-fraction reproducibility. The clinical acquisitions were processed by the standard phasemore » sorting method. The oversampling acquisitions were processed using Dijkstras algorithm to optimize an artifact metric over available image data. Image quality was evaluated with a one-way mixed ANOVA model using a correlation-based artifact metric calculated from the final 4D CT image sets. Spearman correlations and a linear mixed model tested the association between breathing parameters, patient characteristics, and image quality. Results: The oversampling 4D CT scans reduced artifact presence significantly by 27% and 28%, for the first cohort and second cohort respectively. From cohort 2, the inter-replicate deviation for the oversampling method was within approximately 13% of the cross scan average at the 0.05 significance level. Artifact presence for both clinical and oversampling methods was significantly correlated with breathing period (ρ=0.407, p-value<0.032 clinical, ρ=0.296, p-value<0.041 oversampling). Artifact presence in the oversampling method was significantly correlated with amount of data acquired, (ρ=-0.335, p-value<0.02) indicating decreased artifact presence with increased breathing cycles per scan location. Conclusion: The 4D CT oversampling acquisition with optimized sorting reduced artifact presence significantly and reproducibly compared to the phase-sorted clinical acquisition.« less

On the incidence of meteorological and hydrological processors: Effect of resolution, sharpness and reliability of hydrological ensemble forecasts

NASA Astrophysics Data System (ADS)

Abaza, Mabrouk; Anctil, François; Fortin, Vincent; Perreault, Luc

2017-12-01

Meteorological and hydrological ensemble prediction systems are imperfect. Their outputs could often be improved through the use of a statistical processor, opening up the question of the necessity of using both processors (meteorological and hydrological), only one of them, or none. This experiment compares the predictive distributions from four hydrological ensemble prediction systems (H-EPS) utilising the Ensemble Kalman filter (EnKF) probabilistic sequential data assimilation scheme. They differ in the inclusion or not of the Distribution Based Scaling (DBS) method for post-processing meteorological forecasts and the ensemble Bayesian Model Averaging (ensemble BMA) method for hydrological forecast post-processing. The experiment is implemented on three large watersheds and relies on the combination of two meteorological reforecast products: the 4-member Canadian reforecasts from the Canadian Centre for Meteorological and Environmental Prediction (CCMEP) and the 10-member American reforecasts from the National Oceanic and Atmospheric Administration (NOAA), leading to 14 members at each time step. Results show that all four tested H-EPS lead to resolution and sharpness values that are quite similar, with an advantage to DBS + EnKF. The ensemble BMA is unable to compensate for any bias left in the precipitation ensemble forecasts. On the other hand, it succeeds in calibrating ensemble members that are otherwise under-dispersed. If reliability is preferred over resolution and sharpness, DBS + EnKF + ensemble BMA performs best, making use of both processors in the H-EPS system. Conversely, for enhanced resolution and sharpness, DBS is the preferred method.

A service protocol for post-processing of medical images on the mobile device

NASA Astrophysics Data System (ADS)

He, Longjun; Ming, Xing; Xu, Lang; Liu, Qian

2014-03-01

With computing capability and display size growing, the mobile device has been used as a tool to help clinicians view patient information and medical images anywhere and anytime. It is uneasy and time-consuming for transferring medical images with large data size from picture archiving and communication system to mobile client, since the wireless network is unstable and limited by bandwidth. Besides, limited by computing capability, memory and power endurance, it is hard to provide a satisfactory quality of experience for radiologists to handle some complex post-processing of medical images on the mobile device, such as real-time direct interactive three-dimensional visualization. In this work, remote rendering technology is employed to implement the post-processing of medical images instead of local rendering, and a service protocol is developed to standardize the communication between the render server and mobile client. In order to make mobile devices with different platforms be able to access post-processing of medical images, the Extensible Markup Language is taken to describe this protocol, which contains four main parts: user authentication, medical image query/ retrieval, 2D post-processing (e.g. window leveling, pixel values obtained) and 3D post-processing (e.g. maximum intensity projection, multi-planar reconstruction, curved planar reformation and direct volume rendering). And then an instance is implemented to verify the protocol. This instance can support the mobile device access post-processing of medical image services on the render server via a client application or on the web page.

Transmodal comparison of auditory, motor, and visual post-processing with and without intentional short-term memory maintenance.

PubMed

Bender, Stephan; Behringer, Stephanie; Freitag, Christine M; Resch, Franz; Weisbrod, Matthias

2010-12-01

To elucidate the contributions of modality-dependent post-processing in auditory, motor and visual cortical areas to short-term memory. We compared late negative waves (N700) during the post-processing of single lateralized stimuli which were separated by long intertrial intervals across the auditory, motor and visual modalities. Tasks either required or competed with attention to post-processing of preceding events, i.e. active short-term memory maintenance. N700 indicated that cortical post-processing exceeded short movements as well as short auditory or visual stimuli for over half a second without intentional short-term memory maintenance. Modality-specific topographies pointed towards sensory (respectively motor) generators with comparable time-courses across the different modalities. Lateralization and amplitude of auditory/motor/visual N700 were enhanced by active short-term memory maintenance compared to attention to current perceptions or passive stimulation. The memory-related N700 increase followed the characteristic time-course and modality-specific topography of the N700 without intentional memory-maintenance. Memory-maintenance-related lateralized negative potentials may be related to a less lateralised modality-dependent post-processing N700 component which occurs also without intentional memory maintenance (automatic memory trace or effortless attraction of attention). Encoding to short-term memory may involve controlled attention to modality-dependent post-processing. Similar short-term memory processes may exist in the auditory, motor and visual systems. Copyright © 2010 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Towards process-informed bias correction of climate change simulations

NASA Astrophysics Data System (ADS)

Maraun, Douglas; Shepherd, Theodore G.; Widmann, Martin; Zappa, Giuseppe; Walton, Daniel; Gutiérrez, José M.; Hagemann, Stefan; Richter, Ingo; Soares, Pedro M. M.; Hall, Alex; Mearns, Linda O.

2017-11-01

Biases in climate model simulations introduce biases in subsequent impact simulations. Therefore, bias correction methods are operationally used to post-process regional climate projections. However, many problems have been identified, and some researchers question the very basis of the approach. Here we demonstrate that a typical cross-validation is unable to identify improper use of bias correction. Several examples show the limited ability of bias correction to correct and to downscale variability, and demonstrate that bias correction can cause implausible climate change signals. Bias correction cannot overcome major model errors, and naive application might result in ill-informed adaptation decisions. We conclude with a list of recommendations and suggestions for future research to reduce, post-process, and cope with climate model biases.

Ground-to-air flow visualization using Solar Calcium-K line Background-Oriented Schlieren

NASA Astrophysics Data System (ADS)

Hill, Michael A.; Haering, Edward A.

2017-01-01

The Calcium-K Eclipse Background-Oriented Schlieren experiment was performed as a proof of concept test to evaluate the effectiveness of using the solar disk as a background to perform the Background-Oriented Schlieren (BOS) method of flow visualization. A ground-based imaging system was equipped with a Calcium-K line optical etalon filter to enable the use of the chromosphere of the sun as the irregular background to be used for BOS. A US Air Force T-38 aircraft performed three supersonic runs which eclipsed the sun as viewed from the imaging system. The images were successfully post-processed using optical flow methods to qualitatively reveal the density gradients in the flow around the aircraft.

RAPID COMMUNICATION Time-resolved measurements with a vortex flowmeter in a pulsating turbulent flow using wavelet analysis

NASA Astrophysics Data System (ADS)

Laurantzon, F.; Örlü, R.; Segalini, A.; Alfredsson, P. H.

2010-12-01

Vortex flowmeters are commonly employed in technical applications and are obtainable in a variety of commercially available types. However their robustness and accuracy can easily be impaired by environmental conditions, such as inflow disturbances and/or pulsating conditions. Various post-processing techniques of the vortex signal have been used, but all of these methods are so far targeted on obtaining an improved estimate of the time-averaged bulk velocity. Here, on the other hand, we propose, based on wavelet analysis, a straightforward way to utilize the signal from a vortex shedder to extract the time-resolved and thereby the phase-averaged velocity under pulsatile flow conditions. The method was verified with hot-wire and laser Doppler velocimetry measurements.

LUMA: A many-core, Fluid-Structure Interaction solver based on the Lattice-Boltzmann Method

NASA Astrophysics Data System (ADS)

Harwood, Adrian R. G.; O'Connor, Joseph; Sanchez Muñoz, Jonathan; Camps Santasmasas, Marta; Revell, Alistair J.

2018-01-01

The Lattice-Boltzmann Method at the University of Manchester (LUMA) project was commissioned to build a collaborative research environment in which researchers of all abilities can study fluid-structure interaction (FSI) problems in engineering applications from aerodynamics to medicine. It is built on the principles of accessibility, simplicity and flexibility. The LUMA software at the core of the project is a capable FSI solver with turbulence modelling and many-core scalability as well as a wealth of input/output and pre- and post-processing facilities. The software has been validated and several major releases benchmarked on supercomputing facilities internationally. The software architecture is modular and arranged logically using a minimal amount of object-orientation to maintain a simple and accessible software.

LabData database sub-systems for post-processing and quality control of stable isotope and gas chromatography measurements

NASA Astrophysics Data System (ADS)

Suckow, A. O.

2013-12-01

Measurements need post-processing to obtain results that are comparable between laboratories. Raw data may need to be corrected for blank, memory, drift (change of reference values with time), linearity (dependence of reference on signal height) and normalized to international reference materials. Post-processing parameters need to be stored for traceability of results. State of the art stable isotope correction schemes are available based on MS Excel (Geldern and Barth, 2012; Gröning, 2011) or MS Access (Coplen, 1998). These are specialized to stable isotope measurements only, often only to the post-processing of a special run. Embedding of algorithms into a multipurpose database system was missing. This is necessary to combine results of different tracers (3H, 3He, 2H, 18O, CFCs, SF6...) or geochronological tools (Sediment dating e.g. with 210Pb, 137Cs), to relate to attribute data (submitter, batch, project, geographical origin, depth in core, well information etc.) and for further interpretation tools (e.g. lumped parameter modelling). Database sub-systems to the LabData laboratory management system (Suckow and Dumke, 2001) are presented for stable isotopes and for gas chromatographic CFC and SF6 measurements. The sub-system for stable isotopes allows the following post-processing: 1. automated import from measurement software (Isodat, Picarro, LGR), 2. correction for sample-to sample memory, linearity, drift, and renormalization of the raw data. The sub-system for gas chromatography covers: 1. storage of all raw data 2. storage of peak integration parameters 3. correction for blank, efficiency and linearity The user interface allows interactive and graphical control of the post-processing and all corrections by export to and plot in MS Excel and is a valuable tool for quality control. The sub-databases are integrated into LabData, a multi-user client server architecture using MS SQL server as back-end and an MS Access front-end and installed in four laboratories to date. Attribute data storage (unique ID for each subsample, origin, project context etc.) and laboratory management features are included. Export routines to Excel (depth profiles, time series, all possible tracer-versus tracer plots...) and modelling capabilities are add-ons. The source code is public domain and available under the GNU general public licence agreement (GNU-GPL). References Coplen, T.B., 1998. A manual for a laboratory information management system (LIMS) for light stable isotopes. Version 7.0. USGS open file report 98-284. Geldern, R.v., Barth, J.A.C., 2012. Optimization of instrument setup and post-run corrections for oxygen and hydrogen stable isotope measurements of water by isotope ratio infrared spectroscopy (IRIS). Limnology and Oceanography: Methods 10, 1024-1036. Gröning, M., 2011. Improved water δ2H and δ18O calibration and calculation of measurement uncertainty using a simple software tool. Rapid Communications in Mass Spectrometry 25, 2711-2720. Suckow, A., Dumke, I., 2001. A database system for geochemical, isotope hydrological and geochronological laboratories. Radiocarbon 43, 325-337.

Eleventh NASTRAN User's Colloquium

NASA Technical Reports Server (NTRS)

1983-01-01

NASTRAN (NASA STRUCTURAL ANALYSIS) is a large, comprehensive, nonproprietary, general purpose finite element computer code for structural analysis which was developed under NASA sponsorship. The Eleventh Colloquium provides some comprehensive general papers on the application of finite element methods in engineering, comparisons with other approaches, unique applications, pre- and post-processing or auxiliary programs, and new methods of analysis with NASTRAN.

78 FR 69825 - Takes of Marine Mammals Incidental to Specified Activities; Taking Marine Mammals Incidental to a...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-11-21

... availability of the species or stock(s) for subsistence uses (where relevant). Further, the permissible methods... (ITA) under section 101(a)(5)(D) of the MMPA, we must set forth the permissible methods of taking... basis of predicted distances to relevant thresholds in post-processing of observational and acoustic...

GAPPARD: a computationally efficient method of approximating gap-scale disturbance in vegetation models

NASA Astrophysics Data System (ADS)

Scherstjanoi, M.; Kaplan, J. O.; Thürig, E.; Lischke, H.

2013-09-01

Models of vegetation dynamics that are designed for application at spatial scales larger than individual forest gaps suffer from several limitations. Typically, either a population average approximation is used that results in unrealistic tree allometry and forest stand structure, or models have a high computational demand because they need to simulate both a series of age-based cohorts and a number of replicate patches to account for stochastic gap-scale disturbances. The detail required by the latter method increases the number of calculations by two to three orders of magnitude compared to the less realistic population average approach. In an effort to increase the efficiency of dynamic vegetation models without sacrificing realism, we developed a new method for simulating stand-replacing disturbances that is both accurate and faster than approaches that use replicate patches. The GAPPARD (approximating GAP model results with a Probabilistic Approach to account for stand Replacing Disturbances) method works by postprocessing the output of deterministic, undisturbed simulations of a cohort-based vegetation model by deriving the distribution of patch ages at any point in time on the basis of a disturbance probability. With this distribution, the expected value of any output variable can be calculated from the output values of the deterministic undisturbed run at the time corresponding to the patch age. To account for temporal changes in model forcing (e.g., as a result of climate change), GAPPARD performs a series of deterministic simulations and interpolates between the results in the postprocessing step. We integrated the GAPPARD method in the vegetation model LPJ-GUESS, and evaluated it in a series of simulations along an altitudinal transect of an inner-Alpine valley. We obtained results very similar to the output of the original LPJ-GUESS model that uses 100 replicate patches, but simulation time was reduced by approximately the factor 10. Our new method is therefore highly suited for rapidly approximating LPJ-GUESS results, and provides the opportunity for future studies over large spatial domains, allows easier parameterization of tree species, faster identification of areas of interesting simulation results, and comparisons with large-scale datasets and results of other forest models.

Discriminative dictionary learning for abdominal multi-organ segmentation.

PubMed

Tong, Tong; Wolz, Robin; Wang, Zehan; Gao, Qinquan; Misawa, Kazunari; Fujiwara, Michitaka; Mori, Kensaku; Hajnal, Joseph V; Rueckert, Daniel

2015-07-01

An automated segmentation method is presented for multi-organ segmentation in abdominal CT images. Dictionary learning and sparse coding techniques are used in the proposed method to generate target specific priors for segmentation. The method simultaneously learns dictionaries which have reconstructive power and classifiers which have discriminative ability from a set of selected atlases. Based on the learnt dictionaries and classifiers, probabilistic atlases are then generated to provide priors for the segmentation of unseen target images. The final segmentation is obtained by applying a post-processing step based on a graph-cuts method. In addition, this paper proposes a voxel-wise local atlas selection strategy to deal with high inter-subject variation in abdominal CT images. The segmentation performance of the proposed method with different atlas selection strategies are also compared. Our proposed method has been evaluated on a database of 150 abdominal CT images and achieves a promising segmentation performance with Dice overlap values of 94.9%, 93.6%, 71.1%, and 92.5% for liver, kidneys, pancreas, and spleen, respectively. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

Ridge extraction from the time-frequency representation (TFR) of signals based on an image processing approach: application to the analysis of uterine electromyogram AR TFR.

PubMed

Terrien, Jérémy; Marque, Catherine; Germain, Guy

2008-05-01

Time-frequency representations (TFRs) of signals are increasingly being used in biomedical research. Analysis of such representations is sometimes difficult, however, and is often reduced to the extraction of ridges, or local energy maxima. In this paper, we describe a new ridge extraction method based on the image processing technique of active contours or snakes. We have tested our method on several synthetic signals and for the analysis of uterine electromyogram or electrohysterogram (EHG) recorded during gestation in monkeys. We have also evaluated a postprocessing algorithm that is especially suited for EHG analysis. Parameters are evaluated on real EHG signals in different gestational periods. The presented method gives good results when applied to synthetic as well as EHG signals. We have been able to obtain smaller ridge extraction errors when compared to two other methods specially developed for EHG. The gradient vector flow (GVF) snake method, or GVF-snake method, appears to be a good ridge extraction tool, which could be used on TFR of mono or multicomponent signals with good results.

Time-resolved influences of functional DAT1 and COMT variants on visual perception and post-processing.

PubMed

Bender, Stephan; Rellum, Thomas; Freitag, Christine; Resch, Franz; Rietschel, Marcella; Treutlein, Jens; Jennen-Steinmetz, Christine; Brandeis, Daniel; Banaschewski, Tobias; Laucht, Manfred

2012-01-01

Dopamine plays an important role in orienting and the regulation of selective attention to relevant stimulus characteristics. Thus, we examined the influences of functional variants related to dopamine inactivation in the dopamine transporter (DAT1) and catechol-O-methyltransferase genes (COMT) on the time-course of visual processing in a contingent negative variation (CNV) task. 64-channel EEG recordings were obtained from 195 healthy adolescents of a community-based sample during a continuous performance task (A-X version). Early and late CNV as well as preceding visual evoked potential components were assessed. Significant additive main effects of DAT1 and COMT on the occipito-temporal early CNV were observed. In addition, there was a trend towards an interaction between the two polymorphisms. Source analysis showed early CNV generators in the ventral visual stream and in frontal regions. There was a strong negative correlation between occipito-temporal visual post-processing and the frontal early CNV component. The early CNV time interval 500-1000 ms after the visual cue was specifically affected while the preceding visual perception stages were not influenced. Late visual potentials allow the genomic imaging of dopamine inactivation effects on visual post-processing. The same specific time-interval has been found to be affected by DAT1 and COMT during motor post-processing but not motor preparation. We propose the hypothesis that similar dopaminergic mechanisms modulate working memory encoding in both the visual and motor and perhaps other systems.

Tools for 3D scientific visualization in computational aerodynamics

NASA Technical Reports Server (NTRS)

Bancroft, Gordon; Plessel, Todd; Merritt, Fergus; Watson, Val

1989-01-01

The purpose is to describe the tools and techniques in use at the NASA Ames Research Center for performing visualization of computational aerodynamics, for example visualization of flow fields from computer simulations of fluid dynamics about vehicles such as the Space Shuttle. The hardware used for visualization is a high-performance graphics workstation connected to a super computer with a high speed channel. At present, the workstation is a Silicon Graphics IRIS 3130, the supercomputer is a CRAY2, and the high speed channel is a hyperchannel. The three techniques used for visualization are post-processing, tracking, and steering. Post-processing analysis is done after the simulation. Tracking analysis is done during a simulation but is not interactive, whereas steering analysis involves modifying the simulation interactively during the simulation. Using post-processing methods, a flow simulation is executed on a supercomputer and, after the simulation is complete, the results of the simulation are processed for viewing. The software in use and under development at NASA Ames Research Center for performing these types of tasks in computational aerodynamics is described. Workstation performance issues, benchmarking, and high-performance networks for this purpose are also discussed as well as descriptions of other hardware for digital video and film recording.

Streamflow Bias Correction for Climate Change Impact Studies: Harmless Correction or Wrecking Ball?

NASA Astrophysics Data System (ADS)

Nijssen, B.; Chegwidden, O.

2017-12-01

Projections of the hydrologic impacts of climate change rely on a modeling chain that includes estimates of future greenhouse gas emissions, global climate models, and hydrologic models. The resulting streamflow time series are used in turn as input to impact studies. While these flows can sometimes be used directly in these impact studies, many applications require additional post-processing to remove model errors. Water resources models and regulation studies are a prime example of this type of application. These models rely on specific flows and reservoir levels to trigger reservoir releases and diversions and do not function well if the unregulated streamflow inputs are significantly biased in time and/or amount. This post-processing step is typically referred to as bias-correction, even though this step corrects not just the mean but the entire distribution of flows. Various quantile-mapping approaches have been developed that adjust the modeled flows to match a reference distribution for some historic period. Simulations of future flows are then post-processed using this same mapping to remove hydrologic model errors. These streamflow bias-correction methods have received far less scrutiny than the downscaling and bias-correction methods that are used for climate model output, mostly because they are less widely used. However, some of these methods introduce large artifacts in the resulting flow series, in some cases severely distorting the climate change signal that is present in future flows. In this presentation, we discuss our experience with streamflow bias-correction methods as part of a climate change impact study in the Columbia River basin in the Pacific Northwest region of the United States. To support this discussion, we present a novel way to assess whether a streamflow bias-correction method is merely a harmless correction or is more akin to taking a wrecking ball to the climate change signal.

Post-processing of multi-model ensemble river discharge forecasts using censored EMOS

NASA Astrophysics Data System (ADS)

Hemri, Stephan; Lisniak, Dmytro; Klein, Bastian

2014-05-01

When forecasting water levels and river discharge, ensemble weather forecasts are used as meteorological input to hydrologic process models. As hydrologic models are imperfect and the input ensembles tend to be biased and underdispersed, the output ensemble forecasts for river runoff typically are biased and underdispersed, too. Thus, statistical post-processing is required in order to achieve calibrated and sharp predictions. Standard post-processing methods such as Ensemble Model Output Statistics (EMOS) that have their origins in meteorological forecasting are now increasingly being used in hydrologic applications. Here we consider two sub-catchments of River Rhine, for which the forecasting system of the Federal Institute of Hydrology (BfG) uses runoff data that are censored below predefined thresholds. To address this methodological challenge, we develop a censored EMOS method that is tailored to such data. The censored EMOS forecast distribution can be understood as a mixture of a point mass at the censoring threshold and a continuous part based on a truncated normal distribution. Parameter estimates of the censored EMOS model are obtained by minimizing the Continuous Ranked Probability Score (CRPS) over the training dataset. Model fitting on Box-Cox transformed data allows us to take account of the positive skewness of river discharge distributions. In order to achieve realistic forecast scenarios over an entire range of lead-times, there is a need for multivariate extensions. To this end, we smooth the marginal parameter estimates over lead-times. In order to obtain realistic scenarios of discharge evolution over time, the marginal distributions have to be linked with each other. To this end, the multivariate dependence structure can either be adopted from the raw ensemble like in Ensemble Copula Coupling (ECC), or be estimated from observations in a training period. The censored EMOS model has been applied to multi-model ensemble forecasts issued on a daily basis over a period of three years. For the two catchments considered, this resulted in well calibrated and sharp forecast distributions over all lead-times from 1 to 114 h. Training observations tended to be better indicators for the dependence structure than the raw ensemble.

Nineteenth NASTRAN (R) Users' Colloquium

NASA Technical Reports Server (NTRS)

1991-01-01

The proceedings of the the Nineteenth NASTRAN Users' Colloquium held April 22 to 26, 1991 are presented. Topics covered include the application of finite elements in engineering, comparisons with other approaches, unique applications, pre- and postprocessing or auxiliary programs, and new methods of analysis with NASTRAN.

Physics-based process model approach for detecting discontinuity during friction stir welding

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

Shrivastava, Amber; Pfefferkorn, Frank E.; Duffie, Neil A.

2015-02-12

The goal of this work is to develop a method for detecting the creation of discontinuities during friction stir welding. This in situ weld monitoring method could significantly reduce the need for post-process inspection. A process force model and a discontinuity force model were created based on the state-of-the-art understanding of flow around an friction stir welding (FSW) tool. These models are used to predict the FSW forces and size of discontinuities formed in the weld. Friction stir welds with discontinuities and welds without discontinuities were created, and the differences in force dynamics were observed. In this paper, discontinuities weremore » generated by reducing the tool rotation frequency and increasing the tool traverse speed in order to create "cold" welds. Experimental force data for welds with discontinuities and welds without discontinuities compared favorably with the predicted forces. The model currently overpredicts the discontinuity size.« less

BCI Competition IV – Data Set I: Learning Discriminative Patterns for Self-Paced EEG-Based Motor Imagery Detection

PubMed Central

Zhang, Haihong; Guan, Cuntai; Ang, Kai Keng; Wang, Chuanchu

2012-01-01

Detecting motor imagery activities versus non-control in brain signals is the basis of self-paced brain-computer interfaces (BCIs), but also poses a considerable challenge to signal processing due to the complex and non-stationary characteristics of motor imagery as well as non-control. This paper presents a self-paced BCI based on a robust learning mechanism that extracts and selects spatio-spectral features for differentiating multiple EEG classes. It also employs a non-linear regression and post-processing technique for predicting the time-series of class labels from the spatio-spectral features. The method was validated in the BCI Competition IV on Dataset I where it produced the lowest prediction error of class labels continuously. This report also presents and discusses analysis of the method using the competition data set. PMID:22347153

Reprocessing the GRACE-derived gravity field time series based on data-driven method for ocean tide alias error mitigation

NASA Astrophysics Data System (ADS)

Liu, Wei; Sneeuw, Nico; Jiang, Weiping

2017-04-01

GRACE mission has contributed greatly to the temporal gravity field monitoring in the past few years. However, ocean tides cause notable alias errors for single-pair spaceborne gravimetry missions like GRACE in two ways. First, undersampling from satellite orbit induces the aliasing of high-frequency tidal signals into the gravity signal. Second, ocean tide models used for de-aliasing in the gravity field retrieval carry errors, which will directly alias into the recovered gravity field. GRACE satellites are in non-repeat orbit, disabling the alias error spectral estimation based on the repeat period. Moreover, the gravity field recovery is conducted in non-strictly monthly interval and has occasional gaps, which result in an unevenly sampled time series. In view of the two aspects above, we investigate the data-driven method to mitigate the ocean tide alias error in a post-processing mode.

A review of materials engineering in silicon-based optical fibres

NASA Astrophysics Data System (ADS)

Healy, Noel; Gibson, Ursula; Peacock, Anna C.

2018-02-01

Semiconductor optical fibre technologies have grown rapidly in the last decade and there are now a range of production and post-processing techniques that allow for a vast degree of control over the core material's optoelectronic properties. These methodologies and the unique optical fibre geometry provide an exciting platform for materials engineering and fibres can now be produced with single crystal cores, low optical losses, tunable strain, and inscribable phase composition. This review discusses the state-of-the-art regarding the production of silicon optical fibres in amorphous and crystalline form and then looks at the post-processing techniques and the improved material quality and new functionality that they afford.

Copy-move forgery detection utilizing Fourier-Mellin transform log-polar features

NASA Astrophysics Data System (ADS)

Dixit, Rahul; Naskar, Ruchira

2018-03-01

In this work, we address the problem of region duplication or copy-move forgery detection in digital images, along with detection of geometric transforms (rotation and rescale) and postprocessing-based attacks (noise, blur, and brightness adjustment). Detection of region duplication, following conventional techniques, becomes more challenging when an intelligent adversary brings about such additional transforms on the duplicated regions. In this work, we utilize Fourier-Mellin transform with log-polar mapping and a color-based segmentation technique using K-means clustering, which help us to achieve invariance to all the above forms of attacks in copy-move forgery detection of digital images. Our experimental results prove the efficiency of the proposed method and its superiority to the current state of the art.

Comparative analysis of nonlinear dimensionality reduction techniques for breast MRI segmentation

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

Akhbardeh, Alireza; Jacobs, Michael A.; Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205

2012-04-15

Purpose: Visualization of anatomical structures using radiological imaging methods is an important tool in medicine to differentiate normal from pathological tissue and can generate large amounts of data for a radiologist to read. Integrating these large data sets is difficult and time-consuming. A new approach uses both supervised and unsupervised advanced machine learning techniques to visualize and segment radiological data. This study describes the application of a novel hybrid scheme, based on combining wavelet transform and nonlinear dimensionality reduction (NLDR) methods, to breast magnetic resonance imaging (MRI) data using three well-established NLDR techniques, namely, ISOMAP, local linear embedding (LLE), andmore » diffusion maps (DfM), to perform a comparative performance analysis. Methods: Twenty-five breast lesion subjects were scanned using a 3T scanner. MRI sequences used were T1-weighted, T2-weighted, diffusion-weighted imaging (DWI), and dynamic contrast-enhanced (DCE) imaging. The hybrid scheme consisted of two steps: preprocessing and postprocessing of the data. The preprocessing step was applied for B{sub 1} inhomogeneity correction, image registration, and wavelet-based image compression to match and denoise the data. In the postprocessing step, MRI parameters were considered data dimensions and the NLDR-based hybrid approach was applied to integrate the MRI parameters into a single image, termed the embedded image. This was achieved by mapping all pixel intensities from the higher dimension to a lower dimensional (embedded) space. For validation, the authors compared the hybrid NLDR with linear methods of principal component analysis (PCA) and multidimensional scaling (MDS) using synthetic data. For the clinical application, the authors used breast MRI data, comparison was performed using the postcontrast DCE MRI image and evaluating the congruence of the segmented lesions. Results: The NLDR-based hybrid approach was able to define and segment both synthetic and clinical data. In the synthetic data, the authors demonstrated the performance of the NLDR method compared with conventional linear DR methods. The NLDR approach enabled successful segmentation of the structures, whereas, in most cases, PCA and MDS failed. The NLDR approach was able to segment different breast tissue types with a high accuracy and the embedded image of the breast MRI data demonstrated fuzzy boundaries between the different types of breast tissue, i.e., fatty, glandular, and tissue with lesions (>86%). Conclusions: The proposed hybrid NLDR methods were able to segment clinical breast data with a high accuracy and construct an embedded image that visualized the contribution of different radiological parameters.« less

Relative effects of statistical preprocessing and postprocessing on a regional hydrological ensemble prediction system

NASA Astrophysics Data System (ADS)

Sharma, Sanjib; Siddique, Ridwan; Reed, Seann; Ahnert, Peter; Mendoza, Pablo; Mejia, Alfonso

2018-03-01

The relative roles of statistical weather preprocessing and streamflow postprocessing in hydrological ensemble forecasting at short- to medium-range forecast lead times (day 1-7) are investigated. For this purpose, a regional hydrologic ensemble prediction system (RHEPS) is developed and implemented. The RHEPS is comprised of the following components: (i) hydrometeorological observations (multisensor precipitation estimates, gridded surface temperature, and gauged streamflow); (ii) weather ensemble forecasts (precipitation and near-surface temperature) from the National Centers for Environmental Prediction 11-member Global Ensemble Forecast System Reforecast version 2 (GEFSRv2); (iii) NOAA's Hydrology Laboratory-Research Distributed Hydrologic Model (HL-RDHM); (iv) heteroscedastic censored logistic regression (HCLR) as the statistical preprocessor; (v) two statistical postprocessors, an autoregressive model with a single exogenous variable (ARX(1,1)) and quantile regression (QR); and (vi) a comprehensive verification strategy. To implement the RHEPS, 1 to 7 days weather forecasts from the GEFSRv2 are used to force HL-RDHM and generate raw ensemble streamflow forecasts. Forecasting experiments are conducted in four nested basins in the US Middle Atlantic region, ranging in size from 381 to 12 362 km2. Results show that the HCLR preprocessed ensemble precipitation forecasts have greater skill than the raw forecasts. These improvements are more noticeable in the warm season at the longer lead times (> 3 days). Both postprocessors, ARX(1,1) and QR, show gains in skill relative to the raw ensemble streamflow forecasts, particularly in the cool season, but QR outperforms ARX(1,1). The scenarios that implement preprocessing and postprocessing separately tend to perform similarly, although the postprocessing-alone scenario is often more effective. The scenario involving both preprocessing and postprocessing consistently outperforms the other scenarios. In some cases, however, the differences between this scenario and the scenario with postprocessing alone are not as significant. We conclude that implementing both preprocessing and postprocessing ensures the most skill improvements, but postprocessing alone can often be a competitive alternative.

SPRAI: coupling of radiative feedback and primordial chemistry in moving mesh hydrodynamics

NASA Astrophysics Data System (ADS)

Jaura, O.; Glover, S. C. O.; Klessen, R. S.; Paardekooper, J.-P.

2018-04-01

In this paper, we introduce a new radiative transfer code SPRAI (Simplex Photon Radiation in the Arepo Implementation) based on the SIMPLEX radiation transfer method. This method, originally used only for post-processing, is now directly integrated into the AREPO code and takes advantage of its adaptive unstructured mesh. Radiated photons are transferred from the sources through the series of Voronoi gas cells within a specific solid angle. From the photon attenuation, we derive corresponding photon fluxes and ionization rates and feed them to a primordial chemistry module. This gives us a self-consistent method for studying dynamical and chemical processes caused by ionizing sources in primordial gas. Since the computational cost of the SIMPLEX method does not scale directly with the number of sources, it is convenient for studying systems such as primordial star-forming haloes that may form multiple ionizing sources.

A shape-based segmentation method for mobile laser scanning point clouds

NASA Astrophysics Data System (ADS)

Yang, Bisheng; Dong, Zhen

2013-07-01

Segmentation of mobile laser point clouds of urban scenes into objects is an important step for post-processing (e.g., interpretation) of point clouds. Point clouds of urban scenes contain numerous objects with significant size variability, complex and incomplete structures, and holes or variable point densities, raising great challenges for the segmentation of mobile laser point clouds. This paper addresses these challenges by proposing a shape-based segmentation method. The proposed method first calculates the optimal neighborhood size of each point to derive the geometric features associated with it, and then classifies the point clouds according to geometric features using support vector machines (SVMs). Second, a set of rules are defined to segment the classified point clouds, and a similarity criterion for segments is proposed to overcome over-segmentation. Finally, the segmentation output is merged based on topological connectivity into a meaningful geometrical abstraction. The proposed method has been tested on point clouds of two urban scenes obtained by different mobile laser scanners. The results show that the proposed method segments large-scale mobile laser point clouds with good accuracy and computationally effective time cost, and that it segments pole-like objects particularly well.

Point Cloud Generation from Aerial Image Data Acquired by a Quadrocopter Type Micro Unmanned Aerial Vehicle and a Digital Still Camera

PubMed Central

Rosnell, Tomi; Honkavaara, Eija

2012-01-01

The objective of this investigation was to develop and investigate methods for point cloud generation by image matching using aerial image data collected by quadrocopter type micro unmanned aerial vehicle (UAV) imaging systems. Automatic generation of high-quality, dense point clouds from digital images by image matching is a recent, cutting-edge step forward in digital photogrammetric technology. The major components of the system for point cloud generation are a UAV imaging system, an image data collection process using high image overlaps, and post-processing with image orientation and point cloud generation. Two post-processing approaches were developed: one of the methods is based on Bae Systems’ SOCET SET classical commercial photogrammetric software and another is built using Microsoft®’s Photosynth™ service available in the Internet. Empirical testing was carried out in two test areas. Photosynth processing showed that it is possible to orient the images and generate point clouds fully automatically without any a priori orientation information or interactive work. The photogrammetric processing line provided dense and accurate point clouds that followed the theoretical principles of photogrammetry, but also some artifacts were detected. The point clouds from the Photosynth processing were sparser and noisier, which is to a large extent due to the fact that the method is not optimized for dense point cloud generation. Careful photogrammetric processing with self-calibration is required to achieve the highest accuracy. Our results demonstrate the high performance potential of the approach and that with rigorous processing it is possible to reach results that are consistent with theory. We also point out several further research topics. Based on theoretical and empirical results, we give recommendations for properties of imaging sensor, data collection and processing of UAV image data to ensure accurate point cloud generation. PMID:22368479

Point cloud generation from aerial image data acquired by a quadrocopter type micro unmanned aerial vehicle and a digital still camera.

PubMed

Rosnell, Tomi; Honkavaara, Eija

2012-01-01

The objective of this investigation was to develop and investigate methods for point cloud generation by image matching using aerial image data collected by quadrocopter type micro unmanned aerial vehicle (UAV) imaging systems. Automatic generation of high-quality, dense point clouds from digital images by image matching is a recent, cutting-edge step forward in digital photogrammetric technology. The major components of the system for point cloud generation are a UAV imaging system, an image data collection process using high image overlaps, and post-processing with image orientation and point cloud generation. Two post-processing approaches were developed: one of the methods is based on Bae Systems' SOCET SET classical commercial photogrammetric software and another is built using Microsoft(®)'s Photosynth™ service available in the Internet. Empirical testing was carried out in two test areas. Photosynth processing showed that it is possible to orient the images and generate point clouds fully automatically without any a priori orientation information or interactive work. The photogrammetric processing line provided dense and accurate point clouds that followed the theoretical principles of photogrammetry, but also some artifacts were detected. The point clouds from the Photosynth processing were sparser and noisier, which is to a large extent due to the fact that the method is not optimized for dense point cloud generation. Careful photogrammetric processing with self-calibration is required to achieve the highest accuracy. Our results demonstrate the high performance potential of the approach and that with rigorous processing it is possible to reach results that are consistent with theory. We also point out several further research topics. Based on theoretical and empirical results, we give recommendations for properties of imaging sensor, data collection and processing of UAV image data to ensure accurate point cloud generation.

The application of quasi-steady approximation in atomic kinetics in simulation of hohlraum radiation drive

NASA Astrophysics Data System (ADS)

Ren, Guoli; Pei, Wenbing; Lan, Ke; Li, Xin; Hohlraum Physics Team

2014-10-01

In current routine 2D simulation of hohlraum physics, we adopt the principal-quantum-number (n-level) average atom model (AAM) in NLTE plasma description. The more sophisticated atomic kinetics description is better choice, but the in-line calculation consumes much more resource. By distinguishing the much more fast bound-bound atomic processes from the relative slow bound-free atomic processes, we found a method to built up a bound electron distribution (n-level or nl-level) using in-line n-level calculated plasma condition (such as temperature, density, average ionization degree). We name this method ``quasi-steady approximation.'' Using this method and the plasma condition calculated under n-level, we re-build the nl-level bound electron distribution (Pnl), and acquire a new hohlraum radiative drive by post-processing. Comparison with the n-level post-processed hohlraum drive shows that we get an almost identical radiation flux but with more-detailed frequency-dependant structures. Also we use this method in the benchmark gold sphere experiment, the constructed nl-level radiation drive resembles the experimental results and DCA results, while the n-level raditation does not.

False colors removal on the YCr-Cb color space

NASA Astrophysics Data System (ADS)

Tomaselli, Valeria; Guarnera, Mirko; Messina, Giuseppe

2009-01-01

Post-processing algorithms are usually placed in the pipeline of imaging devices to remove residual color artifacts introduced by the demosaicing step. Although demosaicing solutions aim to eliminate, limit or correct false colors and other impairments caused by a non ideal sampling, post-processing techniques are usually more powerful in achieving this purpose. This is mainly because the input of post-processing algorithms is a fully restored RGB color image. Moreover, post-processing can be applied more than once, in order to meet some quality criteria. In this paper we propose an effective technique for reducing the color artifacts generated by conventional color interpolation algorithms, in YCrCb color space. This solution efficiently removes false colors and can be executed while performing the edge emphasis process.

Grain Structure Control of Additively Manufactured Metallic Materials

PubMed Central

Faierson, Eric J.

2017-01-01

Grain structure control is challenging for metal additive manufacturing (AM). Grain structure optimization requires the control of grain morphology with grain size refinement, which can improve the mechanical properties of additive manufactured components. This work summarizes methods to promote fine equiaxed grains in both the additive manufacturing process and subsequent heat treatment. Influences of temperature gradient, solidification velocity and alloy composition on grain morphology are discussed. Equiaxed solidification is greatly promoted by introducing a high density of heterogeneous nucleation sites via powder rate control in the direct energy deposition (DED) technique or powder surface treatment for powder-bed techniques. Grain growth/coarsening during post-processing heat treatment can be restricted by presence of nano-scale oxide particles formed in-situ during AM. Grain refinement of martensitic steels can also be achieved by cyclic austenitizing in post-processing heat treatment. Evidently, new alloy powder design is another sustainable method enhancing the capability of AM for high-performance components with desirable microstructures.

A Preliminary Study of Clinical Abbreviation Disambiguation in Real Time.

PubMed

Wu, Y; Denny, J C; Rosenbloom, S T; Miller, R A; Giuse, D A; Song, M; Xu, H

2015-01-01

To save time, healthcare providers frequently use abbreviations while authoring clinical documents. Nevertheless, abbreviations that authors deem unambiguous often confuse other readers, including clinicians, patients, and natural language processing (NLP) systems. Most current clinical NLP systems "post-process" notes long after clinicians enter them into electronic health record systems (EHRs). Such post-processing cannot guarantee 100% accuracy in abbreviation identification and disambiguation, since multiple alternative interpretations exist. Authors describe a prototype system for real-time Clinical Abbreviation Recognition and Disambiguation (rCARD) - i.e., a system that interacts with authors during note generation to verify correct abbreviation senses. The rCARD system design anticipates future integration with web-based clinical documentation systems to improve quality of healthcare records. When clinicians enter documents, rCARD will automatically recognize each abbreviation. For abbreviations with multiple possible senses, rCARD will show a ranked list of possible meanings with the best predicted sense at the top. The prototype application embodies three word sense disambiguation (WSD) methods to predict the correct senses of abbreviations. We then conducted three experments to evaluate rCARD, including 1) a performance evaluation of different WSD methods; 2) a time evaluation of real-time WSD methods; and 3) a user study of typing clinical sentences with abbreviations using rCARD. Using 4,721 sentences containing 25 commonly observed, highly ambiguous clinical abbreviations, our evaluation showed that the best profile-based method implemented in rCARD achieved a reasonable WSD accuracy of 88.8% (comparable to SVM - 89.5%) and the cost of time for the different WSD methods are also acceptable (ranging from 0.630 to 1.649 milliseconds within the same network). The preliminary user study also showed that the extra time costs by rCARD were about 5% of total document entry time and users did not feel a significant delay when using rCARD for clinical document entry. The study indicates that it is feasible to integrate a real-time, NLP-enabled abbreviation recognition and disambiguation module with clinical documentation systems.

Using modern imaging techniques to old HST data: a summary of the ALICE program.

NASA Astrophysics Data System (ADS)

Choquet, Elodie; Soummer, Remi; Perrin, Marshall; Pueyo, Laurent; Hagan, James Brendan; Zimmerman, Neil; Debes, John Henry; Schneider, Glenn; Ren, Bin; Milli, Julien; Wolff, Schuyler; Stark, Chris; Mawet, Dimitri; Golimowski, David A.; Hines, Dean C.; Roberge, Aki; Serabyn, Eugene

2018-01-01

Direct imaging of extrasolar systems is a powerful technique to study the physical properties of exoplanetary systems and understand their formation and evolution mechanisms. The detection and characterization of these objects are challenged by their high contrast with their host star. Several observing strategies and post-processing algorithms have been developed for ground-based high-contrast imaging instruments, enabling the discovery of directly-imaged and spectrally-characterized exoplanets. The Hubble Space Telescope (HST), pioneer in directly imaging extrasolar systems, has yet been often limited to the detection of bright debris disks systems, with sensitivity limited by the difficulty to implement an optimal PSF subtraction stategy, which is readily offered on ground-based telescopes in pupil tracking mode.The Archival Legacy Investigations of Circumstellar Environments (ALICE) program is a consistent re-analysis of the 10 year old coronagraphic archive of HST's NICMOS infrared imager. Using post-processing methods developed for ground-based observations, we used the whole archive to calibrate PSF temporal variations and improve NICMOS's detection limits. We have now delivered ALICE-reprocessed science products for the whole NICMOS archival data back to the community. These science products, as well as the ALICE pipeline, were used to prototype the JWST coronagraphic data and reduction pipeline. The ALICE program has enabled the detection of 10 faint debris disk systems never imaged before in the near-infrared and several substellar companion candidates, which we are all in the process of characterizing through follow-up observations with both ground-based facilities and HST-STIS coronagraphy. In this publication, we provide a summary of the results of the ALICE program, advertise its science products and discuss the prospects of the program.

