WorldWideScience

Sample records for preprocessed grace-a level-1b

  1. ESA Swarm Mission - Level 1b Products

    Science.gov (United States)

    Tøffner-Clausen, Lars; Floberghagen, Rune; Mecozzi, Riccardo; Menard, Yvon

    2014-05-01

    Swarm, a three-satellite constellation to study the dynamics of the Earth's magnetic field and its interactions with the Earth system, has been launched in November 2013. The objective of the Swarm mission is to provide the best ever survey of the geomagnetic field and its temporal evolution, which will bring new insights into the Earth system by improving our understanding of the Earth's interior and environment. The Level 1b Products of the Swarm mission contain time-series of the quality screened, calibrated, corrected, and fully geo-localized measurements of the magnetic field intensity, the magnetic field vector (provided in both instrument and Earth-fixed frames), the plasma density, temperature, and velocity. Additionally, quality screened and pre-calibrated measurements of the nongravitational accelerations are provided. Geo-localization is performed by 24- channel GPS receivers and by means of unique, three head Advanced Stellar Compasses for high-precision satellite attitude information. The Swarm Level 1b data will be provided in daily products separately for each of the three Swarm spacecrafts. This poster will present detailed lists of the contents of the Swarm Level 1b Products and brief descriptions of the processing algorithms used in the generation of these data.

  2. Processing TES Level-1B Data

    Science.gov (United States)

    DeBaca, Richard C.; Sarkissian, Edwin; Madatyan, Mariyetta; Shepard, Douglas; Gluck, Scott; Apolinski, Mark; McDuffie, James; Tremblay, Dennis

    2006-01-01

    TES L1B Subsystem is a computer program that performs several functions for the Tropospheric Emission Spectrometer (TES). The term "L1B" (an abbreviation of "level 1B"), refers to data, specific to the TES, on radiometric calibrated spectral radiances and their corresponding noise equivalent spectral radiances (NESRs), plus ancillary geolocation, quality, and engineering data. The functions performed by TES L1B Subsystem include shear analysis, monitoring of signal levels, detection of ice build-up, and phase correction and radiometric and spectral calibration of TES target data. Also, the program computes NESRs for target spectra, writes scientific TES level-1B data to hierarchical- data-format (HDF) files for public distribution, computes brightness temperatures, and quantifies interpixel signal variability for the purpose of first-order cloud and heterogeneous land screening by the level-2 software summarized in the immediately following article. This program uses an in-house-developed algorithm, called "NUSRT," to correct instrument line-shape factors.

  3. EOS MLS Level 1B Data Processing Software. Version 3

    Science.gov (United States)

    Perun, Vincent S.; Jarnot, Robert F.; Wagner, Paul A.; Cofield, Richard E., IV; Nguyen, Honghanh T.; Vuu, Christina

    2011-01-01

    This software is an improvement on Version 2, which was described in EOS MLS Level 1B Data Processing, Version 2.2, NASA Tech Briefs, Vol. 33, No. 5 (May 2009), p. 34. It accepts the EOS MLS Level 0 science/engineering data, and the EOS Aura spacecraft ephemeris/attitude data, and produces calibrated instrument radiances and associated engineering and diagnostic data. This version makes the code more robust, improves calibration, provides more diagnostics outputs, defines the Galactic core more finely, and fixes the equator crossing. The Level 1 processing software manages several different tasks. It qualifies each data quantity using instrument configuration and checksum data, as well as data transmission quality flags. Statistical tests are applied for data quality and reasonableness. The instrument engineering data (e.g., voltages, currents, temperatures, and encoder angles) is calibrated by the software, and the filter channel space reference measurements are interpolated onto the times of each limb measurement with the interpolates being differenced from the measurements. Filter channel calibration target measurements are interpolated onto the times of each limb measurement, and are used to compute radiometric gain. The total signal power is determined and analyzed by each digital autocorrelator spectrometer (DACS) during each data integration. The software converts each DACS data integration from an autocorrelation measurement in the time domain into a spectral measurement in the frequency domain, and estimates separately the spectrally, smoothly varying and spectrally averaged components of the limb port signal arising from antenna emission and scattering effects. Limb radiances are also calibrated.

  4. Cryosat Level1b SAR/Sarin: Improving the Quality of the Baseline C Products

    Science.gov (United States)

    Scagliola, M.; Fornari, M.; Tagliani, N.; Frommknecht, B.; Bouffard, J.; Parrinello, T.

    2014-12-01

    CryoSat was launched on the 8th April 2010 and it is the first European ice mission dedicated to monitoring precise changes in the thickness of polar ice sheets and floating sea ice over a 3-year period. Cryosat carries an innovative radar altimeter called the Synthetic Aperture Interferometric Altimeter (SIRAL), that transmits pulses at a high pulse repetition frequency thus making the received echoes phase coherent and suitable for azimuth processing. This allows to reach a significantly improved along track resolution with respect to traditional pulse-width limited altimeters. CryoSat is the first altimetry mission operating in SAR mode and continuous improvement in the Level1 Instrument Processing Facility (IPF1) are being identified, tested and validated in order to improve the quality of the Level1b products. Towards the release of the BaselineC of the CryoSat Level1b SAR/SARin products, that is expected at the end of 2014, several improvements have been identified: a datation bias of about -0.5195 ms will be corrected a range bias of about 0.6730 m will be corrected The range window size will be doubled with respect to BaselineB, so that the in Level1b products the waveforms will be doubled too Improved processing for 1Hz echoes to have sharper waveforms Surface sample stack weighting to filter out the single look echoes acquired at highest look angle, that results in a sharpening of the 20Hz waveforms Additional auxiliary information related to the mispointing angles of the instrument as well as to the stacks of single look echoes will be added This poster details the main quality improvements that are foreseen to be included in the CryoSat Level1b SAR/SARin products in BaselineC.

  5. CryoSat Level1b SAR/SARin: quality improvements towards BaselineC

    Science.gov (United States)

    Scagliola, Michele; Fornari, Marco; Bouzinac, Catherine; Tagliani, Nicolas; Parrinello, Tommaso

    2014-05-01

    CryoSat was launched on the 8th April 2010 and it is the first European ice mission dedicated to monitoring precise changes in the thickness of polar ice sheets and floating sea ice over a 3-year period. Cryosat carries an innovative radar altimeter called the Synthetic Aperture Interferometric Altimeter (SIRAL), that transmits pulses at a high pulse repetition frequency thus making the received echoes phase coherent and suitable for azimuth processing. This allows to reach a significantly improved along track resolution with respect to traditional pulse-width limited altimeters. CryoSat is the first altimetry mission operating in SAR mode and continuous improvement in the Level1 Instrument Processing Facility (IPF1) are being identified, tested and validated in order to improve the quality of the Level1b products. Towards the release of the BaselineC of the CryoSat Level1b SAR/SARin products, that is expected during 2014, several improvements have been identified: • a datation bias of about -0.5195 ms will be corrected • a range bias of about -0.6730 m will be corrected • the waveform length in the Level1b product will be doubled with respect to BaselineB • improved processing for 1Hz echoes to have sharper waveforms • surface sample stack weighting to filter out the single look echoes acquired at highest look angle, that results in a sharpening of the 20Hz waveforms This poster details the main improvements that are foreseen to be included in the CryoSat Level1b SAR/SARin products in BaselineC.

  6. The PSACOIN level 1B exercise: A probabilistic code intercomparison involving a four compartment biosphere model

    International Nuclear Information System (INIS)

    Klos, R.A.; Sinclair, J.E.; Torres, C.; Mobbs, S.F.; Galson, D.A.

    1991-01-01

    The probabilistic Systems Assessment Code (PSAC) User Group of the OECD Nuclear Energy Agency has organised a series of code intercomparison studies of relevance to the performance assessment of underground repositories for radioactive wastes - known collectively by the name PSACOIN. The latest of these to be undertaken is designated PSACOIN Level 1b, and the case specification provides a complete assessment model of the behaviour of radionuclides following release into the biosphere. PSACOIN Level 1b differs from other biosphere oriented intercomparison exercises in that individual dose is the end point of the calculations as opposed to any other intermediate quantity. The PSACOIN Level 1b case specification describes a simple source term which is used to simulate the release of activity to the biosphere from certain types of near surface waste repository, the transport of radionuclides through the biosphere and their eventual uptake by humankind. The biosphere sub model comprises 4 compartments representing top and deep soil layers, river water and river sediment. The transport of radionuclides between the physical compartments is described by ten transfer coefficients and doses to humankind arise from the simultaneous consumption of water, fish, meat, milk, and grain as well as from dust inhalation and external γ-irradiation. The parameters of the exposure pathway sub model are chosen to be representative of an individual living in a small agrarian community. (13 refs., 3 figs., 2 tabs.)

  7. EOS MLS Level 1B Data Processing, Version 2.2

    Science.gov (United States)

    Perun, Vincent; Jarnot, Robert; Pickett, Herbert; Cofield, Richard; Schwartz, Michael; Wagner, Paul

    2009-01-01

    A computer program performs level- 1B processing (the term 1B is explained below) of data from observations of the limb of the Earth by the Earth Observing System (EOS) Microwave Limb Sounder (MLS), which is an instrument aboard the Aura spacecraft. This software accepts, as input, the raw EOS MLS scientific and engineering data and the Aura spacecraft ephemeris and attitude data. Its output consists of calibrated instrument radiances and associated engineering and diagnostic data. [This software is one of several computer programs, denoted product generation executives (PGEs), for processing EOS MLS data. Starting from level 0 (representing the aforementioned raw data, the PGEs and their data products are denoted by alphanumeric labels (e.g., 1B and 2) that signify the successive stages of processing.] At the time of this reporting, this software is at version 2.2 and incorporates improvements over a prior version that make the code more robust, improve calibration, provide more diagnostic outputs, improve the interface with the Level 2 PGE, and effect a 15-percent reduction in file sizes by use of data compression.

  8. Normalization: A Preprocessing Stage

    OpenAIRE

    Patro, S. Gopal Krishna; Sahu, Kishore Kumar

    2015-01-01

    As we know that the normalization is a pre-processing stage of any type problem statement. Especially normalization takes important role in the field of soft computing, cloud computing etc. for manipulation of data like scale down or scale up the range of data before it becomes used for further stage. There are so many normalization techniques are there namely Min-Max normalization, Z-score normalization and Decimal scaling normalization. So by referring these normalization techniques we are ...

  9. CryoSat Level1b SAR/SARin BaselineC: Product Format and Algorithm Improvements

    Science.gov (United States)

    Scagliola, Michele; Fornari, Marco; Di Giacinto, Andrea; Bouffard, Jerome; Féménias, Pierre; Parrinello, Tommaso

    2015-04-01

    CryoSat was launched on the 8th April 2010 and is the first European ice mission dedicated to the monitoring of precise changes in the thickness of polar ice sheets and floating sea ice. Cryosat carries an innovative radar altimeter called the Synthetic Aperture Interferometric Altimeter (SIRAL), that transmits pulses at a high pulse repetition frequency thus making the received echoes phase coherent and suitable for azimuth processing. This allows to reach a significantly improved along track resolution with respect to traditional pulse-width limited altimeters. CryoSat is the first altimetry mission operating in SAR mode and continuous improvements in the Level1 Instrument Processing Facility (IPF1) are being identified, tested and validated in order to improve the quality of the Level1b products. The current IPF, Baseline B, was released in operation in February 2012. A reprocessing campaign followed, in order to reprocess the data since July 2010. After more than 2 years of development, the release in operations of Baseline C is expected in the first half of 2015. BaselineC Level1b products will be distributed in an updated format, including for example the attitude information (roll, pitch and yaw) and, for SAR/SARIN, the waveform length doubled with respect to Baseline B. Moreveor, various algorithm improvements have been identified: • a datation bias of about -0.5195 ms will be corrected (SAR/SARIn) • a range bias of about 0.6730 m will be corrected (SAR/SARIn) • a roll bias of 0.1062 deg and a pitch bias of 0.0520 deg • Surface sample stack weighting to filter out the single look echoes acquired at highest look angle, that results in a sharpening of the 20Hz waveforms With the operational release of BaselineC, the second CryoSat reprocessing campaign will be initiated, taking benefit of the upgrade implemented in the IPF1 processing chain but also at IPF2 level. The reprocessing campaign will cover the full Cryosat mission starting on 16th July 2010

  10. ITSG-Grace2016 data preprocessing methodologies revisited: impact of using Level-1A data products

    Science.gov (United States)

    Klinger, Beate; Mayer-Gürr, Torsten

    2017-04-01

    For the ITSG-Grace2016 release, the gravity field recovery is based on the use of official GRACE (Gravity Recovery and Climate Experiment) Level-1B data products, generated by the Jet Propulsion Laboratory (JPL). Before gravity field recovery, the Level-1B instrument data are preprocessed. This data preprocessing step includes the combination of Level-1B star camera (SCA1B) and angular acceleration (ACC1B) data for an improved attitude determination (sensor fusion), instrument data screening and ACC1B data calibration. Based on a Level-1A test dataset, provided for individual month throughout the GRACE period by the Center of Space Research at the University of Texas at Austin (UTCSR), the impact of using Level-1A instead of Level-1B data products within the ITSG-Grace2016 processing chain is analyzed. We discuss (1) the attitude determination through an optimal combination of SCA1A and ACC1A data using our sensor fusion approach, (2) the impact of the new attitude product on temporal gravity field solutions, and (3) possible benefits of using Level-1A data for instrument data screening and calibration. As the GRACE mission is currently reaching its end-of-life, the presented work aims not only at a better understanding of GRACE science data to reduce the impact of possible error sources on the gravity field recovery, but it also aims at preparing Level-1A data handling capabilities for the GRACE Follow-On mission.