Block-structured grids for complex aerodynamic configurations: Current status

NASA Technical Reports Server (NTRS)

Vatsa, Veer N.; Sanetrik, Mark D.; Parlette, Edward B.

1995-01-01

The status of CFD methods based on the use of block-structured grids for analyzing viscous flows over complex configurations is examined. The objective of the present study is to make a realistic assessment of the usability of such grids for routine computations typically encountered in the aerospace industry. It is recognized at the very outset that the total turnaround time, from the moment the configuration is identified until the computational results have been obtained and postprocessed, is more important than just the computational time. Pertinent examples will be cited to demonstrate the feasibility of solving flow over practical configurations of current interest on block-structured grids.

Note: Fully integrated 3.2 Gbps quantum random number generator with real-time extraction

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

Zhang, Xiao-Guang; Nie, You-Qi; Liang, Hao

2016-07-15

We present a real-time and fully integrated quantum random number generator (QRNG) by measuring laser phase fluctuations. The QRNG scheme based on laser phase fluctuations is featured for its capability of generating ultra-high-speed random numbers. However, the speed bottleneck of a practical QRNG lies on the limited speed of randomness extraction. To close the gap between the fast randomness generation and the slow post-processing, we propose a pipeline extraction algorithm based on Toeplitz matrix hashing and implement it in a high-speed field-programmable gate array. Further, all the QRNG components are integrated into a module, including a compact and actively stabilizedmore » interferometer, high-speed data acquisition, and real-time data post-processing and transmission. The final generation rate of the QRNG module with real-time extraction can reach 3.2 Gbps.« less

Secret information reconciliation based on punctured low-density parity-check codes for continuous-variable quantum key distribution

NASA Astrophysics Data System (ADS)

Jiang, Xue-Qin; Huang, Peng; Huang, Duan; Lin, Dakai; Zeng, Guihua

2017-02-01

Achieving information theoretic security with practical complexity is of great interest to continuous-variable quantum key distribution in the postprocessing procedure. In this paper, we propose a reconciliation scheme based on the punctured low-density parity-check (LDPC) codes. Compared to the well-known multidimensional reconciliation scheme, the present scheme has lower time complexity. Especially when the chosen punctured LDPC code achieves the Shannon capacity, the proposed reconciliation scheme can remove the information that has been leaked to an eavesdropper in the quantum transmission phase. Therefore, there is no information leaked to the eavesdropper after the reconciliation stage. This indicates that the privacy amplification algorithm of the postprocessing procedure is no more needed after the reconciliation process. These features lead to a higher secret key rate, optimal performance, and availability for the involved quantum key distribution scheme.

Computer-aided liver volumetry: performance of a fully-automated, prototype post-processing solution for whole-organ and lobar segmentation based on MDCT imaging.

PubMed

Fananapazir, Ghaneh; Bashir, Mustafa R; Marin, Daniele; Boll, Daniel T

2015-06-01

To evaluate the performance of a prototype, fully-automated post-processing solution for whole-liver and lobar segmentation based on MDCT datasets. A polymer liver phantom was used to assess accuracy of post-processing applications comparing phantom volumes determined via Archimedes' principle with MDCT segmented datasets. For the IRB-approved, HIPAA-compliant study, 25 patients were enrolled. Volumetry performance compared the manual approach with the automated prototype, assessing intraobserver variability, and interclass correlation for whole-organ and lobar segmentation using ANOVA comparison. Fidelity of segmentation was evaluated qualitatively. Phantom volume was 1581.0 ± 44.7 mL, manually segmented datasets estimated 1628.0 ± 47.8 mL, representing a mean overestimation of 3.0%, automatically segmented datasets estimated 1601.9 ± 0 mL, representing a mean overestimation of 1.3%. Whole-liver and segmental volumetry demonstrated no significant intraobserver variability for neither manual nor automated measurements. For whole-liver volumetry, automated measurement repetitions resulted in identical values; reproducible whole-organ volumetry was also achieved with manual segmentation, p(ANOVA) 0.98. For lobar volumetry, automated segmentation improved reproducibility over manual approach, without significant measurement differences for either methodology, p(ANOVA) 0.95-0.99. Whole-organ and lobar segmentation results from manual and automated segmentation showed no significant differences, p(ANOVA) 0.96-1.00. Assessment of segmentation fidelity found that segments I-IV/VI showed greater segmentation inaccuracies compared to the remaining right hepatic lobe segments. Automated whole-liver segmentation showed non-inferiority of fully-automated whole-liver segmentation compared to manual approaches with improved reproducibility and post-processing duration; automated dual-seed lobar segmentation showed slight tendencies for underestimating the right hepatic lobe volume and greater variability in edge detection for the left hepatic lobe compared to manual segmentation.

Simulations for Improved Imaging of Faint Objects at Maui Space Surveillance Site

NASA Astrophysics Data System (ADS)

Holmes, R.; Roggemann, M.; Werth, M.; Lucas, J.; Thompson, D.

A detailed wave-optics simulation is used in conjunction with advanced post-processing algorithms to explore the trade space between image post-processing and adaptive optics for improved imaging of low signal-to-noise ratio (SNR) targets. Target-based guidestars are required for imaging of most active Earth-orbiting satellites because of restrictions on using laser-backscatter-based guidestars in the direction of such objects. With such target-based guidestars and Maui conditions, it is found that significant reductions in adaptive optics actuator and subaperture density can result in improved imaging of fainter objects. Simulation indicates that elimination of adaptive optics produces sub-optimal results for all of the faint-object cases considered. This research was developed with funding from the Defense Advanced Research Projects Agency (DARPA). The views, opinions, and/or findings expressed are those of the author(s) and should not be interpreted as representing the official views or policies of the Department of Defense or the U.S. Government.

Evaluation of Transverse Thermal Stresses in Composite Plates Based on First-Order Shear Deformation Theory

NASA Technical Reports Server (NTRS)

Rolfes, R.; Noor, A. K.; Sparr, H.

1998-01-01

A postprocessing procedure is presented for the evaluation of the transverse thermal stresses in laminated plates. The analytical formulation is based on the first-order shear deformation theory and the plate is discretized by using a single-field displacement finite element model. The procedure is based on neglecting the derivatives of the in-plane forces and the twisting moments, as well as the mixed derivatives of the bending moments, with respect to the in-plane coordinates. The calculated transverse shear stiffnesses reflect the actual stacking sequence of the composite plate. The distributions of the transverse stresses through-the-thickness are evaluated by using only the transverse shear forces and the thermal effects resulting from the finite element analysis. The procedure is implemented into a postprocessing routine which can be easily incorporated into existing commercial finite element codes. Numerical results are presented for four- and ten-layer cross-ply laminates subjected to mechanical and thermal loads.

Performance of a cavity-method-based algorithm for the prize-collecting Steiner tree problem on graphs

NASA Astrophysics Data System (ADS)

Biazzo, Indaco; Braunstein, Alfredo; Zecchina, Riccardo

2012-08-01

We study the behavior of an algorithm derived from the cavity method for the prize-collecting steiner tree (PCST) problem on graphs. The algorithm is based on the zero temperature limit of the cavity equations and as such is formally simple (a fixed point equation resolved by iteration) and distributed (parallelizable). We provide a detailed comparison with state-of-the-art algorithms on a wide range of existing benchmarks, networks, and random graphs. Specifically, we consider an enhanced derivative of the Goemans-Williamson heuristics and the dhea solver, a branch and cut integer linear programming based approach. The comparison shows that the cavity algorithm outperforms the two algorithms in most large instances both in running time and quality of the solution. Finally we prove a few optimality properties of the solutions provided by our algorithm, including optimality under the two postprocessing procedures defined in the Goemans-Williamson derivative and global optimality in some limit cases.

Buried object detection in GPR images

DOEpatents

Paglieroni, David W; Chambers, David H; Bond, Steven W; Beer, W. Reginald

2014-04-29

A method and system for detecting the presence of subsurface objects within a medium is provided. In some embodiments, the imaging and detection system operates in a multistatic mode to collect radar return signals generated by an array of transceiver antenna pairs that is positioned across the surface and that travels down the surface. The imaging and detection system pre-processes the return signal to suppress certain undesirable effects. The imaging and detection system then generates synthetic aperture radar images from real aperture radar images generated from the pre-processed return signal. The imaging and detection system then post-processes the synthetic aperture radar images to improve detection of subsurface objects. The imaging and detection system identifies peaks in the energy levels of the post-processed image frame, which indicates the presence of a subsurface object.

Volumetric calibration of a plenoptic camera

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

Hall, Elise Munz; Fahringer, Timothy W.; Guildenbecher, Daniel Robert

Here, the volumetric calibration of a plenoptic camera is explored to correct for inaccuracies due to real-world lens distortions and thin-lens assumptions in current processing methods. Two methods of volumetric calibration based on a polynomial mapping function that does not require knowledge of specific lens parameters are presented and compared to a calibration based on thin-lens assumptions. The first method, volumetric dewarping, is executed by creation of a volumetric representation of a scene using the thin-lens assumptions, which is then corrected in post-processing using a polynomial mapping function. The second method, direct light-field calibration, uses the polynomial mapping in creationmore » of the initial volumetric representation to relate locations in object space directly to image sensor locations. The accuracy and feasibility of these methods is examined experimentally by capturing images of a known dot card at a variety of depths. Results suggest that use of a 3D polynomial mapping function provides a significant increase in reconstruction accuracy and that the achievable accuracy is similar using either polynomial-mapping-based method. Additionally, direct light-field calibration provides significant computational benefits by eliminating some intermediate processing steps found in other methods. Finally, the flexibility of this method is shown for a nonplanar calibration.« less

Volumetric calibration of a plenoptic camera

DOE PAGES

Hall, Elise Munz; Fahringer, Timothy W.; Guildenbecher, Daniel Robert; ...

2018-02-01

Here, the volumetric calibration of a plenoptic camera is explored to correct for inaccuracies due to real-world lens distortions and thin-lens assumptions in current processing methods. Two methods of volumetric calibration based on a polynomial mapping function that does not require knowledge of specific lens parameters are presented and compared to a calibration based on thin-lens assumptions. The first method, volumetric dewarping, is executed by creation of a volumetric representation of a scene using the thin-lens assumptions, which is then corrected in post-processing using a polynomial mapping function. The second method, direct light-field calibration, uses the polynomial mapping in creationmore » of the initial volumetric representation to relate locations in object space directly to image sensor locations. The accuracy and feasibility of these methods is examined experimentally by capturing images of a known dot card at a variety of depths. Results suggest that use of a 3D polynomial mapping function provides a significant increase in reconstruction accuracy and that the achievable accuracy is similar using either polynomial-mapping-based method. Additionally, direct light-field calibration provides significant computational benefits by eliminating some intermediate processing steps found in other methods. Finally, the flexibility of this method is shown for a nonplanar calibration.« less

The VLITE Post-Processing Pipeline

NASA Astrophysics Data System (ADS)

Richards, Emily E.; Clarke, Tracy; Peters, Wendy; Polisensky, Emil; Kassim, Namir E.

2018-01-01

A post-processing pipeline to adaptively extract and catalog point sources is being developed to enhance the scientific value and accessibility of data products generated by the VLA Low-band Ionosphere and Transient Experiment (VLITE; ) on the Karl G. Jansky Very Large Array (VLA). In contrast to other radio sky surveys, the commensal observing mode of VLITE results in varying depths, sensitivities, and spatial resolutions across the sky based on the configuration of the VLA, location on the sky, and time on source specified by the primary observer for their independent science objectives. Therefore, previously developed tools and methods for generating source catalogs and survey statistics are not always appropriate for VLITE's diverse and growing set of data. A raw catalog of point sources extracted from every VLITE image will be created from source fit parameters stored in a queryable database. Point sources will be measured using the Python Blob Detector and Source Finder software (PyBDSF; Mohan & Rafferty 2015). Sources in the raw catalog will be associated with previous VLITE detections in a resolution- and sensitivity-dependent manner, and cross-matched to other radio sky surveys to aid in the detection of transient and variable sources. Final data products will include separate, tiered point source catalogs grouped by sensitivity limit and spatial resolution.

Post-processing of seismic parameter data based on valid seismic event determination

DOEpatents

McEvilly, Thomas V.

1985-01-01

An automated seismic processing system and method are disclosed, including an array of CMOS microprocessors for unattended battery-powered processing of a multi-station network. According to a characterizing feature of the invention, each channel of the network is independently operable to automatically detect, measure times and amplitudes, and compute and fit Fast Fourier transforms (FFT's) for both P- and S- waves on analog seismic data after it has been sampled at a given rate. The measured parameter data from each channel are then reviewed for event validity by a central controlling microprocessor and if determined by preset criteria to constitute a valid event, the parameter data are passed to an analysis computer for calculation of hypocenter location, running b-values, source parameters, event count, P- wave polarities, moment-tensor inversion, and Vp/Vs ratios. The in-field real-time analysis of data maximizes the efficiency of microearthquake surveys allowing flexibility in experimental procedures, with a minimum of traditional labor-intensive postprocessing. A unique consequence of the system is that none of the original data (i.e., the sensor analog output signals) are necessarily saved after computation, but rather, the numerical parameters generated by the automatic analysis are the sole output of the automated seismic processor.

[InlineEquation not available: see fulltext.]-Means Based Fingerprint Segmentation with Sensor Interoperability

NASA Astrophysics Data System (ADS)

Yang, Gongping; Zhou, Guang-Tong; Yin, Yilong; Yang, Xiukun

2010-12-01

A critical step in an automatic fingerprint recognition system is the segmentation of fingerprint images. Existing methods are usually designed to segment fingerprint images originated from a certain sensor. Thus their performances are significantly affected when dealing with fingerprints collected by different sensors. This work studies the sensor interoperability of fingerprint segmentation algorithms, which refers to the algorithm's ability to adapt to the raw fingerprints obtained from different sensors. We empirically analyze the sensor interoperability problem, and effectively address the issue by proposing a [InlineEquation not available: see fulltext.]-means based segmentation method called SKI. SKI clusters foreground and background blocks of a fingerprint image based on the [InlineEquation not available: see fulltext.]-means algorithm, where a fingerprint block is represented by a 3-dimensional feature vector consisting of block-wise coherence, mean, and variance (abbreviated as CMV). SKI also employs morphological postprocessing to achieve favorable segmentation results. We perform SKI on each fingerprint to ensure sensor interoperability. The interoperability and robustness of our method are validated by experiments performed on a number of fingerprint databases which are obtained from various sensors.

Using Dictionary Pair Learning for Seizure Detection.

PubMed

Ma, Xin; Yu, Nana; Zhou, Weidong

2018-02-13

Automatic seizure detection is extremely important in the monitoring and diagnosis of epilepsy. The paper presents a novel method based on dictionary pair learning (DPL) for seizure detection in the long-term intracranial electroencephalogram (EEG) recordings. First, for the EEG data, wavelet filtering and differential filtering are applied, and the kernel function is performed to make the signal linearly separable. In DPL, the synthesis dictionary and analysis dictionary are learned jointly from original training samples with alternating minimization method, and sparse coefficients are obtained by using of linear projection instead of costly [Formula: see text]-norm or [Formula: see text]-norm optimization. At last, the reconstructed residuals associated with seizure and nonseizure sub-dictionary pairs are calculated as the decision values, and the postprocessing is performed for improving the recognition rate and reducing the false detection rate of the system. A total of 530[Formula: see text]h from 20 patients with 81 seizures were used to evaluate the system. Our proposed method has achieved an average segment-based sensitivity of 93.39%, specificity of 98.51%, and event-based sensitivity of 96.36% with false detection rate of 0.236/h.

Optoelectronic scanning system upgrade by energy center localization methods

NASA Astrophysics Data System (ADS)

Flores-Fuentes, W.; Sergiyenko, O.; Rodriguez-Quiñonez, J. C.; Rivas-López, M.; Hernández-Balbuena, D.; Básaca-Preciado, L. C.; Lindner, L.; González-Navarro, F. F.

2016-11-01

A problem of upgrading an optoelectronic scanning system with digital post-processing of the signal based on adequate methods of energy center localization is considered. An improved dynamic triangulation analysis technique is proposed by an example of industrial infrastructure damage detection. A modification of our previously published method aimed at searching for the energy center of an optoelectronic signal is described. Application of the artificial intelligence algorithm of compensation for the error of determining the angular coordinate in calculating the spatial coordinate through dynamic triangulation is demonstrated. Five energy center localization methods are developed and tested to select the best method. After implementation of these methods, digital compensation for the measurement error, and statistical data analysis, a non-parametric behavior of the data is identified. The Wilcoxon signed rank test is applied to improve the result further. For optical scanning systems, it is necessary to detect a light emitter mounted on the infrastructure being investigated to calculate its spatial coordinate by the energy center localization method.

Regionalization of post-processed ensemble runoff forecasts

NASA Astrophysics Data System (ADS)

Olav Skøien, Jon; Bogner, Konrad; Salamon, Peter; Smith, Paul; Pappenberger, Florian

2016-05-01

For many years, meteorological models have been run with perturbated initial conditions or parameters to produce ensemble forecasts that are used as a proxy of the uncertainty of the forecasts. However, the ensembles are usually both biased (the mean is systematically too high or too low, compared with the observed weather), and has dispersion errors (the ensemble variance indicates a too low or too high confidence in the forecast, compared with the observed weather). The ensembles are therefore commonly post-processed to correct for these shortcomings. Here we look at one of these techniques, referred to as Ensemble Model Output Statistics (EMOS) (Gneiting et al., 2005). Originally, the post-processing parameters were identified as a fixed set of parameters for a region. The application of our work is the European Flood Awareness System (http://www.efas.eu), where a distributed model is run with meteorological ensembles as input. We are therefore dealing with a considerably larger data set than previous analyses. We also want to regionalize the parameters themselves for other locations than the calibration gauges. The post-processing parameters are therefore estimated for each calibration station, but with a spatial penalty for deviations from neighbouring stations, depending on the expected semivariance between the calibration catchment and these stations. The estimated post-processed parameters can then be used for regionalization of the postprocessing parameters also for uncalibrated locations using top-kriging in the rtop-package (Skøien et al., 2006, 2014). We will show results from cross-validation of the methodology and although our interest is mainly in identifying exceedance probabilities for certain return levels, we will also show how the rtop package can be used for creating a set of post-processed ensembles through simulations.

Detection and characterization of lesions on low-radiation-dose abdominal CT images postprocessed with noise reduction filters.

PubMed

Kalra, Mannudeep K; Maher, Michael M; Blake, Michael A; Lucey, Brian C; Karau, Kelly; Toth, Thomas L; Avinash, Gopal; Halpern, Elkan F; Saini, Sanjay

2004-09-01

To assess the effect of noise reduction filters on detection and characterization of lesions on low-radiation-dose abdominal computed tomographic (CT) images. Low-dose CT images of abdominal lesions in 19 consecutive patients (11 women, eight men; age range, 32-78 years) were obtained at reduced tube currents (120-144 mAs). These baseline low-dose CT images were postprocessed with six noise reduction filters; the resulting postprocessed images were then randomly assorted with baseline images. Three radiologists performed independent evaluation of randomized images for presence, number, margins, attenuation, conspicuity, calcification, and enhancement of lesions, as well as image noise. Side-by-side comparison of baseline images with postprocessed images was performed by using a five-point scale for assessing lesion conspicuity and margins, image noise, beam hardening, and diagnostic acceptability. Quantitative noise and contrast-to-noise ratio were obtained for all liver lesions. Statistical analysis was performed by using the Wilcoxon signed rank test, Student t test, and kappa test of agreement. Significant reduction of noise was observed in images postprocessed with filter F compared with the noise in baseline nonfiltered images (P =.004). Although the number of lesions seen on baseline images and that seen on postprocessed images were identical, lesions were less conspicuous on postprocessed images than on baseline images. A decrease in quantitative image noise and contrast-to-noise ratio for liver lesions was noted with all noise reduction filters. There was good interobserver agreement (kappa = 0.7). Although the use of currently available noise reduction filters improves image noise and ameliorates beam-hardening artifacts at low-dose CT, such filters are limited by a compromise in lesion conspicuity and appearance in comparison with lesion conspicuity and appearance on baseline low-dose CT images. Copyright RSNA, 2004

Development of upwind schemes for the Euler equations

NASA Technical Reports Server (NTRS)

Chakravarthy, Sukumar R.

1987-01-01

Described are many algorithmic and computational aspects of upwind schemes and their second-order accurate formulations based on Total-Variation-Diminishing (TVD) approaches. An operational unification of the underlying first-order scheme is first presented encompassing Godunov's, Roe's, Osher's, and Split-Flux methods. For higher order versions, the preprocessing and postprocessing approaches to constructing TVD discretizations are considered. TVD formulations can be used to construct relaxation methods for unfactored implicit upwind schemes, which in turn can be exploited to construct space-marching procedures for even the unsteady Euler equations. A major part of the report describes time- and space-marching procedures for solving the Euler equations in 2-D, 3-D, Cartesian, and curvilinear coordinates. Along with many illustrative examples, several results of efficient computations on 3-D supersonic flows with subsonic pockets are presented.

Percutaneous Vertebroplasty: Preliminary Experiences with Rotational Acquisitions and 3D Reconstructions for Therapy Control

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

Hodek-Wuerz, Roman; Martin, Jean-Baptiste; Wilhelm, Kai

Percutaneous vertebroplasty (PVP) is carried out under fluoroscopic control in most centers. The exclusion of implant leakage and the assessment of implant distribution might be difficult to assess based on two-dimensional radiographic projection images only. We evaluated the feasibility of performing a follow-up examination after PVP with rotational acquisitions and volumetric reconstructions in the angio suite. Twenty consecutive patients underwent standard PVP procedures under fluoroscopic control. Immediate postprocedure evaluation of the implant distribution in the angio suite (BV 3000; Philips, The Netherlands) was performed using rotational acquisitions (typical parameters for the image acquisition included a 17-cm field-of-view, 200 acquired imagesmore » for a total angular range of 180{sup o}). Postprocessing of acquired volumetric datasets included multiplanar reconstruction (MPR), maximum intensity projection (MIP), and volume rendering technique (VRT) images that were displayed as two-dimensional slabs or as entire three-dimensional volumes. Image evaluation included lesion and implant assessment with special attention given to implant leakage. Findings from rotational acquisitions were compared to findings from postinterventional CT. The time to perform and to postprocess the rotational acquisitions was in all cases less then 10 min. Assessment of implant distribution after PVP using rotational image acquisition methods and volumetric reconstructions was possible in all patients. Cement distribution and potential leakage sites were visualized best on MIP images presented as slabs. From a total of 33 detected leakages with CT, 30 could be correctly detected by rotational image acquisition. Rotational image acquisitions and volumetric reconstruction methods provided a fast method to control radiographically the result of PVP in our cases.« less

Shortcomings of low-cost imaging systems for viewing computed radiographs.

PubMed

Ricke, J; Hänninen, E L; Zielinski, C; Amthauer, H; Stroszczynski, C; Liebig, T; Wolf, M; Hosten, N

2000-01-01

To assess potential advantages of a new PC-based viewing tool featuring image post-processing for viewing computed radiographs on low-cost hardware (PC) with a common display card and color monitor, and to evaluate the effect of using color versus monochrome monitors. Computed radiographs of a statistical phantom were viewed on a PC, with and without post-processing (spatial frequency and contrast processing), employing a monochrome or a color monitor. Findings were compared with the viewing on a radiological Workstation and evaluated with ROC analysis. Image post-processing improved the perception of low-contrast details significantly irrespective of the monitor used. No significant difference in perception was observed between monochrome and color monitors. The review at the radiological Workstation was superior to the review done using the PC with image processing. Lower quality hardware (graphic card and monitor) used in low cost PCs negatively affects perception of low-contrast details in computed radiographs. In this situation, it is highly recommended to use spatial frequency and contrast processing. No significant quality gain has been observed for the high-end monochrome monitor compared to the color display. However, the color monitor was affected stronger by high ambient illumination.

Pre- and post-processing for Cosmic/NASTRAN on personal computers and mainframes

NASA Technical Reports Server (NTRS)

Kamel, H. A.; Mobley, A. V.; Nagaraj, B.; Watkins, K. W.

1986-01-01

An interface between Cosmic/NASTRAN and GIFTS has recently been released, combining the powerful pre- and post-processing capabilities of GIFTS with Cosmic/NASTRAN's analysis capabilities. The interface operates on a wide range of computers, even linking Cosmic/NASTRAN and GIFTS when the two are on different computers. GIFTS offers a wide range of elements for use in model construction, each translated by the interface into the nearest Cosmic/NASTRAN equivalent; and the options of automatic or interactive modelling and loading in GIFTS make pre-processing easy and effective. The interface itself includes the programs GFTCOS, which creates the Cosmic/NASTRAN input deck (and, if desired, control deck) from the GIFTS Unified Data Base, COSGFT, which translates the displacements from the Cosmic/NASTRAN analysis back into GIFTS; and HOSTR, which handles stress computations for a few higher-order elements available in the interface, but not supported by the GIFTS processor STRESS. Finally, the versatile display options in GIFTS post-processing allow the user to examine the analysis results through an especially wide range of capabilities, including such possibilities as creating composite loading cases, plotting in color and animating the analysis.

Programmable quantum random number generator without postprocessing.

PubMed

Nguyen, Lac; Rehain, Patrick; Sua, Yong Meng; Huang, Yu-Ping

2018-02-15

We demonstrate a viable source of unbiased quantum random numbers whose statistical properties can be arbitrarily programmed without the need for any postprocessing such as randomness distillation or distribution transformation. It is based on measuring the arrival time of single photons in shaped temporal modes that are tailored with an electro-optical modulator. We show that quantum random numbers can be created directly in customized probability distributions and pass all randomness tests of the NIST and Dieharder test suites without any randomness extraction. The min-entropies of such generated random numbers are measured close to the theoretical limits, indicating their near-ideal statistics and ultrahigh purity. Easy to implement and arbitrarily programmable, this technique can find versatile uses in a multitude of data analysis areas.

Quantum cryptography with finite resources: unconditional security bound for discrete-variable protocols with one-way postprocessing.

PubMed

Scarani, Valerio; Renner, Renato

2008-05-23

We derive a bound for the security of quantum key distribution with finite resources under one-way postprocessing, based on a definition of security that is composable and has an operational meaning. While our proof relies on the assumption of collective attacks, unconditional security follows immediately for standard protocols such as Bennett-Brassard 1984 and six-states protocol. For single-qubit implementations of such protocols, we find that the secret key rate becomes positive when at least N approximately 10(5) signals are exchanged and processed. For any other discrete-variable protocol, unconditional security can be obtained using the exponential de Finetti theorem, but the additional overhead leads to very pessimistic estimates.

a Method for Simultaneous Aerial and Terrestrial Geodata Acquisition for Corridor Mapping

NASA Astrophysics Data System (ADS)

Molina, P.; Blázquez, M.; Sastre, J.; Colomina, I.

2015-08-01

In this paper, we present mapKITE, a new mobile, simultaneous terrestrial and aerial, geodata collection and post-processing method. On one side, the method combines a terrestrial mobile mapping system (TMMS) with an unmanned aerial mapping one, both equipped with remote sensing payloads (at least, a nadir-looking visible-band camera in the UA) by means of which aerial and terrestrial geodata are acquired simultaneously. This tandem geodata acquisition system is based on a terrestrial vehicle (TV) and on an unmanned aircraft (UA) linked by a 'virtual tether', that is, a mechanism based on the real-time supply of UA waypoints by the TV. By means of the TV-to-UA tether, the UA follows the TV keeping a specific relative TV-to-UA spatial configuration enabling the simultaneous operation of both systems to obtain highly redundant and complementary geodata. On the other side, mapKITE presents a novel concept for geodata post-processing favoured by the rich geometrical aspects derived from the mapKITE tandem simultaneous operation. The approach followed for sensor orientation and calibration of the aerial images captured by the UA inherits the principles of Integrated Sensor Orientation (ISO) and adds the pointing-and-scaling photogrammetric measurement of a distinctive element observed in every UA image, which is a coded target mounted on the roof of the TV. By means of the TV navigation system, the orientation of the TV coded target is performed and used in the post-processing UA image orientation approach as a Kinematic Ground Control Point (KGCP). The geometric strength of a mapKITE ISO network is therefore high as it counts with the traditional tie point image measurements, static ground control points, kinematic aerial control and the new point-and-scale measurements of the KGCPs. With such a geometry, reliable system and sensor orientation and calibration and eventual further reduction of the number of traditional ground control points is feasible. The different technical concepts, challenges and breakthroughs behind mapKITE are presented in this paper, such as the TV-to-UA virtual tether and the use of KGCP measurements for UA sensor orientation. In addition, the use in mapKITE of new European GNSS signals such as the Galileo E5 AltBOC is discussed. Because of the critical role of GNSS technologies and the potential impact on the corridor mapping market, the European Commission and the European GNSS Agency, in the frame of the European Union Framework Programme for Research and Innovation "Horizon 2020," have recently awarded the "mapKITE" project to an international consortium of organizations coordinated by GeoNumerics S.L.

Pressurized Anneal of Consolidated Powders

NASA Technical Reports Server (NTRS)

Nemir, David Charles (Inventor); Rubio, Edward S. (Inventor); Beck, Jan Bastian (Inventor)

2017-01-01

Systems and methods for producing a dense, well bonded solid material from a powder may include consolidating the powder utilizing any suitable consolidation method, such as explosive shockwave consolidation. The systems and methods may also include a post-processing thermal treatment that exploits a mismatch between the coefficients of thermal expansion between the consolidated material and the container. Due to the mismatch in the coefficients, internal pressure on the consolidated material during the heat treatment may be increased.

Quantitative Characterizations of Ultrashort Echo (UTE) Images for Supporting Air-Bone Separation in the Head

PubMed Central

Hsu, Shu-Hui; Cao, Yue; Lawrence, Theodore S.; Tsien, Christina; Feng, Mary; Grodzki, David M.; Balter, James M.

2015-01-01

Accurate separation of air and bone is critical for creating synthetic CT from MRI to support Radiation Oncology workflow. This study compares two different ultrashort echo-time sequences in the separation of air from bone, and evaluates post-processing methods that correct intensity nonuniformity of images and account for intensity gradients at tissue boundaries to improve this discriminatory power. CT and MRI scans were acquired on 12 patients under an institution review board-approved prospective protocol. The two MRI sequences tested were ultra-short TE imaging using 3D radial acquisition (UTE), and using pointwise encoding time reduction with radial acquisition (PETRA). Gradient nonlinearity correction was applied to both MR image volumes after acquisition. MRI intensity nonuniformity was corrected by vendor-provided normalization methods, and then further corrected using the N4itk algorithm. To overcome the intensity-gradient at air-tissue boundaries, spatial dilations, from 0 to 4 mm, were applied to threshold-defined air regions from MR images. Receiver operating characteristic (ROC) analyses, by comparing predicted (defined by MR images) versus “true” regions of air and bone (defined by CT images), were performed with and without residual bias field correction and local spatial expansion. The post-processing corrections increased the areas under the ROC curves (AUC) from 0.944 ± 0.012 to 0.976 ± 0.003 for UTE images, and from 0.850 ± 0.022 to 0.887 ± 0.012 for PETRA images, compared to without corrections. When expanding the threshold-defined air volumes, as expected, sensitivity of air identification decreased with an increase in specificity of bone discrimination, but in a non-linear fashion. A 1-mm air mask expansion yielded AUC increases of 1% and 4% for UTE and PETRA images, respectively. UTE images had significantly greater discriminatory power in separating air from bone than PETRA images. Post-processing strategies improved the discriminatory power of air from bone for both UTE and PETRA images, and reduced the difference between the two imaging sequences. Both postprocessed UTE and PETRA images demonstrated sufficient power to discriminate air from bone to support synthetic CT generation from MRI data. PMID:25776205

Stereo matching and view interpolation based on image domain triangulation.

PubMed

Fickel, Guilherme Pinto; Jung, Claudio R; Malzbender, Tom; Samadani, Ramin; Culbertson, Bruce

2013-09-01

This paper presents a new approach for stereo matching and view interpolation problems based on triangular tessellations suitable for a linear array of rectified cameras. The domain of the reference image is initially partitioned into triangular regions using edge and scale information, aiming to place vertices along image edges and increase the number of triangles in textured regions. A region-based matching algorithm is then used to find an initial disparity for each triangle, and a refinement stage is applied to change the disparity at the vertices of the triangles, generating a piecewise linear disparity map. A simple post-processing procedure is applied to connect triangles with similar disparities generating a full 3D mesh related to each camera (view), which are used to generate new synthesized views along the linear camera array. With the proposed framework, view interpolation reduces to the trivial task of rendering polygonal meshes, which can be done very fast, particularly when GPUs are employed. Furthermore, the generated views are hole-free, unlike most point-based view interpolation schemes that require some kind of post-processing procedures to fill holes.

Analysis of Waveform Retracking Methods in Antarctic Ice Sheet Based on CRYOSAT-2 Data

NASA Astrophysics Data System (ADS)

Xiao, F.; Li, F.; Zhang, S.; Hao, W.; Yuan, L.; Zhu, T.; Zhang, Y.; Zhu, C.

2017-09-01

Satellite altimetry plays an important role in many geoscientific and environmental studies of Antarctic ice sheet. The ranging accuracy is degenerated near coasts or over nonocean surfaces, due to waveform contamination. A postprocess technique, known as waveform retracking, can be used to retrack the corrupt waveform and in turn improve the ranging accuracy. In 2010, the CryoSat-2 satellite was launched with the Synthetic aperture Interferometric Radar ALtimeter (SIRAL) onboard. Satellite altimetry waveform retracking methods are discussed in the paper. Six retracking methods including the OCOG method, the threshold method with 10 %, 25 % and 50 % threshold level, the linear and exponential 5-β parametric methods are used to retrack CryoSat-2 waveform over the transect from Zhongshan Station to Dome A. The results show that the threshold retracker performs best with the consideration of waveform retracking success rate and RMS of retracking distance corrections. The linear 5-β parametric retracker gives best waveform retracking precision, but cannot make full use of the waveform data.

Making data matter: Voxel printing for the digital fabrication of data across scales and domains.

PubMed

Bader, Christoph; Kolb, Dominik; Weaver, James C; Sharma, Sunanda; Hosny, Ahmed; Costa, João; Oxman, Neri

2018-05-01

We present a multimaterial voxel-printing method that enables the physical visualization of data sets commonly associated with scientific imaging. Leveraging voxel-based control of multimaterial three-dimensional (3D) printing, our method enables additive manufacturing of discontinuous data types such as point cloud data, curve and graph data, image-based data, and volumetric data. By converting data sets into dithered material deposition descriptions, through modifications to rasterization processes, we demonstrate that data sets frequently visualized on screen can be converted into physical, materially heterogeneous objects. Our approach alleviates the need to postprocess data sets to boundary representations, preventing alteration of data and loss of information in the produced physicalizations. Therefore, it bridges the gap between digital information representation and physical material composition. We evaluate the visual characteristics and features of our method, assess its relevance and applicability in the production of physical visualizations, and detail the conversion of data sets for multimaterial 3D printing. We conclude with exemplary 3D-printed data sets produced by our method pointing toward potential applications across scales, disciplines, and problem domains.

Weighted Mean of Signal Intensity for Unbiased Fiber Tracking of Skeletal Muscles: Development of a New Method and Comparison With Other Correction Techniques.

PubMed

Giraudo, Chiara; Motyka, Stanislav; Weber, Michael; Resinger, Christoph; Thorsten, Feiweier; Traxler, Hannes; Trattnig, Siegfried; Bogner, Wolfgang

2017-08-01

The aim of this study was to investigate the origin of random image artifacts in stimulated echo acquisition mode diffusion tensor imaging (STEAM-DTI), assess the role of averaging, develop an automated artifact postprocessing correction method using weighted mean of signal intensities (WMSIs), and compare it with other correction techniques. Institutional review board approval and written informed consent were obtained. The right calf and thigh of 10 volunteers were scanned on a 3 T magnetic resonance imaging scanner using a STEAM-DTI sequence.Artifacts (ie, signal loss) in STEAM-based DTI, presumably caused by involuntary muscle contractions, were investigated in volunteers and ex vivo (ie, human cadaver calf and turkey leg using the same DTI parameters as for the volunteers). An automated postprocessing artifact correction method based on the WMSI was developed and compared with previous approaches (ie, iteratively reweighted linear least squares and informed robust estimation of tensors by outlier rejection [iRESTORE]). Diffusion tensor imaging and fiber tracking metrics, using different averages and artifact corrections, were compared for region of interest- and mask-based analyses. One-way repeated measures analysis of variance with Greenhouse-Geisser correction and Bonferroni post hoc tests were used to evaluate differences among all tested conditions. Qualitative assessment (ie, images quality) for native and corrected images was performed using the paired t test. Randomly localized and shaped artifacts affected all volunteer data sets. Artifact burden during voluntary muscle contractions increased on average from 23.1% to 77.5% but were absent ex vivo. Diffusion tensor imaging metrics (mean diffusivity, fractional anisotropy, radial diffusivity, and axial diffusivity) had a heterogeneous behavior, but in the range reported by literature. Fiber track metrics (number, length, and volume) significantly improved in both calves and thighs after artifact correction in region of interest- and mask-based analyses (P < 0.05 each). Iteratively reweighted linear least squares and iRESTORE showed equivalent results, but WMSI was faster than iRESTORE. Muscle delineation and artifact load significantly improved after correction (P < 0.05 each). Weighted mean of signal intensity correction significantly improved STEAM-based quantitative DTI analyses and fiber tracking of lower-limb muscles, providing a robust tool for musculoskeletal applications.

Diagnostic Value of Multidetector CT and Its Multiplanar Reformation, Volume Rendering and Virtual Bronchoscopy Postprocessing Techniques for Primary Trachea and Main Bronchus Tumors

PubMed Central

Luo, Mingyue; Duan, Chaijie; Qiu, Jianping; Li, Wenru; Zhu, Dongyun; Cai, Wenli

2015-01-01

Purpose To evaluate the diagnostic value of multidetector CT (MDCT) and its multiplanar reformation (MPR), volume rendering (VR) and virtual bronchoscopy (VB) postprocessing techniques for primary trachea and main bronchus tumors. Methods Detection results of 31 primary trachea and main bronchus tumors with MDCT and its MPR, VR and VB postprocessing techniques, were analyzed retrospectively with regard to tumor locations, tumor morphologies, extramural invasions of tumors, longitudinal involvements of tumors, morphologies and extents of luminal stenoses, distances between main bronchus tumors and trachea carinae, and internal features of tumors. The detection results were compared with that of surgery and pathology. Results Detection results with MDCT and its MPR, VR and VB were consistent with that of surgery and pathology, included tumor locations (tracheae, n = 19; right main bronchi, n = 6; left main bronchi, n = 6), tumor morphologies (endoluminal nodes with narrow bases, n = 2; endoluminal nodes with wide bases, n = 13; both intraluminal and extraluminal masses, n = 16), extramural invasions of tumors (brokethrough only serous membrane, n = 1; 4.0 mm—56.0 mm, n = 14; no clear border with right atelectasis, n = 1), longitudinal involvements of tumors (3.0 mm, n = 1; 5.0 mm—68.0 mm, n = 29; whole right main bronchus wall and trachea carina, n = 1), morphologies of luminal stenoses (irregular, n = 26; circular, n = 3; eccentric, n = 1; conical, n = 1) and extents (mild, n = 5; moderate, n = 7; severe, n = 19), distances between main bronchus tumors and trachea carinae (16.0 mm, n = 1; invaded trachea carina, n = 1; >20.0 mm, n = 10), and internal features of tumors (fairly homogeneous densities with rather obvious enhancements, n = 26; homogeneous density with obvious enhancement, n = 1; homogeneous density without obvious enhancement, n = 1; not enough homogeneous density with obvious enhancement, n = 1; punctate calcification with obvious enhancement, n = 1; low density without obvious enhancement, n = 1). Conclusion MDCT and its MPR, VR and VB images have respective advantages and disadvantages. Their combination could complement to each other to accurately detect locations, natures (benignancy, malignancy or low malignancy), and quantities (extramural invasions, longitudinal involvements, extents of luminal stenoses, distances between main bronchus tumors and trachea carinae) of primary trachea and main bronchus tumors with crucial information for surgical treatment, are highly useful diagnostic methods for primary trachea and main bronchus tumors. PMID:26332466

Proof-of-principle experimental realization of a qubit-like qudit-based quantum key distribution scheme

NASA Astrophysics Data System (ADS)

Wang, Shuang; Yin, Zhen-Qiang; Chau, H. F.; Chen, Wei; Wang, Chao; Guo, Guang-Can; Han, Zheng-Fu

2018-04-01

In comparison to qubit-based protocols, qudit-based quantum key distribution ones generally allow two cooperative parties to share unconditionally secure keys under a higher channel noise. However, it is very hard to prepare and measure the required quantum states in qudit-based protocols in general. One exception is the recently proposed highly error tolerant qudit-based protocol known as the Chau15 (Chau 2015 Phys. Rev. A 92 062324). Remarkably, the state preparation and measurement in this protocol can be done relatively easily since the required states are phase encoded almost like the diagonal basis states of a qubit. Here we report the first proof-of-principle demonstration of the Chau15 protocol. One highlight of our experiment is that its post-processing is based on practical one-way manner, while the original proposal in Chau (2015 Phys. Rev. A 92 062324) relies on complicated two-way post-processing, which is a great challenge in experiment. In addition, by manipulating time-bin qudit and measurement with a variable delay interferometer, our realization is extensible to qudit with high-dimensionality and confirms the experimental feasibility of the Chau15 protocol.

Analog-Based Postprocessing of Navigation-Related Hydrological Ensemble Forecasts

NASA Astrophysics Data System (ADS)

Hemri, S.; Klein, B.

2017-11-01

Inland waterway transport benefits from probabilistic forecasts of water levels as they allow to optimize the ship load and, hence, to minimize the transport costs. Probabilistic state-of-the-art hydrologic ensemble forecasts inherit biases and dispersion errors from the atmospheric ensemble forecasts they are driven with. The use of statistical postprocessing techniques like ensemble model output statistics (EMOS) allows for a reduction of these systematic errors by fitting a statistical model based on training data. In this study, training periods for EMOS are selected based on forecast analogs, i.e., historical forecasts that are similar to the forecast to be verified. Due to the strong autocorrelation of water levels, forecast analogs have to be selected based on entire forecast hydrographs in order to guarantee similar hydrograph shapes. Custom-tailored measures of similarity for forecast hydrographs comprise hydrological series distance (SD), the hydrological matching algorithm (HMA), and dynamic time warping (DTW). Verification against observations reveals that EMOS forecasts for water level at three gauges along the river Rhine with training periods selected based on SD, HMA, and DTW compare favorably with reference EMOS forecasts, which are based on either seasonal training periods or on training periods obtained by dividing the hydrological forecast trajectories into runoff regimes.

Postprocessing classification images

NASA Technical Reports Server (NTRS)

Kan, E. P.

1979-01-01

Program cleans up remote-sensing maps. It can be used with existing image-processing software. Remapped images closely resemble familiar resource information maps and can replace or supplement classification images not postprocessed by this program.