  11. CALIPSO IIR Version 2 Level 1b calibrated radiances: analysis and reduction of residual biases in the Northern Hemisphere

    Science.gov (United States)

    Garnier, Anne; Trémas, Thierry; Pelon, Jacques; Lee, Kam-Pui; Nobileau, Delphine; Gross-Colzy, Lydwine; Pascal, Nicolas; Ferrage, Pascale; Scott, Noëlle A.

    2018-04-01

    Version 2 of the Level 1b calibrated radiances of the Imaging Infrared Radiometer (IIR) on board the Cloud-Aerosol Lidar and Infrared Satellite Observation (CALIPSO) satellite has been released recently. This new version incorporates corrections of small but systematic seasonal calibration biases previously revealed in Version 1 data products mostly north of 30° N. These biases - of different amplitudes in the three IIR channels 8.65 µm (IIR1), 10.6 µm (IIR2), and 12.05 µm (IIR3) - were made apparent by a striping effect in images of IIR inter-channel brightness temperature differences (BTDs) and through seasonal warm biases of nighttime IIR brightness temperatures in the 30-60° N latitude range. The latter were highlighted through observed and simulated comparisons with similar channels of the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the Aqua spacecraft. To characterize the calibration biases affecting Version 1 data, a semi-empirical approach is developed, which is based on the in-depth analysis of the IIR internal calibration procedure in conjunction with observations such as statistical comparisons with similar MODIS/Aqua channels. Two types of calibration biases are revealed: an equalization bias affecting part of the individual IIR images and a global bias affecting the radiometric level of each image. These biases are observed only when the temperature of the instrument increases, and they are found to be functions of elapsed time since night-to-day transition, regardless of the season. Correction coefficients of Version 1 radiances could thus be defined and implemented in the Version 2 code. As a result, the striping effect seen in Version 1 is significantly attenuated in Version 2. Systematic discrepancies between nighttime and daytime IIR-MODIS BTDs in the 30-60° N latitude range in summer are reduced from 0.2 K in Version 1 to 0.1 K in Version 2 for IIR1-MODIS29. For IIR2-MODIS31 and IIR3-MODIS32, they are reduced from 0.4 K

  12. Data preprocessing in data mining

    CERN Document Server

    García, Salvador; Herrera, Francisco

    2015-01-01

    Data Preprocessing for Data Mining addresses one of the most important issues within the well-known Knowledge Discovery from Data process. Data directly taken from the source will likely have inconsistencies, errors or most importantly, it is not ready to be considered for a data mining process. Furthermore, the increasing amount of data in recent science, industry and business applications, calls to the requirement of more complex tools to analyze it. Thanks to data preprocessing, it is possible to convert the impossible into possible, adapting the data to fulfill the input demands of each data mining algorithm. Data preprocessing includes the data reduction techniques, which aim at reducing the complexity of the data, detecting or removing irrelevant and noisy elements from the data. This book is intended to review the tasks that fill the gap between the data acquisition from the source and the data mining process. A comprehensive look from a practical point of view, including basic concepts and surveying t...

  13. Compact Circuit Preprocesses Accelerometer Output

    Science.gov (United States)

    Bozeman, Richard J., Jr.

    1993-01-01

    Compact electronic circuit transfers dc power to, and preprocesses ac output of, accelerometer and associated preamplifier. Incorporated into accelerometer case during initial fabrication or retrofit onto commercial accelerometer. Made of commercial integrated circuits and other conventional components; made smaller by use of micrologic and surface-mount technology.

  14. OMI/Aura Level 1B VIS Zoom-in Geolocated Earthshine Radiances 1-orbit L2 Swath 13x12 km V003

    Data.gov (United States)

    National Aeronautics and Space Administration — The Level-1B (L1B) Radiance Product OML1BRVZ (Version-3) from the Aura-OMI is now available (http://disc.gsfc.nasa.gov/Aura/OMI/oml1brvz_v003.shtml) to public from...

  15. OMI/Aura Level 1B UV Global Geolocated Earthshine Radiances 1-orbit L2 Swath 13x24 km V003

    Data.gov (United States)

    National Aeronautics and Space Administration — The Level-1B (L1B) Radiance Product OML1BRUG (Version-3) from the Aura-OMI is now available to public (http://disc.gsfc.nasa.gov/Aura/OMI/oml1brug_v003.shtml) from...

  16. OMI/Aura Level 1B UV Zoom-in Geolocated Earthshine Radiances 1-orbit L2 Swath 13x12 km V003

    Data.gov (United States)

    National Aeronautics and Space Administration — The Level-1B (L1B) Radiance Product OML1BRUZ (Version-3) from the Aura-OMI is now available (http://disc.gsfc.nasa.gov/Aura/OMI/oml1bruz_v003.shtml) to public from...

  17. Effective Feature Preprocessing for Time Series Forecasting

    DEFF Research Database (Denmark)

    Zhao, Junhua; Dong, Zhaoyang; Xu, Zhao

    2006-01-01

    Time series forecasting is an important area in data mining research. Feature preprocessing techniques have significant influence on forecasting accuracy, therefore are essential in a forecasting model. Although several feature preprocessing techniques have been applied in time series forecasting...... performance in time series forecasting. It is demonstrated in our experiment that, effective feature preprocessing can significantly enhance forecasting accuracy. This research can be a useful guidance for researchers on effectively selecting feature preprocessing techniques and integrating them with time...... series forecasting models....

  18. CryoSat SAR/SARin Level1b products: assessment of BaselineC and improvements towards BaselineD

    Science.gov (United States)

    Scagliola, Michele; Fornari, Marco; Bouffard, Jerome; Parrinello, Tommaso

    2017-04-01

    CryoSat was launched on the 8th April 2010 and is the first European ice mission dedicated to the monitoring of precise changes in the thickness of polar ice sheets and floating sea ice. Cryosat carries an innovative radar altimeter called the Synthetic Aperture Interferometric Altimeter (SIRAL), that transmits pulses at a high pulse repetition frequency thus making the received echoes phase coherent and suitable for azimuth processing. This allows to reach a significantly improved along track resolution with respect to traditional pulse-width limited altimeters. CryoSat is the first altimetry mission operating in SAR mode and continuous improvements in the Level1 Instrument Processing Facility (IPF1) are being identified, tested and validated in order to improve the quality of the Level1b products. The current IPF, Baseline C, was released in operation in April 2015 and the second CryoSat reprocessing campaign was jointly initiated, taking benefit of the upgrade implemented in the IPF1 processing chain but also of some specific configurations for the calibration corrections. In particular, the CryoSat Level1b BaselineC products generated in the framework of the second reprocessing campaign include refined information for what concerns the mispointing angles and the calibration corrections. This poster will thus detail thus the evolutions that are currently planned for the CryoSat BaselineD SAR/SARin Level1b products and the corresponding quality improvements that are expected.