Improved quantification for local regions of interest in preclinical PET imaging

NASA Astrophysics Data System (ADS)

Cal-González, J.; Moore, S. C.; Park, M.-A.; Herraiz, J. L.; Vaquero, J. J.; Desco, M.; Udias, J. M.

2015-09-01

In Positron Emission Tomography, there are several causes of quantitative inaccuracy, such as partial volume or spillover effects. The impact of these effects is greater when using radionuclides that have a large positron range, e.g. 68Ga and 124I, which have been increasingly used in the clinic. We have implemented and evaluated a local projection algorithm (LPA), originally evaluated for SPECT, to compensate for both partial-volume and spillover effects in PET. This method is based on the use of a high-resolution CT or MR image, co-registered with a PET image, which permits a high-resolution segmentation of a few tissues within a volume of interest (VOI) centered on a region within which tissue-activity values need to be estimated. The additional boundary information is used to obtain improved activity estimates for each tissue within the VOI, by solving a simple inversion problem. We implemented this algorithm for the preclinical Argus PET/CT scanner and assessed its performance using the radionuclides 18F, 68Ga and 124I. We also evaluated and compared the results obtained when it was applied during the iterative reconstruction, as well as after the reconstruction as a postprocessing procedure. In addition, we studied how LPA can help to reduce the ‘spillover contamination’, which causes inaccurate quantification of lesions in the immediate neighborhood of large, ‘hot’ sources. Quantification was significantly improved by using LPA, which provided more accurate ratios of lesion-to-background activity concentration for hot and cold regions. For 18F, the contrast was improved from 3.0 to 4.0 in hot lesions (when the true ratio was 4.0) and from 0.16 to 0.06 in cold lesions (true ratio  =  0.0), when using the LPA postprocessing. Furthermore, activity values estimated within the VOI using LPA during reconstruction were slightly more accurate than those obtained by post-processing, while also visually improving the image contrast and uniformity within the VOI.

Improved quantification for local regions of interest in preclinical PET imaging

PubMed Central

Cal-González, J.; Moore, S. C.; Park, M.-A.; Herraiz, J. L.; Vaquero, J. J.; Desco, M.; Udias, J. M.

2015-01-01

In Positron Emission Tomography, there are several causes of quantitative inaccuracy, such as partial volume or spillover effects. The impact of these effects is greater when using radionuclides that have a large positron range, e.g., 68Ga and 124I, which have been increasingly used in the clinic. We have implemented and evaluated a local projection algorithm (LPA), originally evaluated for SPECT, to compensate for both partial-volume and spillover effects in PET. This method is based on the use of a high-resolution CT or MR image, co-registered with a PET image, which permits a high-resolution segmentation of a few tissues within a volume of interest (VOI) centered on a region within which tissue-activity values need to be estimated. The additional boundary information is used to obtain improved activity estimates for each tissue within the VOI, by solving a simple inversion problem. We implemented this algorithm for the preclinical Argus PET/CT scanner and assessed its performance using the radionuclides 18F, 68Ga and 124I. We also evaluated and compared the results obtained when it was applied during the iterative reconstruction, as well as after the reconstruction as a postprocessing procedure. In addition, we studied how LPA can help to reduce the “spillover contamination”, which causes inaccurate quantification of lesions in the immediate neighborhood of large, “hot” sources. Quantification was significantly improved by using LPA, which provided more accurate ratios of lesion-to-background activity concentration for hot and cold regions. For 18F, the contrast was improved from 3.0 to 4.0 in hot lesions (when the true ratio was 4.0) and from 0.16 to 0.06 in cold lesions (true ratio = 0.0), when using the LPA postprocessing. Furthermore, activity values estimated within the VOI using LPA during reconstruction were slightly more accurate than those obtained by post-processing, while also visually improving the image contrast and uniformity within the VOI. PMID:26334312

High temperature, short time pasteurization temperatures inversely affect bacterial numbers during refrigerated storage of pasteurized fluid milk.

PubMed

Ranieri, M L; Huck, J R; Sonnen, M; Barbano, D M; Boor, K J

2009-10-01

The grade A Pasteurized Milk Ordinance specifies minimum processing conditions of 72 degrees C for at least 15 s for high temperature, short time (HTST) pasteurized milk products. Currently, many US milk-processing plants exceed these minimum requirements for fluid milk products. To test the effect of pasteurization temperatures on bacterial numbers in HTST pasteurized milk, 2% fat raw milk was heated to 60 degrees C, homogenized, and treated for 25 s at 1 of 4 different temperatures (72.9, 77.2, 79.9, or 85.2 degrees C) and then held at 6 degrees C for 21 d. Aerobic plate counts were monitored in pasteurized milk samples at d 1, 7, 14, and 21 postprocessing. Bacterial numbers in milk processed at 72.9 degrees C were lower than in milk processed at 85.2 degrees C on each sampling day, indicating that HTST fluid milk-processing temperatures significantly affected bacterial numbers in fluid milk. To assess the microbial ecology of the different milk samples during refrigerated storage, a total of 490 psychrotolerant endospore-forming bacteria were identified using DNA sequence-based subtyping methods. Regardless of processing temperature, >85% of the isolates characterized at d 0, 1, and 7 postprocessing were of the genus Bacillus, whereas more than 92% of isolates characterized at d 14 and 21 postprocessing were of the genus Paenibacillus, indicating that the predominant genera present in HTST-processed milk shifted from Bacillus spp. to Paenibacillus spp. during refrigerated storage. In summary, 1) HTST processing temperatures affected bacterial numbers in refrigerated milk, with higher bacterial numbers in milk processed at higher temperatures; 2) no significant association was observed between genus isolated and pasteurization temperature, suggesting that the genera were not differentially affected by the different processing temperatures; and 3) although typically present at low numbers in raw milk, Paenibacillus spp. are capable of growing to numbers that can exceed Pasteurized Milk Ordinance limits in pasteurized, refrigerated milk.

Eighteenth NASTRAN (R) Users' Colloquium

NASA Technical Reports Server (NTRS)

1990-01-01

This publication is the proceedings of the Eighteenth NASTRAN Users' Colloquium held in Portland, Oregon, April 23-27, 1990. It provides some comprehensive general papers on the application of finite elements in engineering, comparisons with other approaches, unique applications, pre- and post-processing or auxiliary programs, and new methods of analysis with NASTRAN.

Semantic image segmentation with fused CNN features

NASA Astrophysics Data System (ADS)

Geng, Hui-qiang; Zhang, Hua; Xue, Yan-bing; Zhou, Mian; Xu, Guang-ping; Gao, Zan

2017-09-01

Semantic image segmentation is a task to predict a category label for every image pixel. The key challenge of it is to design a strong feature representation. In this paper, we fuse the hierarchical convolutional neural network (CNN) features and the region-based features as the feature representation. The hierarchical features contain more global information, while the region-based features contain more local information. The combination of these two kinds of features significantly enhances the feature representation. Then the fused features are used to train a softmax classifier to produce per-pixel label assignment probability. And a fully connected conditional random field (CRF) is used as a post-processing method to improve the labeling consistency. We conduct experiments on SIFT flow dataset. The pixel accuracy and class accuracy are 84.4% and 34.86%, respectively.

Googling DNA sequences on the World Wide Web.

PubMed

Hajibabaei, Mehrdad; Singer, Gregory A C

2009-11-10

New web-based technologies provide an excellent opportunity for sharing and accessing information and using web as a platform for interaction and collaboration. Although several specialized tools are available for analyzing DNA sequence information, conventional web-based tools have not been utilized for bioinformatics applications. We have developed a novel algorithm and implemented it for searching species-specific genomic sequences, DNA barcodes, by using popular web-based methods such as Google. We developed an alignment independent character based algorithm based on dividing a sequence library (DNA barcodes) and query sequence to words. The actual search is conducted by conventional search tools such as freely available Google Desktop Search. We implemented our algorithm in two exemplar packages. We developed pre and post-processing software to provide customized input and output services, respectively. Our analysis of all publicly available DNA barcode sequences shows a high accuracy as well as rapid results. Our method makes use of conventional web-based technologies for specialized genetic data. It provides a robust and efficient solution for sequence search on the web. The integration of our search method for large-scale sequence libraries such as DNA barcodes provides an excellent web-based tool for accessing this information and linking it to other available categories of information on the web.

Developing a semi/automated protocol to post-process large volume, High-resolution airborne thermal infrared (TIR) imagery for urban waste heat mapping

NASA Astrophysics Data System (ADS)

Rahman, Mir Mustafizur

In collaboration with The City of Calgary 2011 Sustainability Direction and as part of the HEAT (Heat Energy Assessment Technologies) project, the focus of this research is to develop a semi/automated 'protocol' to post-process large volumes of high-resolution (H-res) airborne thermal infrared (TIR) imagery to enable accurate urban waste heat mapping. HEAT is a free GeoWeb service, designed to help Calgary residents improve their home energy efficiency by visualizing the amount and location of waste heat leaving their homes and communities, as easily as clicking on their house in Google Maps. HEAT metrics are derived from 43 flight lines of TABI-1800 (Thermal Airborne Broadband Imager) data acquired on May 13--14, 2012 at night (11:00 pm--5:00 am) over The City of Calgary, Alberta (˜825 km 2) at a 50 cm spatial resolution and 0.05°C thermal resolution. At present, the only way to generate a large area, high-spatial resolution TIR scene is to acquire separate airborne flight lines and mosaic them together. However, the ambient sensed temperature within, and between flight lines naturally changes during acquisition (due to varying atmospheric and local micro-climate conditions), resulting in mosaicked images with different temperatures for the same scene components (e.g. roads, buildings), and mosaic join-lines arbitrarily bisect many thousands of homes. In combination these effects result in reduced utility and classification accuracy including, poorly defined HEAT Metrics, inaccurate hotspot detection and raw imagery that are difficult to interpret. In an effort to minimize these effects, three new semi/automated post-processing algorithms (the protocol) are described, which are then used to generate a 43 flight line mosaic of TABI-1800 data from which accurate Calgary waste heat maps and HEAT metrics can be generated. These algorithms (presented as four peer-reviewed papers)---are: (a) Thermal Urban Road Normalization (TURN)---used to mitigate the microclimatic variability within a thermal flight line based on varying road temperatures; (b) Automated Polynomial Relative Radiometric Normalization (RRN)---which mitigates the between flight line radiometric variability; and (c) Object Based Mosaicking (OBM)---which minimizes the geometric distortion along the mosaic edge between each flight line. A modified Emissivity Modulation technique is also described to correct H-res TIR images for emissivity. This combined radiometric and geometric post-processing protocol (i) increases the visual agreement between TABI-1800 flight lines, (ii) improves radiometric agreement within/between flight lines, (iii) produces a visually seamless mosaic, (iv) improves hot-spot detection and landcover classification accuracy, and (v) provides accurate data for thermal-based HEAT energy models. Keywords: Thermal Infrared, Post-Processing, High Spatial Resolution, Airborne, Thermal Urban Road Normalization (TURN), Relative Radiometric Normalization (RRN), Object Based Mosaicking (OBM), TABI-1800, HEAT, and Automation.

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.

Tools to Develop or Convert MOVES Inputs

EPA Pesticide Factsheets

The following tools are designed to help users develop inputs to MOVES and post-process the output. With the release of MOVES2014, EPA strongly encourages state and local agencies to develop local inputs based on MOVES fleet and activity categories.

Evaluating the convergence between eddy-covariance and biometric methods for assessing carbon budgets of forests.

PubMed

Campioli, M; Malhi, Y; Vicca, S; Luyssaert, S; Papale, D; Peñuelas, J; Reichstein, M; Migliavacca, M; Arain, M A; Janssens, I A

2016-12-14

The eddy-covariance (EC) micro-meteorological technique and the ecology-based biometric methods (BM) are the primary methodologies to quantify CO 2 exchange between terrestrial ecosystems and the atmosphere (net ecosystem production, NEP) and its two components, ecosystem respiration and gross primary production. Here we show that EC and BM provide different estimates of NEP, but comparable ecosystem respiration and gross primary production for forest ecosystems globally. Discrepancies between methods are not related to environmental or stand variables, but are consistently more pronounced for boreal forests where carbon fluxes are smaller. BM estimates are prone to underestimation of net primary production and overestimation of leaf respiration. EC biases are not apparent across sites, suggesting the effectiveness of standard post-processing procedures. Our results increase confidence in EC, show in which conditions EC and BM estimates can be integrated, and which methodological aspects can improve the convergence between EC and BM.

Evaluating the convergence between eddy-covariance and biometric methods for assessing carbon budgets of forests

NASA Astrophysics Data System (ADS)

Campioli, M.; Malhi, Y.; Vicca, S.; Luyssaert, S.; Papale, D.; Peñuelas, J.; Reichstein, M.; Migliavacca, M.; Arain, M. A.; Janssens, I. A.

2016-12-01

The eddy-covariance (EC) micro-meteorological technique and the ecology-based biometric methods (BM) are the primary methodologies to quantify CO2 exchange between terrestrial ecosystems and the atmosphere (net ecosystem production, NEP) and its two components, ecosystem respiration and gross primary production. Here we show that EC and BM provide different estimates of NEP, but comparable ecosystem respiration and gross primary production for forest ecosystems globally. Discrepancies between methods are not related to environmental or stand variables, but are consistently more pronounced for boreal forests where carbon fluxes are smaller. BM estimates are prone to underestimation of net primary production and overestimation of leaf respiration. EC biases are not apparent across sites, suggesting the effectiveness of standard post-processing procedures. Our results increase confidence in EC, show in which conditions EC and BM estimates can be integrated, and which methodological aspects can improve the convergence between EC and BM.

Evaluating the convergence between eddy-covariance and biometric methods for assessing carbon budgets of forests

PubMed Central

Campioli, M.; Malhi, Y.; Vicca, S.; Luyssaert, S.; Papale, D.; Peñuelas, J.; Reichstein, M.; Migliavacca, M.; Arain, M. A.; Janssens, I. A.

2016-01-01

The eddy-covariance (EC) micro-meteorological technique and the ecology-based biometric methods (BM) are the primary methodologies to quantify CO2 exchange between terrestrial ecosystems and the atmosphere (net ecosystem production, NEP) and its two components, ecosystem respiration and gross primary production. Here we show that EC and BM provide different estimates of NEP, but comparable ecosystem respiration and gross primary production for forest ecosystems globally. Discrepancies between methods are not related to environmental or stand variables, but are consistently more pronounced for boreal forests where carbon fluxes are smaller. BM estimates are prone to underestimation of net primary production and overestimation of leaf respiration. EC biases are not apparent across sites, suggesting the effectiveness of standard post-processing procedures. Our results increase confidence in EC, show in which conditions EC and BM estimates can be integrated, and which methodological aspects can improve the convergence between EC and BM. PMID:27966534

Simultaneous calibration of ensemble river flow predictions over an entire range of lead times

NASA Astrophysics Data System (ADS)

Hemri, S.; Fundel, F.; Zappa, M.

2013-10-01

Probabilistic estimates of future water levels and river discharge are usually simulated with hydrologic models using ensemble weather forecasts as main inputs. As hydrologic models are imperfect and the meteorological ensembles tend to be biased and underdispersed, the ensemble forecasts for river runoff typically are biased and underdispersed, too. Thus, in order to achieve both reliable and sharp predictions statistical postprocessing is required. In this work Bayesian model averaging (BMA) is applied to statistically postprocess ensemble runoff raw forecasts for a catchment in Switzerland, at lead times ranging from 1 to 240 h. The raw forecasts have been obtained using deterministic and ensemble forcing meteorological models with different forecast lead time ranges. First, BMA is applied based on mixtures of univariate normal distributions, subject to the assumption of independence between distinct lead times. Then, the independence assumption is relaxed in order to estimate multivariate runoff forecasts over the entire range of lead times simultaneously, based on a BMA version that uses multivariate normal distributions. Since river runoff is a highly skewed variable, Box-Cox transformations are applied in order to achieve approximate normality. Both univariate and multivariate BMA approaches are able to generate well calibrated probabilistic forecasts that are considerably sharper than climatological forecasts. Additionally, multivariate BMA provides a promising approach for incorporating temporal dependencies into the postprocessed forecasts. Its major advantage against univariate BMA is an increase in reliability when the forecast system is changing due to model availability.

Radar signal pre-processing to suppress surface bounce and multipath

DOEpatents

Paglieroni, David W; Mast, Jeffrey E; Beer, N. Reginald

2013-12-31

A method and system for detecting the presence of subsurface objects within a medium is provided. In some embodiments, the imaging and detection system operates in a multistatic mode to collect radar return signals generated by an array of transceiver antenna pairs that is positioned across the surface and that travels down the surface. The imaging and detection system pre-processes that return signal to suppress certain undesirable effects. The imaging and detection system then generates synthetic aperture radar images from real aperture radar images generated from the pre-processed return signal. The imaging and detection system then post-processes the synthetic aperture radar images to improve detection of subsurface objects. The imaging and detection system identifies peaks in the energy levels of the post-processed image frame, which indicates the presence of a subsurface object.

Spatially adaptive migration tomography for multistatic GPR imaging

DOEpatents

Paglieroni, David W; Beer, N. Reginald

2013-08-13

A method and system for detecting the presence of subsurface objects within a medium is provided. In some embodiments, the imaging and detection system operates in a multistatic mode to collect radar return signals generated by an array of transceiver antenna pairs that is positioned across the surface and that travels down the surface. The imaging and detection system pre-processes the return signal to suppress certain undesirable effects. The imaging and detection system then generates synthetic aperture radar images from real aperture radar images generated from the pre-processed return signal. The imaging and detection system then post-processes the synthetic aperture radar images to improve detection of subsurface objects. The imaging and detection system identifies peaks in the energy levels of the post-processed image frame, which indicates the presence of a subsurface object.

Synthetic aperture integration (SAI) algorithm for SAR imaging

DOEpatents

Chambers, David H; Mast, Jeffrey E; Paglieroni, David W; Beer, N. Reginald

2013-07-09

A method and system for detecting the presence of subsurface objects within a medium is provided. In some embodiments, the imaging and detection system operates in a multistatic mode to collect radar return signals generated by an array of transceiver antenna pairs that is positioned across the surface and that travels down the surface. The imaging and detection system pre-processes the return signal to suppress certain undesirable effects. The imaging and detection system then generates synthetic aperture radar images from real aperture radar images generated from the pre-processed return signal. The imaging and detection system then post-processes the synthetic aperture radar images to improve detection of subsurface objects. The imaging and detection system identifies peaks in the energy levels of the post-processed image frame, which indicates the presence of a subsurface object.

Zero source insertion technique to account for undersampling in GPR imaging

DOEpatents

Chambers, David H; Mast, Jeffrey E; Paglieroni, David W

2014-02-25

A method and system for detecting the presence of subsurface objects within a medium is provided. In some embodiments, the imaging and detection system operates in a multistatic mode to collect radar return signals generated by an array of transceiver antenna pairs that is positioned across the surface and that travels down the surface. The imaging and detection system pre-processes the return signal to suppress certain undesirable effects. The imaging and detection system then generates synthetic aperture radar images from real aperture radar images generated from the pre-processed return signal. The imaging and detection system then post-processes the synthetic aperture radar images to improve detection of subsurface objects. The imaging and detection system identifies peaks in the energy levels of the post-processed image frame, which indicates the presence of a subsurface object.

Real-time system for imaging and object detection with a multistatic GPR array

DOEpatents

Paglieroni, David W; Beer, N Reginald; Bond, Steven W; Top, Philip L; Chambers, David H; Mast, Jeffrey E; Donetti, John G; Mason, Blake C; Jones, Steven M

2014-10-07

A method and system for detecting the presence of subsurface objects within a medium is provided. In some embodiments, the imaging and detection system operates in a multistatic mode to collect radar return signals generated by an array of transceiver antenna pairs that is positioned across the surface and that travels down the surface. The imaging and detection system pre-processes the return signal to suppress certain undesirable effects. The imaging and detection system then generates synthetic aperture radar images from real aperture radar images generated from the pre-processed return signal. The imaging and detection system then post-processes the synthetic aperture radar images to improve detection of subsurface objects. The imaging and detection system identifies peaks in the energy levels of the post-processed image frame, which indicates the presence of a subsurface object.

Automatic segmentation of coronary arteries from computed tomography angiography data cloud using optimal thresholding

NASA Astrophysics Data System (ADS)

Ansari, Muhammad Ahsan; Zai, Sammer; Moon, Young Shik

2017-01-01

Manual analysis of the bulk data generated by computed tomography angiography (CTA) is time consuming, and interpretation of such data requires previous knowledge and expertise of the radiologist. Therefore, an automatic method that can isolate the coronary arteries from a given CTA dataset is required. We present an automatic yet effective segmentation method to delineate the coronary arteries from a three-dimensional CTA data cloud. Instead of a region growing process, which is usually time consuming and prone to leakages, the method is based on the optimal thresholding, which is applied globally on the Hessian-based vesselness measure in a localized way (slice by slice) to track the coronaries carefully to their distal ends. Moreover, to make the process automatic, we detect the aorta using the Hough transform technique. The proposed segmentation method is independent of the starting point to initiate its process and is fast in the sense that coronary arteries are obtained without any preprocessing or postprocessing steps. We used 12 real clinical datasets to show the efficiency and accuracy of the presented method. Experimental results reveal that the proposed method achieves 95% average accuracy.

Catchment virtual observatory for sharing flow and transport models outputs: using residence time distribution to compare contrasting catchments

NASA Astrophysics Data System (ADS)

Thomas, Zahra; Rousseau-Gueutin, Pauline; Kolbe, Tamara; Abbott, Ben; Marcais, Jean; Peiffer, Stefan; Frei, Sven; Bishop, Kevin; Le Henaff, Geneviève; Squividant, Hervé; Pichelin, Pascal; Pinay, Gilles; de Dreuzy, Jean-Raynald

2017-04-01

The distribution of groundwater residence time in a catchment provides synoptic information about catchment functioning (e.g. nutrient retention and removal, hydrograph flashiness). In contrast with interpreted model results, which are often not directly comparable between studies, residence time distribution is a general output that could be used to compare catchment behaviors and test hypotheses about landscape controls on catchment functioning. In this goal, we created a virtual observatory platform called Catchment Virtual Observatory for Sharing Flow and Transport Model Outputs (COnSOrT). The main goal of COnSOrT is to collect outputs from calibrated groundwater models from a wide range of environments. By comparing a wide variety of catchments from different climatic, topographic and hydrogeological contexts, we expect to enhance understanding of catchment connectivity, resilience to anthropogenic disturbance, and overall functioning. The web-based observatory will also provide software tools to analyze model outputs. The observatory will enable modelers to test their models in a wide range of catchment environments to evaluate the generality of their findings and robustness of their post-processing methods. Researchers with calibrated numerical models can benefit from observatory by using the post-processing methods to implement a new approach to analyzing their data. Field scientists interested in contributing data could invite modelers associated with the observatory to test their models against observed catchment behavior. COnSOrT will allow meta-analyses with community contributions to generate new understanding and identify promising pathways forward to moving beyond single catchment ecohydrology. Keywords: Residence time distribution, Models outputs, Catchment hydrology, Inter-catchment comparison

A locally conservative stabilized continuous Galerkin finite element method for two-phase flow in poroelastic subsurfaces

NASA Astrophysics Data System (ADS)

Deng, Q.; Ginting, V.; McCaskill, B.; Torsu, P.

2017-10-01

We study the application of a stabilized continuous Galerkin finite element method (CGFEM) in the simulation of multiphase flow in poroelastic subsurfaces. The system involves a nonlinear coupling between the fluid pressure, subsurface's deformation, and the fluid phase saturation, and as such, we represent this coupling through an iterative procedure. Spatial discretization of the poroelastic system employs the standard linear finite element in combination with a numerical diffusion term to maintain stability of the algebraic system. Furthermore, direct calculation of the normal velocities from pressure and deformation does not entail a locally conservative field. To alleviate this drawback, we propose an element based post-processing technique through which local conservation can be established. The performance of the method is validated through several examples illustrating the convergence of the method, the effectivity of the stabilization term, and the ability to achieve locally conservative normal velocities. Finally, the efficacy of the method is demonstrated through simulations of realistic multiphase flow in poroelastic subsurfaces.

A Fast Radio Burst Search Method for VLBI Observation

NASA Astrophysics Data System (ADS)

Liu, Lei; Tong, Fengxian; Zheng, Weimin; Zhang, Juan; Tong, Li

2018-02-01

We introduce the cross-spectrum-based fast radio burst (FRB) search method for Very Long Baseline Interferometer (VLBI) observation. This method optimizes the fringe fitting scheme in geodetic VLBI data post-processing, which fully utilizes the cross-spectrum fringe phase information and therefore maximizes the power of single-pulse signals. Working with cross-spectrum greatly reduces the effect of radio frequency interference compared with using auto-power spectrum. Single-pulse detection confidence increases by cross-identifying detections from multiple baselines. By combining the power of multiple baselines, we may improve the detection sensitivity. Our method is similar to that of coherent beam forming, but without the computational expense to form a great number of beams to cover the whole field of view of our telescopes. The data processing pipeline designed for this method is easy to implement and parallelize, which can be deployed in various kinds of VLBI observations. In particular, we point out that VGOS observations are very suitable for FRB search.

To acquire more detailed radiation drive by use of ``quasi-steady'' approximation in atomic kinetics

NASA Astrophysics Data System (ADS)

Ren, Guoli; Pei, Wenbing; Lan, Ke; Gu, Peijun; Li, Xin

2012-10-01

In current routine 2D simulation of hohlraum physics, we adopt the principal-quantum- number(n-level) average atom model(AAM) in NLTE plasma description. However, the detailed experimental frequency-dependant radiative drive differs from our n-level simulated drive, which reminds us the need of a more detailed atomic kinetics description. The orbital-quantum- number(nl-level) average atom model is a natural consideration, however the nl-level in-line calculation needs much more computational resource. By distinguishing the rapid bound-bound atomic processes from the relative slow bound-free atomic processes, we found a method to build up a more detailed bound electron distribution(nl-level even nlm-level) using in-line n-level calculated plasma conditions(temperature, density, and average ionization degree). We name this method ``quasi-steady approximation'' in atomic kinetics. Using this method, we re-build the nl-level bound electron distribution (Pnl), and acquire a new hohlraum radiative drive by post-processing. Comparison with the n-level post-processed hohlraum drive shows that we get an almost identical radiation flux but with more fine frequency-denpending spectrum structure which appears only in nl-level transition with same n number(n=0) .

Chimera Grid Tools

NASA Technical Reports Server (NTRS)

Chan, William M.; Rogers, Stuart E.; Nash, Steven M.; Buning, Pieter G.; Meakin, Robert

2005-01-01

Chimera Grid Tools (CGT) is a software package for performing computational fluid dynamics (CFD) analysis utilizing the Chimera-overset-grid method. For modeling flows with viscosity about geometrically complex bodies in relative motion, the Chimera-overset-grid method is among the most computationally cost-effective methods for obtaining accurate aerodynamic results. CGT contains a large collection of tools for generating overset grids, preparing inputs for computer programs that solve equations of flow on the grids, and post-processing of flow-solution data. The tools in CGT include grid editing tools, surface-grid-generation tools, volume-grid-generation tools, utility scripts, configuration scripts, and tools for post-processing (including generation of animated images of flows and calculating forces and moments exerted on affected bodies). One of the tools, denoted OVERGRID, is a graphical user interface (GUI) that serves to visualize the grids and flow solutions and provides central access to many other tools. The GUI facilitates the generation of grids for a new flow-field configuration. Scripts that follow the grid generation process can then be constructed to mostly automate grid generation for similar configurations. CGT is designed for use in conjunction with a computer-aided-design program that provides the geometry description of the bodies, and a flow-solver program.

New technique for ensemble dressing combining Multimodel SuperEnsemble and precipitation PDF

NASA Astrophysics Data System (ADS)

Cane, D.; Milelli, M.

2009-09-01

The Multimodel SuperEnsemble technique (Krishnamurti et al., Science 285, 1548-1550, 1999) is a postprocessing method for the estimation of weather forecast parameters reducing direct model output errors. It differs from other ensemble analysis techniques by the use of an adequate weighting of the input forecast models to obtain a combined estimation of meteorological parameters. Weights are calculated by least-square minimization of the difference between the model and the observed field during a so-called training period. Although it can be applied successfully on the continuous parameters like temperature, humidity, wind speed and mean sea level pressure (Cane and Milelli, Meteorologische Zeitschrift, 15, 2, 2006), the Multimodel SuperEnsemble gives good results also when applied on the precipitation, a parameter quite difficult to handle with standard post-processing methods. Here we present our methodology for the Multimodel precipitation forecasts applied on a wide spectrum of results over Piemonte very dense non-GTS weather station network. We will focus particularly on an accurate statistical method for bias correction and on the ensemble dressing in agreement with the observed precipitation forecast-conditioned PDF. Acknowledgement: this work is supported by the Italian Civil Defence Department.

Low-Rank Linear Dynamical Systems for Motor Imagery EEG.

PubMed

Zhang, Wenchang; Sun, Fuchun; Tan, Chuanqi; Liu, Shaobo

2016-01-01

The common spatial pattern (CSP) and other spatiospectral feature extraction methods have become the most effective and successful approaches to solve the problem of motor imagery electroencephalography (MI-EEG) pattern recognition from multichannel neural activity in recent years. However, these methods need a lot of preprocessing and postprocessing such as filtering, demean, and spatiospectral feature fusion, which influence the classification accuracy easily. In this paper, we utilize linear dynamical systems (LDSs) for EEG signals feature extraction and classification. LDSs model has lots of advantages such as simultaneous spatial and temporal feature matrix generation, free of preprocessing or postprocessing, and low cost. Furthermore, a low-rank matrix decomposition approach is introduced to get rid of noise and resting state component in order to improve the robustness of the system. Then, we propose a low-rank LDSs algorithm to decompose feature subspace of LDSs on finite Grassmannian and obtain a better performance. Extensive experiments are carried out on public dataset from "BCI Competition III Dataset IVa" and "BCI Competition IV Database 2a." The results show that our proposed three methods yield higher accuracies compared with prevailing approaches such as CSP and CSSP.

Efficient brain lesion segmentation using multi-modality tissue-based feature selection and support vector machines.

PubMed

Fiot, Jean-Baptiste; Cohen, Laurent D; Raniga, Parnesh; Fripp, Jurgen

2013-09-01

Support vector machines (SVM) are machine learning techniques that have been used for segmentation and classification of medical images, including segmentation of white matter hyper-intensities (WMH). Current approaches using SVM for WMH segmentation extract features from the brain and classify these followed by complex post-processing steps to remove false positives. The method presented in this paper combines advanced pre-processing, tissue-based feature selection and SVM classification to obtain efficient and accurate WMH segmentation. Features from 125 patients, generated from up to four MR modalities [T1-w, T2-w, proton-density and fluid attenuated inversion recovery(FLAIR)], differing neighbourhood sizes and the use of multi-scale features were compared. We found that although using all four modalities gave the best overall classification (average Dice scores of 0.54  ±  0.12, 0.72  ±  0.06 and 0.82  ±  0.06 respectively for small, moderate and severe lesion loads); this was not significantly different (p = 0.50) from using just T1-w and FLAIR sequences (Dice scores of 0.52  ±  0.13, 0.71  ±  0.08 and 0.81  ±  0.07). Furthermore, there was a negligible difference between using 5 × 5 × 5 and 3 × 3 × 3 features (p = 0.93). Finally, we show that careful consideration of features and pre-processing techniques not only saves storage space and computation time but also leads to more efficient classification, which outperforms the one based on all features with post-processing. Copyright © 2013 John Wiley & Sons, Ltd.

Performance of post-processing algorithms for rainfall intensity using measurements from tipping-bucket rain gauges

NASA Astrophysics Data System (ADS)

Stagnaro, Mattia; Colli, Matteo; Lanza, Luca Giovanni; Chan, Pak Wai

2016-11-01

Eight rainfall events recorded from May to September 2013 at Hong Kong International Airport (HKIA) have been selected to investigate the performance of post-processing algorithms used to calculate the rainfall intensity (RI) from tipping-bucket rain gauges (TBRGs). We assumed a drop-counter catching-type gauge as a working reference and compared rainfall intensity measurements with two calibrated TBRGs operated at a time resolution of 1 min. The two TBRGs differ in their internal mechanics, one being a traditional single-layer dual-bucket assembly, while the other has two layers of buckets. The drop-counter gauge operates at a time resolution of 10 s, while the time of tipping is recorded for the two TBRGs. The post-processing algorithms employed for the two TBRGs are based on the assumption that the tip volume is uniformly distributed over the inter-tip period. A series of data of an ideal TBRG is reconstructed using the virtual time of tipping derived from the drop-counter data. From the comparison between the ideal gauge and the measurements from the two real TBRGs, the performances of different post-processing and correction algorithms are statistically evaluated over the set of recorded rain events. The improvement obtained by adopting the inter-tip time algorithm in the calculation of the RI is confirmed. However, by comparing the performance of the real and ideal TBRGs, the beneficial effect of the inter-tip algorithm is shown to be relevant for the mid-low range (6-50 mmh-1) of rainfall intensity values (where the sampling errors prevail), while its role vanishes with increasing RI in the range where the mechanical errors prevail.

Advances of lab-on-a-chip in isolation, detection and post-processing of circulating tumour cells.

PubMed

Yu, Ling; Ng, Shu Rui; Xu, Yang; Dong, Hua; Wang, Ying Jun; Li, Chang Ming

2013-08-21

Circulating tumour cells (CTCs) are shed by primary tumours and are found in the peripheral blood of patients with metastatic cancers. Recent studies have shown that the number of CTCs corresponds with disease severity and prognosis. Therefore, detection and further functional analysis of CTCs are important for biomedical science, early diagnosis of cancer metastasis and tracking treatment efficacy in cancer patients, especially in point-of-care applications. Over the last few years, there has been an increasing shift towards not only capturing and detecting these rare cells, but also ensuring their viability for post-processing, such as cell culture and genetic analysis. High throughput lab-on-a-chip (LOC) has been fuelled up to process and analyse heterogeneous real patient samples while gaining profound insights for cancer biology. In this review, we highlight how miniaturisation strategies together with nanotechnologies have been used to advance LOC for capturing, separating, enriching and detecting different CTCs efficiently, while meeting the challenges of cell viability, high throughput multiplex or single-cell detection and post-processing. We begin this survey with an introduction to CTC biology, followed by description of the use of various materials, microstructures and nanostructures for design of LOC to achieve miniaturisation, as well as how various CTC capture or separation strategies can enhance cell capture and enrichment efficiencies, purity and viability. The significant progress of various nanotechnologies-based detection techniques to achieve high sensitivities and low detection limits for viable CTCs and/or to enable CTC post-processing are presented and the fundamental insights are also discussed. Finally, the challenges and perspectives of the technologies are enumerated.

Post-processing of metal matrix composites by friction stir processing

NASA Astrophysics Data System (ADS)

Sharma, Vipin; Singla, Yogesh; Gupta, Yashpal; Raghuwanshi, Jitendra

2018-05-01

In metal matrix composites non-uniform distribution of reinforcement particles resulted in adverse affect on the mechanical properties. It is of great interest to explore post-processing techniques that can eliminate particle distribution heterogeneity. Friction stir processing is a relatively newer technique used for post-processing of metal matrix composites to improve homogeneity in particles distribution. In friction stir processing, synergistic effect of stirring, extrusion and forging resulted in refinement of grains, reduction of reinforcement particles size, uniformity in particles distribution, reduction in microstructural heterogeneity and elimination of defects.

FreeSurfer-initiated fully-automated subcortical brain segmentation in MRI using Large Deformation Diffeomorphic Metric Mapping.

PubMed

Khan, Ali R; Wang, Lei; Beg, Mirza Faisal

2008-07-01

Fully-automated brain segmentation methods have not been widely adopted for clinical use because of issues related to reliability, accuracy, and limitations of delineation protocol. By combining the probabilistic-based FreeSurfer (FS) method with the Large Deformation Diffeomorphic Metric Mapping (LDDMM)-based label-propagation method, we are able to increase reliability and accuracy, and allow for flexibility in template choice. Our method uses the automated FreeSurfer subcortical labeling to provide a coarse-to-fine introduction of information in the LDDMM template-based segmentation resulting in a fully-automated subcortical brain segmentation method (FS+LDDMM). One major advantage of the FS+LDDMM-based approach is that the automatically generated segmentations generated are inherently smooth, thus subsequent steps in shape analysis can directly follow without manual post-processing or loss of detail. We have evaluated our new FS+LDDMM method on several databases containing a total of 50 subjects with different pathologies, scan sequences and manual delineation protocols for labeling the basal ganglia, thalamus, and hippocampus. In healthy controls we report Dice overlap measures of 0.81, 0.83, 0.74, 0.86 and 0.75 for the right caudate nucleus, putamen, pallidum, thalamus and hippocampus respectively. We also find statistically significant improvement of accuracy in FS+LDDMM over FreeSurfer for the caudate nucleus and putamen of Huntington's disease and Tourette's syndrome subjects, and the right hippocampus of Schizophrenia subjects.

Anatomical Calibration through Post-Processing of Standard Motion Tests Data.

PubMed

Kong, Weisheng; Sessa, Salvatore; Zecca, Massimiliano; Takanishi, Atsuo

2016-11-28

The inertial measurement unit is popularly used as a wearable and flexible tool for human motion tracking. Sensor-to-body alignment, or anatomical calibration (AC), is fundamental to improve accuracy and reliability. Current AC methods either require extra movements or are limited to specific joints. In this research, the authors propose a novel method to achieve AC from standard motion tests (such as walking, or sit-to-stand), and compare the results with the AC obtained from specially designed movements. The proposed method uses the limited acceleration range on medial-lateral direction, and applies principal component analysis to estimate the sagittal plane, while the vertical direction is estimated from acceleration during quiet stance. The results show a good correlation between the two sets of IMUs placed on frontal/back and lateral sides of head, trunk and lower limbs. Moreover, repeatability and convergence were verified. The AC obtained from sit-to-stand and walking achieved similar results as the movements specifically designed for upper and lower body AC, respectively, except for the feet. Therefore, the experiments without AC performed can be recovered through post-processing on the walking and sit-to-stand data. Moreover, extra movements for AC can be avoided during the experiment and instead achieved through the proposed method.

Methane Post-Processing for Oxygen Loop Closure

NASA Technical Reports Server (NTRS)

Greenwood, Zachary W.; Abney, Morgan B.; Miller, Lee

2016-01-01

State-of-the-art United States Atmospheric Revitalization carbon dioxide (CO2) reduction is based on the Sabatier reaction process, which recovers approximately 50% of the oxygen (O2) from crew metabolic CO2. Oxygen recovery from carbon dioxide is constrained by the limited availability of reactant hydrogen. Post-processing of methane to recover hydrogen with the Umpqua Research Company Plasma Pyrolysis Assembly (PPA) has the potential to further close the Atmospheric Revitalization oxygen loop. The PPA decomposes methane into hydrogen and hydrocarbons, predominantly acetylene, and a small amount of solid carbon. The hydrogen must then be purified before it can be recycled for additional oxygen recovery. Long duration testing and evaluation of a four crew-member sized PPA and a discussion of hydrogen recycling system architectures are presented.

A Post-Processing Receiver for the Lunar Laser Communications Demonstration Project

NASA Technical Reports Server (NTRS)

Srinivasan, Meera; Birnbaum, Kevin; Cheng, Michael; Quirk, Kevin

2013-01-01

The Lunar Laser Communications Demonstration Project undertaken by MIT Lincoln Laboratory and NASA's Goddard Space Flight Center will demonstrate high-rate laser communications from lunar orbit to the Earth. NASA's Jet Propulsion Laboratory is developing a backup ground station supporting a data rate of 39 Mbps that is based on a non-real-time software post-processing receiver architecture. This approach entails processing sample-rate-limited data without feedback in the presence high uncertainty in downlink clock characteristics under low signal flux conditions. In this paper we present a receiver concept that addresses these challenges with descriptions of the photodetector assembly, sample acquisition and recording platform, and signal processing approach. End-to-end coded simulation and laboratory data analysis results are presented that validate the receiver conceptual design.

GAPPARD: a computationally efficient method of approximating gap-scale disturbance in vegetation models

NASA Astrophysics Data System (ADS)

Scherstjanoi, M.; Kaplan, J. O.; Thürig, E.; Lischke, H.

2013-02-01

Models of vegetation dynamics that are designed for application at spatial scales larger than individual forest gaps suffer from several limitations. Typically, either a population average approximation is used that results in unrealistic tree allometry and forest stand structure, or models have a high computational demand because they need to simulate both a series of age-based cohorts and a number of replicate patches to account for stochastic gap-scale disturbances. The detail required by the latter method increases the number of calculations by two to three orders of magnitude compared to the less realistic population average approach. In an effort to increase the efficiency of dynamic vegetation models without sacrificing realism, and to explore patterns of spatial scaling in forests, we developed a new method for simulating stand-replacing disturbances that is both accurate and 10-50x faster than approaches that use replicate patches. The GAPPARD (approximating GAP model results with a Probabilistic Approach to account for stand Replacing Disturbances) method works by postprocessing the output of deterministic, undisturbed simulations of a cohort-based vegetation model by deriving the distribution of patch ages at any point in time on the basis of a disturbance probability. With this distribution, the expected value of any output variable can be calculated from the output values of the deterministic undisturbed run at the time corresponding to the patch age. To account for temporal changes in model forcing, e.g., as a result of climate change, GAPPARD performs a series of deterministic simulations and interpolates between the results in the postprocessing step. We integrated the GAPPARD method in the forest models LPJ-GUESS and TreeM-LPJ, and evaluated these in a series of simulations along an altitudinal transect of an inner-alpine valley. With GAPPARD applied to LPJ-GUESS results were insignificantly different from the output of the original model LPJ-GUESS using 100 replicate patches, but simulation time was reduced by approximately the factor 10. Our new method is therefore highly suited rapidly approximating LPJ-GUESS results, and provides the opportunity for future studies over large spatial domains, allows easier parameterization of tree species, faster identification of areas of interesting simulation results, and comparisons with large-scale datasets and forest models.

Opportunities of CMOS-MEMS integration through LSI foundry and open facility

NASA Astrophysics Data System (ADS)

Mita, Yoshio; Lebrasseur, Eric; Okamoto, Yuki; Marty, Frédéfic; Setoguchi, Ryota; Yamada, Kentaro; Mori, Isao; Morishita, Satoshi; Imai, Yoshiaki; Hosaka, Kota; Hirakawa, Atsushi; Inoue, Shu; Kubota, Masanori; Denoual, Matthieu

2017-06-01

Since the 2000s, several countries have established micro- and nanofabrication platforms for the research and education community as national projects. By combining such platforms with VLSI multichip foundry services, various integrated devices, referred to as “CMOS-MEMS”, can be realized without constructing an entire cleanroom. In this paper, we summarize MEMS-last postprocess schemes for CMOS devices on a bulk silicon wafer as well as on a silicon-on-insulator (SOI) wafer using an open-access cleanroom of the Nanotechnology Platform of MEXT Japan. The integration devices presented in this article are free-standing structures and postprocess isolated LSI devices. Postprocess issues are identified with their solutions, such as the reactive ion etching (RIE) lag for dry release and the impact of the deep RIE (DRIE) postprocess on transistor characteristics. Integration with nonsilicon materials is proposed as one of the future directions.

Dynamic mechanical properties of hydroxyapatite/polyethylene oxide nanocomposites: characterizing isotropic and post-processing microstructures

NASA Astrophysics Data System (ADS)

Shofner, Meisha; Lee, Ji Hoon

2012-02-01

Compatible component interfaces in polymer nanocomposites can be used to facilitate a dispersed morphology and improved physical properties as has been shown extensively in experimental results concerning amorphous matrix nanocomposites. In this research, a block copolymer compatibilized interface is employed in a semi-crystalline matrix to prevent large scale nanoparticle clustering and enable microstructure construction with post-processing drawing. The specific materials used are hydroxyapatite nanoparticles coated with a polyethylene oxide-b-polymethacrylic acid block copolymer and a polyethylene oxide matrix. Two particle shapes are used: spherical and needle-shaped. Characterization of the dynamic mechanical properties indicated that the two nanoparticle systems provided similar levels of reinforcement to the matrix. For the needle-shaped nanoparticles, the post-processing step increased matrix crystallinity and changed the thermomechanical reinforcement trends. These results will be used to further refine the post-processing parameters to achieve a nanocomposite microstructure with triangulated arrays of nanoparticles.

Analyzing locomotion synthesis with feature-based motion graphs.

PubMed

Mahmudi, Mentar; Kallmann, Marcelo

2013-05-01

We propose feature-based motion graphs for realistic locomotion synthesis among obstacles. Among several advantages, feature-based motion graphs achieve improved results in search queries, eliminate the need of postprocessing for foot skating removal, and reduce the computational requirements in comparison to traditional motion graphs. Our contributions are threefold. First, we show that choosing transitions based on relevant features significantly reduces graph construction time and leads to improved search performances. Second, we employ a fast channel search method that confines the motion graph search to a free channel with guaranteed clearance among obstacles, achieving faster and improved results that avoid expensive collision checking. Lastly, we present a motion deformation model based on Inverse Kinematics applied over the transitions of a solution branch. Each transition is assigned a continuous deformation range that does not exceed the original transition cost threshold specified by the user for the graph construction. The obtained deformation improves the reachability of the feature-based motion graph and in turn also reduces the time spent during search. The results obtained by the proposed methods are evaluated and quantified, and they demonstrate significant improvements in comparison to traditional motion graph techniques.

An interactive graphics system to facilitate finite element structural analysis

NASA Technical Reports Server (NTRS)

Burk, R. C.; Held, F. H.

1973-01-01

The characteristics of an interactive graphics systems to facilitate the finite element method of structural analysis are described. The finite element model analysis consists of three phases: (1) preprocessing (model generation), (2) problem solution, and (3) postprocessing (interpretation of results). The advantages of interactive graphics to finite element structural analysis are defined.

Post-processing method to reduce noise while preserving high time resolution in aethalometer real-time black carbon data

EPA Science Inventory

Real-time aerosol black carbon (BC) data, presented at time resolutions on the order of seconds to minutes, is desirable in field and source characterization studies measuring rapidly varying concentrations of BC. The Optimized Noise-reduction Averaging (ONA) algorithm has been d...

The Twenty-First NASTRAN (R) Users' Colloquium

NASA Technical Reports Server (NTRS)

1993-01-01

This publication contains the proceedings of the Twenty-First NASTRAN Users' Colloquium held in Tampa, FL, April 26 through April 30, 1993. It provides some comprehensive general papers on the application of finite elements in engineering, comparisons with other approaches, unique applications, pre-and postprocessing with other auxiliary programs and new methods of analysis with NASTRAN.

Point target detection utilizing super-resolution strategy for infrared scanning oversampling system

NASA Astrophysics Data System (ADS)

Wang, Longguang; Lin, Zaiping; Deng, Xinpu; An, Wei

2017-11-01

To improve the resolution of remote sensing infrared images, infrared scanning oversampling system is employed with information amount quadrupled, which contributes to the target detection. Generally the image data from double-line detector of infrared scanning oversampling system is shuffled to a whole oversampled image to be post-processed, whereas the aliasing between neighboring pixels leads to image degradation with a great impact on target detection. This paper formulates a point target detection method utilizing super-resolution (SR) strategy concerning infrared scanning oversampling system, with an accelerated SR strategy proposed to realize fast de-aliasing of the oversampled image and an adaptive MRF-based regularization designed to achieve the preserving and aggregation of target energy. Extensive experiments demonstrate the superior detection performance, robustness and efficiency of the proposed method compared with other state-of-the-art approaches.

Composite Characterization Using Laser Doppler Vibrometry and Multi-Frequency Wavenumber Analysis

NASA Technical Reports Server (NTRS)

Juarez, Peter; Leckey, Cara

2015-01-01

NASA has recognized the need for better characterization of composite materials to support advances in aeronautics and the next generation of space exploration vehicles. An area of related research is the evaluation of impact induced delaminations. Presented is a non-contact method of measuring the ply depth of impact delamination damage in a composite through use of a Scanning Laser Doppler Vibrometer (SLDV), multi-frequency wavenumber analysis, and a wavenumber-ply correlation algorithm. A single acquisition of a chirp excited lamb wavefield in an impacted composite is post-processed into a numerous single frequency excitation wavefields through a deconvolution process. A spatially windowed wavenumber analysis then extracts local wavenumbers from the wavefield, which are then correlated to theoretical dispersion curves for ply depth determination. SLDV based methods to characterize as-manufactured composite variation using wavefield analysis will also be discussed.

LISA Framework for Enhancing Gravitational Wave Signal Extraction Techniques

NASA Technical Reports Server (NTRS)

Thompson, David E.; Thirumalainambi, Rajkumar

2006-01-01

This paper describes the development of a Framework for benchmarking and comparing signal-extraction and noise-interference-removal methods that are applicable to interferometric Gravitational Wave detector systems. The primary use is towards comparing signal and noise extraction techniques at LISA frequencies from multiple (possibly confused) ,gravitational wave sources. The Framework includes extensive hybrid learning/classification algorithms, as well as post-processing regularization methods, and is based on a unique plug-and-play (component) architecture. Published methods for signal extraction and interference removal at LISA Frequencies are being encoded, as well as multiple source noise models, so that the stiffness of GW Sensitivity Space can be explored under each combination of methods. Furthermore, synthetic datasets and source models can be created and imported into the Framework, and specific degraded numerical experiments can be run to test the flexibility of the analysis methods. The Framework also supports use of full current LISA Testbeds, Synthetic data systems, and Simulators already in existence through plug-ins and wrappers, thus preserving those legacy codes and systems in tact. Because of the component-based architecture, all selected procedures can be registered or de-registered at run-time, and are completely reusable, reconfigurable, and modular.

Ross filter pairs for metal artefact reduction in x-ray tomography: a case study based on imaging and segmentation of metallic implants

NASA Astrophysics Data System (ADS)

Arhatari, Benedicta D.; Abbey, Brian

2018-01-01

Ross filter pairs have recently been demonstrated as a highly effective means of producing quasi-monoenergetic beams from polychromatic X-ray sources. They have found applications in both X-ray spectroscopy and for elemental separation in X-ray computed tomography (XCT). Here we explore whether they could be applied to the problem of metal artefact reduction (MAR) for applications in medical imaging. Metal artefacts are a common problem in X-ray imaging of metal implants embedded in bone and soft tissue. A number of data post-processing approaches to MAR have been proposed in the literature, however these can be time-consuming and sometimes have limited efficacy. Here we describe and demonstrate an alternative approach based on beam conditioning using Ross filter pairs. This approach obviates the need for any complex post-processing of the data and enables MAR and segmentation from the surrounding tissue by exploiting the absorption edge contrast of the implant.

Design sensitivity analysis and optimization tool (DSO) for sizing design applications

NASA Technical Reports Server (NTRS)

Chang, Kuang-Hua; Choi, Kyung K.; Perng, Jyh-Hwa

1992-01-01

The DSO tool, a structural design software system that provides the designer with a graphics-based menu-driven design environment to perform easy design optimization for general applications, is presented. Three design stages, preprocessing, design sensitivity analysis, and postprocessing, are implemented in the DSO to allow the designer to carry out the design process systematically. A framework, including data base, user interface, foundation class, and remote module, has been designed and implemented to facilitate software development for the DSO. A number of dedicated commercial software/packages have been integrated in the DSO to support the design procedures. Instead of parameterizing an FEM, design parameters are defined on a geometric model associated with physical quantities, and the continuum design sensitivity analysis theory is implemented to compute design sensitivity coefficients using postprocessing data from the analysis codes. A tracked vehicle road wheel is given as a sizing design application to demonstrate the DSO's easy and convenient design optimization process.

PyCDT: A Python toolkit for modeling point defects in semiconductors and insulators

DOE PAGES

Broberg, Danny; Medasani, Bharat; Zimmermann, Nils E. R.; ...

2018-02-13

Point defects have a strong impact on the performance of semiconductor and insulator materials used in technological applications, spanning microelectronics to energy conversion and storage. The nature of the dominant defect types, how they vary with processing conditions, and their impact on materials properties are central aspects that determine the performance of a material in a certain application. This information is, however, difficult to access directly from experimental measurements. Consequently, computational methods, based on electronic density functional theory (DFT), have found widespread use in the calculation of point-defect properties. Here we have developed the Python Charged Defect Toolkit (PyCDT) tomore » expedite the setup and post-processing of defect calculations with widely used DFT software. PyCDT has a user-friendly command-line interface and provides a direct interface with the Materials Project database. This allows for setting up many charged defect calculations for any material of interest, as well as post-processing and applying state-of-the-art electrostatic correction terms. Our paper serves as a documentation for PyCDT, and demonstrates its use in an application to the well-studied GaAs compound semiconductor. As a result, we anticipate that the PyCDT code will be useful as a framework for undertaking readily reproducible calculations of charged point-defect properties, and that it will provide a foundation for automated, high-throughput calculations.« less

A robust technique based on VLM and Frangi filter for retinal vessel extraction and denoising.

PubMed

Khan, Khan Bahadar; Khaliq, Amir A; Jalil, Abdul; Shahid, Muhammad

2018-01-01

The exploration of retinal vessel structure is colossally important on account of numerous diseases including stroke, Diabetic Retinopathy (DR) and coronary heart diseases, which can damage the retinal vessel structure. The retinal vascular network is very hard to be extracted due to its spreading and diminishing geometry and contrast variation in an image. The proposed technique consists of unique parallel processes for denoising and extraction of blood vessels in retinal images. In the preprocessing section, an adaptive histogram equalization enhances dissimilarity between the vessels and the background and morphological top-hat filters are employed to eliminate macula and optic disc, etc. To remove local noise, the difference of images is computed from the top-hat filtered image and the high-boost filtered image. Frangi filter is applied at multi scale for the enhancement of vessels possessing diverse widths. Segmentation is performed by using improved Otsu thresholding on the high-boost filtered image and Frangi's enhanced image, separately. In the postprocessing steps, a Vessel Location Map (VLM) is extracted by using raster to vector transformation. Postprocessing steps are employed in a novel way to reject misclassified vessel pixels. The final segmented image is obtained by using pixel-by-pixel AND operation between VLM and Frangi output image. The method has been rigorously analyzed on the STARE, DRIVE and HRF datasets.

Wireless GPS-based phase-locked synchronization system for outdoor environment.

PubMed

Meyer, Frédéric; Bahr, Alexander; Lochmatter, Thomas; Borrani, Fabio

2012-01-03

Synchronization of data coming from different sources is of high importance in biomechanics to ensure reliable analyses. This synchronization can either be performed through hardware to obtain perfect matching of data, or post-processed digitally. Hardware synchronization can be achieved using trigger cables connecting different devices in many situations; however, this is often impractical, and sometimes impossible in outdoors situations. The aim of this paper is to describe a wireless system for outdoor use, allowing synchronization of different types of - potentially embedded and moving - devices. In this system, each synchronization device is composed of: (i) a GPS receiver (used as time reference), (ii) a radio transmitter, and (iii) a microcontroller. These components are used to provide synchronized trigger signals at the desired frequency to the measurement device connected. The synchronization devices communicate wirelessly, are very lightweight, battery-operated and thus very easy to set up. They are adaptable to every measurement device equipped with either trigger input or recording channel. The accuracy of the system was validated using an oscilloscope. The mean synchronization error was found to be 0.39 μs and pulses are generated with an accuracy of <2 μs. The system provides synchronization accuracy about two orders of magnitude better than commonly used post-processing methods, and does not suffer from any drift in trigger generation. Copyright © 2011 Elsevier Ltd. All rights reserved.

PyCDT: A Python toolkit for modeling point defects in semiconductors and insulators

NASA Astrophysics Data System (ADS)

Broberg, Danny; Medasani, Bharat; Zimmermann, Nils E. R.; Yu, Guodong; Canning, Andrew; Haranczyk, Maciej; Asta, Mark; Hautier, Geoffroy

2018-05-01

Point defects have a strong impact on the performance of semiconductor and insulator materials used in technological applications, spanning microelectronics to energy conversion and storage. The nature of the dominant defect types, how they vary with processing conditions, and their impact on materials properties are central aspects that determine the performance of a material in a certain application. This information is, however, difficult to access directly from experimental measurements. Consequently, computational methods, based on electronic density functional theory (DFT), have found widespread use in the calculation of point-defect properties. Here we have developed the Python Charged Defect Toolkit (PyCDT) to expedite the setup and post-processing of defect calculations with widely used DFT software. PyCDT has a user-friendly command-line interface and provides a direct interface with the Materials Project database. This allows for setting up many charged defect calculations for any material of interest, as well as post-processing and applying state-of-the-art electrostatic correction terms. Our paper serves as a documentation for PyCDT, and demonstrates its use in an application to the well-studied GaAs compound semiconductor. We anticipate that the PyCDT code will be useful as a framework for undertaking readily reproducible calculations of charged point-defect properties, and that it will provide a foundation for automated, high-throughput calculations.

PyCDT: A Python toolkit for modeling point defects in semiconductors and insulators

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

Broberg, Danny; Medasani, Bharat; Zimmermann, Nils E. R.

Point defects have a strong impact on the performance of semiconductor and insulator materials used in technological applications, spanning microelectronics to energy conversion and storage. The nature of the dominant defect types, how they vary with processing conditions, and their impact on materials properties are central aspects that determine the performance of a material in a certain application. This information is, however, difficult to access directly from experimental measurements. Consequently, computational methods, based on electronic density functional theory DFT), have found widespread use in the calculation of point defect properties. Here we have developed the Python Charged Defect Toolkit (PyCDT)more » to expedite the setup and post-processing of defect calculations with widely used DFT software. PyCDT has a user-friendly command-line interface and provides a direct interface with the Materials Project database. This allows for setting up many charged defect calculations for any material of interest, as well as post-processing and applying state-of-the-art electrostatic correction terms. Our paper serves as a documentation for PyCDT, and demonstrates its use in an application to the well-studied GaAs compound semiconductor. We anticipate that the PyCDT code will be useful as a framework for undertaking readily reproducible calculations of charged point-defect properties, and that it will provide a foundation for automated, high-throughput calculations.« less

PyCDT: A Python toolkit for modeling point defects in semiconductors and insulators

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

Broberg, Danny; Medasani, Bharat; Zimmermann, Nils E. R.

Point defects have a strong impact on the performance of semiconductor and insulator materials used in technological applications, spanning microelectronics to energy conversion and storage. The nature of the dominant defect types, how they vary with processing conditions, and their impact on materials properties are central aspects that determine the performance of a material in a certain application. This information is, however, difficult to access directly from experimental measurements. Consequently, computational methods, based on electronic density functional theory (DFT), have found widespread use in the calculation of point-defect properties. Here we have developed the Python Charged Defect Toolkit (PyCDT) tomore » expedite the setup and post-processing of defect calculations with widely used DFT software. PyCDT has a user-friendly command-line interface and provides a direct interface with the Materials Project database. This allows for setting up many charged defect calculations for any material of interest, as well as post-processing and applying state-of-the-art electrostatic correction terms. Our paper serves as a documentation for PyCDT, and demonstrates its use in an application to the well-studied GaAs compound semiconductor. As a result, we anticipate that the PyCDT code will be useful as a framework for undertaking readily reproducible calculations of charged point-defect properties, and that it will provide a foundation for automated, high-throughput calculations.« less

Real-Time and Post-Processed Georeferencing for Hyperpspectral Drone Remote Sensing

NASA Astrophysics Data System (ADS)

Oliveira, R. A.; Khoramshahi, E.; Suomalainen, J.; Hakala, T.; Viljanen, N.; Honkavaara, E.

2018-05-01

The use of drones and photogrammetric technologies are increasing rapidly in different applications. Currently, drone processing workflow is in most cases based on sequential image acquisition and post-processing, but there are great interests towards real-time solutions. Fast and reliable real-time drone data processing can benefit, for instance, environmental monitoring tasks in precision agriculture and in forest. Recent developments in miniaturized and low-cost inertial measurement systems and GNSS sensors, and Real-time kinematic (RTK) position data are offering new perspectives for the comprehensive remote sensing applications. The combination of these sensors and light-weight and low-cost multi- or hyperspectral frame sensors in drones provides the opportunity of creating near real-time or real-time remote sensing data of target object. We have developed a system with direct georeferencing onboard drone to be used combined with hyperspectral frame cameras in real-time remote sensing applications. The objective of this study is to evaluate the real-time georeferencing comparing with post-processing solutions. Experimental data sets were captured in agricultural and forested test sites using the system. The accuracy of onboard georeferencing data were better than 0.5 m. The results showed that the real-time remote sensing is promising and feasible in both test sites.

Improving medium-range ensemble streamflow forecasts through statistical post-processing

NASA Astrophysics Data System (ADS)

Mendoza, Pablo; Wood, Andy; Clark, Elizabeth; Nijssen, Bart; Clark, Martyn; Ramos, Maria-Helena; Nowak, Kenneth; Arnold, Jeffrey

2017-04-01

Probabilistic hydrologic forecasts are a powerful source of information for decision-making in water resources operations. A common approach is the hydrologic model-based generation of streamflow forecast ensembles, which can be implemented to account for different sources of uncertainties - e.g., from initial hydrologic conditions (IHCs), weather forecasts, and hydrologic model structure and parameters. In practice, hydrologic ensemble forecasts typically have biases and spread errors stemming from errors in the aforementioned elements, resulting in a degradation of probabilistic properties. In this work, we compare several statistical post-processing techniques applied to medium-range ensemble streamflow forecasts obtained with the System for Hydromet Applications, Research and Prediction (SHARP). SHARP is a fully automated prediction system for the assessment and demonstration of short-term to seasonal streamflow forecasting applications, developed by the National Center for Atmospheric Research, University of Washington, U.S. Army Corps of Engineers, and U.S. Bureau of Reclamation. The suite of post-processing techniques includes linear blending, quantile mapping, extended logistic regression, quantile regression, ensemble analogs, and the generalized linear model post-processor (GLMPP). We assess and compare these techniques using multi-year hindcasts in several river basins in the western US. This presentation discusses preliminary findings about the effectiveness of the techniques for improving probabilistic skill, reliability, discrimination, sharpness and resolution.

In-process and post-process measurements of drill wear for control of the drilling process

NASA Astrophysics Data System (ADS)

Liu, Tien-I.; Liu, George; Gao, Zhiyu

2011-12-01

Optical inspection was used in this research for the post-process measurements of drill wear. A precision toolmakers" microscope was used. Indirect index, cutting force, is used for in-process drill wear measurements. Using in-process measurements to estimate the drill wear for control purpose can decrease the operation cost and enhance the product quality and safety. The challenge is to correlate the in-process cutting force measurements with the post-process optical inspection of drill wear. To find the most important feature, the energy principle was used in this research. It is necessary to select only the cutting force feature which shows the highest sensitivity to drill wear. The best feature selected is the peak of torque in the drilling process. Neuro-fuzzy systems were used for correlation purposes. The Adaptive-Network-Based Fuzzy Inference System (ANFIS) can construct fuzzy rules with membership functions to generate an input-output pair. A 1x6 ANFIS architecture with product of sigmoid membership functions can in-process measure the drill wear with an error as low as 0.15%. This is extremely important for control of the drilling process. Furthermore, the measurement of drill wear was performed under different drilling conditions. This shows that ANFIS has the capability of generalization.

Method of making low work function component

DOEpatents

Robinson, Vance [Niskayuna, NY; Weaver, Stanton Earl [Northville, NY; Michael, Joseph Darryl [Delmar, NY

2011-11-15

A method for fabricating a component is disclosed. The method includes: providing a member having an effective work function of an initial value, disposing a sacrificial layer on a surface of the member, disposing a first agent within the member to obtain a predetermined concentration of the agent at said surface of the member, annealing the member, and removing the sacrificial layer to expose said surface of the member, wherein said surface has a post-process effective work function that is different from the initial value.

Metal artifact reduction using a patch-based reconstruction for digital breast tomosynthesis

NASA Astrophysics Data System (ADS)

Borges, Lucas R.; Bakic, Predrag R.; Maidment, Andrew D. A.; Vieira, Marcelo A. C.

2017-03-01

Digital breast tomosynthesis (DBT) is rapidly emerging as the main clinical tool for breast cancer screening. Although several reconstruction methods for DBT are described by the literature, one common issue is the interplane artifacts caused by out-of-focus features. For breasts containing highly attenuating features, such as surgical clips and large calcifications, the artifacts are even more apparent and can limit the detection and characterization of lesions by the radiologist. In this work, we propose a novel method of combining backprojected data into tomographic slices using a patch-based approach, commonly used in denoising. Preliminary tests were performed on a geometry phantom and on an anthropomorphic phantom containing metal inserts. The reconstructed images were compared to a commercial reconstruction solution. Qualitative assessment of the reconstructed images provides evidence that the proposed method reduces artifacts while maintaining low noise levels. Objective assessment supports the visual findings. The artifact spread function shows that the proposed method is capable of suppressing artifacts generated by highly attenuating features. The signal difference to noise ratio shows that the noise levels of the proposed and commercial methods are comparable, even though the commercial method applies post-processing filtering steps, which were not implemented on the proposed method. Thus, the proposed method can produce tomosynthesis reconstructions with reduced artifacts and low noise levels.

IR-thermography for Quality Prediction in Selective Laser Deburring

NASA Astrophysics Data System (ADS)

Möller, Mauritz; Conrad, Christian; Haimerl, Walter; Emmelmann, Claus

Selective Laser Deburring (SLD) is an innovative edge-refinement process being developed at the Laser Zentrum Nord (LZN) in Hamburg. It offers a wear-free processing of defined radii and bevels at the edges as well as the possibility to deburr several materials with the same laser source. Sheet metal parts of various applications need to be post-processed to remove sharp edges and burrs remaining from the initial production process. Thus, SLD will provide an extended degree of automation for the next generation of manufacturing facilities. This paper investigates the dependence between the deburring result and the temperature field in- and post-process. In order to achieve this, the surface temperature near to the deburred edge is monitored with IR-thermography. Different strategies are discussed for the approach using the IR-information as a quality assurance. Additional experiments are performed to rate the accuracy of the quality prediction method in different deburring applications.

Towards robust deconvolution of low-dose perfusion CT: sparse perfusion deconvolution using online dictionary learning.

PubMed

Fang, Ruogu; Chen, Tsuhan; Sanelli, Pina C

2013-05-01

Computed tomography perfusion (CTP) is an important functional imaging modality in the evaluation of cerebrovascular diseases, particularly in acute stroke and vasospasm. However, the post-processed parametric maps of blood flow tend to be noisy, especially in low-dose CTP, due to the noisy contrast enhancement profile and the oscillatory nature of the results generated by the current computational methods. In this paper, we propose a robust sparse perfusion deconvolution method (SPD) to estimate cerebral blood flow in CTP performed at low radiation dose. We first build a dictionary from high-dose perfusion maps using online dictionary learning and then perform deconvolution-based hemodynamic parameters estimation on the low-dose CTP data. Our method is validated on clinical data of patients with normal and pathological CBF maps. The results show that we achieve superior performance than existing methods, and potentially improve the differentiation between normal and ischemic tissue in the brain. Copyright © 2013 Elsevier B.V. All rights reserved.

Targets Mask U-Net for Wind Turbines Detection in Remote Sensing Images

NASA Astrophysics Data System (ADS)

Han, M.; Wang, H.; Wang, G.; Liu, Y.

2018-04-01

To detect wind turbines precisely and quickly in very high resolution remote sensing images (VHRRSI) we propose target mask U-Net. This convolution neural network (CNN), which is carefully designed to be a wide-field detector, models the pixel class assignment to wind turbines and their context information. The shadow, which is the context information of the target in this study, has been regarded as part of a wind turbine instance. We have trained the target mask U-Net on training dataset, which is composed of down sampled image blocks and instance mask blocks. Some post-processes have been integrated to eliminate wrong spots and produce bounding boxes of wind turbine instances. The evaluation metrics prove the reliability and effectiveness of our method for the average F1-score of our detection method is up to 0.97. The comparison of detection accuracy and time consuming with the weakly supervised targets detection method based on CNN illustrates the superiority of our method.

Multisensor Super Resolution Using Directionally-Adaptive Regularization for UAV Images

PubMed Central

Kang, Wonseok; Yu, Soohwan; Ko, Seungyong; Paik, Joonki

2015-01-01

In various unmanned aerial vehicle (UAV) imaging applications, the multisensor super-resolution (SR) technique has become a chronic problem and attracted increasing attention. Multisensor SR algorithms utilize multispectral low-resolution (LR) images to make a higher resolution (HR) image to improve the performance of the UAV imaging system. The primary objective of the paper is to develop a multisensor SR method based on the existing multispectral imaging framework instead of using additional sensors. In order to restore image details without noise amplification or unnatural post-processing artifacts, this paper presents an improved regularized SR algorithm by combining the directionally-adaptive constraints and multiscale non-local means (NLM) filter. As a result, the proposed method can overcome the physical limitation of multispectral sensors by estimating the color HR image from a set of multispectral LR images using intensity-hue-saturation (IHS) image fusion. Experimental results show that the proposed method provides better SR results than existing state-of-the-art SR methods in the sense of objective measures. PMID:26007744

Multisensor Super Resolution Using Directionally-Adaptive Regularization for UAV Images.

PubMed

Kang, Wonseok; Yu, Soohwan; Ko, Seungyong; Paik, Joonki

2015-05-22

In various unmanned aerial vehicle (UAV) imaging applications, the multisensor super-resolution (SR) technique has become a chronic problem and attracted increasing attention. Multisensor SR algorithms utilize multispectral low-resolution (LR) images to make a higher resolution (HR) image to improve the performance of the UAV imaging system. The primary objective of the paper is to develop a multisensor SR method based on the existing multispectral imaging framework instead of using additional sensors. In order to restore image details without noise amplification or unnatural post-processing artifacts, this paper presents an improved regularized SR algorithm by combining the directionally-adaptive constraints and multiscale non-local means (NLM) filter. As a result, the proposed method can overcome the physical limitation of multispectral sensors by estimating the color HR image from a set of multispectral LR images using intensity-hue-saturation (IHS) image fusion. Experimental results show that the proposed method provides better SR results than existing state-of-the-art SR methods in the sense of objective measures.

Towards robust deconvolution of low-dose perfusion CT: Sparse perfusion deconvolution using online dictionary learning

PubMed Central

Fang, Ruogu; Chen, Tsuhan; Sanelli, Pina C.

2014-01-01

Computed tomography perfusion (CTP) is an important functional imaging modality in the evaluation of cerebrovascular diseases, particularly in acute stroke and vasospasm. However, the post-processed parametric maps of blood flow tend to be noisy, especially in low-dose CTP, due to the noisy contrast enhancement profile and the oscillatory nature of the results generated by the current computational methods. In this paper, we propose a robust sparse perfusion deconvolution method (SPD) to estimate cerebral blood flow in CTP performed at low radiation dose. We first build a dictionary from high-dose perfusion maps using online dictionary learning and then perform deconvolution-based hemodynamic parameters estimation on the low-dose CTP data. Our method is validated on clinical data of patients with normal and pathological CBF maps. The results show that we achieve superior performance than existing methods, and potentially improve the differentiation between normal and ischemic tissue in the brain. PMID:23542422

Comparative study of CW, nanosecond- and femtosecond-pulsed laser microcutting of AZ31 magnesium alloy stents.

PubMed

Gökhan Demir, Ali; Previtali, Barbara

2014-06-01

Magnesium alloys constitute an interesting solution for cardiovascular stents due to their biocompatibility and biodegradability in human body. Laser microcutting is the industrially accepted method for stent manufacturing. However, the laser-material interaction should be well investigated to control the quality characteristics of the microcutting process that concern the surface roughness, chemical composition, and microstructure of the final device. Despite the recent developments in industrial laser systems, a universal laser source that can be manipulated flexibly in terms of process parameters is far from reality. Therefore, comparative studies are required to demonstrate processing capabilities. In particular, the laser pulse duration is a key factor determining the processing regime. This work approaches the laser microcutting of AZ31 Mg alloy from the perspective of a comparative study to evaluate the machining capabilities in continuous wave (CW), ns- and fs-pulsed regimes. Three industrial grade machining systems were compared to reach a benchmark in machining quality, productivity, and ease of postprocessing. The results confirmed that moving toward the ultrashort pulse domain the machining quality increases, but the need for postprocessing remains. The real advantage of ultrashort pulsed machining was the ease in postprocessing and maintaining geometrical integrity of the stent mesh after chemical etching. Resultantly, the overall production cycle time was shortest for fs-pulsed laser system, despite the fact that CW laser system provided highest cutting speed.

Pre- and Post-Processing Tools to Create and Characterize Particle-Based Composite Model Structures

DTIC Science & Technology

2017-11-01

ARL-TR-8213 ● NOV 2017 US Army Research Laboratory Pre- and Post -Processing Tools to Create and Characterize Particle-Based...ARL-TR-8213 ● NOV 2017 US Army Research Laboratory Pre- and Post -Processing Tools to Create and Characterize Particle-Based Composite...AND SUBTITLE Pre- and Post -Processing Tools to Create and Characterize Particle-Based Composite Model Structures 5a. CONTRACT NUMBER 5b. GRANT

Assembling proteomics data as a prerequisite for the analysis of large scale experiments

PubMed Central

Schmidt, Frank; Schmid, Monika; Thiede, Bernd; Pleißner, Klaus-Peter; Böhme, Martina; Jungblut, Peter R

2009-01-01

Background Despite the complete determination of the genome sequence of a huge number of bacteria, their proteomes remain relatively poorly defined. Beside new methods to increase the number of identified proteins new database applications are necessary to store and present results of large- scale proteomics experiments. Results In the present study, a database concept has been developed to address these issues and to offer complete information via a web interface. In our concept, the Oracle based data repository system SQL-LIMS plays the central role in the proteomics workflow and was applied to the proteomes of Mycobacterium tuberculosis, Helicobacter pylori, Salmonella typhimurium and protein complexes such as 20S proteasome. Technical operations of our proteomics labs were used as the standard for SQL-LIMS template creation. By means of a Java based data parser, post-processed data of different approaches, such as LC/ESI-MS, MALDI-MS and 2-D gel electrophoresis (2-DE), were stored in SQL-LIMS. A minimum set of the proteomics data were transferred in our public 2D-PAGE database using a Java based interface (Data Transfer Tool) with the requirements of the PEDRo standardization. Furthermore, the stored proteomics data were extractable out of SQL-LIMS via XML. Conclusion The Oracle based data repository system SQL-LIMS played the central role in the proteomics workflow concept. Technical operations of our proteomics labs were used as standards for SQL-LIMS templates. Using a Java based parser, post-processed data of different approaches such as LC/ESI-MS, MALDI-MS and 1-DE and 2-DE were stored in SQL-LIMS. Thus, unique data formats of different instruments were unified and stored in SQL-LIMS tables. Moreover, a unique submission identifier allowed fast access to all experimental data. This was the main advantage compared to multi software solutions, especially if personnel fluctuations are high. Moreover, large scale and high-throughput experiments must be managed in a comprehensive repository system such as SQL-LIMS, to query results in a systematic manner. On the other hand, these database systems are expensive and require at least one full time administrator and specialized lab manager. Moreover, the high technical dynamics in proteomics may cause problems to adjust new data formats. To summarize, SQL-LIMS met the requirements of proteomics data handling especially in skilled processes such as gel-electrophoresis or mass spectrometry and fulfilled the PSI standardization criteria. The data transfer into a public domain via DTT facilitated validation of proteomics data. Additionally, evaluation of mass spectra by post-processing using MS-Screener improved the reliability of mass analysis and prevented storage of data junk. PMID:19166578

Post-Processing of Low Dose Mammography Images

DTIC Science & Technology

2002-05-01

method of restoring images in the presence of blur as well as noise ” (12:276). The deblurring and denoising characteristics make Wiener filtering...independent noise . The signal dependant scatter noise can be modeled as blur in the mammography image. A Wiener filter with deblurring characteristics can...centered on. This method is used to eradicate noise impulses with high 26 pixel values (2:7). For the research at hand, the median filter would

Low-Grade Glioma Segmentation Based on CNN with Fully Connected CRF

PubMed Central

Li, Zeju; Shi, Zhifeng; Guo, Yi; Chen, Liang; Mao, Ying

2017-01-01

This work proposed a novel automatic three-dimensional (3D) magnetic resonance imaging (MRI) segmentation method which would be widely used in the clinical diagnosis of the most common and aggressive brain tumor, namely, glioma. The method combined a multipathway convolutional neural network (CNN) and fully connected conditional random field (CRF). Firstly, 3D information was introduced into the CNN which makes more accurate recognition of glioma with low contrast. Then, fully connected CRF was added as a postprocessing step which purposed more delicate delineation of glioma boundary. The method was applied to T2flair MRI images of 160 low-grade glioma patients. With 59 cases of data training and manual segmentation as the ground truth, the Dice similarity coefficient (DSC) of our method was 0.85 for the test set of 101 MRI images. The results of our method were better than those of another state-of-the-art CNN method, which gained the DSC of 0.76 for the same dataset. It proved that our method could produce better results for the segmentation of low-grade gliomas. PMID:29065666

Low-Grade Glioma Segmentation Based on CNN with Fully Connected CRF.

PubMed

Li, Zeju; Wang, Yuanyuan; Yu, Jinhua; Shi, Zhifeng; Guo, Yi; Chen, Liang; Mao, Ying

2017-01-01

This work proposed a novel automatic three-dimensional (3D) magnetic resonance imaging (MRI) segmentation method which would be widely used in the clinical diagnosis of the most common and aggressive brain tumor, namely, glioma. The method combined a multipathway convolutional neural network (CNN) and fully connected conditional random field (CRF). Firstly, 3D information was introduced into the CNN which makes more accurate recognition of glioma with low contrast. Then, fully connected CRF was added as a postprocessing step which purposed more delicate delineation of glioma boundary. The method was applied to T2flair MRI images of 160 low-grade glioma patients. With 59 cases of data training and manual segmentation as the ground truth, the Dice similarity coefficient (DSC) of our method was 0.85 for the test set of 101 MRI images. The results of our method were better than those of another state-of-the-art CNN method, which gained the DSC of 0.76 for the same dataset. It proved that our method could produce better results for the segmentation of low-grade gliomas.

On the accuracy of the LSC-IVR approach for excitation energy transfer in molecular aggregates

NASA Astrophysics Data System (ADS)

Teh, Hung-Hsuan; Cheng, Yuan-Chung

2017-04-01

We investigate the applicability of the linearized semiclassical initial value representation (LSC-IVR) method to excitation energy transfer (EET) problems in molecular aggregates by simulating the EET dynamics of a dimer model in a wide range of parameter regime and comparing the results to those obtained from a numerically exact method. It is found that the LSC-IVR approach yields accurate population relaxation rates and decoherence rates in a broad parameter regime. However, the classical approximation imposed by the LSC-IVR method does not satisfy the detailed balance condition, generally leading to incorrect equilibrium populations. Based on this observation, we propose a post-processing algorithm to solve the long time equilibrium problem and demonstrate that this long-time correction method successfully removed the deviations from exact results for the LSC-IVR method in all of the regimes studied in this work. Finally, we apply the LSC-IVR method to simulate EET dynamics in the photosynthetic Fenna-Matthews-Olson complex system, demonstrating that the LSC-IVR method with long-time correction provides excellent description of coherent EET dynamics in this typical photosynthetic pigment-protein complex.

A SAS-based solution to evaluate study design efficiency of phase I pediatric oncology trials via discrete event simulation.

PubMed

Barrett, Jeffrey S; Jayaraman, Bhuvana; Patel, Dimple; Skolnik, Jeffrey M

2008-06-01

Previous exploration of oncology study design efficiency has focused on Markov processes alone (probability-based events) without consideration for time dependencies. Barriers to study completion include time delays associated with patient accrual, inevaluability (IE), time to dose limiting toxicities (DLT) and administrative and review time. Discrete event simulation (DES) can incorporate probability-based assignment of DLT and IE frequency, correlated with cohort in the case of DLT, with time-based events defined by stochastic relationships. A SAS-based solution to examine study efficiency metrics and evaluate design modifications that would improve study efficiency is presented. Virtual patients are simulated with attributes defined from prior distributions of relevant patient characteristics. Study population datasets are read into SAS macros which select patients and enroll them into a study based on the specific design criteria if the study is open to enrollment. Waiting times, arrival times and time to study events are also sampled from prior distributions; post-processing of study simulations is provided within the decision macros and compared across designs in a separate post-processing algorithm. This solution is examined via comparison of the standard 3+3 decision rule relative to the "rolling 6" design, a newly proposed enrollment strategy for the phase I pediatric oncology setting.

OzFlux data: network integration from collection to curation

NASA Astrophysics Data System (ADS)

Isaac, Peter; Cleverly, James; McHugh, Ian; van Gorsel, Eva; Ewenz, Cacilia; Beringer, Jason

2017-06-01

Measurement of the exchange of energy and mass between the surface and the atmospheric boundary-layer by the eddy covariance technique has undergone great change in the last 2 decades. Early studies of these exchanges were confined to brief field campaigns in carefully controlled conditions followed by months of data analysis. Current practice is to run tower-based eddy covariance systems continuously over several years due to the need for continuous monitoring as part of a global effort to develop local-, regional-, continental- and global-scale budgets of carbon, water and energy. Efficient methods of processing the increased quantities of data are needed to maximise the time available for analysis and interpretation. Standardised methods are needed to remove differences in data processing as possible contributors to observed spatial variability. Furthermore, public availability of these data sets assists with undertaking global research efforts. The OzFlux data path has been developed (i) to provide a standard set of quality control and post-processing tools across the network, thereby facilitating inter-site integration and spatial comparisons; (ii) to increase the time available to researchers for analysis and interpretation by reducing the time spent collecting and processing data; (iii) to propagate both data and metadata to the final product; and (iv) to facilitate the use of the OzFlux data by adopting a standard file format and making the data available from web-based portals. Discovery of the OzFlux data set is facilitated through incorporation in FLUXNET data syntheses and the publication of collection metadata via the RIF-CS format. This paper serves two purposes. The first is to describe the data sets, along with their quality control and post-processing, for the other papers of this Special Issue. The second is to provide an example of one solution to the data collection and curation challenges that are encountered by similar flux tower networks worldwide.

Post-processing techniques to enhance reliability of assignment algorithm based performance measures : [technical summary].

DOT National Transportation Integrated Search

2011-01-01

Travel demand modeling plays a key role in the transportation system planning and evaluation process. The four-step sequential travel demand model is the most widely used technique in practice. Traffic assignment is the key step in the conventional f...

Insertion of lithium into electrochromic devices after completion

DOEpatents

Berland, Brian Spencer; Lanning, Bruce Roy; Frey, Jonathan Mack; Barrett, Kathryn Suzanne; DuPont, Paul Damon; Schaller, Ronald William

2015-12-22

The present disclosure describes methods of inserting lithium into an electrochromic device after completion. In the disclosed methods, an ideal amount of lithium can be added post-fabrication to maximize or tailor the free lithium ion density of a layer or the coloration range of a device. Embodiments are directed towards a method to insert lithium into the main device layers of an electrochromic device as a post-processing step after the device has been manufactured. In an embodiment, the methods described are designed to maximize the coloration range while compensating for blind charge loss.

Sea ice in the Baltic Sea - revisiting BASIS ice, a historical data set covering the period 1960/1961-1978/1979

NASA Astrophysics Data System (ADS)

Löptien, U.; Dietze, H.

2014-12-01

The Baltic Sea is a seasonally ice-covered, marginal sea in central northern Europe. It is an essential waterway connecting highly industrialised countries. Because ship traffic is intermittently hindered by sea ice, the local weather services have been monitoring sea ice conditions for decades. In the present study we revisit a historical monitoring data set, covering the winters 1960/1961 to 1978/1979. This data set, dubbed Data Bank for Baltic Sea Ice and Sea Surface Temperatures (BASIS) ice, is based on hand-drawn maps that were collected and then digitised in 1981 in a joint project of the Finnish Institute of Marine Research (today the Finnish Meteorological Institute (FMI)) and the Swedish Meteorological and Hydrological Institute (SMHI). BASIS ice was designed for storage on punch cards and all ice information is encoded by five digits. This makes the data hard to access. Here we present a post-processed product based on the original five-digit code. Specifically, we convert to standard ice quantities (including information on ice types), which we distribute in the current and free Network Common Data Format (NetCDF). Our post-processed data set will help to assess numerical ice models and provide easy-to-access unique historical reference material for sea ice in the Baltic Sea. In addition we provide statistics showcasing the data quality. The website http://www.baltic-ocean.org hosts the post-processed data and the conversion code. The data are also archived at the Data Publisher for Earth & Environmental Science, PANGAEA (doi:10.1594/PANGAEA.832353).

Diagnostic Value of Multidetector CT and Its Multiplanar Reformation, Volume Rendering and Virtual Bronchoscopy Postprocessing Techniques for Primary Trachea and Main Bronchus Tumors.

PubMed

Luo, Mingyue; Duan, Chaijie; Qiu, Jianping; Li, Wenru; Zhu, Dongyun; Cai, Wenli

2015-01-01

To evaluate the diagnostic value of multidetector CT (MDCT) and its multiplanar reformation (MPR), volume rendering (VR) and virtual bronchoscopy (VB) postprocessing techniques for primary trachea and main bronchus tumors. Detection results of 31 primary trachea and main bronchus tumors with MDCT and its MPR, VR and VB postprocessing techniques, were analyzed retrospectively with regard to tumor locations, tumor morphologies, extramural invasions of tumors, longitudinal involvements of tumors, morphologies and extents of luminal stenoses, distances between main bronchus tumors and trachea carinae, and internal features of tumors. The detection results were compared with that of surgery and pathology. Detection results with MDCT and its MPR, VR and VB were consistent with that of surgery and pathology, included tumor locations (tracheae, n = 19; right main bronchi, n = 6; left main bronchi, n = 6), tumor morphologies (endoluminal nodes with narrow bases, n = 2; endoluminal nodes with wide bases, n = 13; both intraluminal and extraluminal masses, n = 16), extramural invasions of tumors (brokethrough only serous membrane, n = 1; 4.0 mm-56.0 mm, n = 14; no clear border with right atelectasis, n = 1), longitudinal involvements of tumors (3.0 mm, n = 1; 5.0 mm-68.0 mm, n = 29; whole right main bronchus wall and trachea carina, n = 1), morphologies of luminal stenoses (irregular, n = 26; circular, n = 3; eccentric, n = 1; conical, n = 1) and extents (mild, n = 5; moderate, n = 7; severe, n = 19), distances between main bronchus tumors and trachea carinae (16.0 mm, n = 1; invaded trachea carina, n = 1; >20.0 mm, n = 10), and internal features of tumors (fairly homogeneous densities with rather obvious enhancements, n = 26; homogeneous density with obvious enhancement, n = 1; homogeneous density without obvious enhancement, n = 1; not enough homogeneous density with obvious enhancement, n = 1; punctate calcification with obvious enhancement, n = 1; low density without obvious enhancement, n = 1). MDCT and its MPR, VR and VB images have respective advantages and disadvantages. Their combination could complement to each other to accurately detect locations, natures (benignancy, malignancy or low malignancy), and quantities (extramural invasions, longitudinal involvements, extents of luminal stenoses, distances between main bronchus tumors and trachea carinae) of primary trachea and main bronchus tumors with crucial information for surgical treatment, are highly useful diagnostic methods for primary trachea and main bronchus tumors.