  19. Psacoin level 1B intercomparison: An International code intercomparison exercise on a hypothetical safety assessment case study for radioactive waste disposal systems

    International Nuclear Information System (INIS)

    Klos, R.A.; Sinclair, J.E.; Torres, C.; Bergstroem, U.; Galson, D.A.

    1993-06-01

    This report focuses on the biosphere modelling aspects of the assessment of the radiological impact of the disposal of radioactive waste in greater detail. Seven exposure pathways are modelled: drinking water, freshwater fish, meat, milk and grain consumption as well as external gamma irradiation and contaminated dust inhalation. The accumulation of radionuclides, released in groundwaters, in the upper soil is also modelled. The objectives of this Level 1b exercise can be summarized as follows: 1 to gain experience in the application of probabilistic systems assessment methodology to transport and radiological exposure sub-models for the biosphere and hence to methods of estimating the total risk to individuals or groups of individuals; 2 to contribute to the verification of biosphere transport and exposure sub-models; 3 to investigate the effects of parameter uncertainty in the biosphere transport and exposure sub-models on the estimate of mean dose to individuals exposed via several exposure pathways

  20. Retinal Image Preprocessing: Background and Noise Segmentation

    Directory of Open Access Journals (Sweden)

    Usman Akram

    2012-09-01

    Full Text Available Retinal images are used for the automated screening and diagnosis of diabetic retinopathy. The retinal image quality must be improved for the detection of features and abnormalities and for this purpose preprocessing of retinal images is vital. In this paper, we present a novel automated approach for preprocessing of colored retinal images. The proposed technique improves the quality of input retinal image by separating the background and noisy area from the overall image. It contains coarse segmentation and fine segmentation. Standard retinal images databases Diaretdb0, Diaretdb1, DRIVE and STARE are used to test the validation of our preprocessing technique. The experimental results show the validity of proposed preprocessing technique.

  1. Facilitating Watermark Insertion by Preprocessing Media

    Directory of Open Access Journals (Sweden)

    Matt L. Miller

    2004-10-01

    Full Text Available There are several watermarking applications that require the deployment of a very large number of watermark embedders. These applications often have severe budgetary constraints that limit the computation resources that are available. Under these circumstances, only simple embedding algorithms can be deployed, which have limited performance. In order to improve performance, we propose preprocessing the original media. It is envisaged that this preprocessing occurs during content creation and has no budgetary or computational constraints. Preprocessing combined with simple embedding creates a watermarked Work, the performance of which exceeds that of simple embedding alone. However, this performance improvement is obtained without any increase in the computational complexity of the embedder. Rather, the additional computational burden is shifted to the preprocessing stage. A simple example of this procedure is described and experimental results confirm our assertions.

  2. Practical Secure Computation with Pre-Processing

    DEFF Research Database (Denmark)

    Zakarias, Rasmus Winther

    Secure Multiparty Computation has been divided between protocols best suited for binary circuits and protocols best suited for arithmetic circuits. With their MiniMac protocol in [DZ13], Damgård and Zakarias take an important step towards bridging these worlds with an arithmetic protocol tuned...... space for pre-processing material than computing the non-linear parts online (depends on the quality of circuit of course). Surprisingly, even for our optimized AES-circuit this is not the case. We further improve the design of the pre-processing material and end up with only 10 megabyes of pre...... a protocol for small field arithmetic to do fast large integer multipli- cations. This is achieved by devising pre-processing material that allows the Toom-Cook multiplication algorithm to run between the parties with linear communication complexity. With this result computation on the CPU by the parties...

  3. The 1989 ENDF pre-processing codes

    International Nuclear Information System (INIS)

    Cullen, D.E.; McLaughlin, P.K.

    1989-12-01

    This document summarizes the 1989 version of the ENDF pre-processing codes which are required for processing evaluated nuclear data coded in the format ENDF-4, ENDF-5, or ENDF-6. The codes are available from the IAEA Nuclear Data Section, free of charge upon request. (author)

  4. Preprocessing Moist Lignocellulosic Biomass for Biorefinery Feedstocks

    Energy Technology Data Exchange (ETDEWEB)

    Neal Yancey; Christopher T. Wright; Craig Conner; J. Richard Hess

    2009-06-01

    Biomass preprocessing is one of the primary operations in the feedstock assembly system of a lignocellulosic biorefinery. Preprocessing is generally accomplished using industrial grinders to format biomass materials into a suitable biorefinery feedstock for conversion to ethanol and other bioproducts. Many factors affect machine efficiency and the physical characteristics of preprocessed biomass. For example, moisture content of the biomass as received from the point of production has a significant impact on overall system efficiency and can significantly affect the characteristics (particle size distribution, flowability, storability, etc.) of the size-reduced biomass. Many different grinder configurations are available on the market, each with advantages under specific conditions. Ultimately, the capacity and/or efficiency of the grinding process can be enhanced by selecting the grinder configuration that optimizes grinder performance based on moisture content and screen size. This paper discusses the relationships of biomass moisture with respect to preprocessing system performance and product physical characteristics and compares data obtained on corn stover, switchgrass, and wheat straw as model feedstocks during Vermeer HG 200 grinder testing. During the tests, grinder screen configuration and biomass moisture content were varied and tested to provide a better understanding of their relative impact on machine performance and the resulting feedstock physical characteristics and uniformity relative to each crop tested.

  5. Reliable RANSAC Using a Novel Preprocessing Model

    Directory of Open Access Journals (Sweden)

    Xiaoyan Wang

    2013-01-01

    Full Text Available Geometric assumption and verification with RANSAC has become a crucial step for corresponding to local features due to its wide applications in biomedical feature analysis and vision computing. However, conventional RANSAC is very time-consuming due to redundant sampling times, especially dealing with the case of numerous matching pairs. This paper presents a novel preprocessing model to explore a reduced set with reliable correspondences from initial matching dataset. Both geometric model generation and verification are carried out on this reduced set, which leads to considerable speedups. Afterwards, this paper proposes a reliable RANSAC framework using preprocessing model, which was implemented and verified using Harris and SIFT features, respectively. Compared with traditional RANSAC, experimental results show that our method is more efficient.

  6. The 1996 ENDF pre-processing codes

    International Nuclear Information System (INIS)

    Cullen, D.E.