Postprocessing techniques for 3D non-linear structures

NASA Technical Reports Server (NTRS)

Gallagher, Richard S.

1987-01-01

How graphics postprocessing techniques are currently used to examine the results of 3-D nonlinear analyses, some new techniques which take advantage of recent technology, and how these results relate to both the finite element model and its geometric parent are reviewed.

Post-processing procedure for industrial quantum key distribution systems

NASA Astrophysics Data System (ADS)

Kiktenko, Evgeny; Trushechkin, Anton; Kurochkin, Yury; Fedorov, Aleksey

2016-08-01

We present algorithmic solutions aimed on post-processing procedure for industrial quantum key distribution systems with hardware sifting. The main steps of the procedure are error correction, parameter estimation, and privacy amplification. Authentication of classical public communication channel is also considered.

3D photo mosaicing of Tagiri shallow vent field by an autonomous underwater vehicle (3rd report) - Mosaicing method based on navigation data and visual features -

NASA Astrophysics Data System (ADS)

Maki, Toshihiro; Ura, Tamaki; Singh, Hanumant; Sakamaki, Takashi

Large-area seafloor imaging will bring significant benefits to various fields such as academics, resource survey, marine development, security, and search-and-rescue. The authors have proposed a navigation method of an autonomous underwater vehicle for seafloor imaging, and verified its performance through mapping tubeworm colonies with the area of 3,000 square meters using the AUV Tri-Dog 1 at Tagiri vent field, Kagoshima bay in Japan (Maki et al., 2008, 2009). This paper proposes a post-processing method to build a natural photo mosaic from a number of pictures taken by an underwater platform. The method firstly removes lens distortion, invariances of color and lighting from each image, and then ortho-rectification is performed based on camera pose and seafloor estimated by navigation data. The image alignment is based on both navigation data and visual characteristics, implemented as an expansion of the image based method (Pizarro et al., 2003). Using the two types of information realizes an image alignment that is consistent both globally and locally, as well as making the method applicable to data sets with little visual keys. The method was evaluated using a data set obtained by the AUV Tri-Dog 1 at the vent field in Sep. 2009. A seamless, uniformly illuminated photo mosaic covering the area of around 500 square meters was created from 391 pictures, which covers unique features of the field such as bacteria mats and tubeworm colonies.

LTRsift: a graphical user interface for semi-automatic classification and postprocessing of de novo detected LTR retrotransposons

PubMed Central

2012-01-01

Background Long terminal repeat (LTR) retrotransposons are a class of eukaryotic mobile elements characterized by a distinctive sequence similarity-based structure. Hence they are well suited for computational identification. Current software allows for a comprehensive genome-wide de novo detection of such elements. The obvious next step is the classification of newly detected candidates resulting in (super-)families. Such a de novo classification approach based on sequence-based clustering of transposon features has been proposed before, resulting in a preliminary assignment of candidates to families as a basis for subsequent manual refinement. However, such a classification workflow is typically split across a heterogeneous set of glue scripts and generic software (for example, spreadsheets), making it tedious for a human expert to inspect, curate and export the putative families produced by the workflow. Results We have developed LTRsift, an interactive graphical software tool for semi-automatic postprocessing of de novo predicted LTR retrotransposon annotations. Its user-friendly interface offers customizable filtering and classification functionality, displaying the putative candidate groups, their members and their internal structure in a hierarchical fashion. To ease manual work, it also supports graphical user interface-driven reassignment, splitting and further annotation of candidates. Export of grouped candidate sets in standard formats is possible. In two case studies, we demonstrate how LTRsift can be employed in the context of a genome-wide LTR retrotransposon survey effort. Conclusions LTRsift is a useful and convenient tool for semi-automated classification of newly detected LTR retrotransposons based on their internal features. Its efficient implementation allows for convenient and seamless filtering and classification in an integrated environment. Developed for life scientists, it is helpful in postprocessing and refining the output of software for predicting LTR retrotransposons up to the stage of preparing full-length reference sequence libraries. The LTRsift software is freely available at http://www.zbh.uni-hamburg.de/LTRsift under an open-source license. PMID:23131050

LTRsift: a graphical user interface for semi-automatic classification and postprocessing of de novo detected LTR retrotransposons.

PubMed

Steinbiss, Sascha; Kastens, Sascha; Kurtz, Stefan

2012-11-07

Long terminal repeat (LTR) retrotransposons are a class of eukaryotic mobile elements characterized by a distinctive sequence similarity-based structure. Hence they are well suited for computational identification. Current software allows for a comprehensive genome-wide de novo detection of such elements. The obvious next step is the classification of newly detected candidates resulting in (super-)families. Such a de novo classification approach based on sequence-based clustering of transposon features has been proposed before, resulting in a preliminary assignment of candidates to families as a basis for subsequent manual refinement. However, such a classification workflow is typically split across a heterogeneous set of glue scripts and generic software (for example, spreadsheets), making it tedious for a human expert to inspect, curate and export the putative families produced by the workflow. We have developed LTRsift, an interactive graphical software tool for semi-automatic postprocessing of de novo predicted LTR retrotransposon annotations. Its user-friendly interface offers customizable filtering and classification functionality, displaying the putative candidate groups, their members and their internal structure in a hierarchical fashion. To ease manual work, it also supports graphical user interface-driven reassignment, splitting and further annotation of candidates. Export of grouped candidate sets in standard formats is possible. In two case studies, we demonstrate how LTRsift can be employed in the context of a genome-wide LTR retrotransposon survey effort. LTRsift is a useful and convenient tool for semi-automated classification of newly detected LTR retrotransposons based on their internal features. Its efficient implementation allows for convenient and seamless filtering and classification in an integrated environment. Developed for life scientists, it is helpful in postprocessing and refining the output of software for predicting LTR retrotransposons up to the stage of preparing full-length reference sequence libraries. The LTRsift software is freely available at http://www.zbh.uni-hamburg.de/LTRsift under an open-source license.

A robust post-processing workflow for datasets with motion artifacts in diffusion kurtosis imaging.

PubMed

Li, Xianjun; Yang, Jian; Gao, Jie; Luo, Xue; Zhou, Zhenyu; Hu, Yajie; Wu, Ed X; Wan, Mingxi

2014-01-01

The aim of this study was to develop a robust post-processing workflow for motion-corrupted datasets in diffusion kurtosis imaging (DKI). The proposed workflow consisted of brain extraction, rigid registration, distortion correction, artifacts rejection, spatial smoothing and tensor estimation. Rigid registration was utilized to correct misalignments. Motion artifacts were rejected by using local Pearson correlation coefficient (LPCC). The performance of LPCC in characterizing relative differences between artifacts and artifact-free images was compared with that of the conventional correlation coefficient in 10 randomly selected DKI datasets. The influence of rejected artifacts with information of gradient directions and b values for the parameter estimation was investigated by using mean square error (MSE). The variance of noise was used as the criterion for MSEs. The clinical practicality of the proposed workflow was evaluated by the image quality and measurements in regions of interest on 36 DKI datasets, including 18 artifact-free (18 pediatric subjects) and 18 motion-corrupted datasets (15 pediatric subjects and 3 essential tremor patients). The relative difference between artifacts and artifact-free images calculated by LPCC was larger than that of the conventional correlation coefficient (p<0.05). It indicated that LPCC was more sensitive in detecting motion artifacts. MSEs of all derived parameters from the reserved data after the artifacts rejection were smaller than the variance of the noise. It suggested that influence of rejected artifacts was less than influence of noise on the precision of derived parameters. The proposed workflow improved the image quality and reduced the measurement biases significantly on motion-corrupted datasets (p<0.05). The proposed post-processing workflow was reliable to improve the image quality and the measurement precision of the derived parameters on motion-corrupted DKI datasets. The workflow provided an effective post-processing method for clinical applications of DKI in subjects with involuntary movements.

Mechanical behavior of post-processed Inconel 718 manufactured through the electron beam melting process

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

Kirka, Michael M.; Medina, Frank; Dehoff, Ryan R.

Here, the electron beam melting (EBM) process was used to fabricate Inconel 718. The microstructure and tensile properties were characterized in both the as-fabricated and post-processed state transverse (T-orientation) and longitudinal (L-orientation) to the build direction. Post-processing involved both a hot isostatic pressing (HIP) and solution treatment and aging (STA) to homogenize the microstructure. In the as-fabricated state, EBM Inconel 718 exhibits a spatially dependent microstructure that is a function of build height. Spanning the last few layers is a cored dendritic structure comprised of the products (carbides and Laves phase) predicted under equilibrium solidification conditions. With increasing distance frommore » the build's top surface, the cored dendritic structure becomes increasingly homogeneous with complete dissolution of the secondary dendrite arms. Further, temporal phase kinetics are observed to lead to the dissolution of the strengthening γ"γ" and precipitation of networks of fine δ needles that span the grains. Microstructurally, post-processing resulted in dissolution of the δ networks and homogeneous precipitation of γ'"γ'" throughout the height of the build. In the as-fabricated state, the monotonic tensile behavior exhibits a height sensitivity within the T-orientation at both 20 and 650 °C. Along the L-orientation, the tensile behavior exhibits strength values comparable to the reference wrought material in the fully heat-treated state. After post-processing, the yield strength, ultimate strength, and elongation at failure for the EBM Inconel 718 were observed to have beneficially increased compared to the as-fabricated material. Further, as a result of post-processing the spatial variance of the ultimate yield strength and elongation at failure within the transverse direction decreased by 4 and 3× respectively.« less

Mechanical behavior of post-processed Inconel 718 manufactured through the electron beam melting process

DOE PAGES

Kirka, Michael M.; Medina, Frank; Dehoff, Ryan R.; ...

2016-10-21

Here, the electron beam melting (EBM) process was used to fabricate Inconel 718. The microstructure and tensile properties were characterized in both the as-fabricated and post-processed state transverse (T-orientation) and longitudinal (L-orientation) to the build direction. Post-processing involved both a hot isostatic pressing (HIP) and solution treatment and aging (STA) to homogenize the microstructure. In the as-fabricated state, EBM Inconel 718 exhibits a spatially dependent microstructure that is a function of build height. Spanning the last few layers is a cored dendritic structure comprised of the products (carbides and Laves phase) predicted under equilibrium solidification conditions. With increasing distance frommore » the build's top surface, the cored dendritic structure becomes increasingly homogeneous with complete dissolution of the secondary dendrite arms. Further, temporal phase kinetics are observed to lead to the dissolution of the strengthening γ"γ" and precipitation of networks of fine δ needles that span the grains. Microstructurally, post-processing resulted in dissolution of the δ networks and homogeneous precipitation of γ'"γ'" throughout the height of the build. In the as-fabricated state, the monotonic tensile behavior exhibits a height sensitivity within the T-orientation at both 20 and 650 °C. Along the L-orientation, the tensile behavior exhibits strength values comparable to the reference wrought material in the fully heat-treated state. After post-processing, the yield strength, ultimate strength, and elongation at failure for the EBM Inconel 718 were observed to have beneficially increased compared to the as-fabricated material. Further, as a result of post-processing the spatial variance of the ultimate yield strength and elongation at failure within the transverse direction decreased by 4 and 3× respectively.« less

Laser post-processing of halide perovskites for enhanced photoluminescence and absorbance

NASA Astrophysics Data System (ADS)

Tiguntseva, E. Y.; Saraeva, I. N.; Kudryashov, S. I.; Ushakova, E. V.; Komissarenko, F. E.; Ishteev, A. R.; Tsypkin, A. N.; Haroldson, R.; Milichko, V. A.; Zuev, D. A.; Makarov, S. V.; Zakhidov, A. A.

2017-11-01

Hybrid halide perovskites have emerged as one of the most promising type of materials for thin-film photovoltaic and light-emitting devices. Further boosting their performance is critically important for commercialization. Here we use femtosecond laser for post-processing of organo-metalic perovskite (MAPbI3) films. The high throughput laser approaches include both ablative silicon nanoparticles integration and laser-induced annealing. By using these techniques, we achieve strong enhancement of photoluminescence as well as useful light absorption. As a result, we observed experimentally 10-fold enhancement of absorbance in a perovskite layer with the silicon nanoparticles. Direct laser annealing allows for increasing of photoluminescence over 130%, and increase absorbance over 300% in near-IR range. We believe that the developed approaches pave the way to novel scalable and highly effective designs of perovskite based devices.

A multiscale curvature algorithm for classifying discrete return LiDAR in forested environments

Treesearch

Jeffrey S. Evans; Andrew T. Hudak

2007-01-01

One prerequisite to the use of light detection and ranging (LiDAR) across disciplines is differentiating ground from nonground returns. The objective was to automatically and objectively classify points within unclassified LiDAR point clouds, with few model parameters and minimal postprocessing. Presented is an automated method for classifying LiDAR returns as ground...

Accelerating EPI distortion correction by utilizing a modern GPU-based parallel computation.

PubMed

Yang, Yao-Hao; Huang, Teng-Yi; Wang, Fu-Nien; Chuang, Tzu-Chao; Chen, Nan-Kuei

2013-04-01

The combination of phase demodulation and field mapping is a practical method to correct echo planar imaging (EPI) geometric distortion. However, since phase dispersion accumulates in each phase-encoding step, the calculation complexity of phase modulation is Ny-fold higher than conventional image reconstructions. Thus, correcting EPI images via phase demodulation is generally a time-consuming task. Parallel computing by employing general-purpose calculations on graphics processing units (GPU) can accelerate scientific computing if the algorithm is parallelized. This study proposes a method that incorporates the GPU-based technique into phase demodulation calculations to reduce computation time. The proposed parallel algorithm was applied to a PROPELLER-EPI diffusion tensor data set. The GPU-based phase demodulation method reduced the EPI distortion correctly, and accelerated the computation. The total reconstruction time of the 16-slice PROPELLER-EPI diffusion tensor images with matrix size of 128 × 128 was reduced from 1,754 seconds to 101 seconds by utilizing the parallelized 4-GPU program. GPU computing is a promising method to accelerate EPI geometric correction. The resulting reduction in computation time of phase demodulation should accelerate postprocessing for studies performed with EPI, and should effectuate the PROPELLER-EPI technique for clinical practice. Copyright © 2011 by the American Society of Neuroimaging.

Recent Developments in Advanced Automated Post-Processing at AMOS

DTIC Science & Technology

2014-09-01

Borelli KJS Consulting Lisa Thompson Air Force Research Laboratory ABSTRACT A new automated post-processing system has been developed to...the existing algorithms in addition to the development of new data processing features. 6. REFERENCES 1 Matson, C.L., Beckner, C.C., Borelli , K

Color postprocessing for 3-dimensional finite element mesh quality evaluation and evolving graphical workstation

NASA Technical Reports Server (NTRS)

Panthaki, Malcolm J.

1987-01-01

Three general tasks on general-purpose, interactive color graphics postprocessing for three-dimensional computational mechanics were accomplished. First, the existing program (POSTPRO3D) is ported to a high-resolution device. In the course of this transfer, numerous enhancements are implemented in the program. The performance of the hardware was evaluated from the point of view of engineering postprocessing, and the characteristics of future hardware were discussed. Second, interactive graphical tools implemented to facilitate qualitative mesh evaluation from a single analysis. The literature was surveyed and a bibliography compiled. Qualitative mesh sensors were examined, and the use of two-dimensional plots of unaveraged responses on the surface of three-dimensional continua was emphasized in an interactive color raster graphics environment. Finally, a postprocessing environment was designed for state-of-the-art workstation technology. Modularity, personalization of the environment, integration of the engineering design processes, and the development and use of high-level graphics tools are some of the features of the intended environment.

Cryo-balloon catheter localization in fluoroscopic images

NASA Astrophysics Data System (ADS)

Kurzendorfer, Tanja; Brost, Alexander; Jakob, Carolin; Mewes, Philip W.; Bourier, Felix; Koch, Martin; Kurzidim, Klaus; Hornegger, Joachim; Strobel, Norbert

2013-03-01

Minimally invasive catheter ablation has become the preferred treatment option for atrial fibrillation. Although the standard ablation procedure involves ablation points set by radio-frequency catheters, cryo-balloon catheters have even been reported to be more advantageous in certain cases. As electro-anatomical mapping systems do not support cryo-balloon ablation procedures, X-ray guidance is needed. However, current methods to provide support for cryo-balloon catheters in fluoroscopically guided ablation procedures rely heavily on manual user interaction. To improve this, we propose a first method for automatic cryo-balloon catheter localization in fluoroscopic images based on a blob detection algorithm. Our method is evaluated on 24 clinical images from 17 patients. The method successfully detected the cryoballoon in 22 out of 24 images, yielding a success rate of 91.6 %. The successful localization achieved an accuracy of 1.00 mm +/- 0.44 mm. Even though our methods currently fails in 8.4 % of the images available, it still offers a significant improvement over manual methods. Furthermore, detecting a landmark point along the cryo-balloon catheter can be a very important step for additional post-processing operations.

Super-pixel extraction based on multi-channel pulse coupled neural network

NASA Astrophysics Data System (ADS)

Xu, GuangZhu; Hu, Song; Zhang, Liu; Zhao, JingJing; Fu, YunXia; Lei, BangJun

2018-04-01

Super-pixel extraction techniques group pixels to form over-segmented image blocks according to the similarity among pixels. Compared with the traditional pixel-based methods, the image descripting method based on super-pixel has advantages of less calculation, being easy to perceive, and has been widely used in image processing and computer vision applications. Pulse coupled neural network (PCNN) is a biologically inspired model, which stems from the phenomenon of synchronous pulse release in the visual cortex of cats. Each PCNN neuron can correspond to a pixel of an input image, and the dynamic firing pattern of each neuron contains both the pixel feature information and its context spatial structural information. In this paper, a new color super-pixel extraction algorithm based on multi-channel pulse coupled neural network (MPCNN) was proposed. The algorithm adopted the block dividing idea of SLIC algorithm, and the image was divided into blocks with same size first. Then, for each image block, the adjacent pixels of each seed with similar color were classified as a group, named a super-pixel. At last, post-processing was adopted for those pixels or pixel blocks which had not been grouped. Experiments show that the proposed method can adjust the number of superpixel and segmentation precision by setting parameters, and has good potential for super-pixel extraction.

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

Comparison of nine tractography algorithms for detecting abnormal structural brain networks in Alzheimer’s disease

PubMed Central

Zhan, Liang; Zhou, Jiayu; Wang, Yalin; Jin, Yan; Jahanshad, Neda; Prasad, Gautam; Nir, Talia M.; Leonardo, Cassandra D.; Ye, Jieping; Thompson, Paul M.; for the Alzheimer’s Disease Neuroimaging Initiative

2015-01-01

Alzheimer’s disease (AD) involves a gradual breakdown of brain connectivity, and network analyses offer a promising new approach to track and understand disease progression. Even so, our ability to detect degenerative changes in brain networks depends on the methods used. Here we compared several tractography and feature extraction methods to see which ones gave best diagnostic classification for 202 people with AD, mild cognitive impairment or normal cognition, scanned with 41-gradient diffusion-weighted magnetic resonance imaging as part of the Alzheimer’s Disease Neuroimaging Initiative (ADNI) project. We computed brain networks based on whole brain tractography with nine different methods – four of them tensor-based deterministic (FACT, RK2, SL, and TL), two orientation distribution function (ODF)-based deterministic (FACT, RK2), two ODF-based probabilistic approaches (Hough and PICo), and one “ball-and-stick” approach (Probtrackx). Brain networks derived from different tractography algorithms did not differ in terms of classification performance on ADNI, but performing principal components analysis on networks helped classification in some cases. Small differences may still be detectable in a truly vast cohort, but these experiments help assess the relative advantages of different tractography algorithms, and different post-processing choices, when used for classification. PMID:25926791

An adaptive optics imaging system designed for clinical use.

PubMed

Zhang, Jie; Yang, Qiang; Saito, Kenichi; Nozato, Koji; Williams, David R; Rossi, Ethan A

2015-06-01

Here we demonstrate a new imaging system that addresses several major problems limiting the clinical utility of conventional adaptive optics scanning light ophthalmoscopy (AOSLO), including its small field of view (FOV), reliance on patient fixation for targeting imaging, and substantial post-processing time. We previously showed an efficient image based eye tracking method for real-time optical stabilization and image registration in AOSLO. However, in patients with poor fixation, eye motion causes the FOV to drift substantially, causing this approach to fail. We solve that problem here by tracking eye motion at multiple spatial scales simultaneously by optically and electronically integrating a wide FOV SLO (WFSLO) with an AOSLO. This multi-scale approach, implemented with fast tip/tilt mirrors, has a large stabilization range of ± 5.6°. Our method consists of three stages implemented in parallel: 1) coarse optical stabilization driven by a WFSLO image, 2) fine optical stabilization driven by an AOSLO image, and 3) sub-pixel digital registration of the AOSLO image. We evaluated system performance in normal eyes and diseased eyes with poor fixation. Residual image motion with incremental compensation after each stage was: 1) ~2-3 arc minutes, (arcmin) 2) ~0.5-0.8 arcmin and, 3) ~0.05-0.07 arcmin, for normal eyes. Performance in eyes with poor fixation was: 1) ~3-5 arcmin, 2) ~0.7-1.1 arcmin and 3) ~0.07-0.14 arcmin. We demonstrate that this system is capable of reducing image motion by a factor of ~400, on average. This new optical design provides additional benefits for clinical imaging, including a steering subsystem for AOSLO that can be guided by the WFSLO to target specific regions of interest such as retinal pathology and real-time averaging of registered images to eliminate image post-processing.

Fuzzy Filtering Method for Color Videos Corrupted by Additive Noise

PubMed Central

Ponomaryov, Volodymyr I.; Montenegro-Monroy, Hector; Nino-de-Rivera, Luis

2014-01-01

A novel method for the denoising of color videos corrupted by additive noise is presented in this paper. The proposed technique consists of three principal filtering steps: spatial, spatiotemporal, and spatial postprocessing. In contrast to other state-of-the-art algorithms, during the first spatial step, the eight gradient values in different directions for pixels located in the vicinity of a central pixel as well as the R, G, and B channel correlation between the analogous pixels in different color bands are taken into account. These gradient values give the information about the level of contamination then the designed fuzzy rules are used to preserve the image features (textures, edges, sharpness, chromatic properties, etc.). In the second step, two neighboring video frames are processed together. Possible local motions between neighboring frames are estimated using block matching procedure in eight directions to perform interframe filtering. In the final step, the edges and smoothed regions in a current frame are distinguished for final postprocessing filtering. Numerous simulation results confirm that this novel 3D fuzzy method performs better than other state-of-the-art techniques in terms of objective criteria (PSNR, MAE, NCD, and SSIM) as well as subjective perception via the human vision system in the different color videos. PMID:24688428

Method of calibrating an interferometer and reducing its systematic noise

NASA Technical Reports Server (NTRS)

Hammer, Philip D. (Inventor)

1997-01-01

Methods of operation and data analysis for an interferometer so as to eliminate the errors contributed by non-responsive or unstable pixels, interpixel gain variations that drift over time, and spurious noise that would otherwise degrade the operation of the interferometer are disclosed. The methods provide for either online or post-processing calibration. The methods apply prescribed reversible transformations that exploit the physical properties of interferograms obtained from said interferometer to derive a calibration reference signal for subsequent treatment of said interferograms for interpixel gain variations. A self-consistent approach for treating bad pixels is incorporated into the methods.

Correcting bulk in-plane motion artifacts in MRI using the point spread function.

PubMed

Lin, Wei; Wehrli, Felix W; Song, Hee Kwon

2005-09-01

A technique is proposed for correcting both translational and rotational motion artifacts in magnetic resonance imaging without the need to collect additional navigator data or to perform intensive postprocessing. The method is based on measuring the point spread function (PSF) by attaching one or two point-sized markers to the main imaging object. Following the isolation of a PSF marker from the acquired image, translational motion could be corrected directly from the modulation transfer function, without the need to determine the object's positions during the scan, although the shifts could be extracted if desired. Rotation is detected by analyzing the relative displacements of two such markers. The technique was evaluated with simulations, phantom and in vivo experiments.

Evaluation of microfluidic channels with optical coherence tomography

NASA Astrophysics Data System (ADS)

Czajkowski, J.; Prykäri, T.; Alarousu, E.; Lauri, J.; Myllylä, R.

2010-11-01

Application of time domain, ultra high resolution optical coherence tomography (UHR-OCT) in evaluation of microfluidic channels is demonstrated. Presented study was done using experimental UHR-OCT device based on a Kerr-lens mode locked Ti:sapphire femtosecond laser, a photonic crystal fibre and modified, free-space Michelson interferometer. To show potential of the technique, microfluidic chip fabricated by VTT Center for Printed Intelligence (Oulu, Finland) was measured. Ability for full volumetric reconstruction in non-contact manner enabled complete characterization of closed entity of a microfluidic channel without contamination and harm for the sample. Measurement, occurring problems, and methods of postprocessing for raw data are described. Results present completely resolved physical structure of the channel, its spatial dimensions, draft angles and evaluation of lamination quality.

Carbon nanotube thin film strain sensor models assembled using nano- and micro-scale imaging

NASA Astrophysics Data System (ADS)

Lee, Bo Mi; Loh, Kenneth J.; Yang, Yuan-Sen

2017-07-01

Nanomaterial-based thin films, particularly those based on carbon nanotubes (CNT), have brought forth tremendous opportunities for designing next-generation strain sensors. However, their strain sensing properties can vary depending on fabrication method, post-processing treatment, and types of CNTs and polymers employed. The objective of this study was to derive a CNT-based thin film strain sensor model using inputs from nano-/micro-scale experimental measurements of nanotube physical properties. This study began with fabricating ultra-low-concentration CNT-polymer thin films, followed by imaging them using atomic force microscopy. Image processing was employed for characterizing CNT dispersed shapes, lengths, and other physical attributes, and results were used for building five different types of thin film percolation-based models. Numerical simulations were conducted to assess how the morphology of dispersed CNTs in its 2D matrix affected bulk film electrical and electromechanical (strain sensing) properties. The simulation results showed that CNT morphology had a significant impact on strain sensing performance.

Wire-positioning algorithm for coreless Hall array sensors in current measurement

NASA Astrophysics Data System (ADS)

Chen, Wenli; Zhang, Huaiqing; Chen, Lin; Gu, Shanyun

2018-05-01

This paper presents a scheme of circular-arrayed, coreless Hall-effect current transformers. It can satisfy the demands of wide dynamic range and bandwidth current in the distribution system, as well as the demand of AC and DC simultaneous measurements. In order to improve the signal to noise ratio (SNR) of the sensor, a wire-positioning algorithm is proposed, which can improve the measurement accuracy based on the post-processing of measurement data. The simulation results demonstrate that the maximum errors are 70%, 6.1% and 0.95% corresponding to Ampère’s circuital method, approximate positioning algorithm and precise positioning algorithm, respectively. It is obvious that the accuracy of the positioning algorithm is significantly improved when compared with that of the Ampère’s circuital method. The maximum error of the positioning algorithm is smaller in the experiment.

Improvements on non-equilibrium and transport Green function techniques: The next-generation TRANSIESTA

NASA Astrophysics Data System (ADS)

Papior, Nick; Lorente, Nicolás; Frederiksen, Thomas; García, Alberto; Brandbyge, Mads

2017-03-01

We present novel methods implemented within the non-equilibrium Green function code (NEGF) TRANSIESTA based on density functional theory (DFT). Our flexible, next-generation DFT-NEGF code handles devices with one or multiple electrodes (Ne ≥ 1) with individual chemical potentials and electronic temperatures. We describe its novel methods for electrostatic gating, contour optimizations, and assertion of charge conservation, as well as the newly implemented algorithms for optimized and scalable matrix inversion, performance-critical pivoting, and hybrid parallelization. Additionally, a generic NEGF "post-processing" code (TBTRANS/PHTRANS) for electron and phonon transport is presented with several novelties such as Hamiltonian interpolations, Ne ≥ 1 electrode capability, bond-currents, generalized interface for user-defined tight-binding transport, transmission projection using eigenstates of a projected Hamiltonian, and fast inversion algorithms for large-scale simulations easily exceeding 106 atoms on workstation computers. The new features of both codes are demonstrated and bench-marked for relevant test systems.

Fast and accurate Voronoi density gridding from Lagrangian hydrodynamics data

NASA Astrophysics Data System (ADS)

Petkova, Maya A.; Laibe, Guillaume; Bonnell, Ian A.

2018-01-01

Voronoi grids have been successfully used to represent density structures of gas in astronomical hydrodynamics simulations. While some codes are explicitly built around using a Voronoi grid, others, such as Smoothed Particle Hydrodynamics (SPH), use particle-based representations and can benefit from constructing a Voronoi grid for post-processing their output. So far, calculating the density of each Voronoi cell from SPH data has been done numerically, which is both slow and potentially inaccurate. This paper proposes an alternative analytic method, which is fast and accurate. We derive an expression for the integral of a cubic spline kernel over the volume of a Voronoi cell and link it to the density of the cell. Mass conservation is ensured rigorously by the procedure. The method can be applied more broadly to integrate a spherically symmetric polynomial function over the volume of a random polyhedron.

Electrochemical and mechanical polishing and shaping method and system

NASA Technical Reports Server (NTRS)

Engelhaupt, Darell E. (Inventor); Gubarev, Mikhail V. (Inventor); Jones, William David (Inventor); Ramsey, Brian D. (Inventor); Benson, Carl M. (Inventor)

2011-01-01

A method and system are provided for the shaping and polishing of the surface of a material selected from the group consisting of electrically semi-conductive materials and conductive materials. An electrically non-conductive polishing lap incorporates a conductive electrode such that, when the polishing lap is placed on the material's surface, the electrode is placed in spaced-apart juxtaposition with respect to the material's surface. A liquid electrolyte is disposed between the material's surface and the electrode. The electrolyte has an electrochemical stability constant such that cathodic material deposition on the electrode is not supported when a current flows through the electrode, the electrolyte and the material. As the polishing lap and the material surface experience relative movement, current flows through the electrode based on (i) adherence to Faraday's Law, and (ii) a pre-processing profile of the surface and a desired post-processing profile of the surface.

Nondestructive Evaluation of Carbon Fiber Bicycle Frames Using Infrared Thermography

PubMed Central

Ibarra-Castanedo, Clemente; Klein, Matthieu; Maldague, Xavier; Sanchez-Beato, Alvaro

2017-01-01

Bicycle frames made of carbon fibre are extremely popular for high-performance cycling due to the stiffness-to-weight ratio, which enables greater power transfer. However, products manufactured using carbon fibre are sensitive to impact damage. Therefore, intelligent nondestructive evaluation is a required step to prevent failures and ensure a secure usage of the bicycle. This work proposes an inspection method based on active thermography, a proven technique successfully applied to other materials. Different configurations for the inspection are tested, including power and heating time. Moreover, experiments are applied to a real bicycle frame with generated impact damage of different energies. Tests show excellent results, detecting the generated damage during the inspection. When the results are combined with advanced image post-processing methods, the SNR is greatly increased, and the size and localization of the defects are clearly visible in the images. PMID:29156650

Comparison of GOES Cloud Classification Algorithms Employing Explicit and Implicit Physics

NASA Technical Reports Server (NTRS)

Bankert, Richard L.; Mitrescu, Cristian; Miller, Steven D.; Wade, Robert H.

2009-01-01

Cloud-type classification based on multispectral satellite imagery data has been widely researched and demonstrated to be useful for distinguishing a variety of classes using a wide range of methods. The research described here is a comparison of the classifier output from two very different algorithms applied to Geostationary Operational Environmental Satellite (GOES) data over the course of one year. The first algorithm employs spectral channel thresholding and additional physically based tests. The second algorithm was developed through a supervised learning method with characteristic features of expertly labeled image samples used as training data for a 1-nearest-neighbor classification. The latter's ability to identify classes is also based in physics, but those relationships are embedded implicitly within the algorithm. A pixel-to-pixel comparison analysis was done for hourly daytime scenes within a region in the northeastern Pacific Ocean. Considerable agreement was found in this analysis, with many of the mismatches or disagreements providing insight to the strengths and limitations of each classifier. Depending upon user needs, a rule-based or other postprocessing system that combines the output from the two algorithms could provide the most reliable cloud-type classification.

Pre- and Post-Processing Tools to Streamline the CFD Process

NASA Technical Reports Server (NTRS)

Dorney, Suzanne Miller

2002-01-01

This viewgraph presentation provides information on software development tools to facilitate the use of CFD (Computational Fluid Dynamics) codes. The specific CFD codes FDNS and CORSAIR are profiled, and uses for software development tools with these codes during pre-processing, interim-processing, and post-processing are explained.

Correction of Dual-PRF Doppler Velocity Outliers in the Presence of Aliasing

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

Altube, Patricia; Bech, Joan; Argemí, Oriol

In Doppler weather radars, the presence of unfolding errors or outliers is a well-known quality issue for radial velocity fields estimated using the dual–pulse repetition frequency (PRF) technique. Postprocessing methods have been developed to correct dual-PRF outliers, but these need prior application of a dealiasing algorithm for an adequate correction. Our paper presents an alternative procedure based on circular statistics that corrects dual-PRF errors in the presence of extended Nyquist aliasing. The correction potential of the proposed method is quantitatively tested by means of velocity field simulations and is exemplified in the application to real cases, including severe storm events.more » The comparison with two other existing correction methods indicates an improved performance in the correction of clustered outliers. The technique we propose is well suited for real-time applications requiring high-quality Doppler radar velocity fields, such as wind shear and mesocyclone detection algorithms, or assimilation in numerical weather prediction models.« less

Automated Reconstruction of Three-Dimensional Fish Motion, Forces, and Torques

PubMed Central

Voesenek, Cees J.; Pieters, Remco P. M.; van Leeuwen, Johan L.

2016-01-01

Fish can move freely through the water column and make complex three-dimensional motions to explore their environment, escape or feed. Nevertheless, the majority of swimming studies is currently limited to two-dimensional analyses. Accurate experimental quantification of changes in body shape, position and orientation (swimming kinematics) in three dimensions is therefore essential to advance biomechanical research of fish swimming. Here, we present a validated method that automatically tracks a swimming fish in three dimensions from multi-camera high-speed video. We use an optimisation procedure to fit a parameterised, morphology-based fish model to each set of video images. This results in a time sequence of position, orientation and body curvature. We post-process this data to derive additional kinematic parameters (e.g. velocities, accelerations) and propose an inverse-dynamics method to compute the resultant forces and torques during swimming. The presented method for quantifying 3D fish motion paves the way for future analyses of swimming biomechanics. PMID:26752597

Correction of Dual-PRF Doppler Velocity Outliers in the Presence of Aliasing

DOE PAGES

Altube, Patricia; Bech, Joan; Argemí, Oriol; ...

2017-07-18

In Doppler weather radars, the presence of unfolding errors or outliers is a well-known quality issue for radial velocity fields estimated using the dual–pulse repetition frequency (PRF) technique. Postprocessing methods have been developed to correct dual-PRF outliers, but these need prior application of a dealiasing algorithm for an adequate correction. Our paper presents an alternative procedure based on circular statistics that corrects dual-PRF errors in the presence of extended Nyquist aliasing. The correction potential of the proposed method is quantitatively tested by means of velocity field simulations and is exemplified in the application to real cases, including severe storm events.more » The comparison with two other existing correction methods indicates an improved performance in the correction of clustered outliers. The technique we propose is well suited for real-time applications requiring high-quality Doppler radar velocity fields, such as wind shear and mesocyclone detection algorithms, or assimilation in numerical weather prediction models.« less

Post-processing of 3D-printed parts using femtosecond and picosecond laser radiation

NASA Astrophysics Data System (ADS)

Mingareev, Ilya; Gehlich, Nils; Bonhoff, Tobias; Meiners, Wilhelm; Kelbassa, Ingomar; Biermann, Tim; Richardson, Martin C.

2014-03-01

Additive manufacturing, also known as 3D-printing, is a near-net shape manufacturing approach, delivering part geometry that can be considerably affected by various process conditions, heat-induced distortions, solidified melt droplets, partially fused powders, and surface modifications induced by the manufacturing tool motion and processing strategy. High-repetition rate femtosecond and picosecond laser radiation was utilized to improve surface quality of metal parts manufactured by laser additive techniques. Different laser scanning approaches were utilized to increase the ablation efficiency and to reduce the surface roughness while preserving the initial part geometry. We studied post-processing of 3D-shaped parts made of Nickel- and Titanium-base alloys by utilizing Selective Laser Melting (SLM) and Laser Metal Deposition (LMD) as additive manufacturing techniques. Process parameters such as the pulse energy, the number of layers and their spatial separation were varied. Surface processing in several layers was necessary to remove the excessive material, such as individual powder particles, and to reduce the average surface roughness from asdeposited 22-45 μm to a few microns. Due to the ultrafast laser-processing regime and the small heat-affected zone induced in materials, this novel integrated manufacturing approach can be used to post-process parts made of thermally and mechanically sensitive materials, and to attain complex designed shapes with micrometer precision.

Influence of Finite Element Software on Energy Release Rates Computed Using the Virtual Crack Closure Technique

NASA Technical Reports Server (NTRS)

Krueger, Ronald; Goetze, Dirk; Ransom, Jonathon (Technical Monitor)

2006-01-01

Strain energy release rates were computed along straight delamination fronts of Double Cantilever Beam, End-Notched Flexure and Single Leg Bending specimens using the Virtual Crack Closure Technique (VCCT). Th e results were based on finite element analyses using ABAQUS# and ANSYS# and were calculated from the finite element results using the same post-processing routine to assure a consistent procedure. Mixed-mode strain energy release rates obtained from post-processing finite elem ent results were in good agreement for all element types used and all specimens modeled. Compared to previous studies, the models made of s olid twenty-node hexahedral elements and solid eight-node incompatible mode elements yielded excellent results. For both codes, models made of standard brick elements and elements with reduced integration did not correctly capture the distribution of the energy release rate acr oss the width of the specimens for the models chosen. The results suggested that element types with similar formulation yield matching results independent of the finite element software used. For comparison, m ixed-mode strain energy release rates were also calculated within ABAQUS#/Standard using the VCCT for ABAQUS# add on. For all specimens mod eled, mixed-mode strain energy release rates obtained from ABAQUS# finite element results using post-processing were almost identical to re sults calculated using the VCCT for ABAQUS# add on.

Assimilating the Future for Better Forecasts and Earlier Warnings

NASA Astrophysics Data System (ADS)

Du, H.; Wheatcroft, E.; Smith, L. A.

2016-12-01

Multi-model ensembles have become popular tools to account for some of the uncertainty due to model inadequacy in weather and climate simulation-based predictions. The current multi-model forecasts focus on combining single model ensemble forecasts by means of statistical post-processing. Assuming each model is developed independently or with different primary target variables, each is likely to contain different dynamical strengths and weaknesses. Using statistical post-processing, such information is only carried by the simulations under a single model ensemble: no advantage is taken to influence simulations under the other models. A novel methodology, named Multi-model Cross Pollination in Time, is proposed for multi-model ensemble scheme with the aim of integrating the dynamical information regarding the future from each individual model operationally. The proposed approach generates model states in time via applying data assimilation scheme(s) to yield truly "multi-model trajectories". It is demonstrated to outperform traditional statistical post-processing in the 40-dimensional Lorenz96 flow. Data assimilation approaches are originally designed to improve state estimation from the past to the current time. The aim of this talk is to introduce a framework that uses data assimilation to improve model forecasts at future time (not to argue for any one particular data assimilation scheme). Illustration of applying data assimilation "in the future" to provide early warning of future high-impact events is also presented.

How to detect and reduce movement artifacts in near-infrared imaging using moving standard deviation and spline interpolation.

PubMed

Scholkmann, F; Spichtig, S; Muehlemann, T; Wolf, M

2010-05-01

Near-infrared imaging (NIRI) is a neuroimaging technique which enables us to non-invasively measure hemodynamic changes in the human brain. Since the technique is very sensitive, the movement of a subject can cause movement artifacts (MAs), which affect the signal quality and results to a high degree. No general method is yet available to reduce these MAs effectively. The aim was to develop a new MA reduction method. A method based on moving standard deviation and spline interpolation was developed. It enables the semi-automatic detection and reduction of MAs in the data. It was validated using simulated and real NIRI signals. The results show that a significant reduction of MAs and an increase in signal quality are achieved. The effectiveness and usability of the method is demonstrated by the improved detection of evoked hemodynamic responses. The present method can not only be used in the postprocessing of NIRI signals but also for other kinds of data containing artifacts, for example ECG or EEG signals.

Addressing Phase Errors in Fat-Water Imaging Using a Mixed Magnitude/Complex Fitting Method

PubMed Central

Hernando, D.; Hines, C. D. G.; Yu, H.; Reeder, S.B.

2012-01-01

Accurate, noninvasive measurements of liver fat content are needed for the early diagnosis and quantitative staging of nonalcoholic fatty liver disease. Chemical shift-based fat quantification methods acquire images at multiple echo times using a multiecho spoiled gradient echo sequence, and provide fat fraction measurements through postprocessing. However, phase errors, such as those caused by eddy currents, can adversely affect fat quantification. These phase errors are typically most significant at the first echo of the echo train, and introduce bias in complex-based fat quantification techniques. These errors can be overcome using a magnitude-based technique (where the phase of all echoes is discarded), but at the cost of significantly degraded signal-to-noise ratio, particularly for certain choices of echo time combinations. In this work, we develop a reconstruction method that overcomes these phase errors without the signal-to-noise ratio penalty incurred by magnitude fitting. This method discards the phase of the first echo (which is often corrupted) while maintaining the phase of the remaining echoes (where phase is unaltered). We test the proposed method on 104 patient liver datasets (from 52 patients, each scanned twice), where the fat fraction measurements are compared to coregistered spectroscopy measurements. We demonstrate that mixed fitting is able to provide accurate fat fraction measurements with high signal-to-noise ratio and low bias over a wide choice of echo combinations. PMID:21713978

Rapid Screening of Chemical Constituents in Rhizoma Anemarrhenae by UPLC-Q-TOF/MS Combined with Data Postprocessing Techniques

PubMed Central

Shan, Lanlan; Wu, Yuanyuan; Yuan, Lei; Zhang, Yani

2017-01-01

Rhizoma Anemarrhenae, a famous traditional Chinese medicine (TCM), is the dried rhizome of Anemarrhena asphodeloides Bge. (Anemarrhena Bunge of Liliaceae). The medicine presents anti-inflammatory, antipyretic, sedative, and diuretic effects. The chemical constituents of Rhizoma Anemarrhenae are complex and diverse, mainly including steroidal saponins, flavonoids, phenylpropanoids, benzophenones, and alkaloids. In this study, UPLC-Q-TOF/MS was used in combination with data postprocessing techniques, including characteristic fragments filter and neutral loss filter, to rapidly classify and identify the five types of substances in Rhizoma Anemarrhenae. On the basis of numerous literature reviews and according to the corresponding characteristic fragments produced by different types of compounds in combination with neutral loss filtering, we summarized the fragmentation patterns of the main five types of compounds and successfully screened and identified 32 chemical constituents in Rhizoma Anemarrhenae. The components included 18 steroidal saponins, 6 flavonoids, 4 phenylpropanoids, 2 alkaloids, and 2 benzophenones. The method established in this study provided necessary data for the study on the pharmacological effects of Rhizoma Anemarrhenae and also provided the basis for the chemical analysis and quality control of TCMs to promote the development of a method for chemical research on TCMs. PMID:29234389

MDCT evaluation of potential living renal donor, prior to laparoscopic donor nephrectomy: What the transplant surgeon wants to know?

PubMed Central

Ghonge, Nitin P; Gadanayak, Satyabrat; Rajakumari, Vijaya

2014-01-01

As Laparoscopic Donor Nephrectomy (LDN) offers several advantages for the donor such as lesser post-operative pain, fewer cosmetic concerns and faster recovery time, there is growing global trend towards LDN as compared to open nephrectomy. Comprehensive pre-LDN donor evaluation includes assessment of renal morphology including pelvi-calyceal and vascular system. Apart from donor selection, evaluation of the regional anatomy allows precise surgical planning. Due to limited visualization during laparoscopic renal harvesting, detailed pre-transplant evaluation of regional anatomy, including the renal venous anatomy is of utmost importance. MDCT is the modality of choice for pre-LDN evaluation of potential renal donors. Apart from appropriate scan protocol and post-processing methods, detailed understanding of surgical techniques is essential for the Radiologist for accurate image interpretation during pre-LDN MDCT evaluation of potential renal donors. This review article describes MDCT evaluation of potential living renal donor, prior to LDN with emphasis on scan protocol, post-processing methods and image interpretation. The article laid special emphasis on surgical perspectives of pre-LDN MDCT evaluation and addresses important points which transplant surgeons want to know. PMID:25489130

Rapid Screening of Chemical Constituents in Rhizoma Anemarrhenae by UPLC-Q-TOF/MS Combined with Data Postprocessing Techniques.

PubMed

Shan, Lanlan; Wu, Yuanyuan; Yuan, Lei; Zhang, Yani; Xu, Yanyan; Li, Yubo

2017-01-01

Rhizoma Anemarrhenae , a famous traditional Chinese medicine (TCM), is the dried rhizome of Anemarrhena asphodeloides Bge. ( Anemarrhena Bunge of Liliaceae). The medicine presents anti-inflammatory, antipyretic, sedative, and diuretic effects. The chemical constituents of Rhizoma Anemarrhenae are complex and diverse, mainly including steroidal saponins, flavonoids, phenylpropanoids, benzophenones, and alkaloids. In this study, UPLC-Q-TOF/MS was used in combination with data postprocessing techniques, including characteristic fragments filter and neutral loss filter, to rapidly classify and identify the five types of substances in Rhizoma Anemarrhenae . On the basis of numerous literature reviews and according to the corresponding characteristic fragments produced by different types of compounds in combination with neutral loss filtering, we summarized the fragmentation patterns of the main five types of compounds and successfully screened and identified 32 chemical constituents in Rhizoma Anemarrhenae . The components included 18 steroidal saponins, 6 flavonoids, 4 phenylpropanoids, 2 alkaloids, and 2 benzophenones. The method established in this study provided necessary data for the study on the pharmacological effects of Rhizoma Anemarrhenae and also provided the basis for the chemical analysis and quality control of TCMs to promote the development of a method for chemical research on TCMs.

Experimental Tracking of Limit-Point Bifurcations and Backbone Curves Using Control-Based Continuation

NASA Astrophysics Data System (ADS)

Renson, Ludovic; Barton, David A. W.; Neild, Simon A.

Control-based continuation (CBC) is a means of applying numerical continuation directly to a physical experiment for bifurcation analysis without the use of a mathematical model. CBC enables the detection and tracking of bifurcations directly, without the need for a post-processing stage as is often the case for more traditional experimental approaches. In this paper, we use CBC to directly locate limit-point bifurcations of a periodically forced oscillator and track them as forcing parameters are varied. Backbone curves, which capture the overall frequency-amplitude dependence of the system’s forced response, are also traced out directly. The proposed method is demonstrated on a single-degree-of-freedom mechanical system with a nonlinear stiffness characteristic. Results are presented for two configurations of the nonlinearity — one where it exhibits a hardening stiffness characteristic and one where it exhibits softening-hardening.

Key Reconciliation for High Performance Quantum Key Distribution

PubMed Central

Martinez-Mateo, Jesus; Elkouss, David; Martin, Vicente

2013-01-01

Quantum Key Distribution is carving its place among the tools used to secure communications. While a difficult technology, it enjoys benefits that set it apart from the rest, the most prominent is its provable security based on the laws of physics. QKD requires not only the mastering of signals at the quantum level, but also a classical processing to extract a secret-key from them. This postprocessing has been customarily studied in terms of the efficiency, a figure of merit that offers a biased view of the performance of real devices. Here we argue that it is the throughput the significant magnitude in practical QKD, specially in the case of high speed devices, where the differences are more marked, and give some examples contrasting the usual postprocessing schemes with new ones from modern coding theory. A good understanding of its implications is very important for the design of modern QKD devices. PMID:23546440

Security proof of continuous-variable quantum key distribution using three coherent states

NASA Astrophysics Data System (ADS)

Brádler, Kamil; Weedbrook, Christian

2018-02-01

We introduce a ternary quantum key distribution (QKD) protocol and asymptotic security proof based on three coherent states and homodyne detection. Previous work had considered the binary case of two coherent states and here we nontrivially extend this to three. Our motivation is to leverage the practical benefits of both discrete and continuous (Gaussian) encoding schemes creating a best-of-both-worlds approach; namely, the postprocessing of discrete encodings and the hardware benefits of continuous ones. We present a thorough and detailed security proof in the limit of infinite signal states which allows us to lower bound the secret key rate. We calculate this is in the context of collective eavesdropping attacks and reverse reconciliation postprocessing. Finally, we compare the ternary coherent state protocol to other well-known QKD schemes (and fundamental repeaterless limits) in terms of secret key rates and loss.

Non-invasive imaging methods applied to neo- and paleontological cephalopod research

NASA Astrophysics Data System (ADS)

Hoffmann, R.; Schultz, J. A.; Schellhorn, R.; Rybacki, E.; Keupp, H.; Gerden, S. R.; Lemanis, R.; Zachow, S.

2013-11-01

Several non-invasive methods are common practice in natural sciences today. Here we present how they can be applied and contribute to current topics in cephalopod (paleo-) biology. Different methods will be compared in terms of time necessary to acquire the data, amount of data, accuracy/resolution, minimum-maximum size of objects that can be studied, of the degree of post-processing needed and availability. Main application of the methods is seen in morphometry and volumetry of cephalopod shells in order to improve our understanding of diversity and disparity, functional morphology and biology of extinct and extant cephalopods.

Unbiased All-Optical Random-Number Generator

NASA Astrophysics Data System (ADS)

Steinle, Tobias; Greiner, Johannes N.; Wrachtrup, Jörg; Giessen, Harald; Gerhardt, Ilja

2017-10-01

The generation of random bits is of enormous importance in modern information science. Cryptographic security is based on random numbers which require a physical process for their generation. This is commonly performed by hardware random-number generators. These often exhibit a number of problems, namely experimental bias, memory in the system, and other technical subtleties, which reduce the reliability in the entropy estimation. Further, the generated outcome has to be postprocessed to "iron out" such spurious effects. Here, we present a purely optical randomness generator, based on the bistable output of an optical parametric oscillator. Detector noise plays no role and postprocessing is reduced to a minimum. Upon entering the bistable regime, initially the resulting output phase depends on vacuum fluctuations. Later, the phase is rigidly locked and can be well determined versus a pulse train, which is derived from the pump laser. This delivers an ambiguity-free output, which is reliably detected and associated with a binary outcome. The resulting random bit stream resembles a perfect coin toss and passes all relevant randomness measures. The random nature of the generated binary outcome is furthermore confirmed by an analysis of resulting conditional entropies.

Integrating magnetic resonance imaging postprocessing results into neuronavigation for electrode implantation and resection of subtle focal cortical dysplasia in previously cryptogenic epilepsy.

PubMed

Wellmer, Jörg; Parpaley, Yaroslav; von Lehe, Marec; Huppertz, Hans-Jürgen

2010-01-01

Focal cortical dysplasias (FCDs) are highly epileptogenic lesions. Surgical removal is frequently the best treatment option for pharmacoresistant epilepsy. However, subtle FCDs may remain undetected even after high-resolution magnetic resonance imaging (MRI). Morphometric MRI analysis, which compares the individual brain with a normal database, can facilitate the detection of FCDs. We describe how the results of normal database-based MRI postprocessing can be used to guide stereotactic electrode implantation and subsequent resection of lesions that are suspected to be FCDs. A presurgical evaluation was conducted on a 19-year-old woman with pharmacoresistant hypermotor seizures. Conventional high-resolution MRI was classified as negative for epileptogenic lesions. However, morphometric analysis of the spatially normalized MRI revealed abnormal gyration and blurring of the gray-white matter junction, which was suggestive of a small and deeply seated FCD in the left frontal lobe. The brain region highlighted by morphometric analysis was marked as a region of interest, transferred back to the original dimension of the individual MRI, and imported into a neuronavigation system. This allowed the region of interest-targeted stereotactic implantation of 2 depth electrodes, by which seizure onset was confirmed in the lesion. The electrodes also guided the final resection, which rendered the patient seizure-free. The lesion was histologically classified as FCD Palmini and Lüders IIB. Transferring normal database-based MRI postprocessing results into a neuronavigation system is a new and worthwhile extension of multimodal neuronavigation. The combination of resulting regions of interest with functional and anatomic data may facilitate planning of electrode implantation for invasive electroencephalographic recordings and the final resection of small or deeply seated FCDs.

Impacts of weighting climate models for hydro-meteorological climate change studies

NASA Astrophysics Data System (ADS)

Chen, Jie; Brissette, François P.; Lucas-Picher, Philippe; Caya, Daniel

2017-06-01

Weighting climate models is controversial in climate change impact studies using an ensemble of climate simulations from different climate models. In climate science, there is a general consensus that all climate models should be considered as having equal performance or in other words that all projections are equiprobable. On the other hand, in the impacts and adaptation community, many believe that climate models should be weighted based on their ability to better represent various metrics over a reference period. The debate appears to be partly philosophical in nature as few studies have investigated the impact of using weights in projecting future climate changes. The present study focuses on the impact of assigning weights to climate models for hydrological climate change studies. Five methods are used to determine weights on an ensemble of 28 global climate models (GCMs) adapted from the Coupled Model Intercomparison Project Phase 5 (CMIP5) database. Using a hydrological model, streamflows are computed over a reference (1961-1990) and future (2061-2090) periods, with and without post-processing climate model outputs. The impacts of using different weighting schemes for GCM simulations are then analyzed in terms of ensemble mean and uncertainty. The results show that weighting GCMs has a limited impact on both projected future climate in term of precipitation and temperature changes and hydrology in terms of nine different streamflow criteria. These results apply to both raw and post-processed GCM model outputs, thus supporting the view that climate models should be considered equiprobable.

The development of algorithms for the deployment of new version of GEM-detector-based acquisition system

NASA Astrophysics Data System (ADS)

Krawczyk, Rafał D.; Czarski, Tomasz; Kolasiński, Piotr; Linczuk, Paweł; Poźniak, Krzysztof T.; Chernyshova, Maryna; Kasprowicz, Grzegorz; Wojeński, Andrzej; Zabolotny, Wojciech; Zienkiewicz, Paweł

2016-09-01

This article is an overview of what has been implemented in the process of development and testing the GEM detector based acquisition system in terms of post-processing algorithms. Information is given on mex functions for extended statistics collection, unified hex topology and optimized S-DAQ algorithm for splitting overlapped signals. Additional discussion on bottlenecks and major factors concerning optimization is presented.

The convergence of spectral methods for nonlinear conservation laws

NASA Technical Reports Server (NTRS)

Tadmor, Eitan

1987-01-01

The convergence of the Fourier method for scalar nonlinear conservation laws which exhibit spontaneous shock discontinuities is discussed. Numerical tests indicate that the convergence may (and in fact in some cases must) fail, with or without post-processing of the numerical solution. Instead, a new kind of spectrally accurate vanishing viscosity is introduced to augment the Fourier approximation of such nonlinear conservation laws. Using compensated compactness arguments, it is shown that this spectral viscosity prevents oscillations, and convergence to the unique entropy solution follows.

Living in the Post-Process Writing Center

ERIC Educational Resources Information Center

Shafer, Gregory

2012-01-01

In this article, the author talks about the college writing center, which is a place of political confrontation, where cultural issues involving dialect and values are probed, contested, and negotiated. He suggests a post-process approach to composition--one that ushers writers into a world of exploration and social engagement--one that transcends…

U.S. Geological Survey groundwater toolbox, a graphical and mapping interface for analysis of hydrologic data (version 1.0): user guide for estimation of base flow, runoff, and groundwater recharge from streamflow data

USGS Publications Warehouse

Barlow, Paul M.; Cunningham, William L.; Zhai, Tong; Gray, Mark

2015-01-01

This report is a user guide for the streamflow-hydrograph analysis methods provided with version 1.0 of the U.S. Geological Survey (USGS) Groundwater Toolbox computer program. These include six hydrograph-separation methods to determine the groundwater-discharge (base-flow) and surface-runoff components of streamflow—the Base-Flow Index (BFI; Standard and Modified), HYSEP (Fixed Interval, Sliding Interval, and Local Minimum), and PART methods—and the RORA recession-curve displacement method and associated RECESS program to estimate groundwater recharge from streamflow data. The Groundwater Toolbox is a customized interface built on the nonproprietary, open source MapWindow geographic information system software. The program provides graphing, mapping, and analysis capabilities in a Microsoft Windows computing environment. In addition to the four hydrograph-analysis methods, the Groundwater Toolbox allows for the retrieval of hydrologic time-series data (streamflow, groundwater levels, and precipitation) from the USGS National Water Information System, downloading of a suite of preprocessed geographic information system coverages and meteorological data from the National Oceanic and Atmospheric Administration National Climatic Data Center, and analysis of data with several preprocessing and postprocessing utilities. With its data retrieval and analysis tools, the Groundwater Toolbox provides methods to estimate many of the components of the water budget for a hydrologic basin, including precipitation; streamflow; base flow; runoff; groundwater recharge; and total, groundwater, and near-surface evapotranspiration.

Evaluation of ensemble precipitation forecasts generated through post-processing in a Canadian catchment

NASA Astrophysics Data System (ADS)

Jha, Sanjeev K.; Shrestha, Durga L.; Stadnyk, Tricia A.; Coulibaly, Paulin

2018-03-01

Flooding in Canada is often caused by heavy rainfall during the snowmelt period. Hydrologic forecast centers rely on precipitation forecasts obtained from numerical weather prediction (NWP) models to enforce hydrological models for streamflow forecasting. The uncertainties in raw quantitative precipitation forecasts (QPFs) are enhanced by physiography and orography effects over a diverse landscape, particularly in the western catchments of Canada. A Bayesian post-processing approach called rainfall post-processing (RPP), developed in Australia (Robertson et al., 2013; Shrestha et al., 2015), has been applied to assess its forecast performance in a Canadian catchment. Raw QPFs obtained from two sources, Global Ensemble Forecasting System (GEFS) Reforecast 2 project, from the National Centers for Environmental Prediction, and Global Deterministic Forecast System (GDPS), from Environment and Climate Change Canada, are used in this study. The study period from January 2013 to December 2015 covered a major flood event in Calgary, Alberta, Canada. Post-processed results show that the RPP is able to remove the bias and reduce the errors of both GEFS and GDPS forecasts. Ensembles generated from the RPP reliably quantify the forecast uncertainty.

A computerized recognition system for the home-based physiotherapy exercises using an RGBD camera.

PubMed

Ar, Ilktan; Akgul, Yusuf Sinan

2014-11-01

Computerized recognition of the home based physiotherapy exercises has many benefits and it has attracted considerable interest among the computer vision community. However, most methods in the literature view this task as a special case of motion recognition. In contrast, we propose to employ the three main components of a physiotherapy exercise (the motion patterns, the stance knowledge, and the exercise object) as different recognition tasks and embed them separately into the recognition system. The low level information about each component is gathered using machine learning methods. Then, we use a generative Bayesian network to recognize the exercise types by combining the information from these sources at an abstract level, which takes the advantage of domain knowledge for a more robust system. Finally, a novel postprocessing step is employed to estimate the exercise repetitions counts. The performance evaluation of the system is conducted with a new dataset which contains RGB (red, green, and blue) and depth videos of home-based exercise sessions for commonly applied shoulder and knee exercises. The proposed system works without any body-part segmentation, bodypart tracking, joint detection, and temporal segmentation methods. In the end, favorable exercise recognition rates and encouraging results on the estimation of repetition counts are obtained.

Manufacture of a Polyaniline Nanofiber Ammonia Sensor Integrated with a Readout Circuit Using the CMOS-MEMS Technique

PubMed Central

Liu, Mao-Chen; Dai, Ching-Liang; Chan, Chih-Hua; Wu, Chyan-Chyi

2009-01-01

This study presents the fabrication of a polyaniline nanofiber ammonia sensor integrated with a readout circuit on a chip using the commercial 0.35 μm complementary metal oxide semiconductor (CMOS) process and a post-process. The micro ammonia sensor consists of a sensing resistor and an ammonia sensing film. Polyaniline prepared by a chemical polymerization method was adopted as the ammonia sensing film. The fabrication of the ammonia sensor needs a post-process to etch the sacrificial layers and to expose the sensing resistor, and then the ammonia sensing film is coated on the sensing resistor. The ammonia sensor, which is of resistive type, changes its resistance when the sensing film adsorbs or desorbs ammonia gas. A readout circuit is employed to convert the resistance of the ammonia sensor into the voltage output. Experimental results show that the sensitivity of the ammonia sensor is about 0.88 mV/ppm at room temperature. PMID:22399944

Manufacture of a Polyaniline Nanofiber Ammonia Sensor Integrated with a Readout Circuit Using the CMOS-MEMS Technique.

PubMed

Liu, Mao-Chen; Dai, Ching-Liang; Chan, Chih-Hua; Wu, Chyan-Chyi

2009-01-01

This study presents the fabrication of a polyaniline nanofiber ammonia sensor integrated with a readout circuit on a chip using the commercial 0.35 μm complementary metal oxide semiconductor (CMOS) process and a post-process. The micro ammonia sensor consists of a sensing resistor and an ammonia sensing film. Polyaniline prepared by a chemical polymerization method was adopted as the ammonia sensing film. The fabrication of the ammonia sensor needs a post-process to etch the sacrificial layers and to expose the sensing resistor, and then the ammonia sensing film is coated on the sensing resistor. The ammonia sensor, which is of resistive type, changes its resistance when the sensing film adsorbs or desorbs ammonia gas. A readout circuit is employed to convert the resistance of the ammonia sensor into the voltage output. Experimental results show that the sensitivity of the ammonia sensor is about 0.88 mV/ppm at room temperature.

Manufacture of radio frequency micromachined switches with annealing.

PubMed

Lin, Cheng-Yang; Dai, Ching-Liang

2014-01-17

The fabrication and characterization of a radio frequency (RF) micromachined switch with annealing were presented. The structure of the RF switch consists of a membrane, coplanar waveguide (CPW) lines, and eight springs. The RF switch is manufactured using the complementary metal oxide semiconductor (CMOS) process. The switch requires a post-process to release the membrane and springs. The post-process uses a wet etching to remove the sacrificial silicon dioxide layer, and to obtain the suspended structures of the switch. In order to improve the residual stress of the switch, an annealing process is applied to the switch, and the membrane obtains an excellent flatness. The finite element method (FEM) software CoventorWare is utilized to simulate the stress and displacement of the RF switch. Experimental results show that the RF switch has an insertion loss of 0.9 dB at 35 GHz and an isolation of 21 dB at 39 GHz. The actuation voltage of the switch is 14 V.

Manufacture of Radio Frequency Micromachined Switches with Annealing

PubMed Central

Lin, Cheng-Yang; Dai, Ching-Liang

2014-01-01

The fabrication and characterization of a radio frequency (RF) micromachined switch with annealing were presented. The structure of the RF switch consists of a membrane, coplanar waveguide (CPW) lines, and eight springs. The RF switch is manufactured using the complementary metal oxide semiconductor (CMOS) process. The switch requires a post-process to release the membrane and springs. The post-process uses a wet etching to remove the sacrificial silicon dioxide layer, and to obtain the suspended structures of the switch. In order to improve the residual stress of the switch, an annealing process is applied to the switch, and the membrane obtains an excellent flatness. The finite element method (FEM) software CoventorWare is utilized to simulate the stress and displacement of the RF switch. Experimental results show that the RF switch has an insertion loss of 0.9 dB at 35 GHz and an isolation of 21 dB at 39 GHz. The actuation voltage of the switch is 14 V. PMID:24445415

A Fast Smoothing Algorithm for Post-Processing of Surface Reflectance Spectra Retrieved from Airborne Imaging Spectrometer Data

PubMed Central

Gao, Bo-Cai; Liu, Ming

2013-01-01

Surface reflectance spectra retrieved from remotely sensed hyperspectral imaging data using radiative transfer models often contain residual atmospheric absorption and scattering effects. The reflectance spectra may also contain minor artifacts due to errors in radiometric and spectral calibrations. We have developed a fast smoothing technique for post-processing of retrieved surface reflectance spectra. In the present spectral smoothing technique, model-derived reflectance spectra are first fit using moving filters derived with a cubic spline smoothing algorithm. A common gain curve, which contains minor artifacts in the model-derived reflectance spectra, is then derived. This gain curve is finally applied to all of the reflectance spectra in a scene to obtain the spectrally smoothed surface reflectance spectra. Results from analysis of hyperspectral imaging data collected with the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data are given. Comparisons between the smoothed spectra and those derived with the empirical line method are also presented. PMID:24129022

Multi-font printed Mongolian document recognition system

NASA Astrophysics Data System (ADS)

Peng, Liangrui; Liu, Changsong; Ding, Xiaoqing; Wang, Hua; Jin, Jianming

2009-01-01

Mongolian is one of the major ethnic languages in China. Large amount of Mongolian printed documents need to be digitized in digital library and various applications. Traditional Mongolian script has unique writing style and multi-font-type variations, which bring challenges to Mongolian OCR research. As traditional Mongolian script has some characteristics, for example, one character may be part of another character, we define the character set for recognition according to the segmented components, and the components are combined into characters by rule-based post-processing module. For character recognition, a method based on visual directional feature and multi-level classifiers is presented. For character segmentation, a scheme is used to find the segmentation point by analyzing the properties of projection and connected components. As Mongolian has different font-types which are categorized into two major groups, the parameter of segmentation is adjusted for each group. A font-type classification method for the two font-type group is introduced. For recognition of Mongolian text mixed with Chinese and English, language identification and relevant character recognition kernels are integrated. Experiments show that the presented methods are effective. The text recognition rate is 96.9% on the test samples from practical documents with multi-font-types and mixed scripts.

Quality of reconstruction of compressed off-axis digital holograms by frequency filtering and wavelets.

PubMed

Cheremkhin, Pavel A; Kurbatova, Ekaterina A

2018-01-01

Compression of digital holograms can significantly help with the storage of objects and data in 2D and 3D form, its transmission, and its reconstruction. Compression of standard images by methods based on wavelets allows high compression ratios (up to 20-50 times) with minimum losses of quality. In the case of digital holograms, application of wavelets directly does not allow high values of compression to be obtained. However, additional preprocessing and postprocessing can afford significant compression of holograms and the acceptable quality of reconstructed images. In this paper application of wavelet transforms for compression of off-axis digital holograms are considered. The combined technique based on zero- and twin-order elimination, wavelet compression of the amplitude and phase components of the obtained Fourier spectrum, and further additional compression of wavelet coefficients by thresholding and quantization is considered. Numerical experiments on reconstruction of images from the compressed holograms are performed. The comparative analysis of applicability of various wavelets and methods of additional compression of wavelet coefficients is performed. Optimum parameters of compression of holograms by the methods can be estimated. Sizes of holographic information were decreased up to 190 times.

Removal of correlated noise online for in situ measurements by using multichannel magnetic resonance sounding system

NASA Astrophysics Data System (ADS)

Lin, Tingting; Zhang, Siyuan; Zhang, Yang; Wan, Ling; Lin, Jun

2017-01-01

Compared with the other geophysical approaches, magnetic resonance sounding (MRS) technique is direct and nondestructive in subsurface water exploration. It provides water content distribution and estimates hydrogeological properties. The biggest challenge is that MRS measurement always suffers bad signal-to-noise ratio, and it can be carried out only far from sources of noise. To solve this problem, a series of de-noising methods are developed. However, most of them are post-processing, leading the data quality uncontrolled for in situ measurements. In the present study, a new approach that removal of correlated noise online is found to overcome the restriction. Based on LabVIEW, a method is provided to enable online data quality control by the way of realizing signal acquisition and noise filtering simultaneously. Using one or more reference coils, adaptive noise cancellation based on LabVIEW to eliminate the correlated noise is available for in situ measurements. The approach was examined through numerical simulation and field measurements. The correlated noise is mitigated effectively and the application of MRS measurements is feasible in high-level noise environment. The method shortens the measurement time and improves the measurement efficiency.

Supersampling multiframe blind deconvolution resolution enhancement of adaptive optics compensated imagery of low earth orbit satellites

NASA Astrophysics Data System (ADS)

Gerwe, David R.; Lee, David J.; Barchers, Jeffrey D.

2002-09-01

We describe a postprocessing methodology for reconstructing undersampled image sequences with randomly varying blur that can provide image enhancement beyond the sampling resolution of the sensor. This method is demonstrated on simulated imagery and on adaptive-optics-(AO)-compensated imagery taken by the Starfire Optical Range 3.5-m telescope that has been artificially undersampled. Also shown are the results of multiframe blind deconvolution of some of the highest quality optical imagery of low earth orbit satellites collected with a ground-based telescope to date. The algorithm used is a generalization of multiframe blind deconvolution techniques that include a representation of spatial sampling by the focal plane array elements based on a forward stochastic model. This generalization enables the random shifts and shape of the AO- compensated point spread function (PSF) to be used to partially eliminate the aliasing effects associated with sub-Nyquist sampling of the image by the focal plane array. The method could be used to reduce resolution loss that occurs when imaging in wide- field-of-view (FOV) modes.

Post-processing of auditory steady-state responses to correct spectral leakage.

PubMed

Felix, Leonardo Bonato; de Sá, Antonio Mauricio Ferreira Leite Miranda; Mendes, Eduardo Mazoni Andrade Marçal; Moraes, Márcio Flávio Dutra

2009-06-30

Auditory steady-state responses (ASSRs) are electrical manifestations of brain due to high rate sound stimulation. These evoked responses can be used to assess the hearing capabilities of a subject in an objective, automatic fashion. Usually, the detection protocol is accomplished by frequency-domain techniques, such as magnitude-squared coherence, whose estimation is based on the fast Fourier transform (FFT) of several data segments. In practice, the FFT-based spectrum may spread out the energy of a given frequency to its side bins and this escape of energy in the spectrum is called spectral leakage. The distortion of the spectrum due to leakage may severely compromise statistical significance of objective detection. This work presents an offline, a posteriori method for spectral leakage minimization in the frequency-domain analysis of ASSRs using coherent sampling criterion and interpolation in time. The technique was applied to the local field potentials of 10 Wistar rats and the results, together with those from simulated data, indicate that a leakage-free analysis of ASSRs is possible for any dataset if the methods showed in this paper were followed.

Motion compensated shape error concealment.

PubMed

Schuster, Guido M; Katsaggelos, Aggelos K

2006-02-01

The introduction of Video Objects (VOs) is one of the innovations of MPEG-4. The alpha-plane of a VO defines its shape at a given instance in time and hence determines the boundary of its texture. In packet-based networks, shape, motion, and texture are subject to loss. While there has been considerable attention paid to the concealment of texture and motion errors, little has been done in the field of shape error concealment. In this paper we propose a post-processing shape error concealment technique that uses the motion compensated boundary information of the previously received alpha-plane. The proposed approach is based on matching received boundary segments in the current frame to the boundary in the previous frame. This matching is achieved by finding a maximally smooth motion vector field. After the current boundary segments are matched to the previous boundary, the missing boundary pieces are reconstructed by motion compensation. Experimental results demonstrating the performance of the proposed motion compensated shape error concealment method, and comparing it with the previously proposed weighted side matching method are presented.

Dynamic online surveys and experiments with the free open-source software dynQuest.

PubMed

Rademacher, Jens D M; Lippke, Sonia

2007-08-01

With computers and the World Wide Web widely available, collecting data through Web browsers is an attractive method utilized by the social sciences. In this article, conducting PC- and Web-based trials with the software package dynQuest is described. The software manages dynamic questionnaire-based trials over the Internet or on single computers, possibly as randomized control trials (RCT), if two or more groups are involved. The choice of follow-up questions can depend on previous responses, as needed for matched interventions. Data are collected in a simple text-based database that can be imported easily into other programs for postprocessing and statistical analysis. The software consists of platform-independent scripts written in the programming language PERL that use the common gateway interface between Web browser and server for submission of data through HTML forms. Advantages of dynQuest are parsimony, simplicity in use and installation, transparency, and reliability. The program is available as open-source freeware from the authors.

A Patch-Based Approach for the Segmentation of Pathologies: Application to Glioma Labelling.

PubMed

Cordier, Nicolas; Delingette, Herve; Ayache, Nicholas

2016-04-01

In this paper, we describe a novel and generic approach to address fully-automatic segmentation of brain tumors by using multi-atlas patch-based voting techniques. In addition to avoiding the local search window assumption, the conventional patch-based framework is enhanced through several simple procedures: an improvement of the training dataset in terms of both label purity and intensity statistics, augmented features to implicitly guide the nearest-neighbor-search, multi-scale patches, invariance to cube isometries, stratification of the votes with respect to cases and labels. A probabilistic model automatically delineates regions of interest enclosing high-probability tumor volumes, which allows the algorithm to achieve highly competitive running time despite minimal processing power and resources. This method was evaluated on Multimodal Brain Tumor Image Segmentation challenge datasets. State-of-the-art results are achieved, with a limited learning stage thus restricting the risk of overfit. Moreover, segmentation smoothness does not involve any post-processing.

Detection of molecular particles in live cells via machine learning.

PubMed

Jiang, Shan; Zhou, Xiaobo; Kirchhausen, Tom; Wong, Stephen T C

2007-08-01

Clathrin-coated pits play an important role in removing proteins and lipids from the plasma membrane and transporting them to the endosomal compartment. It is, however, still unclear whether there exist "hot spots" for the formation of Clathrin-coated pits or the pits and arrays formed randomly on the plasma membrane. To answer this question, first of all, many hundreds of individual pits need to be detected accurately and separated in live-cell microscope movies to capture and monitor how pits and vesicles were formed. Because of the noisy background and the low contrast of the live-cell movies, the existing image analysis methods, such as single threshold, edge detection, and morphological operation, cannot be used. Thus, this paper proposes a machine learning method, which is based on Haar features, to detect the particle's position. Results show that this method can successfully detect most of particles in the image. In order to get the accurate boundaries of these particles, several post-processing methods are applied and signal-to-noise ratio analysis is also performed to rule out the weak spots. Copyright 2007 International Society for Analytical Cytology.

Post-processing method for wind speed ensemble forecast using wind speed and direction

NASA Astrophysics Data System (ADS)

Sofie Eide, Siri; Bjørnar Bremnes, John; Steinsland, Ingelin

2017-04-01

Statistical methods are widely applied to enhance the quality of both deterministic and ensemble NWP forecasts. In many situations, like wind speed forecasting, most of the predictive information is contained in one variable in the NWP models. However, in statistical calibration of deterministic forecasts it is often seen that including more variables can further improve forecast skill. For ensembles this is rarely taken advantage of, mainly due to that it is generally not straightforward how to include multiple variables. In this study, it is demonstrated how multiple variables can be included in Bayesian model averaging (BMA) by using a flexible regression method for estimating the conditional means. The method is applied to wind speed forecasting at 204 Norwegian stations based on wind speed and direction forecasts from the ECMWF ensemble system. At about 85 % of the sites the ensemble forecasts were improved in terms of CRPS by adding wind direction as predictor compared to only using wind speed. On average the improvements were about 5 %, but mainly for moderate to strong wind situations. For weak wind speeds adding wind direction had more or less neutral impact.

Essentially nonoscillatory postprocessing filtering methods

NASA Technical Reports Server (NTRS)

Lafon, F.; Osher, S.

1992-01-01

High order accurate centered flux approximations used in the computation of numerical solutions to nonlinear partial differential equations produce large oscillations in regions of sharp transitions. Here, we present a new class of filtering methods denoted by Essentially Nonoscillatory Least Squares (ENOLS), which constructs an upgraded filtered solution that is close to the physically correct weak solution of the original evolution equation. Our method relies on the evaluation of a least squares polynomial approximation to oscillatory data using a set of points which is determined via the ENO network. Numerical results are given in one and two space dimensions for both scalar and systems of hyperbolic conservation laws. Computational running time, efficiency, and robustness of method are illustrated in various examples such as Riemann initial data for both Burgers' and Euler's equations of gas dynamics. In all standard cases, the filtered solution appears to converge numerically to the correct solution of the original problem. Some interesting results based on nonstandard central difference schemes, which exactly preserve entropy, and have been recently shown generally not to be weakly convergent to a solution of the conservation law, are also obtained using our filters.

A Software Platform for Post-Processing Waveform-Based NDE

NASA Technical Reports Server (NTRS)

Roth, Donald J.; Martin, Richard E.; Seebo, Jeff P.; Trinh, Long B.; Walker, James L.; Winfree, William P.

2007-01-01

Ultrasonic, microwave, and terahertz nondestructive evaluation imaging systems generally require the acquisition of waveforms at each scan point to form an image. For such systems, signal and image processing methods are commonly needed to extract information from the waves and improve resolution of, and highlight, defects in the image. Since some similarity exists for all waveform-based NDE methods, it would seem a common software platform containing multiple signal and image processing techniques to process the waveforms and images makes sense where multiple techniques, scientists, engineers, and organizations are involved. This presentation describes NASA Glenn Research Center's approach in developing a common software platform for processing waveform-based NDE signals and images. This platform is currently in use at NASA Glenn and at Lockheed Martin Michoud Assembly Facility for processing of pulsed terahertz and ultrasonic data. Highlights of the software operation will be given. A case study will be shown for use with terahertz data. The authors also request scientists and engineers who are interested in sharing customized signal and image processing algorithms to contribute to this effort by letting the authors code up and include these algorithms in future releases.

Parallel workflow tools to facilitate human brain MRI post-processing

PubMed Central

Cui, Zaixu; Zhao, Chenxi; Gong, Gaolang

2015-01-01

Multi-modal magnetic resonance imaging (MRI) techniques are widely applied in human brain studies. To obtain specific brain measures of interest from MRI datasets, a number of complex image post-processing steps are typically required. Parallel workflow tools have recently been developed, concatenating individual processing steps and enabling fully automated processing of raw MRI data to obtain the final results. These workflow tools are also designed to make optimal use of available computational resources and to support the parallel processing of different subjects or of independent processing steps for a single subject. Automated, parallel MRI post-processing tools can greatly facilitate relevant brain investigations and are being increasingly applied. In this review, we briefly summarize these parallel workflow tools and discuss relevant issues. PMID:26029043

Mass spectrometry-based protein identification with accurate statistical significance assignment.

PubMed

Alves, Gelio; Yu, Yi-Kuo

2015-03-01

Assigning statistical significance accurately has become increasingly important as metadata of many types, often assembled in hierarchies, are constructed and combined for further biological analyses. Statistical inaccuracy of metadata at any level may propagate to downstream analyses, undermining the validity of scientific conclusions thus drawn. From the perspective of mass spectrometry-based proteomics, even though accurate statistics for peptide identification can now be achieved, accurate protein level statistics remain challenging. We have constructed a protein ID method that combines peptide evidences of a candidate protein based on a rigorous formula derived earlier; in this formula the database P-value of every peptide is weighted, prior to the final combination, according to the number of proteins it maps to. We have also shown that this protein ID method provides accurate protein level E-value, eliminating the need of using empirical post-processing methods for type-I error control. Using a known protein mixture, we find that this protein ID method, when combined with the Sorić formula, yields accurate values for the proportion of false discoveries. In terms of retrieval efficacy, the results from our method are comparable with other methods tested. The source code, implemented in C++ on a linux system, is available for download at ftp://ftp.ncbi.nlm.nih.gov/pub/qmbp/qmbp_ms/RAId/RAId_Linux_64Bit. Published by Oxford University Press 2014. This work is written by US Government employees and is in the public domain in the US.

Modeling experimental plasma diagnostics in the FLASH code: Thomson scattering

NASA Astrophysics Data System (ADS)

Weide, Klaus; Flocke, Norbert; Feister, Scott; Tzeferacos, Petros; Lamb, Donald

2017-10-01

Spectral analysis of the Thomson scattering of laser light sent into a plasma provides an experimental method to quantify plasma properties in laser-driven plasma experiments. We have implemented such a synthetic Thomson scattering diagnostic unit in the FLASH code, to emulate the probe-laser propagation, scattering and spectral detection. User-defined laser rays propagate into the FLASH simulation region and experience scattering (change in direction and frequency) based on plasma parameters. After scattering, the rays propagate out of the interaction region and are spectrally characterized. The diagnostic unit can be used either during a physics simulation or in post-processing of simulation results. FLASH is publicly available at flash.uchicago.edu. U.S. DOE NNSA, U.S. DOE NNSA ASC, U.S. DOE Office of Science and NSF.

Droplet-Based Segregation and Extraction of Concentrated Samples

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

Buie, C R; Buckley, P; Hamilton, J

2007-02-23

Microfluidic analysis often requires sample concentration and separation techniques to isolate and detect analytes of interest. Complex or scarce samples may also require an orthogonal separation and detection method or off-chip analysis to confirm results. To perform these additional steps, the concentrated sample plug must be extracted from the primary microfluidic channel with minimal sample loss and dilution. We investigated two extraction techniques; injection of immiscible fluid droplets into the sample stream (''capping'''') and injection of the sample into an immiscible fluid stream (''extraction''). From our results we conclude that capping is the more effective partitioning technique. Furthermore, this functionalitymore » enables additional off-chip post-processing procedures such as DNA/RNA microarray analysis, realtime polymerase chain reaction (RT-PCR), and culture growth to validate chip performance.« less

User guide for MODPATH Version 7—A particle-tracking model for MODFLOW

USGS Publications Warehouse

Pollock, David W.

2016-09-26

MODPATH is a particle-tracking post-processing program designed to work with MODFLOW, the U.S. Geological Survey (USGS) finite-difference groundwater flow model. MODPATH version 7 is the fourth major release since its original publication. Previous versions were documented in USGS Open-File Reports 89–381 and 94–464 and in USGS Techniques and Methods 6–A41.MODPATH version 7 works with MODFLOW-2005 and MODFLOW–USG. Support for unstructured grids in MODFLOW–USG is limited to smoothed, rectangular-based quadtree and quadpatch grids.A software distribution package containing the computer program and supporting documentation, such as input instructions, output file descriptions, and example problems, is available from the USGS over the Internet (http://water.usgs.gov/ogw/modpath/).

Tampered Region Localization of Digital Color Images Based on JPEG Compression Noise

NASA Astrophysics Data System (ADS)

Wang, Wei; Dong, Jing; Tan, Tieniu

With the availability of various digital image edit tools, seeing is no longer believing. In this paper, we focus on tampered region localization for image forensics. We propose an algorithm which can locate tampered region(s) in a lossless compressed tampered image when its unchanged region is output of JPEG decompressor. We find the tampered region and the unchanged region have different responses for JPEG compression. The tampered region has stronger high frequency quantization noise than the unchanged region. We employ PCA to separate different spatial frequencies quantization noises, i.e. low, medium and high frequency quantization noise, and extract high frequency quantization noise for tampered region localization. Post-processing is involved to get final localization result. The experimental results prove the effectiveness of our proposed method.

FPGA implementation of high-performance QC-LDPC decoder for optical communications

NASA Astrophysics Data System (ADS)

Zou, Ding; Djordjevic, Ivan B.

2015-01-01

Forward error correction is as one of the key technologies enabling the next-generation high-speed fiber optical communications. Quasi-cyclic (QC) low-density parity-check (LDPC) codes have been considered as one of the promising candidates due to their large coding gain performance and low implementation complexity. In this paper, we present our designed QC-LDPC code with girth 10 and 25% overhead based on pairwise balanced design. By FPGAbased emulation, we demonstrate that the 5-bit soft-decision LDPC decoder can achieve 11.8dB net coding gain with no error floor at BER of 10-15 avoiding using any outer code or post-processing method. We believe that the proposed single QC-LDPC code is a promising solution for 400Gb/s optical communication systems and beyond.

Association rule mining in the US Vaccine Adverse Event Reporting System (VAERS).

PubMed

Wei, Lai; Scott, John

2015-09-01

Spontaneous adverse event reporting systems are critical tools for monitoring the safety of licensed medical products. Commonly used signal detection algorithms identify disproportionate product-adverse event pairs and may not be sensitive to more complex potential signals. We sought to develop a computationally tractable multivariate data-mining approach to identify product-multiple adverse event associations. We describe an application of stepwise association rule mining (Step-ARM) to detect potential vaccine-symptom group associations in the US Vaccine Adverse Event Reporting System. Step-ARM identifies strong associations between one vaccine and one or more adverse events. To reduce the number of redundant association rules found by Step-ARM, we also propose a clustering method for the post-processing of association rules. In sample applications to a trivalent intradermal inactivated influenza virus vaccine and to measles, mumps, rubella, and varicella (MMRV) vaccine and in simulation studies, we find that Step-ARM can detect a variety of medically coherent potential vaccine-symptom group signals efficiently. In the MMRV example, Step-ARM appears to outperform univariate methods in detecting a known safety signal. Our approach is sensitive to potentially complex signals, which may be particularly important when monitoring novel medical countermeasure products such as pandemic influenza vaccines. The post-processing clustering algorithm improves the applicability of the approach as a screening method to identify patterns that may merit further investigation. Copyright © 2015 John Wiley & Sons, Ltd.

An artifacts removal post-processing for epiphyseal region-of-interest (EROI) localization in automated bone age assessment (BAA)

PubMed Central

2011-01-01

Background Segmentation is the most crucial part in the computer-aided bone age assessment. A well-known type of segmentation performed in the system is adaptive segmentation. While providing better result than global thresholding method, the adaptive segmentation produces a lot of unwanted noise that could affect the latter process of epiphysis extraction. Methods A proposed method with anisotropic diffusion as pre-processing and a novel Bounded Area Elimination (BAE) post-processing algorithm to improve the algorithm of ossification site localization technique are designed with the intent of improving the adaptive segmentation result and the region-of interest (ROI) localization accuracy. Results The results are then evaluated by quantitative analysis and qualitative analysis using texture feature evaluation. The result indicates that the image homogeneity after anisotropic diffusion has improved averagely on each age group for 17.59%. Results of experiments showed that the smoothness has been improved averagely 35% after BAE algorithm and the improvement of ROI localization has improved for averagely 8.19%. The MSSIM has improved averagely 10.49% after performing the BAE algorithm on the adaptive segmented hand radiograph. Conclusions The result indicated that hand radiographs which have undergone anisotropic diffusion have greatly reduced the noise in the segmented image and the result as well indicated that the BAE algorithm proposed is capable of removing the artifacts generated in adaptive segmentation. PMID:21952080

Compensated individually addressable array technology for human breast imaging

DOEpatents

Lewis, D. Kent

2003-01-01

A method of forming broad bandwidth acoustic or microwave beams which encompass array design, array excitation, source signal preprocessing, and received signal postprocessing. This technique uses several different methods to achieve improvement over conventional array systems. These methods are: 1) individually addressable array elements; 2) digital-to-analog converters for the source signals; 3) inverse filtering from source precompensation; and 4) spectral extrapolation to expand the bandwidth of the received signals. The components of the system will be used as follows: 1) The individually addressable array allows scanning around and over an object, such as a human breast, without any moving parts. The elements of the array are broad bandwidth elements and efficient radiators, as well as detectors. 2) Digital-to-analog converters as the source signal generators allow virtually any radiated field to be created in the half-space in front of the array. 3) Preprocessing allows for corrections in the system, most notably in the response of the individual elements and in the ability to increase contrast and resolution of signal propagating through the medium under investigation. 4) Postprocessing allows the received broad bandwidth signals to be expanded in a process similar to analytic continuation. Used together, the system allows for compensation to create beams of any desired shape, control the wave fields generated to correct for medium differences, and improve contract and resolution in and through the medium.