    1996-01-01

    The codes are named 'the Pre-processing' codes, because they are designed to pre-process ENDF/B data, for later, further processing for use in applications. This is a modular set of computer codes, each of which reads and writes evaluated nuclear data in the ENDF/B format. Each code performs one or more independent operations on the data, as described below. These codes are designed to be computer independent, and are presently operational on every type of computer from large mainframe computer to small personal computers, such as IBM-PC and Power MAC. The codes are available from the IAEA Nuclear Data Section, free of charge upon request. (author)

  7. Boosting reversible pushdown machines by preprocessing

    DEFF Research Database (Denmark)

    Axelsen, Holger Bock; Kutrib, Martin; Malcher, Andreas

    2016-01-01

    languages, whereas for reversible pushdown automata the accepted family of languages lies strictly in between the reversible deterministic context-free languages and the real-time deterministic context-free languages. Moreover, it is shown that the computational power of both types of machines...... is not changed by allowing the preprocessing sequential transducer to work irreversibly. Finally, we examine the closure properties of the family of languages accepted by such machines....

  8. The 1992 ENDF Pre-processing codes

    International Nuclear Information System (INIS)

    Cullen, D.E.

    1992-01-01

    This document summarizes the 1992 version of the ENDF pre-processing codes which are required for processing evaluated nuclear data coded in the format ENDF-4, ENDF-5, or ENDF-6. Included are the codes CONVERT, MERGER, LINEAR, RECENT, SIGMA1, LEGEND, FIXUP, GROUPIE, DICTION, MIXER, VIRGIN, COMPLOT, EVALPLOT, RELABEL. Some of the functions of these codes are: to calculate cross-sections from resonance parameters; to calculate angular distributions, group average, mixtures of cross-sections, etc; to produce graphical plottings and data comparisons. The codes are designed to operate on virtually any type of computer including PC's. They are available from the IAEA Nuclear Data Section, free of charge upon request, on magnetic tape or a set of HD diskettes. (author)

  9. GRace: a MATLAB-based application for fitting the discrimination-association model.

    Science.gov (United States)

    Stefanutti, Luca; Vianello, Michelangelo; Anselmi, Pasquale; Robusto, Egidio

    2014-10-28

    The Implicit Association Test (IAT) is a computerized two-choice discrimination task in which stimuli have to be categorized as belonging to target categories or attribute categories by pressing, as quickly and accurately as possible, one of two response keys. The discrimination association model has been recently proposed for the analysis of reaction time and accuracy of an individual respondent to the IAT. The model disentangles the influences of three qualitatively different components on the responses to the IAT: stimuli discrimination, automatic association, and termination criterion. The article presents General Race (GRace), a MATLAB-based application for fitting the discrimination association model to IAT data. GRace has been developed for Windows as a standalone application. It is user-friendly and does not require any programming experience. The use of GRace is illustrated on the data of a Coca Cola-Pepsi Cola IAT, and the results of the analysis are interpreted and discussed.

  10. MERIS Level-1B Reduced Resolution

    Data.gov (United States)

    National Aeronautics and Space Administration — MERIS is a programmable, medium-spectral resolution, imaging spectrometer operating in the solar reflective spectral range. Fifteen spectral bands can be selected by...

  11. The Effect of Preprocessing on Arabic Document Categorization

    Directory of Open Access Journals (Sweden)

    Abdullah Ayedh

    2016-04-01

    Full Text Available Preprocessing is one of the main components in a conventional document categorization (DC framework. This paper aims to highlight the effect of preprocessing tasks on the efficiency of the Arabic DC system. In this study, three classification techniques are used, namely, naive Bayes (NB, k-nearest neighbor (KNN, and support vector machine (SVM. Experimental analysis on Arabic datasets reveals that preprocessing techniques have a significant impact on the classification accuracy, especially with complicated morphological structure of the Arabic language. Choosing appropriate combinations of preprocessing tasks provides significant improvement on the accuracy of document categorization depending on the feature size and classification techniques. Findings of this study show that the SVM technique has outperformed the KNN and NB techniques. The SVM technique achieved 96.74% micro-F1 value by using the combination of normalization and stemming as preprocessing tasks.

  12. CSS Preprocessing: Tools and Automation Techniques

    Directory of Open Access Journals (Sweden)

    Ricardo Queirós

    2018-01-01

    Full Text Available Cascading Style Sheets (CSS is a W3C specification for a style sheet language used for describing the presentation of a document written in a markup language, more precisely, for styling Web documents. However, in the last few years, the landscape for CSS development has changed dramatically with the appearance of several languages and tools aiming to help developers build clean, modular and performance-aware CSS. These new approaches give developers mechanisms to preprocess CSS rules through the use of programming constructs, defined as CSS preprocessors, with the ultimate goal to bring those missing constructs to the CSS realm and to foster stylesheets structured programming. At the same time, a new set of tools appeared, defined as postprocessors, for extension and automation purposes covering a broad set of features ranging from identifying unused and duplicate code to applying vendor prefixes. With all these tools and techniques in hands, developers need to provide a consistent workflow to foster CSS modular coding. This paper aims to present an introductory survey on the CSS processors. The survey gathers information on a specific set of processors, categorizes them and compares their features regarding a set of predefined criteria such as: maturity, coverage and performance. Finally, we propose a basic set of best practices in order to setup a simple and pragmatic styling code workflow.

  13. Gravity gradient preprocessing at the GOCE HPF

    Science.gov (United States)

    Bouman, J.; Rispens, S.; Gruber, T.; Schrama, E.; Visser, P.; Tscherning, C. C.; Veicherts, M.

    2009-04-01

    One of the products derived from the GOCE observations are the gravity gradients. These gravity gradients are provided in the Gradiometer Reference Frame (GRF) and are calibrated in-flight using satellite shaking and star sensor data. In order to use these gravity gradients for application in Earth sciences and gravity field analysis, additional pre-processing needs to be done, including corrections for temporal gravity field signals to isolate the static gravity field part, screening for outliers, calibration by comparison with existing external gravity field information and error assessment. The temporal gravity gradient corrections consist of tidal and non-tidal corrections. These are all generally below the gravity gradient error level, which is predicted to show a 1/f behaviour for low frequencies. In the outlier detection the 1/f error is compensated for by subtracting a local median from the data, while the data error is assessed using the median absolute deviation. The local median acts as a high-pass filter and it is robust as is the median absolute deviation. Three different methods have been implemented for the calibration of the gravity gradients. All three methods use a high-pass filter to compensate for the 1/f gravity gradient error. The baseline method uses state-of-the-art global gravity field models and the most accurate results are obtained if star sensor misalignments are estimated along with the calibration parameters. A second calibration method uses GOCE GPS data to estimate a low degree gravity field model as well as gravity gradient scale factors. Both methods allow to estimate gravity gradient scale factors down to the 10-3 level. The third calibration method uses high accurate terrestrial gravity data in selected regions to validate the gravity gradient scale factors, focussing on the measurement band. Gravity gradient scale factors may be estimated down to the 10-2 level with this method.

  14. A survey of visual preprocessing and shape representation techniques

    Science.gov (United States)

    Olshausen, Bruno A.