Nuts and Bolts of CEST MR imaging

PubMed Central

Liu, Guanshu; Song, Xiaolei; Chan, Kannie W.Y.

2013-01-01

Chemical Exchange Saturation Transfer (CEST) has emerged as a novel MRI contrast mechanism that is well suited for molecular imaging studies. This new mechanism can be used to detect small amounts of contrast agent through saturation of rapidly exchanging protons on these agents, allowing a wide range of applications. CEST technology has a number of indispensable features, such as the possibility of simultaneous detection of multiple “colors” of agents and detecting changes in their environment (e.g. pH, metabolites, etc) through MR contrast. Currently a large number of new imaging schemes and techniques have been developed to improve the temporal resolution and specificity and to correct the influence of B0 and B1 inhomogeneities. In this review, the techniques developed over the last decade have been summarized with the different imaging strategies and post-processing methods discussed from a practical point of view including describing their relative merits for detecting CEST agents. The goal of the present work is to provide the reader with a fundamental understanding of the techniques developed, and to provide guidance to help refine future applications of this technology. This review is organized into three main sections: Basics of CEST Contrast, Implementation, Post-Processing, and also includes a brief Introduction section and Summary. The Basics of CEST Contrast section contains a description of the relevant background theory for saturation transfer and frequency labeled transfer, and a brief discussion of methods to determine exchange rates. The Implementation section contains a description of the practical considerations in conducting CEST MRI studies, including choice of magnetic field, pulse sequence, saturation pulse, imaging scheme, and strategies to separate MT and CEST. The Post-Processing section contains a description of the typical image processing employed for B0/B1 correction, Z-spectral interpolation, frequency selective detection, and improving CEST contrast maps. PMID:23303716

Automated glioblastoma segmentation based on a multiparametric structured unsupervised classification.

PubMed

Juan-Albarracín, Javier; Fuster-Garcia, Elies; Manjón, José V; Robles, Montserrat; Aparici, F; Martí-Bonmatí, L; García-Gómez, Juan M

2015-01-01

Automatic brain tumour segmentation has become a key component for the future of brain tumour treatment. Currently, most of brain tumour segmentation approaches arise from the supervised learning standpoint, which requires a labelled training dataset from which to infer the models of the classes. The performance of these models is directly determined by the size and quality of the training corpus, whose retrieval becomes a tedious and time-consuming task. On the other hand, unsupervised approaches avoid these limitations but often do not reach comparable results than the supervised methods. In this sense, we propose an automated unsupervised method for brain tumour segmentation based on anatomical Magnetic Resonance (MR) images. Four unsupervised classification algorithms, grouped by their structured or non-structured condition, were evaluated within our pipeline. Considering the non-structured algorithms, we evaluated K-means, Fuzzy K-means and Gaussian Mixture Model (GMM), whereas as structured classification algorithms we evaluated Gaussian Hidden Markov Random Field (GHMRF). An automated postprocess based on a statistical approach supported by tissue probability maps is proposed to automatically identify the tumour classes after the segmentations. We evaluated our brain tumour segmentation method with the public BRAin Tumor Segmentation (BRATS) 2013 Test and Leaderboard datasets. Our approach based on the GMM model improves the results obtained by most of the supervised methods evaluated with the Leaderboard set and reaches the second position in the ranking. Our variant based on the GHMRF achieves the first position in the Test ranking of the unsupervised approaches and the seventh position in the general Test ranking, which confirms the method as a viable alternative for brain tumour segmentation.

Characterization of Adrenal Adenoma by Gaussian Model-Based Algorithm.

PubMed

Hsu, Larson D; Wang, Carolyn L; Clark, Toshimasa J

2016-01-01

We confirmed that computed tomography (CT) attenuation values of pixels in an adrenal nodule approximate a Gaussian distribution. Building on this and the previously described histogram analysis method, we created an algorithm that uses mean and standard deviation to estimate the percentage of negative attenuation pixels in an adrenal nodule, thereby allowing differentiation of adenomas and nonadenomas. The institutional review board approved both components of this study in which we developed and then validated our criteria. In the first, we retrospectively assessed CT attenuation values of adrenal nodules for normality using a 2-sample Kolmogorov-Smirnov test. In the second, we evaluated a separate cohort of patients with adrenal nodules using both the conventional 10HU unit mean attenuation method and our Gaussian model-based algorithm. We compared the sensitivities of the 2 methods using McNemar's test. A total of 183 of 185 observations (98.9%) demonstrated a Gaussian distribution in adrenal nodule pixel attenuation values. The sensitivity and specificity of our Gaussian model-based algorithm for identifying adrenal adenoma were 86.1% and 83.3%, respectively. The sensitivity and specificity of the mean attenuation method were 53.2% and 94.4%, respectively. The sensitivities of the 2 methods were significantly different (P value < 0.001). In conclusion, the CT attenuation values within an adrenal nodule follow a Gaussian distribution. Our Gaussian model-based algorithm can characterize adrenal adenomas with higher sensitivity than the conventional mean attenuation method. The use of our algorithm, which does not require additional postprocessing, may increase workflow efficiency and reduce unnecessary workup of benign nodules. Copyright © 2016 Elsevier Inc. All rights reserved.

Analysis of entropy extraction efficiencies in random number generation systems

NASA Astrophysics Data System (ADS)

Wang, Chao; Wang, Shuang; Chen, Wei; Yin, Zhen-Qiang; Han, Zheng-Fu

2016-05-01

Random numbers (RNs) have applications in many areas: lottery games, gambling, computer simulation, and, most importantly, cryptography [N. Gisin et al., Rev. Mod. Phys. 74 (2002) 145]. In cryptography theory, the theoretical security of the system calls for high quality RNs. Therefore, developing methods for producing unpredictable RNs with adequate speed is an attractive topic. Early on, despite the lack of theoretical support, pseudo RNs generated by algorithmic methods performed well and satisfied reasonable statistical requirements. However, as implemented, those pseudorandom sequences were completely determined by mathematical formulas and initial seeds, which cannot introduce extra entropy or information. In these cases, “random” bits are generated that are not at all random. Physical random number generators (RNGs), which, in contrast to algorithmic methods, are based on unpredictable physical random phenomena, have attracted considerable research interest. However, the way that we extract random bits from those physical entropy sources has a large influence on the efficiency and performance of the system. In this manuscript, we will review and discuss several randomness extraction schemes that are based on radiation or photon arrival times. We analyze the robustness, post-processing requirements and, in particular, the extraction efficiency of those methods to aid in the construction of efficient, compact and robust physical RNG systems.

Inverse Monte Carlo method in a multilayered tissue model for diffuse reflectance spectroscopy

NASA Astrophysics Data System (ADS)

Fredriksson, Ingemar; Larsson, Marcus; Strömberg, Tomas

2012-04-01

Model based data analysis of diffuse reflectance spectroscopy data enables the estimation of optical and structural tissue parameters. The aim of this study was to present an inverse Monte Carlo method based on spectra from two source-detector distances (0.4 and 1.2 mm), using a multilayered tissue model. The tissue model variables include geometrical properties, light scattering properties, tissue chromophores such as melanin and hemoglobin, oxygen saturation and average vessel diameter. The method utilizes a small set of presimulated Monte Carlo data for combinations of different levels of epidermal thickness and tissue scattering. The path length distributions in the different layers are stored and the effect of the other parameters is added in the post-processing. The accuracy of the method was evaluated using Monte Carlo simulations of tissue-like models containing discrete blood vessels, evaluating blood tissue fraction and oxygenation. It was also compared to a homogeneous model. The multilayer model performed better than the homogeneous model and all tissue parameters significantly improved spectral fitting. Recorded in vivo spectra were fitted well at both distances, which we previously found was not possible with a homogeneous model. No absolute intensity calibration is needed and the algorithm is fast enough for real-time processing.

A finite-element toolbox for the stationary Gross-Pitaevskii equation with rotation

NASA Astrophysics Data System (ADS)

Vergez, Guillaume; Danaila, Ionut; Auliac, Sylvain; Hecht, Frédéric

2016-12-01

We present a new numerical system using classical finite elements with mesh adaptivity for computing stationary solutions of the Gross-Pitaevskii equation. The programs are written as a toolbox for FreeFem++ (www.freefem.org), a free finite-element software available for all existing operating systems. This offers the advantage to hide all technical issues related to the implementation of the finite element method, allowing to easily code various numerical algorithms. Two robust and optimized numerical methods were implemented to minimize the Gross-Pitaevskii energy: a steepest descent method based on Sobolev gradients and a minimization algorithm based on the state-of-the-art optimization library Ipopt. For both methods, mesh adaptivity strategies are used to reduce the computational time and increase the local spatial accuracy when vortices are present. Different run cases are made available for 2D and 3D configurations of Bose-Einstein condensates in rotation. An optional graphical user interface is also provided, allowing to easily run predefined cases or with user-defined parameter files. We also provide several post-processing tools (like the identification of quantized vortices) that could help in extracting physical features from the simulations. The toolbox is extremely versatile and can be easily adapted to deal with different physical models.

On the dosimetric effect and reduction of inverse consistency and transitivity errors in deformable image registration for dose accumulation

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

Bender, Edward T.; Hardcastle, Nicholas; Tome, Wolfgang A.

2012-01-15

Purpose: Deformable image registration (DIR) is necessary for accurate dose accumulation between multiple radiotherapy image sets. DIR algorithms can suffer from inverse and transitivity inconsistencies. When using deformation vector fields (DVFs) that exhibit inverse-inconsistency and are nontransitive, dose accumulation on a given image set via different image pathways will lead to different accumulated doses. The purpose of this study was to investigate the dosimetric effect of and propose a postprocessing solution to reduce inverse consistency and transitivity errors. Methods: Four MVCT images and four phases of a lung 4DCT, each with an associated calculated dose, were selected for analysis. DVFsmore » between all four images in each data set were created using the Fast Symmetric Demons algorithm. Dose was accumulated on the fourth image in each set using DIR via two different image pathways. The two accumulated doses on the fourth image were compared. The inverse consistency and transitivity errors in the DVFs were then reduced. The dose accumulation was repeated using the processed DVFs, the results of which were compared with the accumulated dose from the original DVFs. To evaluate the influence of the postprocessing technique on DVF accuracy, the original and processed DVF accuracy was evaluated on the lung 4DCT data on which anatomical landmarks had been identified by an expert. Results: Dose accumulation to the same image via different image pathways resulted in two different accumulated dose results. After the inverse consistency errors were reduced, the difference between the accumulated doses diminished. The difference was further reduced after reducing the transitivity errors. The postprocessing technique had minimal effect on the accuracy of the DVF for the lung 4DCT images. Conclusions: This study shows that inverse consistency and transitivity errors in DIR have a significant dosimetric effect in dose accumulation; Depending on the image pathway taken to accumulate the dose, different results may be obtained. A postprocessing technique that reduces inverse consistency and transitivity error is presented, which allows for consistent dose accumulation regardless of the image pathway followed.« less

Centimeter-Level Robust Gnss-Aided Inertial Post-Processing for Mobile Mapping Without Local Reference Stations

NASA Astrophysics Data System (ADS)

Hutton, J. J.; Gopaul, N.; Zhang, X.; Wang, J.; Menon, V.; Rieck, D.; Kipka, A.; Pastor, F.

2016-06-01

For almost two decades mobile mapping systems have done their georeferencing using Global Navigation Satellite Systems (GNSS) to measure position and inertial sensors to measure orientation. In order to achieve cm level position accuracy, a technique referred to as post-processed carrier phase differential GNSS (DGNSS) is used. For this technique to be effective the maximum distance to a single Reference Station should be no more than 20 km, and when using a network of Reference Stations the distance to the nearest station should no more than about 70 km. This need to set up local Reference Stations limits productivity and increases costs, especially when mapping large areas or long linear features such as roads or pipelines. An alternative technique to DGNSS for high-accuracy positioning from GNSS is the so-called Precise Point Positioning or PPP method. In this case instead of differencing the rover observables with the Reference Station observables to cancel out common errors, an advanced model for every aspect of the GNSS error chain is developed and parameterized to within an accuracy of a few cm. The Trimble Centerpoint RTX positioning solution combines the methodology of PPP with advanced ambiguity resolution technology to produce cm level accuracies without the need for local reference stations. It achieves this through a global deployment of highly redundant monitoring stations that are connected through the internet and are used to determine the precise satellite data with maximum accuracy, robustness, continuity and reliability, along with advance algorithms and receiver and antenna calibrations. This paper presents a new post-processed realization of the Trimble Centerpoint RTX technology integrated into the Applanix POSPac MMS GNSS-Aided Inertial software for mobile mapping. Real-world results from over 100 airborne flights evaluated against a DGNSS network reference are presented which show that the post-processed Centerpoint RTX solution agrees with the DGNSS solution to better than 2.9 cm RMSE Horizontal and 5.5 cm RMSE Vertical. Such accuracies are sufficient to meet the requirements for a majority of airborne mapping applications.

Method of making large area conformable shape structures for detector/sensor applications using glass drawing technique and postprocessing

DOEpatents

Ivanov, Ilia N [Knoxville, TN; Simpson, John T [Clinton, IN

2012-01-24

A method of making a large area conformable shape structure comprises drawing a plurality of tubes to form a plurality of drawn tubes, and cutting the plurality of drawn tubes into cut drawn tubes of a predetermined shape. The cut drawn tubes have a first end and a second end along the longitudinal direction of the cut drawn tubes. The method further comprises conforming the first end of the cut drawn tubes into a predetermined curve to form the large area conformable shape structure, wherein the cut drawn tubes contain a material.

INFARCT DENSITY DISTRIBUTION BY MRI IN THE PORCINE MODEL OF ACUTE AND CHRONIC MYOCARDIAL INFARCTION AS A POTENTIAL METHOD TRANSFERABLE TO THE CLINIC

PubMed Central

Varga-Szemes, Akos; Simor, Tamas; Lenkey, Zsofia; van der Geest, Rob J; Kirschner, Robert; Toth, Levente; Brott, Brigitta C.; Ada, Elgavish; Elgavish, Gabriel A.

2014-01-01

Purpose To study the feasibility of a myocardial infarct (MI) quantification method (Signal Intensity-based Percent Infarct Mapping, SI-PIM) that is able to evaluate not only the size, but also the density distribution of the MI. Methods In 14 male swine, MI was generated by 90 minutes of closed-chest balloon occlusion followed by reperfusion. Seven (n=7) or 56 (n=7) days after reperfusion, Gd-DTPA-bolus and continuous-infusion enhanced Late Gadolinium Enhancement (LGE) MRI, and R1-mapping were carried out and post mortem triphenyl-tetrazolium-chloride (TTC) staining was performed. MI was quantified using binary (2 or 5 standard deviations, SD), SI-PIM and R1-PIM methods. Infarct Fraction (IF), and Infarct-Involved Voxel Fraction (IIVF) were determined by each MRI method. Bias of each method was compared to the TTC technique. Results The accuracy of MI quantification did not depend on the method of contrast administration or the age of the MI. IFs obtained by either of the two PIM methods were statistically not different from the IFs derived from the TTC measurements at either MI age. IFs obtained from the binary 2SD method overestimated IF obtained from TTC. IIVF among the three different PIM methods did not vary, but with the binary methods the IIVF gradually decreased with increasing the threshold limit. Conclusions The advantage of SI-PIM over the conventional binary method is the ability to represent not only IF but also the density distribution of the MI. Since the SI-PIM methods are based on a single LGE acquisition, the bolus-data-based SI-PIM method can effortlessly be incorporated into the clinical image post-processing procedure. PMID:24718787

A new framework for analysing automated acoustic species-detection data: occupancy estimation and optimization of recordings post-processing

USGS Publications Warehouse

Chambert, Thierry A.; Waddle, J. Hardin; Miller, David A.W.; Walls, Susan; Nichols, James D.

2018-01-01

The development and use of automated species-detection technologies, such as acoustic recorders, for monitoring wildlife are rapidly expanding. Automated classification algorithms provide a cost- and time-effective means to process information-rich data, but often at the cost of additional detection errors. Appropriate methods are necessary to analyse such data while dealing with the different types of detection errors.We developed a hierarchical modelling framework for estimating species occupancy from automated species-detection data. We explore design and optimization of data post-processing procedures to account for detection errors and generate accurate estimates. Our proposed method accounts for both imperfect detection and false positive errors and utilizes information about both occurrence and abundance of detections to improve estimation.Using simulations, we show that our method provides much more accurate estimates than models ignoring the abundance of detections. The same findings are reached when we apply the methods to two real datasets on North American frogs surveyed with acoustic recorders.When false positives occur, estimator accuracy can be improved when a subset of detections produced by the classification algorithm is post-validated by a human observer. We use simulations to investigate the relationship between accuracy and effort spent on post-validation, and found that very accurate occupancy estimates can be obtained with as little as 1% of data being validated.Automated monitoring of wildlife provides opportunity and challenges. Our methods for analysing automated species-detection data help to meet key challenges unique to these data and will prove useful for many wildlife monitoring programs.

Estimation of breast percent density in raw and processed full field digital mammography images via adaptive fuzzy c-means clustering and support vector machine segmentation

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

Keller, Brad M.; Nathan, Diane L.; Wang Yan

Purpose: The amount of fibroglandular tissue content in the breast as estimated mammographically, commonly referred to as breast percent density (PD%), is one of the most significant risk factors for developing breast cancer. Approaches to quantify breast density commonly focus on either semiautomated methods or visual assessment, both of which are highly subjective. Furthermore, most studies published to date investigating computer-aided assessment of breast PD% have been performed using digitized screen-film mammograms, while digital mammography is increasingly replacing screen-film mammography in breast cancer screening protocols. Digital mammography imaging generates two types of images for analysis, raw (i.e., 'FOR PROCESSING') andmore » vendor postprocessed (i.e., 'FOR PRESENTATION'), of which postprocessed images are commonly used in clinical practice. Development of an algorithm which effectively estimates breast PD% in both raw and postprocessed digital mammography images would be beneficial in terms of direct clinical application and retrospective analysis. Methods: This work proposes a new algorithm for fully automated quantification of breast PD% based on adaptive multiclass fuzzy c-means (FCM) clustering and support vector machine (SVM) classification, optimized for the imaging characteristics of both raw and processed digital mammography images as well as for individual patient and image characteristics. Our algorithm first delineates the breast region within the mammogram via an automated thresholding scheme to identify background air followed by a straight line Hough transform to extract the pectoral muscle region. The algorithm then applies adaptive FCM clustering based on an optimal number of clusters derived from image properties of the specific mammogram to subdivide the breast into regions of similar gray-level intensity. Finally, a SVM classifier is trained to identify which clusters within the breast tissue are likely fibroglandular, which are then aggregated into a final dense tissue segmentation that is used to compute breast PD%. Our method is validated on a group of 81 women for whom bilateral, mediolateral oblique, raw and processed screening digital mammograms were available, and agreement is assessed with both continuous and categorical density estimates made by a trained breast-imaging radiologist. Results: Strong association between algorithm-estimated and radiologist-provided breast PD% was detected for both raw (r= 0.82, p < 0.001) and processed (r= 0.85, p < 0.001) digital mammograms on a per-breast basis. Stronger agreement was found when overall breast density was assessed on a per-woman basis for both raw (r= 0.85, p < 0.001) and processed (0.89, p < 0.001) mammograms. Strong agreement between categorical density estimates was also seen (weighted Cohen's {kappa}{>=} 0.79). Repeated measures analysis of variance demonstrated no statistically significant differences between the PD% estimates (p > 0.1) due to either presentation of the image (raw vs processed) or method of PD% assessment (radiologist vs algorithm). Conclusions: The proposed fully automated algorithm was successful in estimating breast percent density from both raw and processed digital mammographic images. Accurate assessment of a woman's breast density is critical in order for the estimate to be incorporated into risk assessment models. These results show promise for the clinical application of the algorithm in quantifying breast density in a repeatable manner, both at time of imaging as well as in retrospective studies.« less

Estimation of breast percent density in raw and processed full field digital mammography images via adaptive fuzzy c-means clustering and support vector machine segmentation

PubMed Central

Keller, Brad M.; Nathan, Diane L.; Wang, Yan; Zheng, Yuanjie; Gee, James C.; Conant, Emily F.; Kontos, Despina

2012-01-01

Purpose: The amount of fibroglandular tissue content in the breast as estimated mammographically, commonly referred to as breast percent density (PD%), is one of the most significant risk factors for developing breast cancer. Approaches to quantify breast density commonly focus on either semiautomated methods or visual assessment, both of which are highly subjective. Furthermore, most studies published to date investigating computer-aided assessment of breast PD% have been performed using digitized screen-film mammograms, while digital mammography is increasingly replacing screen-film mammography in breast cancer screening protocols. Digital mammography imaging generates two types of images for analysis, raw (i.e., “FOR PROCESSING”) and vendor postprocessed (i.e., “FOR PRESENTATION”), of which postprocessed images are commonly used in clinical practice. Development of an algorithm which effectively estimates breast PD% in both raw and postprocessed digital mammography images would be beneficial in terms of direct clinical application and retrospective analysis. Methods: This work proposes a new algorithm for fully automated quantification of breast PD% based on adaptive multiclass fuzzy c-means (FCM) clustering and support vector machine (SVM) classification, optimized for the imaging characteristics of both raw and processed digital mammography images as well as for individual patient and image characteristics. Our algorithm first delineates the breast region within the mammogram via an automated thresholding scheme to identify background air followed by a straight line Hough transform to extract the pectoral muscle region. The algorithm then applies adaptive FCM clustering based on an optimal number of clusters derived from image properties of the specific mammogram to subdivide the breast into regions of similar gray-level intensity. Finally, a SVM classifier is trained to identify which clusters within the breast tissue are likely fibroglandular, which are then aggregated into a final dense tissue segmentation that is used to compute breast PD%. Our method is validated on a group of 81 women for whom bilateral, mediolateral oblique, raw and processed screening digital mammograms were available, and agreement is assessed with both continuous and categorical density estimates made by a trained breast-imaging radiologist. Results: Strong association between algorithm-estimated and radiologist-provided breast PD% was detected for both raw (r = 0.82, p < 0.001) and processed (r = 0.85, p < 0.001) digital mammograms on a per-breast basis. Stronger agreement was found when overall breast density was assessed on a per-woman basis for both raw (r = 0.85, p < 0.001) and processed (0.89, p < 0.001) mammograms. Strong agreement between categorical density estimates was also seen (weighted Cohen's κ ≥ 0.79). Repeated measures analysis of variance demonstrated no statistically significant differences between the PD% estimates (p > 0.1) due to either presentation of the image (raw vs processed) or method of PD% assessment (radiologist vs algorithm). Conclusions: The proposed fully automated algorithm was successful in estimating breast percent density from both raw and processed digital mammographic images. Accurate assessment of a woman's breast density is critical in order for the estimate to be incorporated into risk assessment models. These results show promise for the clinical application of the algorithm in quantifying breast density in a repeatable manner, both at time of imaging as well as in retrospective studies. PMID:22894417

Evaluation of a Post-Processing Approach for Multiscale Analysis of Biphasic Mechanics of Chondrocytes

PubMed Central

Sibole, Scott C.; Maas, Steve; Halloran, Jason P.; Weiss, Jeffrey A.; Erdemir, Ahmet

2014-01-01

Understanding the mechanical behavior of chondrocytes as a result of cartilage tissue mechanics has significant implications for both evaluation of mechanobiological function and to elaborate on damage mechanisms. A common procedure for prediction of chondrocyte mechanics (and of cell mechanics in general) relies on a computational post-processing approach where tissue level deformations drive cell level models. Potential loss of information in this numerical coupling approach may cause erroneous cellular scale results, particularly during multiphysics analysis of cartilage. The goal of this study was to evaluate the capacity of 1st and 2nd order data passing to predict chondrocyte mechanics by analyzing cartilage deformations obtained for varying complexity of loading scenarios. A tissue scale model with a sub-region incorporating representation of chondron size and distribution served as control. The postprocessing approach first required solution of a homogeneous tissue level model, results of which were used to drive a separate cell level model (same characteristics as the subregion of control model). The 1st data passing appeared to be adequate for simplified loading of the cartilage and for a subset of cell deformation metrics, e.g., change in aspect ratio. The 2nd order data passing scheme was more accurate, particularly when asymmetric permeability of the tissue boundaries were considered. Yet, the method exhibited limitations for predictions of instantaneous metrics related to the fluid phase, e.g., mass exchange rate. Nonetheless, employing higher-order data exchange schemes may be necessary to understand the biphasic mechanics of cells under lifelike tissue loading states for the whole time history of the simulation. PMID:23809004

Analysis of deep inferior epigastric perforator (DIEP) arteries by using MDCTA: Comparison between 2 post-processing techniques.

PubMed

Saba, Luca; Atzeni, Matteo; Ribuffo, Diego; Mallarini, Giorgio; Suri, Jasjit S

2012-08-01

Our purpose was to compare two post-processing techniques, Maximum-Intensity-Projection (MIP) and Volume Rendering (VR) for the study of perforator arteries. Thirty patients who underwent Multi-Detector-Row CT Angiography (MDCTA) between February 2010 and May 2010 were retrospectively analyzed. For each patient and for each reconstruction method, the image quality was evaluated and the inter- and intra-observer agreement was calculated according to the Cohen statistics. The Hounsfield Unit (HU) value in the common femoral artery was quantified and the correlation (Pearson Statistic) between image quality and HU value was explored. The Pearson r between the right and left common femoral artery was excellent (r=0.955). The highest image quality score was obtained using MIP for both observers (total value 75, with a mean value 2.67 for observer 1 and total value of 79 and a mean value of 2.82 for observer 2). The highest agreement between the two observers was detected using the MIP protocol with a Cohen kappa value of 0.856. The ROC area under the curve (Az) for the VR is 0.786 (0.086 SD; p value=0.0009) whereas the ROC area under the curve (Az) for the MIP is 0.0928 (0.051 SD; p value=0.0001). MIP showed the optimal inter- and intra-observer agreement and the highest quality scores and therefore should be used as post-processing techniques in the analysis of perforating arteries. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Simulating patient-specific heart shape and motion using SPECT perfusion images with the MCAT phantom

NASA Astrophysics Data System (ADS)

Faber, Tracy L.; Garcia, Ernest V.; Lalush, David S.; Segars, W. Paul; Tsui, Benjamin M.

2001-05-01

The spline-based Mathematical Cardiac Torso (MCAT) phantom is a realistic software simulation designed to simulate single photon emission computed tomographic (SPECT) data. It incorporates a heart model of known size and shape; thus, it is invaluable for measuring accuracy of acquisition, reconstruction, and post-processing routines. New functionality has been added by replacing the standard heart model with left ventricular (LV) epicaridal and endocardial surface points detected from actual patient SPECT perfusion studies. LV surfaces detected from standard post-processing quantitation programs are converted through interpolation in space and time into new B-spline models. Perfusion abnormalities are added to the model based on results of standard perfusion quantification. The new LV is translated and rotated to fit within existing atria and right ventricular models, which are scaled based on the size of the LV. Simulations were created for five different patients with myocardial infractions who had undergone SPECT perfusion imaging. Shape, size, and motion of the resulting activity map were compared visually to the original SPECT images. In all cases, size, shape and motion of simulated LVs matched well with the original images. Thus, realistic simulations with known physiologic and functional parameters can be created for evaluating efficacy of processing algorithms.

Density implications of shift compensation postprocessing in holographic storage systems

NASA Astrophysics Data System (ADS)

Menetrier, Laure; Burr, Geoffrey W.

2003-02-01

We investigate the effect of data page misregistration, and its subsequent correction in postprocessing, on the storage density of holographic data storage systems. A numerical simulation is used to obtain the bit-error rate as a function of hologram aperture, page misregistration, pixel fill factors, and Gaussian additive intensity noise. Postprocessing of simulated data pages is performed by a nonlinear pixel shift compensation algorithm [Opt. Lett. 26, 542 (2001)]. The performance of this algorithm is analyzed in the presence of noise by determining the achievable areal density. The impact of inaccurate measurements of page misregistration is also investigated. Results show that the shift-compensation algorithm can provide almost complete immunity to page misregistration, although at some penalty to the baseline areal density offered by a system with zero tolerance to misalignment.

Pippi — Painless parsing, post-processing and plotting of posterior and likelihood samples

NASA Astrophysics Data System (ADS)

Scott, Pat

2012-11-01

Interpreting samples from likelihood or posterior probability density functions is rarely as straightforward as it seems it should be. Producing publication-quality graphics of these distributions is often similarly painful. In this short note I describe pippi, a simple, publicly available package for parsing and post-processing such samples, as well as generating high-quality PDF graphics of the results. Pippi is easily and extensively configurable and customisable, both in its options for parsing and post-processing samples, and in the visual aspects of the figures it produces. I illustrate some of these using an existing supersymmetric global fit, performed in the context of a gamma-ray search for dark matter. Pippi can be downloaded and followed at http://github.com/patscott/pippi.

Modelling and control for laser based welding processes: modern methods of process control to improve quality of laser-based joining methods

NASA Astrophysics Data System (ADS)

Zäh, Ralf-Kilian; Mosbach, Benedikt; Hollwich, Jan; Faupel, Benedikt

2017-02-01

To ensure the competitiveness of manufacturing companies it is indispensable to optimize their manufacturing processes. Slight variations of process parameters and machine settings have only marginally effects on the product quality. Therefore, the largest possible editing window is required. Such parameters are, for example, the movement of the laser beam across the component for the laser keyhole welding. That`s why it is necessary to keep the formation of welding seams within specified limits. Therefore, the quality of laser welding processes is ensured, by using post-process methods, like ultrasonic inspection, or special in-process methods. These in-process systems only achieve a simple evaluation which shows whether the weld seam is acceptable or not. Furthermore, in-process systems use no feedback for changing the control variables such as speed of the laser or adjustment of laser power. In this paper the research group presents current results of the research field of Online Monitoring, Online Controlling and Model predictive controlling in laser welding processes to increase the product quality. To record the characteristics of the welding process, tested online methods are used during the process. Based on the measurement data, a state space model is ascertained, which includes all the control variables of the system. Depending on simulation tools the model predictive controller (MPC) is designed for the model and integrated into an NI-Real-Time-System.

Fabrication of elastomeric silk fibers.

PubMed

Bradner, Sarah A; Partlow, Benjamin P; Cebe, Peggy; Omenetto, Fiorenzo G; Kaplan, David L

2017-09-01

Methods to generate fibers from hydrogels, with control over mechanical properties, fiber diameter, and crystallinity, while retaining cytocompatibility and degradability, would expand options for biomaterials. Here, we exploited features of silk fibroin protein for the formation of tunable silk hydrogel fibers. The biological, chemical, and morphological features inherent to silk were combined with elastomeric properties gained through enzymatic crosslinking of the protein. Postprocessing via methanol and autoclaving provided tunable control of fiber features. Mechanical, optical, and chemical analyses demonstrated control of fiber properties by exploiting the physical cross-links, and generating double network hydrogels consisting of chemical and physical cross-links. Structure and chemical analyses revealed crystallinity from 30 to 50%, modulus from 0.5 to 4 MPa, and ultimate strength 1-5 MPa depending on the processing method. Fabrication and postprocessing combined provided fibers with extensibility from 100 to 400% ultimate strain. Fibers strained to 100% exhibited fourth order birefringence, revealing macroscopic orientation driven by chain mobility. The physical cross-links were influenced in part by the drying rate of fabricated materials, where bound water, packing density, and microstructural homogeneity influenced cross-linking efficiency. The ability to generate robust and versatile hydrogel microfibers is desirable for bottom-up assembly of biological tissues and for broader biomaterial applications. © 2017 Wiley Periodicals, Inc.

DREAM: An Efficient Methodology for DSMC Simulation of Unsteady Processes

NASA Astrophysics Data System (ADS)

Cave, H. M.; Jermy, M. C.; Tseng, K. C.; Wu, J. S.

2008-12-01

A technique called the DSMC Rapid Ensemble Averaging Method (DREAM) for reducing the statistical scatter in the output from unsteady DSMC simulations is introduced. During post-processing by DREAM, the DSMC algorithm is re-run multiple times over a short period before the temporal point of interest thus building up a combination of time- and ensemble-averaged sampling data. The particle data is regenerated several mean collision times before the output time using the particle data generated during the original DSMC run. This methodology conserves the original phase space data from the DSMC run and so is suitable for reducing the statistical scatter in highly non-equilibrium flows. In this paper, the DREAM-II method is investigated and verified in detail. Propagating shock waves at high Mach numbers (Mach 8 and 12) are simulated using a parallel DSMC code (PDSC) and then post-processed using DREAM. The ability of DREAM to obtain the correct particle velocity distribution in the shock structure is demonstrated and the reduction of statistical scatter in the output macroscopic properties is measured. DREAM is also used to reduce the statistical scatter in the results from the interaction of a Mach 4 shock with a square cavity and for the interaction of a Mach 12 shock on a wedge in a channel.

Laser-Based Measurements of OH, Temperature, and Water Vapor Concentration in a Hydrocarbon-Fueled Scramjet (POSTPRINT)

DTIC Science & Technology

2008-07-01

hours. The detector signals are post-processed with a software lock-in amplifier to recover the WMS-1f and WMS-2f signals. The TDLAS sensor utilizes...Figure 6. Schematic of TDLAS sensor for temperature and water vapor concentration. Fiber Diode lasers Grating Fiber Detectors Demultiplexer Multiplexer...within the combustor. Tunable diode laser- based absorption spectroscopy ( TDLAS ) is used to measure water vapor concentration and static temperature near

The Laboratory for Individualized Breast Radiodensity Assessment (LIBRA) | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

LIBRA is a fully-automatic breast density estimation software solution based on a published algorithm that works on either raw (i.e., “FOR PROCESSING”) or vendor post-processed (i.e., “FOR PRESENTATION”) digital mammography images. LIBRA has been applied to over 30,000 screening exams and is being increasingly utilized in larger studies.

Interactive vs. automatic ultrasound image segmentation methods for staging hepatic lipidosis.

PubMed

Weijers, Gert; Starke, Alexander; Haudum, Alois; Thijssen, Johan M; Rehage, Jürgen; De Korte, Chris L

2010-07-01

The aim of this study was to test the hypothesis that automatic segmentation of vessels in ultrasound (US) images can produce similar or better results in grading fatty livers than interactive segmentation. A study was performed in postpartum dairy cows (N=151), as an animal model of human fatty liver disease, to test this hypothesis. Five transcutaneous and five intraoperative US liver images were acquired in each animal and a liverbiopsy was taken. In liver tissue samples, triacylglycerol (TAG) was measured by biochemical analysis and hepatic diseases other than hepatic lipidosis were excluded by histopathologic examination. Ultrasonic tissue characterization (UTC) parameters--Mean echo level, standard deviation (SD) of echo level, signal-to-noise ratio (SNR), residual attenuation coefficient (ResAtt) and axial and lateral speckle size--were derived using a computer-aided US (CAUS) protocol and software package. First, the liver tissue was interactively segmented by two observers. With increasing fat content, fewer hepatic vessels were visible in the ultrasound images and, therefore, a smaller proportion of the liver needed to be excluded from these images. Automatic-segmentation algorithms were implemented and it was investigated whether better results could be achieved than with the subjective and time-consuming interactive-segmentation procedure. The automatic-segmentation algorithms were based on both fixed and adaptive thresholding techniques in combination with a 'speckle'-shaped moving-window exclusion technique. All data were analyzed with and without postprocessing as contained in CAUS and with different automated-segmentation techniques. This enabled us to study the effect of the applied postprocessing steps on single and multiple linear regressions ofthe various UTC parameters with TAG. Improved correlations for all US parameters were found by using automatic-segmentation techniques. Stepwise multiple linear-regression formulas where derived and used to predict TAG level in the liver. Receiver-operating-characteristics (ROC) analysis was applied to assess the performance and area under the curve (AUC) of predicting TAG and to compare the sensitivity and specificity of the methods. Best speckle-size estimates and overall performance (R2 = 0.71, AUC = 0.94) were achieved by using an SNR-based adaptive automatic-segmentation method (used TAG threshold: 50 mg/g liver wet weight). Automatic segmentation is thus feasible and profitable.

Registration of pencil beam proton radiography data with X-ray CT.

PubMed

Deffet, Sylvain; Macq, Benoît; Righetto, Roberto; Vander Stappen, François; Farace, Paolo

2017-10-01

Proton radiography seems to be a promising tool for assessing the quality of the stopping power computation in proton therapy. However, range error maps obtained on the basis of proton radiographs are very sensitive to small misalignment between the planning CT and the proton radiography acquisitions. In order to be able to mitigate misalignment in postprocessing, the authors implemented a fast method for registration between pencil proton radiography data obtained with a multilayer ionization chamber (MLIC) and an X-ray CT acquired on a head phantom. The registration was performed by optimizing a cost function which performs a comparison between the acquired data and simulated integral depth-dose curves. Two methodologies were considered, one based on dual orthogonal projections and the other one on a single projection. For each methodology, the robustness of the registration algorithm with respect to three confounding factors (measurement noise, CT calibration errors, and spot spacing) was investigated by testing the accuracy of the method through simulations based on a CT scan of a head phantom. The present registration method showed robust convergence towards the optimal solution. For the level of measurement noise and the uncertainty in the stopping power computation expected in proton radiography using a MLIC, the accuracy appeared to be better than 0.3° for angles and 0.3 mm for translations by use of the appropriate cost function. The spot spacing analysis showed that a spacing larger than the 5 mm used by other authors for the investigation of a MLIC for proton radiography led to results with absolute accuracy better than 0.3° for angles and 1 mm for translations when orthogonal proton radiographs were fed into the algorithm. In the case of a single projection, 6 mm was the largest spot spacing presenting an acceptable registration accuracy. For registration of proton radiography data with X-ray CT, the use of a direct ray-tracing algorithm to compute sums of squared differences and corrections of range errors showed very good accuracy and robustness with respect to three confounding factors: measurement noise, calibration error, and spot spacing. It is therefore a suitable algorithm to use in the in vivo range verification framework, allowing to separate in postprocessing the proton range uncertainty due to setup errors from the other sources of uncertainty. © 2017 American Association of Physicists in Medicine.

Self-calibrated humidity sensor in CMOS without post-processing.

PubMed

Nizhnik, Oleg; Higuchi, Kohei; Maenaka, Kazusuke

2012-01-01

A 1.1 μW power dissipation, voltage-output humidity sensor with 10% relative humidity accuracy was developed in the LFoundry 0.15 μm CMOS technology without post-processing. The sensor consists of a woven lateral array of electrodes implemented in CMOS top metal, a humidity-sensitive layer of Intervia Photodielectric 8023D-10, a CMOS capacitance to voltage converter, and the self-calibration circuitry.

Semi-supervised word polarity identification in resource-lean languages.

PubMed

Dehdarbehbahani, Iman; Shakery, Azadeh; Faili, Heshaam

2014-10-01

Sentiment words, as fundamental constitutive parts of subjective sentences, have a substantial effect on analysis of opinions, emotions and beliefs. Most of the proposed methods for identifying the semantic orientations of words exploit rich linguistic resources such as WordNet, subjectivity corpora, or polarity tagged words. Shortage of such linguistic resources in resource-lean languages affects the performance of word polarity identification in these languages. In this paper, we present a method which exploits a language with rich subjectivity analysis resources (English) to identify the polarity of words in a resource-lean foreign language. The English WordNet and a sparse foreign WordNet infrastructure are used to create a heterogeneous, multilingual and weighted semantic network. To identify the semantic orientation of foreign words, a random walk based method is applied to the semantic network along with a set of automatically weighted English positive and negative seeds. In a post-processing phase, synonym and antonym relations in the foreign WordNet are used to filter the random walk results. Our experiments on English and Persian languages show that the proposed method can outperform state-of-the-art word polarity identification methods in both languages. Copyright © 2014 Elsevier Ltd. All rights reserved.

Recovery of chemical Estimates by Field Inhomogeneity Neighborhood Error Detection (REFINED): Fat/Water Separation at 7T

PubMed Central

Narayan, Sreenath; Kalhan, Satish C.; Wilson, David L.

2012-01-01

I.Abstract Purpose To reduce swaps in fat-water separation methods, a particular issue on 7T small animal scanners due to field inhomogeneity, using image postprocessing innovations that detect and correct errors in the B0 field map. Materials and Methods Fat-water decompositions and B0 field maps were computed for images of mice acquired on a 7T Bruker BioSpec scanner, using a computationally efficient method for solving the Markov Random Field formulation of the multi-point Dixon model. The B0 field maps were processed with a novel hole-filling method, based on edge strength between regions, and a novel k-means method, based on field-map intensities, which were iteratively applied to automatically detect and reinitialize error regions in the B0 field maps. Errors were manually assessed in the B0 field maps and chemical parameter maps both before and after error correction. Results Partial swaps were found in 6% of images when processed with FLAWLESS. After REFINED correction, only 0.7% of images contained partial swaps, resulting in an 88% decrease in error rate. Complete swaps were not problematic. Conclusion Ex post facto error correction is a viable supplement to a priori techniques for producing globally smooth B0 field maps, without partial swaps. With our processing pipeline, it is possible to process image volumes rapidly, robustly, and almost automatically. PMID:23023815

Methane Post-Processing and Hydrogen Separation for Spacecraft Oxygen Loop Closure

NASA Technical Reports Server (NTRS)

Greenwood, Zachary W.; Abeny, Morgan B.; Wall, Terry; Miller, Lee A.; Wheeler, Richard R., Jr.

2017-01-01

State-of-the-art life support oxygen recovery technology on the International Space Station is based on the Sabatier reaction where only about half of the oxygen required for the crew is recovered from metabolic carbon dioxide (CO2). The Sabatier reaction produces water as the primary product and methane as a byproduct. Oxygen recovery is constrained by both the limited availability of reactant hydrogen from water electrolysis and Sabatier methane (CH4) being vented as a waste product resulting in a continuous loss of reactant hydrogen. Post-processing methane with the Plasma Pyrolysis Assembly (PPA) to recover this hydrogen has the potential to substantially increase oxygen recovery and thus dramatically reduce the logistical challenges associated with oxygen resupply. The PPA decomposes methane into predominantly hydrogen and acetylene. A purification system is necessary to purify hydrogen before it is recycled back to the Sabatier reactor. Testing and evaluation of acetylene removal systems and PPA system architectures are presented and discussed.

Vortex Shedding Inside a Baffled Air Duct

NASA Technical Reports Server (NTRS)

Davis, Philip; Kenny, R. Jeremy

2010-01-01

Common in the operation of both segmented and un-segmented large solid rocket motors is the occurrence of vortex shedding within the motor chamber. A portion of the energy within a shed vortex is converted to acoustic energy, potentially driving the longitudinal acoustic modes of the motor in a quasi-discrete fashion. This vortex shedding-acoustic mode excitation event occurs for every Reusable Solid Rocket Motor (RSRM) operation, giving rise to subsequent axial thrust oscillations. In order to better understand this vortex shedding/acoustic mode excitation phenomena, unsteady CFD simulations were run for both a test geometry and the full scale RSRM geometry. This paper covers the results from the subscale geometry runs, which were based on work focusing on the RSRM hydrodynamics. Unsteady CFD simulation parameters, including boundary conditions and post-processing returns, are reviewed. The results were further post-processed to identify active acoustic modes and vortex shedding characteristics. Probable locations for acoustic energy generation, and subsequent acoustic mode excitation, are discussed.

Scripting MODFLOW model development using Python and FloPy

USGS Publications Warehouse

Bakker, Mark; Post, Vincent E. A.; Langevin, Christian D.; Hughes, Joseph D.; White, Jeremy; Starn, Jeffrey; Fienen, Michael N.

2016-01-01

Graphical user interfaces (GUIs) are commonly used to construct and postprocess numerical groundwater flow and transport models. Scripting model development with the programming language Python is presented here as an alternative approach. One advantage of Python is that there are many packages available to facilitate the model development process, including packages for plotting, array manipulation, optimization, and data analysis. For MODFLOW-based models, the FloPy package was developed by the authors to construct model input files, run the model, and read and plot simulation results. Use of Python with the available scientific packages and FloPy facilitates data exploration, alternative model evaluations, and model analyses that can be difficult to perform with GUIs. Furthermore, Python scripts are a complete, transparent, and repeatable record of the modeling process. The approach is introduced with a simple FloPy example to create and postprocess a MODFLOW model. A more complicated capture-fraction analysis with a real-world model is presented to demonstrate the types of analyses that can be performed using Python and FloPy.

Computer-assisted segmentation of white matter lesions in 3D MR images using support vector machine.

PubMed

Lao, Zhiqiang; Shen, Dinggang; Liu, Dengfeng; Jawad, Abbas F; Melhem, Elias R; Launer, Lenore J; Bryan, R Nick; Davatzikos, Christos

2008-03-01

Brain lesions, especially white matter lesions (WMLs), are associated with cardiac and vascular disease, but also with normal aging. Quantitative analysis of WML in large clinical trials is becoming more and more important. In this article, we present a computer-assisted WML segmentation method, based on local features extracted from multiparametric magnetic resonance imaging (MRI) sequences (ie, T1-weighted, T2-weighted, proton density-weighted, and fluid attenuation inversion recovery MRI scans). A support vector machine classifier is first trained on expert-defined WMLs, and is then used to classify new scans. Postprocessing analysis further reduces false positives by using anatomic knowledge and measures of distance from the training set. Cross-validation on a population of 35 patients from three different imaging sites with WMLs of varying sizes, shapes, and locations tests the robustness and accuracy of the proposed segmentation method, compared with the manual segmentation results from two experienced neuroradiologists.

Calculation of the detection limits for radionuclides identified in gamma-ray spectra based on post-processing peak analysis results.

PubMed

Korun, M; Vodenik, B; Zorko, B

2018-03-01

A new method for calculating the detection limits of gamma-ray spectrometry measurements is presented. The method is applicable for gamma-ray emitters, irrespective of the influences of the peaked background, the origin of the background and the overlap with other peaks. It offers the opportunity for multi-gamma-ray emitters to calculate the common detection limit, corresponding to more peaks. The detection limit is calculated by approximating the dependence of the uncertainty in the indication on its value with a second-order polynomial. In this approach the relation between the input quantities and the detection limit are described by an explicit expression and can be easy investigated. The detection limit is calculated from the data usually provided by the reports of peak-analyzing programs: the peak areas and their uncertainties. As a result, the need to use individual channel contents for calculating the detection limit is bypassed. Copyright © 2017 Elsevier Ltd. All rights reserved.

Enhanced Positive-Contrast Visualization of Paramagnetic Contrast Agents Using Phase Images

PubMed Central

Mills, Parker H.; Ahrens, Eric T.

2009-01-01

Iron oxide–based MRI contrast agents are increasingly being used to noninvasively track cells, target molecular epitopes, and monitor gene expression in vivo. Detecting regions of contrast agent accumulation can be challenging if resulting contrast is subtle relative to endogenous tissue hypointensities. A postprocessing method is presented that yields enhanced positive-contrast images from the phase map associated with T2*-weighted MRI data. As examples, the method was applied to an agarose gel phantom doped with superparamagnetic iron-oxide nanoparticles and in vivo and ex vivo mouse brains inoculated with recombinant viruses delivering transgenes that induce overexpression of paramagnetic ferritin. Overall, this approach generates images that exhibit a 1- to 8-fold improvement in contrast-to-noise ratio in regions where paramagnetic agents are present compared to conventional magnitude images. This approach can be used in conjunction with conventional T2* pulse sequences, requires no prescans or increased scan time, and can be applied retrospectively to previously acquired data. PMID:19780169

Rock fracture skeleton tracing by image processing and quantitative analysis by geometry features

NASA Astrophysics Data System (ADS)

Liang, Yanjie

2016-06-01

In rock engineering, fracture measurement is important for many applications. This paper proposes a novel method for rock fracture skeleton tracing and analyzing. As for skeleton localizing, the curvilinear fractures are multiscale enhanced based on a Hessian matrix, after image binarization, and clutters are post-processed by image analysis; subsequently, the fracture skeleton is extracted via ridge detection combined with a distance transform and thinning algorithm, after which gap sewing and burrs removal repair the skeleton. In regard to skeleton analyzing, the roughness and distribution of a fracture network are respectively described by the fractal dimensions D s and D b; the intersection and fragmentation of a fracture network are respectively characterized by the average number of ends and junctions per fracture N average and the average length per fracture L average. Three rock fracture surfaces are analyzed for experiments and the results verify that both the fracture tracing accuracy and the analysis feasibility are satisfactory using the new method.

Extending the Capture Volume of an Iris Recognition System Using Wavefront Coding and Super-Resolution.

PubMed

Hsieh, Sheng-Hsun; Li, Yung-Hui; Tien, Chung-Hao; Chang, Chin-Chen

2016-12-01

Iris recognition has gained increasing popularity over the last few decades; however, the stand-off distance in a conventional iris recognition system is too short, which limits its application. In this paper, we propose a novel hardware-software hybrid method to increase the stand-off distance in an iris recognition system. When designing the system hardware, we use an optimized wavefront coding technique to extend the depth of field. To compensate for the blurring of the image caused by wavefront coding, on the software side, the proposed system uses a local patch-based super-resolution method to restore the blurred image to its clear version. The collaborative effect of the new hardware design and software post-processing showed great potential in our experiment. The experimental results showed that such improvement cannot be achieved by using a hardware-or software-only design. The proposed system can increase the capture volume of a conventional iris recognition system by three times and maintain the system's high recognition rate.

A finite element conjugate gradient FFT method for scattering

NASA Technical Reports Server (NTRS)

Collins, Jeffery D.; Zapp, John; Hsa, Chang-Yu; Volakis, John L.

1990-01-01

An extension of a two dimensional formulation is presented for a three dimensional body of revolution. With the introduction of a Fourier expansion of the vector electric and magnetic fields, a coupled two dimensional system is generated and solved via the finite element method. An exact boundary condition is employed to terminate the mesh and the fast fourier transformation (FFT) is used to evaluate the boundary integrals for low O(n) memory demand when an iterative solution algorithm is used. By virtue of the finite element method, the algorithm is applicable to structures of arbitrary material composition. Several improvements to the two dimensional algorithm are also described. These include: (1) modifications for terminating the mesh at circular boundaries without distorting the convolutionality of the boundary integrals; (2) the development of nonproprietary mesh generation routines for two dimensional applications; (3) the development of preprocessors for interfacing SDRC IDEAS with the main algorithm; and (4) the development of post-processing algorithms based on the public domain package GRAFIC to generate two and three dimensional gray level and color field maps.

Retinal blood vessel segmentation using fully convolutional network with transfer learning.

PubMed

Jiang, Zhexin; Zhang, Hao; Wang, Yi; Ko, Seok-Bum

2018-04-26

Since the retinal blood vessel has been acknowledged as an indispensable element in both ophthalmological and cardiovascular disease diagnosis, the accurate segmentation of the retinal vessel tree has become the prerequisite step for automated or computer-aided diagnosis systems. In this paper, a supervised method is presented based on a pre-trained fully convolutional network through transfer learning. This proposed method has simplified the typical retinal vessel segmentation problem from full-size image segmentation to regional vessel element recognition and result merging. Meanwhile, additional unsupervised image post-processing techniques are applied to this proposed method so as to refine the final result. Extensive experiments have been conducted on DRIVE, STARE, CHASE_DB1 and HRF databases, and the accuracy of the cross-database test on these four databases is state-of-the-art, which also presents the high robustness of the proposed approach. This successful result has not only contributed to the area of automated retinal blood vessel segmentation but also supports the effectiveness of transfer learning when applying deep learning technique to medical imaging. Copyright © 2018 Elsevier Ltd. All rights reserved.

Retrieval of land cover information under thin fog in Landsat TM image

NASA Astrophysics Data System (ADS)

Wei, Yuchun

2008-04-01

Thin fog, which often appears in remote sensing image of subtropical climate region, has resulted in the low image quantity and bad image mapping. Therefore, it is necessary to develop the image processing method to retrieve land cover information under thin fog. In this paper, the Landsat TM image near the Taihu Lake that is in the subtropical climate zone of China was used as an example, and the workflow and method used to retrieve the land cover information under thin fog have been built based on ENVI software and a single TM image. The basic step covers three parts: 1) isolating the thin fog area in image according to the spectral difference of different bands; 2) retrieving the visible band information of different land cover types under thin fog from the near-infrared bands according to the relationships between near-infrared bands and visible bands of different land cover types in the area without fog; 3) image post-process. The result showed that the method in the paper is easy and suitable, and can be used to improve the quantity of TM image mapping more effectively.

An automated method to find reaction mechanisms and solve the kinetics in organometallic catalysis.

PubMed

Varela, J A; Vázquez, S A; Martínez-Núñez, E

2017-05-01

A novel computational method is proposed in this work for use in discovering reaction mechanisms and solving the kinetics of transition metal-catalyzed reactions. The method does not rely on either chemical intuition or assumed a priori mechanisms, and it works in a fully automated fashion. Its core is a procedure, recently developed by one of the authors, that combines accelerated direct dynamics with an efficient geometry-based post-processing algorithm to find transition states (Martinez-Nunez, E., J. Comput. Chem. 2015 , 36 , 222-234). In the present work, several auxiliary tools have been added to deal with the specific features of transition metal catalytic reactions. As a test case, we chose the cobalt-catalyzed hydroformylation of ethylene because of its well-established mechanism, and the fact that it has already been used in previous automated computational studies. Besides the generally accepted mechanism of Heck and Breslow, several side reactions, such as hydrogenation of the alkene, emerged from our calculations. Additionally, the calculated rate law for the hydroformylation reaction agrees reasonably well with those obtained in previous experimental and theoretical studies.

Quantitative Proteomics via High Resolution MS Quantification: Capabilities and Limitations

PubMed Central

Higgs, Richard E.; Butler, Jon P.; Han, Bomie; Knierman, Michael D.

2013-01-01

Recent improvements in the mass accuracy and resolution of mass spectrometers have led to renewed interest in label-free quantification using data from the primary mass spectrum (MS1) acquired from data-dependent proteomics experiments. The capacity for higher specificity quantification of peptides from samples enriched for proteins of biological interest offers distinct advantages for hypothesis generating experiments relative to immunoassay detection methods or prespecified peptide ions measured by multiple reaction monitoring (MRM) approaches. Here we describe an evaluation of different methods to post-process peptide level quantification information to support protein level inference. We characterize the methods by examining their ability to recover a known dilution of a standard protein in background matrices of varying complexity. Additionally, the MS1 quantification results are compared to a standard, targeted, MRM approach on the same samples under equivalent instrument conditions. We show the existence of multiple peptides with MS1 quantification sensitivity similar to the best MRM peptides for each of the background matrices studied. Based on these results we provide recommendations on preferred approaches to leveraging quantitative measurements of multiple peptides to improve protein level inference. PMID:23710359

Direct-Solve Image-Based Wavefront Sensing

NASA Technical Reports Server (NTRS)

Lyon, Richard G.

2009-01-01

A method of wavefront sensing (more precisely characterized as a method of determining the deviation of a wavefront from a nominal figure) has been invented as an improved means of assessing the performance of an optical system as affected by such imperfections as misalignments, design errors, and fabrication errors. The method is implemented by software running on a single-processor computer that is connected, via a suitable interface, to the image sensor (typically, a charge-coupled device) in the system under test. The software collects a digitized single image from the image sensor. The image is displayed on a computer monitor. The software directly solves for the wavefront in a time interval of a fraction of a second. A picture of the wavefront is displayed. The solution process involves, among other things, fast Fourier transforms. It has been reported to the effect that some measure of the wavefront is decomposed into modes of the optical system under test, but it has not been reported whether this decomposition is postprocessing of the solution or part of the solution process.

Incorporating deliverable monitor unit constraints into spot intensity optimization in intensity modulated proton therapy treatment planning

PubMed Central

Cao, Wenhua; Lim, Gino; Li, Xiaoqiang; Li, Yupeng; Zhu, X. Ronald; Zhang, Xiaodong

2014-01-01

The purpose of this study is to investigate the feasibility and impact of incorporating deliverable monitor unit (MU) constraints into spot intensity optimization in intensity modulated proton therapy (IMPT) treatment planning. The current treatment planning system (TPS) for IMPT disregards deliverable MU constraints in the spot intensity optimization (SIO) routine. It performs a post-processing procedure on an optimized plan to enforce deliverable MU values that are required by the spot scanning proton delivery system. This procedure can create a significant dose distribution deviation between the optimized and post-processed deliverable plans, especially when small spot spacings are used. In this study, we introduce a two-stage linear programming (LP) approach to optimize spot intensities and constrain deliverable MU values simultaneously, i.e., a deliverable spot intensity optimization (DSIO) model. Thus, the post-processing procedure is eliminated and the associated optimized plan deterioration can be avoided. Four prostate cancer cases at our institution were selected for study and two parallel opposed beam angles were planned for all cases. A quadratic programming (QP) based model without MU constraints, i.e., a conventional spot intensity optimization (CSIO) model, was also implemented to emulate the commercial TPS. Plans optimized by both the DSIO and CSIO models were evaluated for five different settings of spot spacing from 3 mm to 7 mm. For all spot spacings, the DSIO-optimized plans yielded better uniformity for the target dose coverage and critical structure sparing than did the CSIO-optimized plans. With reduced spot spacings, more significant improvements in target dose uniformity and critical structure sparing were observed in the DSIO- than in the CSIO-optimized plans. Additionally, better sparing of the rectum and bladder was achieved when reduced spacings were used for the DSIO-optimized plans. The proposed DSIO approach ensures the deliverability of optimized IMPT plans that take into account MU constraints. This eliminates the post-processing procedure required by the TPS as well as the resultant deteriorating effect on ultimate dose distributions. This approach therefore allows IMPT plans to adopt all possible spot spacings optimally. Moreover, dosimetric benefits can be achieved using smaller spot spacings. PMID:23835656

Kinematic reconstruction in cardiovascular imaging.

PubMed

Bastarrika, G; Huebra Rodríguez, I J González de la; Calvo-Imirizaldu, M; Suárez Vega, V M; Alonso-Burgos, A

2018-05-17

Advances in clinical applications of computed tomography have been accompanied by improvements in advanced post-processing tools. In addition to multiplanar reconstructions, curved planar reconstructions, maximum intensity projections, and volumetric reconstructions, very recently kinematic reconstruction has been developed. This new technique, based on mathematical models that simulate the propagation of light beams through a volume of data, makes it possible to obtain very realistic three dimensional images. This article illustrates examples of kinematic reconstructions and compares them with classical volumetric reconstructions in patients with cardiovascular disease in a way that makes it easy to establish the differences between the two types of reconstruction. Kinematic reconstruction is a new method for representing three dimensional images that facilitates the explanation and comprehension of the findings. Copyright © 2018 SERAM. Publicado por Elsevier España, S.L.U. All rights reserved.

Toward detection of marine vehicles on horizon from buoy camera

NASA Astrophysics Data System (ADS)

Fefilatyev, Sergiy; Goldgof, Dmitry B.; Langebrake, Lawrence

2007-10-01

This paper presents a new technique for automatic detection of marine vehicles in open sea from a buoy camera system using computer vision approach. Users of such system include border guards, military, port safety and flow management, sanctuary protection personnel. The system is intended to work autonomously, taking images of the surrounding ocean surface and analyzing them on the subject of presence of marine vehicles. The goal of the system is to detect an approximate window around the ship and prepare the small image for transmission and human evaluation. The proposed computer vision-based algorithm combines horizon detection method with edge detection and post-processing. The dataset of 100 images is used to evaluate the performance of proposed technique. We discuss promising results of ship detection and suggest necessary improvements for achieving better performance.

Topology-optimization-based design method of flexures for mounting the primary mirror of a large-aperture space telescope.

PubMed

Hu, Rui; Liu, Shutian; Li, Quhao

2017-05-20

For the development of a large-aperture space telescope, one of the key techniques is the method for designing the flexures for mounting the primary mirror, as the flexures are the key components. In this paper, a topology-optimization-based method for designing flexures is presented. The structural performances of the mirror system under multiple load conditions, including static gravity and thermal loads, as well as the dynamic vibration, are considered. The mirror surface shape error caused by gravity and the thermal effect is treated as the objective function, and the first-order natural frequency of the mirror structural system is taken as the constraint. The pattern repetition constraint is added, which can ensure symmetrical material distribution. The topology optimization model for flexure design is established. The substructuring method is also used to condense the degrees of freedom (DOF) of all the nodes of the mirror system, except for the nodes that are linked to the mounting flexures, to reduce the computation effort during the optimization iteration process. A potential optimized configuration is achieved by solving the optimization model and post-processing. A detailed shape optimization is subsequently conducted to optimize its dimension parameters. Our optimization method deduces new mounting structures that significantly enhance the optical performance of the mirror system compared to the traditional methods, which only focus on the parameters of existing structures. Design results demonstrate the effectiveness of the proposed optimization method.

Bayer image parallel decoding based on GPU

NASA Astrophysics Data System (ADS)

Hu, Rihui; Xu, Zhiyong; Wei, Yuxing; Sun, Shaohua

2012-11-01

In the photoelectrical tracking system, Bayer image is decompressed in traditional method, which is CPU-based. However, it is too slow when the images become large, for example, 2K×2K×16bit. In order to accelerate the Bayer image decoding, this paper introduces a parallel speedup method for NVIDA's Graphics Processor Unit (GPU) which supports CUDA architecture. The decoding procedure can be divided into three parts: the first is serial part, the second is task-parallelism part, and the last is data-parallelism part including inverse quantization, inverse discrete wavelet transform (IDWT) as well as image post-processing part. For reducing the execution time, the task-parallelism part is optimized by OpenMP techniques. The data-parallelism part could advance its efficiency through executing on the GPU as CUDA parallel program. The optimization techniques include instruction optimization, shared memory access optimization, the access memory coalesced optimization and texture memory optimization. In particular, it can significantly speed up the IDWT by rewriting the 2D (Tow-dimensional) serial IDWT into 1D parallel IDWT. Through experimenting with 1K×1K×16bit Bayer image, data-parallelism part is 10 more times faster than CPU-based implementation. Finally, a CPU+GPU heterogeneous decompression system was designed. The experimental result shows that it could achieve 3 to 5 times speed increase compared to the CPU serial method.

Enhanced cortical thickness measurements for rodent brains via Lagrangian-based RK4 streamline computation

NASA Astrophysics Data System (ADS)

Lee, Joohwi; Kim, Sun Hyung; Oguz, Ipek; Styner, Martin

2016-03-01

The cortical thickness of the mammalian brain is an important morphological characteristic that can be used to investigate and observe the brain's developmental changes that might be caused by biologically toxic substances such as ethanol or cocaine. Although various cortical thickness analysis methods have been proposed that are applicable for human brain and have developed into well-validated open-source software packages, cortical thickness analysis methods for rodent brains have not yet become as robust and accurate as those designed for human brains. Based on a previously proposed cortical thickness measurement pipeline for rodent brain analysis,1 we present an enhanced cortical thickness pipeline in terms of accuracy and anatomical consistency. First, we propose a Lagrangian-based computational approach in the thickness measurement step in order to minimize local truncation error using the fourth-order Runge-Kutta method. Second, by constructing a line object for each streamline of the thickness measurement, we can visualize the way the thickness is measured and achieve sub-voxel accuracy by performing geometric post-processing. Last, with emphasis on the importance of an anatomically consistent partial differential equation (PDE) boundary map, we propose an automatic PDE boundary map generation algorithm that is specific to rodent brain anatomy, which does not require manual labeling. The results show that the proposed cortical thickness pipeline can produce statistically significant regions that are not observed in the previous cortical thickness analysis pipeline.

A new full-field digital mammography system with and without the use of an advanced post-processing algorithm: comparison of image quality and diagnostic performance.

PubMed

Ahn, Hye Shin; Kim, Sun Mi; Jang, Mijung; Yun, Bo La; Kim, Bohyoung; Ko, Eun Sook; Han, Boo-Kyung; Chang, Jung Min; Yi, Ann; Cho, Nariya; Moon, Woo Kyung; Choi, Hye Young

2014-01-01

To compare new full-field digital mammography (FFDM) with and without use of an advanced post-processing algorithm to improve image quality, lesion detection, diagnostic performance, and priority rank. During a 22-month period, we prospectively enrolled 100 cases of specimen FFDM mammography (Brestige®), which was performed alone or in combination with a post-processing algorithm developed by the manufacturer: group A (SMA), specimen mammography without application of "Mammogram enhancement ver. 2.0"; group B (SMB), specimen mammography with application of "Mammogram enhancement ver. 2.0". Two sets of specimen mammographies were randomly reviewed by five experienced radiologists. Image quality, lesion detection, diagnostic performance, and priority rank with regard to image preference were evaluated. Three aspects of image quality (overall quality, contrast, and noise) of the SMB were significantly superior to those of SMA (p < 0.05). SMB was significantly superior to SMA for visualizing calcifications (p < 0.05). Diagnostic performance, as evaluated by cancer score, was similar between SMA and SMB. SMB was preferred to SMA by four of the five reviewers. The post-processing algorithm may improve image quality with better image preference in FFDM than without use of the software.

Improving Robustness of Hydrologic Ensemble Predictions Through Probabilistic Pre- and Post-Processing in Sequential Data Assimilation

NASA Astrophysics Data System (ADS)

Wang, S.; Ancell, B. C.; Huang, G. H.; Baetz, B. W.

2018-03-01

Data assimilation using the ensemble Kalman filter (EnKF) has been increasingly recognized as a promising tool for probabilistic hydrologic predictions. However, little effort has been made to conduct the pre- and post-processing of assimilation experiments, posing a significant challenge in achieving the best performance of hydrologic predictions. This paper presents a unified data assimilation framework for improving the robustness of hydrologic ensemble predictions. Statistical pre-processing of assimilation experiments is conducted through the factorial design and analysis to identify the best EnKF settings with maximized performance. After the data assimilation operation, statistical post-processing analysis is also performed through the factorial polynomial chaos expansion to efficiently address uncertainties in hydrologic predictions, as well as to explicitly reveal potential interactions among model parameters and their contributions to the predictive accuracy. In addition, the Gaussian anamorphosis is used to establish a seamless bridge between data assimilation and uncertainty quantification of hydrologic predictions. Both synthetic and real data assimilation experiments are carried out to demonstrate feasibility and applicability of the proposed methodology in the Guadalupe River basin, Texas. Results suggest that statistical pre- and post-processing of data assimilation experiments provide meaningful insights into the dynamic behavior of hydrologic systems and enhance robustness of hydrologic ensemble predictions.

Efficient high-rate satellite clock estimation for PPP ambiguity resolution using carrier-ranges.

PubMed

Chen, Hua; Jiang, Weiping; Ge, Maorong; Wickert, Jens; Schuh, Harald

2014-11-25

In order to catch up the short-term clock variation of GNSS satellites, clock corrections must be estimated and updated at a high-rate for Precise Point Positioning (PPP). This estimation is already very time-consuming for the GPS constellation only as a great number of ambiguities need to be simultaneously estimated. However, on the one hand better estimates are expected by including more stations, and on the other hand satellites from different GNSS systems must be processed integratively for a reliable multi-GNSS positioning service. To alleviate the heavy computational burden, epoch-differenced observations are always employed where ambiguities are eliminated. As the epoch-differenced method can only derive temporal clock changes which have to be aligned to the absolute clocks but always in a rather complicated way, in this paper, an efficient method for high-rate clock estimation is proposed using the concept of "carrier-range" realized by means of PPP with integer ambiguity resolution. Processing procedures for both post- and real-time processing are developed, respectively. The experimental validation shows that the computation time could be reduced to about one sixth of that of the existing methods for post-processing and less than 1 s for processing a single epoch of a network with about 200 stations in real-time mode after all ambiguities are fixed. This confirms that the proposed processing strategy will enable the high-rate clock estimation for future multi-GNSS networks in post-processing and possibly also in real-time mode.

Rotorcraft Flight Simulation Computer Program C81 with DATAMAP interface. Volume I. User’s Manual

DTIC Science & Technology

1981-10-01

any one of the RWAS tables to simulate the defined effect of that input, care must be exercised to assure that the table used is based on the correct... IMPROVED MANEUVER AUTOPILOT HAVE BEEN INSTALLED IN AGAPBO. A NEW LISTING OF THE CONTENTS OF THE ANALYTICAL DATA BASE WILL BE GENERATED DURING THE WEEK...of the program (Reference 1) has been improved by providing the cap- ability to generate Postprocessing Data Blocks containing selected variables

Groundwater flow and solute transport modelling from within R: Development of the RMODFLOW and RMT3DMS packages.

NASA Astrophysics Data System (ADS)

Rogiers, Bart

2015-04-01

Since a few years, an increasing number of contributed R packages is becoming available, in the field of hydrology. Hydrological time series analysis packages, lumped conceptual rainfall-runoff models, distributed hydrological models, weather generators, and different calibration and uncertainty estimation methods are all available. Also a few packages are available for solving partial differential equations. Subsurface hydrological modelling is however still seldomly performed in R, or with codes interfaced with R, despite the fact that excellent geostatistical packages, model calibration/inversion options and state-of-the-art visualization libraries are available. Moreover, other popular scientific programming languages like matlab and python have packages for pre- and post-processing files of MODFLOW (Harbaugh 2005) and MT3DMS (Zheng 2010) models. To fill this gap, we present here the development versions of the RMODFLOW and RMT3DMS packages, which allow pre- and post-processing MODFLOW and MT3DMS input and output files from within R. File reading and writing functions are currently available for different packages, and plotting functions are foreseen making use of the ggplot2 package (plotting system based on the grammar of graphics; Wickham 2009). The S3 generic-function object oriented programming style is used for this. An example is provided, making modifications to an existing model, and visualization of the model output. References Harbaugh, A. (2005). MODFLOW-2005: The US Geological Survey Modular Ground-water Model--the Ground-water Flow Process, U.S. Geological Survey Techniques and Methods 6-A16 (p. 253). Wickham, H. (2009). ggplot2: elegant graphics for data analysis. Springer New York, 2009. Zheng, C. (2010). MT3DMS v5.3, a modular three-dimensional multispecies transport model for simulation of advection, dispersion and chemical reactions of contaminants in groundwater systems. Supplemental User's Guide. (p. 56).

An adaptive optics imaging system designed for clinical use

PubMed Central

Zhang, Jie; Yang, Qiang; Saito, Kenichi; Nozato, Koji; Williams, David R.; Rossi, Ethan A.

2015-01-01

Here we demonstrate a new imaging system that addresses several major problems limiting the clinical utility of conventional adaptive optics scanning light ophthalmoscopy (AOSLO), including its small field of view (FOV), reliance on patient fixation for targeting imaging, and substantial post-processing time. We previously showed an efficient image based eye tracking method for real-time optical stabilization and image registration in AOSLO. However, in patients with poor fixation, eye motion causes the FOV to drift substantially, causing this approach to fail. We solve that problem here by tracking eye motion at multiple spatial scales simultaneously by optically and electronically integrating a wide FOV SLO (WFSLO) with an AOSLO. This multi-scale approach, implemented with fast tip/tilt mirrors, has a large stabilization range of ± 5.6°. Our method consists of three stages implemented in parallel: 1) coarse optical stabilization driven by a WFSLO image, 2) fine optical stabilization driven by an AOSLO image, and 3) sub-pixel digital registration of the AOSLO image. We evaluated system performance in normal eyes and diseased eyes with poor fixation. Residual image motion with incremental compensation after each stage was: 1) ~2–3 arc minutes, (arcmin) 2) ~0.5–0.8 arcmin and, 3) ~0.05–0.07 arcmin, for normal eyes. Performance in eyes with poor fixation was: 1) ~3–5 arcmin, 2) ~0.7–1.1 arcmin and 3) ~0.07–0.14 arcmin. We demonstrate that this system is capable of reducing image motion by a factor of ~400, on average. This new optical design provides additional benefits for clinical imaging, including a steering subsystem for AOSLO that can be guided by the WFSLO to target specific regions of interest such as retinal pathology and real-time averaging of registered images to eliminate image post-processing. PMID:26114033

Automated Glioblastoma Segmentation Based on a Multiparametric Structured Unsupervised Classification

PubMed Central

Juan-Albarracín, Javier; Fuster-Garcia, Elies; Manjón, José V.; Robles, Montserrat; Aparici, F.; Martí-Bonmatí, L.; García-Gómez, Juan M.

2015-01-01

Automatic brain tumour segmentation has become a key component for the future of brain tumour treatment. Currently, most of brain tumour segmentation approaches arise from the supervised learning standpoint, which requires a labelled training dataset from which to infer the models of the classes. The performance of these models is directly determined by the size and quality of the training corpus, whose retrieval becomes a tedious and time-consuming task. On the other hand, unsupervised approaches avoid these limitations but often do not reach comparable results than the supervised methods. In this sense, we propose an automated unsupervised method for brain tumour segmentation based on anatomical Magnetic Resonance (MR) images. Four unsupervised classification algorithms, grouped by their structured or non-structured condition, were evaluated within our pipeline. Considering the non-structured algorithms, we evaluated K-means, Fuzzy K-means and Gaussian Mixture Model (GMM), whereas as structured classification algorithms we evaluated Gaussian Hidden Markov Random Field (GHMRF). An automated postprocess based on a statistical approach supported by tissue probability maps is proposed to automatically identify the tumour classes after the segmentations. We evaluated our brain tumour segmentation method with the public BRAin Tumor Segmentation (BRATS) 2013 Test and Leaderboard datasets. Our approach based on the GMM model improves the results obtained by most of the supervised methods evaluated with the Leaderboard set and reaches the second position in the ranking. Our variant based on the GHMRF achieves the first position in the Test ranking of the unsupervised approaches and the seventh position in the general Test ranking, which confirms the method as a viable alternative for brain tumour segmentation. PMID:25978453

Automatic detection of echolocation clicks based on a Gabor model of their waveform.

PubMed

Madhusudhana, Shyam; Gavrilov, Alexander; Erbe, Christine

2015-06-01

Prior research has shown that echolocation clicks of several species of terrestrial and marine fauna can be modelled as Gabor-like functions. Here, a system is proposed for the automatic detection of a variety of such signals. By means of mathematical formulation, it is shown that the output of the Teager-Kaiser Energy Operator (TKEO) applied to Gabor-like signals can be approximated by a Gaussian function. Based on the inferences, a detection algorithm involving the post-processing of the TKEO outputs is presented. The ratio of the outputs of two moving-average filters, a Gaussian and a rectangular filter, is shown to be an effective detection parameter. Detector performance is assessed using synthetic and real (taken from MobySound database) recordings. The detection method is shown to work readily with a variety of echolocation clicks and in various recording scenarios. The system exhibits low computational complexity and operates several times faster than real-time. Performance comparisons are made to other publicly available detectors including pamguard.

Reconstruction and separation of vibratory field using structural holography

NASA Astrophysics Data System (ADS)

Chesnais, C.; Totaro, N.; Thomas, J.-H.; Guyader, J.-L.

2017-02-01

A method for reconstructing and separating vibratory field on a plate-like structure is presented. The method, called "Structural Holography" is derived from classical Near-field Acoustic Holography (NAH) but in the vibratory domain. In this case, the plate displacement is measured on one-dimensional lines (the holograms) and used to reconstruct the entire two-dimensional displacement field. As a consequence, remote measurements on non directly accessible zones are possible with Structural Holography. Moreover, as it is based on the decomposition of the field into forth and back waves, Structural Holography permits to separate forces in the case of multi-sources excitation. The theoretical background of the Structural Holography method is described first. Then, to illustrate the process and the possibilities of Structural Holography, the academic test case of an infinite plate excited by few point forces is presented. With the principle of vibratory field separation, the displacement fields produced by each point force separately is reconstructed. However, the displacement field is not always meaningful and some additional treatments are mandatory to localize the position of point forces for example. From the simple example of an infinite plate, a post-processing based on the reconstruction of the structural intensity field is thus proposed. Finally, Structural Holography is generalized to finite plates and applied to real experimental measurements

Impulse excitation scanning acoustic microscopy for local quantification of Rayleigh surface wave velocity using B-scan analysis

NASA Astrophysics Data System (ADS)

Cherry, M.; Dierken, J.; Boehnlein, T.; Pilchak, A.; Sathish, S.; Grandhi, R.

2018-01-01

A new technique for performing quantitative scanning acoustic microscopy imaging of Rayleigh surface wave (RSW) velocity was developed based on b-scan processing. In this technique, the focused acoustic beam is moved through many defocus distances over the sample and excited with an impulse excitation, and advanced algorithms based on frequency filtering and the Hilbert transform are used to post-process the b-scans to estimate the Rayleigh surface wave velocity. The new method was used to estimate the RSW velocity on an optically flat E6 glass sample, and the velocity was measured at ±2 m/s and the scanning time per point was on the order of 1.0 s, which are both improvement from the previous two-point defocus method. The new method was also applied to the analysis of two titanium samples, and the velocity was estimated with very low standard deviation in certain large grains on the sample. A new behavior was observed with the b-scan analysis technique where the amplitude of the surface wave decayed dramatically on certain crystallographic orientations. The new technique was also compared with previous results, and the new technique has been found to be much more reliable and to have higher contrast than previously possible with impulse excitation.

Research on the magnetorheological finishing of large aperture off-axis aspheric optical surfaces for zinc sulfide

NASA Astrophysics Data System (ADS)

Zhang, Yunfei; Huang, Wen; Zheng, Yongcheng; Ji, Fang; Xu, Min; Duan, Zhixin; Luo, Qing; Liu, Qian; Xiao, Hong

2016-03-01

Zinc sulfide is a kind of typical infrared optical material, commonly produced using single point diamond turning (SPDT). SPDT can efficiently produce zinc sulfide aspheric surfaces with micro-roughness and acceptable figure error. However the tool marks left by the diamond turning process cause high micro-roughness that degrades the optical performance when used in the visible region of the spectrum. Magnetorheological finishing (MRF) is a deterministic, sub-aperture polishing technology that is very helpful in improving both surface micro-roughness and surface figure.This paper mainly investigates the MRF technology of large aperture off-axis aspheric optical surfaces for zinc sulfide. The topological structure and coordinate transformation of a MRF machine tool PKC1200Q2 are analyzed and its kinematics is calculated, then the post-processing algorithm model of MRF for an optical lens is established. By taking the post-processing of off-axis aspheric surfacefor example, a post-processing algorithm that can be used for a raster tool path is deduced and the errors produced by the approximate treatment are analyzed. A polishing algorithm of trajectory planning and dwell time based on matrix equation and optimization theory is presented in this paper. Adopting this algorithm an experiment is performed to machining a large-aperture off-axis aspheric surface on the MRF machine developed by ourselves. After several times' polishing, the figure accuracy PV is proved from 3.3λ to 2.0λ and RMS from 0.451λ to 0.327λ. This algorithm is used to polish the other shapes including spheres, aspheres and prisms.

Seek and destroy process: Listeria monocytogenes process controls in the ready-to-eat meat and poultry industry.

PubMed

Malley, Thomas J V; Butts, John; Wiedmann, Martin

2015-02-01

The majority of human listeriosis cases appear to be caused by consumption of ready-to-eat (RTE) foods contaminated at the time of consumption with high levels of Listeria monocytogenes. Although strategies to prevent growth of L. monocytogenes in RTE products are critical for reducing the incidence of human listeriosis, control of postprocessing environmental contamination of RTE meat and poultry products is an essential component of a comprehensive L. monocytogenes intervention and control program. Complete elimination of postprocessing L. monocytogenes contamination is challenging because this pathogen is common in various environments outside processing plants and can persist in food processing environments for years. Persistent L. monocytogenes strains in processing plants have been identified as the most common postprocessing contaminants of RTE foods and the cause of multiple listeriosis outbreaks. Identification and elimination of L. monocytogenes strains persisting in processing plants is thus critical for (i) compliance with zero-tolerance regulations for L. monocytogenes in U.S. RTE meat and poultry products and (ii) reduction of the incidence of human listeriosis. The seek-and-destroy process is a systematic approach to finding sites of persistent strains (niches) in food processing plants, with the goal of either eradicating or mitigating effects of these strains. This process has been used effectively to address persistent L. monocytogenes contamination in food processing plants, as supported by peer-reviewed evidence detailed here. Thus, a regulatory environment that encourages aggressive environmental Listeria testing is required to facilitate continued use of this science-based strategy for controlling L. monocytogenes in RTE foods.

Enhanced HTS hit selection via a local hit rate analysis.

PubMed

Posner, Bruce A; Xi, Hualin; Mills, James E J

2009-10-01

The postprocessing of high-throughput screening (HTS) results is complicated by the occurrence of false positives (inactive compounds misidentified as active by the primary screen) and false negatives (active compounds misidentified as inactive by the primary screen). An activity cutoff is frequently used to select "active" compounds from HTS data; however, this approach is insensitive to both false positives and false negatives. An alternative method that can minimize the occurrence of these artifacts will increase the efficiency of hit selection and therefore lead discovery. In this work, rather than merely using the activity of a given compound, we look at the presence and absence of activity among all compounds in its "chemical space neighborhood" to give a degree of confidence in its activity. We demonstrate that this local hit rate (LHR) analysis method outperforms hit selection based on ranking by primary screen activity values across ten diverse high throughput screens, spanning both cell-based and biochemical assay formats of varying biology and robustness. On average, the local hit rate analysis method was approximately 2.3-fold and approximately 1.3-fold more effective in identifying active compounds and active chemical series, respectively, than selection based on primary activity alone. Moreover, when applied to finding false negatives, this method was 2.3-fold better than ranking by primary activity alone. In most cases, novel hit series were identified that would have otherwise been missed. Additional uses of and observations regarding this HTS analysis approach are also discussed.

Interventional MR: vascular applications.

PubMed

Smits, H F; Bos, C; van der Weide, R; Bakker, C J

1999-01-01

Three strategies for visualisation of MR-dedicated guidewires and catheters have been proposed, namely active tracking, the technique of locally induced field inhomogeneity and passive susceptibility-based tracking. In this article the pros and cons of these techniques are discussed, including the development of MR-dedicated guidewires and catheters, scan techniques, post-processing tools, and display facilities for MR tracking. Finally, some of the results obtained with MR tracking are discussed.

Multi-link laser interferometer architecture for a next generation GRACE

NASA Astrophysics Data System (ADS)

Francis, Samuel Peter

When GRACE Follow-On (GRACE-FO) launches, it will be the first time a laser interferometer has been used to measure displacement between spacecraft. In the future, interspacecraft laser interferometry will be used in LISA, a space-based gravitational wave detector, that requires the change in separation between three spacecraft to be measured with a resolution of 1 pm/rtHz. The sensitivity of an interspacecraft interferometer is potentially limited by spacecraft degrees-of-freedom, such as rotation, coupling into the interspacecraft displacement measurement. GRACE-FO and LISA therefore have strict requirements placed on the positioning and alignment of the interferometers during spacecraft integration. Decades of work has gone into adapting traditionally lab-based techniques for these space applications. As an example, GRACE-FO stops rotation of the two spacecraft from coupling into displacement using the triple mirror assembly. The triple mirror assembly is a precision optic, comprised of three mirrors, that function as a retroreflector. Provided the triple mirror assembly vertex coincides with the spacecraft centre of mass, any spacecraft rotation will asymmetrically lengthen and shorten the optical pathlengths of the incoming and outgoing beams, ensuring that the round trip pathlength between the spacecraft is unaffected. To achieve the required displacement sensitivity, the triple mirror assembly vertex must be positioned within 0.5 mm of the spacecraft centre of mass, making spacecraft integration challenging. In this thesis a new, all-fibre interferometer architecture is presented that aims to simplify the positioning and alignment of space-based interferometers. Using multiple interspacecraft link measurements and high-speed signal processing the interspacecraft displacement is synthesised in post-processing. The multi-link interferometry concept is similar to the triple mirror assembly's symmetric suppression of rotation, however, since the rotation-to-pathlength cancellation is performed in post-processing, the weighting of each interspacecraft link measurement can be optimised to completely cancel any rotation coupled error. Consequently, any uncertainty in the positioning of the multi-link interferometer during spacecraft integration can be corrected for in post-processing. The strict hardware integration requirements of current interferometers can therefore be relaxed, enabling a new class of simpler, cheaper missions. (Abstract shortened by ProQuest.).

The effect of postprocessing on tensile property and microstructure evolution of friction stir welding aluminum alloy joint

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

Hu, Z.L., E-mail: zhilihuhit@163.com; State Key Laboratory of Advanced Welding and Joining, Harbin Institute of Technology, Harbin 150001; State Key Laboratory of Materials Processing and Die & Mould Technology, Huazhong University of Science and Technology

Friction stir welding is an efficient manufacturing method for joining aluminum alloy and can dramatically reduce grain size conferring excellent plastic deformation properties. Consequently, friction stir welding is used to manufacture tailor welded blanks to optimize weight or performance in the final component. In the study, the microstructural evolution and mechanical properties of friction stir welding joint during plastic forming and subsequent heat treatment were investigated. The microstructural characteristics of the friction stir welding joints were studied by Electron Backscattered Diffraction and Transmission Electron Microscopy. The mechanical properties were evaluated by tensile and microhardness tests. It is found that themore » tensile and yield strengths of friction stir welding joints are significantly improved after severe plastic deformation due to the grain refinement. Following heat treatment, the strength of the friction stir welding joints significantly decrease due to the obvious abnormal grain growth. Careful attention must be given to the processing route of any friction stir welding joint intended for plastic forming, especially the annealing between forming passes. Severe plastic deforming of the friction stir welding joint leads to a high level of stored energy/dislocation density, which causes the abnormal grain growth during subsequent heat treatment, and consequently reduce the mechanical properties of the friction stir welding joint. - Highlights: • Great changes are observed in the microstructure of FSW joint after postprocessing. • Postprocessing shows great effect on the microstructure stability of FSW joint. • The weld shows more significant decrease in strength than the BM due to the AGG. • Attention must be given to the processing route of FSW joint for plastic forming.« less