    1988-01-01

    Many recent theories and methods proposed for visual preprocessing and shape representation are summarized. The survey brings together research from the fields of biology, psychology, computer science, electrical engineering, and most recently, neural networks. It was motivated by the need to preprocess images for a sparse distributed memory (SDM), but the techniques presented may also prove useful for applying other associative memories to visual pattern recognition. The material of this survey is divided into three sections: an overview of biological visual processing; methods of preprocessing (extracting parts of shape, texture, motion, and depth); and shape representation and recognition (form invariance, primitives and structural descriptions, and theories of attention).

  15. Impact of data transformation and preprocessing in supervised ...

    African Journals Online (AJOL)

    Impact of data transformation and preprocessing in supervised learning ... Nowadays, the ideas of integrating machine learning techniques in power system has ... The proposed algorithm used Python-based split train and k-fold model ...

  16. Preprocessing Algorithm for Deciphering Historical Inscriptions Using String Metric

    Directory of Open Access Journals (Sweden)

    Lorand Lehel Toth

    2016-07-01

    Full Text Available The article presents the improvements in the preprocessing part of the deciphering method (shortly preprocessing algorithm for historical inscriptions of unknown origin. Glyphs used in historical inscriptions changed through time; therefore, various versions of the same script may contain different glyphs for each grapheme. The purpose of the preprocessing algorithm is reducing the running time of the deciphering process by filtering out the less probable interpretations of the examined inscription. However, the first version of the preprocessing algorithm leads incorrect outcome or no result in the output in certain cases. Therefore, its improved version was developed to find the most similar words in the dictionary by relaying the search conditions more accurately, but still computationally effectively. Moreover, a sophisticated similarity metric used to determine the possible meaning of the unknown inscription is introduced. The results of the evaluations are also detailed.

  17. Preprocessing of emotional visual information in the human piriform cortex.

    Science.gov (United States)

    Schulze, Patrick; Bestgen, Anne-Kathrin; Lech, Robert K; Kuchinke, Lars; Suchan, Boris

    2017-08-23

    This study examines the processing of visual information by the olfactory system in humans. Recent data point to the processing of visual stimuli by the piriform cortex, a region mainly known as part of the primary olfactory cortex. Moreover, the piriform cortex generates predictive templates of olfactory stimuli to facilitate olfactory processing. This study fills the gap relating to the question whether this region is also capable of preprocessing emotional visual information. To gain insight into the preprocessing and transfer of emotional visual information into olfactory processing, we recorded hemodynamic responses during affective priming using functional magnetic resonance imaging (fMRI). Odors of different valence (pleasant, neutral and unpleasant) were primed by images of emotional facial expressions (happy, neutral and disgust). Our findings are the first to demonstrate that the piriform cortex preprocesses emotional visual information prior to any olfactory stimulation and that the emotional connotation of this preprocessing is subsequently transferred and integrated into an extended olfactory network for olfactory processing.

  18. Evaluating the impact of image preprocessing on iris segmentation

    Directory of Open Access Journals (Sweden)

    José F. Valencia-Murillo

    2014-08-01

    Full Text Available Segmentation is one of the most important stages in iris recognition systems. In this paper, image preprocessing algorithms are applied in order to evaluate their impact on successful iris segmentation. The preprocessing algorithms are based on histogram adjustment, Gaussian filters and suppression of specular reflections in human eye images. The segmentation method introduced by Masek is applied on 199 images acquired under unconstrained conditions, belonging to the CASIA-irisV3 database, before and after applying the preprocessing algorithms. Then, the impact of image preprocessing algorithms on the percentage of successful iris segmentation is evaluated by means of a visual inspection of images in order to determine if circumferences of iris and pupil were detected correctly. An increase from 59% to 73% in percentage of successful iris segmentation is obtained with an algorithm that combine elimination of specular reflections, followed by the implementation of a Gaussian filter having a 5x5 kernel. The results highlight the importance of a preprocessing stage as a previous step in order to improve the performance during the edge detection and iris segmentation processes.

  19. Effects of preprocessing method on TVOC emission of car mat

    Science.gov (United States)

    Wang, Min; Jia, Li

    2013-02-01

    The effects of the mat preprocessing method on total volatile organic compounds (TVOC) emission of car mat are studied in this paper. An appropriate TVOC emission period for car mat is suggested. The emission factors for total volatile organic compounds from three kinds of new car mats are discussed. The car mats are preprocessed by washing, baking and ventilation. When car mats are preprocessed by washing, the TVOC emission for all samples tested are lower than that preprocessed in other methods. The TVOC emission is in stable situation for a minimum of 4 days. The TVOC emitted from some samples may exceed 2500μg/kg. But the TVOC emitted from washed Polyamide (PA) and wool mat is less than 2500μg/kg. The emission factors of total volatile organic compounds (TVOC) are experimentally investigated in the case of different preprocessing methods. The air temperature in environment chamber and the water temperature for washing are important factors influencing on emission of car mats.

  20. Effect of microaerobic fermentation in preprocessing fibrous lignocellulosic materials.

    Science.gov (United States)

    Alattar, Manar Arica; Green, Terrence R; Henry, Jordan; Gulca, Vitalie; Tizazu, Mikias; Bergstrom, Robby; Popa, Radu

    2012-06-01

    Amending soil with organic matter is common in agricultural and logging practices. Such amendments have benefits to soil fertility and crop yields. These benefits may be increased if material is preprocessed before introduction into soil. We analyzed the efficiency of microaerobic fermentation (MF), also referred to as Bokashi, in preprocessing fibrous lignocellulosic (FLC) organic materials using varying produce amendments and leachate treatments. Adding produce amendments increased leachate production and fermentation rates and decreased the biological oxygen demand of the leachate. Continuously draining leachate without returning it to the fermentors led to acidification and decreased concentrations of polysaccharides (PS) in leachates. PS fragmentation and the production of soluble metabolites and gases stabilized in fermentors in about 2-4 weeks. About 2 % of the carbon content was lost as CO(2). PS degradation rates, upon introduction of processed materials into soil, were similar to unfermented FLC. Our results indicate that MF is insufficient for adequate preprocessing of FLC material.

  1. Real-time topic-aware influence maximization using preprocessing.

    Science.gov (United States)

    Chen, Wei; Lin, Tian; Yang, Cheng

    2016-01-01

    Influence maximization is the task of finding a set of seed nodes in a social network such that the influence spread of these seed nodes based on certain influence diffusion model is maximized. Topic-aware influence diffusion models have been recently proposed to address the issue that influence between a pair of users are often topic-dependent and information, ideas, innovations etc. being propagated in networks are typically mixtures of topics. In this paper, we focus on the topic-aware influence maximization task. In particular, we study preprocessing methods to avoid redoing influence maximization for each mixture from scratch. We explore two preprocessing algorithms with theoretical justifications. Our empirical results on data obtained in a couple of existing studies demonstrate that one of our algorithms stands out as a strong candidate providing microsecond online response time and competitive influence spread, with reasonable preprocessing effort.

  2. Micro-Analyzer: automatic preprocessing of Affymetrix microarray data.

    Science.gov (United States)

    Guzzi, Pietro Hiram; Cannataro, Mario

    2013-08-01

    A current trend in genomics is the investigation of the cell mechanism using different technologies, in order to explain the relationship among genes, molecular processes and diseases. For instance, the combined use of gene-expression arrays and genomic arrays has been demonstrated as an effective instrument in clinical practice. Consequently, in a single experiment different kind of microarrays may be used, resulting in the production of different types of binary data (images and textual raw data). The analysis of microarray data requires an initial preprocessing phase, that makes raw data suitable for use on existing analysis platforms, such as the TIGR M4 (TM4) Suite. An additional challenge to be faced by emerging data analysis platforms is the ability to treat in a combined way those different microarray formats coupled with clinical data. In fact, resulting integrated data may include both numerical and symbolic data (e.g. gene expression and SNPs regarding molecular data), as well as temporal data (e.g. the response to a drug, time to progression and survival rate), regarding clinical data. Raw data preprocessing is a crucial step in analysis but is often performed in a manual and error prone way using different software tools. Thus novel, platform independent, and possibly open source tools enabling the semi-automatic preprocessing and annotation of different microarray data are needed. The paper presents Micro-Analyzer (Microarray Analyzer), a cross-platform tool for the automatic normalization, summarization and annotation of Affymetrix gene expression and SNP binary data. It represents the evolution of the μ-CS tool, extending the preprocessing to SNP arrays that were not allowed in μ-CS. The Micro-Analyzer is provided as a Java standalone tool and enables users to read, preprocess and analyse binary microarray data (gene expression and SNPs) by invoking TM4 platform. It avoids: (i) the manual invocation of external tools (e.g. the Affymetrix Power

  3. Pre-processing for Triangulation of Probabilistic Networks

    NARCIS (Netherlands)

    Bodlaender, H.L.; Koster, A.M.C.A.; Eijkhof, F. van den; Gaag, L.C. van der

    2001-01-01

    The currently most efficient algorithm for inference with a probabilistic network builds upon a triangulation of a networks graph. In this paper, we show that pre-processing can help in finding good triangulations for probabilistic networks, that is, triangulations with a minimal maximum

  4. Orthogonal feature selection method. [For preprocessing of man spectral data

    Energy Technology Data Exchange (ETDEWEB)

    Kowalski, B R [Univ. of Washington, Seattle; Bender, C F

    1976-01-01

    A new method of preprocessing spectral data for extraction of molecular structural information is desired. This SELECT method generates orthogonal features that are important for classification purposes and that also retain their identity to the original measurements. A brief introduction to chemical pattern recognition is presented. A brief description of the method and an application to mass spectral data analysis follow. (BLM)

  5. Image preprocessing study on KPCA-based face recognition

    Science.gov (United States)

    Li, Xuan; Li, Dehua

    2015-12-01

    Face recognition as an important biometric identification method, with its friendly, natural, convenient advantages, has obtained more and more attention. This paper intends to research a face recognition system including face detection, feature extraction and face recognition, mainly through researching on related theory and the key technology of various preprocessing methods in face detection process, using KPCA method, focuses on the different recognition results in different preprocessing methods. In this paper, we choose YCbCr color space for skin segmentation and choose integral projection for face location. We use erosion and dilation of the opening and closing operation and illumination compensation method to preprocess face images, and then use the face recognition method based on kernel principal component analysis method for analysis and research, and the experiments were carried out using the typical face database. The algorithms experiment on MATLAB platform. Experimental results show that integration of the kernel method based on PCA algorithm under certain conditions make the extracted features represent the original image information better for using nonlinear feature extraction method, which can obtain higher recognition rate. In the image preprocessing stage, we found that images under various operations may appear different results, so as to obtain different recognition rate in recognition stage. At the same time, in the process of the kernel principal component analysis, the value of the power of the polynomial function can affect the recognition result.

  6. An Effective Measured Data Preprocessing Method in Electrical Impedance Tomography

    Directory of Open Access Journals (Sweden)

    Chenglong Yu

    2014-01-01

    Full Text Available As an advanced process detection technology, electrical impedance tomography (EIT has widely been paid attention to and studied in the industrial fields. But the EIT techniques are greatly limited to the low spatial resolutions. This problem may result from the incorrect preprocessing of measuring data and lack of general criterion to evaluate different preprocessing processes. In this paper, an EIT data preprocessing method is proposed by all rooting measured data and evaluated by two constructed indexes based on all rooted EIT measured data. By finding the optimums of the two indexes, the proposed method can be applied to improve the EIT imaging spatial resolutions. In terms of a theoretical model, the optimal rooting times of the two indexes range in [0.23, 0.33] and in [0.22, 0.35], respectively. Moreover, these factors that affect the correctness of the proposed method are generally analyzed. The measuring data preprocessing is necessary and helpful for any imaging process. Thus, the proposed method can be generally and widely used in any imaging process. Experimental results validate the two proposed indexes.

  7. Research on pre-processing of QR Code

    Science.gov (United States)

    Sun, Haixing; Xia, Haojie; Dong, Ning

    2013-10-01

    QR code encodes many kinds of information because of its advantages: large storage capacity, high reliability, full arrange of utter-high-speed reading, small printing size and high-efficient representation of Chinese characters, etc. In order to obtain the clearer binarization image from complex background, and improve the recognition rate of QR code, this paper researches on pre-processing methods of QR code (Quick Response Code), and shows algorithms and results of image pre-processing for QR code recognition. Improve the conventional method by changing the Souvola's adaptive text recognition method. Additionally, introduce the QR code Extraction which adapts to different image size, flexible image correction approach, and improve the efficiency and accuracy of QR code image processing.

  8. Linguistic Preprocessing and Tagging for Problem Report Trend Analysis

    Science.gov (United States)

    Beil, Robert J.; Malin, Jane T.

    2012-01-01

    Mr. Robert Beil, Systems Engineer at Kennedy Space Center (KSC), requested the NASA Engineering and Safety Center (NESC) develop a prototype tool suite that combines complementary software technology used at Johnson Space Center (JSC) and KSC for problem report preprocessing and semantic tag extraction, to improve input to data mining and trend analysis. This document contains the outcome of the assessment and the Findings, Observations and NESC Recommendations.

  9. Learning and Generalisation in Neural Networks with Local Preprocessing

    OpenAIRE

    Kutsia, Merab

    2007-01-01

    We study learning and generalisation ability of a specific two-layer feed-forward neural network and compare its properties to that of a simple perceptron. The input patterns are mapped nonlinearly onto a hidden layer, much larger than the input layer, and this mapping is either fixed or may result from an unsupervised learning process. Such preprocessing of initially uncorrelated random patterns results in the correlated patterns in the hidden layer. The hidden-to-output mapping of the net...

  10. Summary of ENDF/B pre-processing codes

    International Nuclear Information System (INIS)

    Cullen, D.E.

    1981-12-01

    This document contains the summary documentation for the ENDF/B pre-processing codes: LINEAR, RECENT, SIGMA1, GROUPIE, EVALPLOT, MERGER, DICTION, CONVERT. This summary documentation is merely a copy of the comment cards that appear at the beginning of each programme; these comment cards always reflect the latest status of input options, etc. For the latest published documentation on the methods used in these codes see UCRL-50400, Vol.17 parts A-E, Lawrence Livermore Laboratory (1979)

  11. Pre-processing by data augmentation for improved ellipse fitting.

    Science.gov (United States)

    Kumar, Pankaj; Belchamber, Erika R; Miklavcic, Stanley J

    2018-01-01

    Ellipse fitting is a highly researched and mature topic. Surprisingly, however, no existing method has thus far considered the data point eccentricity in its ellipse fitting procedure. Here, we introduce the concept of eccentricity of a data point, in analogy with the idea of ellipse eccentricity. We then show empirically that, irrespective of ellipse fitting method used, the root mean square error (RMSE) of a fit increases with the eccentricity of the data point set. The main contribution of the paper is based on the hypothesis that if the data point set were pre-processed to strategically add additional data points in regions of high eccentricity, then the quality of a fit could be improved. Conditional validity of this hypothesis is demonstrated mathematically using a model scenario. Based on this confirmation we propose an algorithm that pre-processes the data so that data points with high eccentricity are replicated. The improvement of ellipse fitting is then demonstrated empirically in real-world application of 3D reconstruction of a plant root system for phenotypic analysis. The degree of improvement for different underlying ellipse fitting methods as a function of data noise level is also analysed. We show that almost every method tested, irrespective of whether it minimizes algebraic error or geometric error, shows improvement in the fit following data augmentation using the proposed pre-processing algorithm.

  12. A Stereo Music Preprocessing Scheme for Cochlear Implant Users.

    Science.gov (United States)

    Buyens, Wim; van Dijk, Bas; Wouters, Jan; Moonen, Marc

    2015-10-01

    Listening to music is still one of the more challenging aspects of using a cochlear implant (CI) for most users. Simple musical structures, a clear rhythm/beat, and lyrics that are easy to follow are among the top factors contributing to music appreciation for CI users. Modifying the audio mix of complex music potentially improves music enjoyment in CI users. A stereo music preprocessing scheme is described in which vocals, drums, and bass are emphasized based on the representation of the harmonic and the percussive components in the input spectrogram, combined with the spatial allocation of instruments in typical stereo recordings. The scheme is assessed with postlingually deafened CI subjects (N = 7) using pop/rock music excerpts with different complexity levels. The scheme is capable of modifying relative instrument level settings, with the aim of improving music appreciation in CI users, and allows individual preference adjustments. The assessment with CI subjects confirms the preference for more emphasis on vocals, drums, and bass as offered by the preprocessing scheme, especially for songs with higher complexity. The stereo music preprocessing scheme has the potential to improve music enjoyment in CI users by modifying the audio mix in widespread (stereo) music recordings. Since music enjoyment in CI users is generally poor, this scheme can assist the music listening experience of CI users as a training or rehabilitation tool.

  13. Optimization of miRNA-seq data preprocessing.

    Science.gov (United States)

    Tam, Shirley; Tsao, Ming-Sound; McPherson, John D

    2015-11-01

    The past two decades of microRNA (miRNA) research has solidified the role of these small non-coding RNAs as key regulators of many biological processes and promising biomarkers for disease. The concurrent development in high-throughput profiling technology has further advanced our understanding of the impact of their dysregulation on a global scale. Currently, next-generation sequencing is the platform of choice for the discovery and quantification of miRNAs. Despite this, there is no clear consensus on how the data should be preprocessed before conducting downstream analyses. Often overlooked, data preprocessing is an essential step in data analysis: the presence of unreliable features and noise can affect the conclusions drawn from downstream analyses. Using a spike-in dilution study, we evaluated the effects of several general-purpose aligners (BWA, Bowtie, Bowtie 2 and Novoalign), and normalization methods (counts-per-million, total count scaling, upper quartile scaling, Trimmed Mean of M, DESeq, linear regression, cyclic loess and quantile) with respect to the final miRNA count data distribution, variance, bias and accuracy of differential expression analysis. We make practical recommendations on the optimal preprocessing methods for the extraction and interpretation of miRNA count data from small RNA-sequencing experiments. © The Author 2015. Published by Oxford University Press.

  14. Comparison of multivariate preprocessing techniques as applied to electronic tongue based pattern classification for black tea

    International Nuclear Information System (INIS)

    Palit, Mousumi; Tudu, Bipan; Bhattacharyya, Nabarun; Dutta, Ankur; Dutta, Pallab Kumar; Jana, Arun; Bandyopadhyay, Rajib; Chatterjee, Anutosh

    2010-01-01

    In an electronic tongue, preprocessing on raw data precedes pattern analysis and choice of the appropriate preprocessing technique is crucial for the performance of the pattern classifier. While attempting to classify different grades of black tea using a voltammetric electronic tongue, different preprocessing techniques have been explored and a comparison of their performances is presented in this paper. The preprocessing techniques are compared first by a quantitative measurement of separability followed by principle component analysis; and then two different supervised pattern recognition models based on neural networks are used to evaluate the performance of the preprocessing techniques.

  15. Parallel pipeline algorithm of real time star map preprocessing

    Science.gov (United States)

    Wang, Hai-yong; Qin, Tian-mu; Liu, Jia-qi; Li, Zhi-feng; Li, Jian-hua

    2016-03-01

    To improve the preprocessing speed of star map and reduce the resource consumption of embedded system of star tracker, a parallel pipeline real-time preprocessing algorithm is presented. The two characteristics, the mean and the noise standard deviation of the background gray of a star map, are firstly obtained dynamically by the means that the intervene of the star image itself to the background is removed in advance. The criterion on whether or not the following noise filtering is needed is established, then the extraction threshold value is assigned according to the level of background noise, so that the centroiding accuracy is guaranteed. In the processing algorithm, as low as two lines of pixel data are buffered, and only 100 shift registers are used to record the connected domain label, by which the problems of resources wasting and connected domain overflow are solved. The simulating results show that the necessary data of the selected bright stars could be immediately accessed in a delay time as short as 10us after the pipeline processing of a 496×496 star map in 50Mb/s is finished, and the needed memory and registers resource total less than 80kb. To verify the accuracy performance of the algorithm proposed, different levels of background noise are added to the processed ideal star map, and the statistic centroiding error is smaller than 1/23 pixel under the condition that the signal to noise ratio is greater than 1. The parallel pipeline algorithm of real time star map preprocessing helps to increase the data output speed and the anti-dynamic performance of star tracker.

  16. Contour extraction of echocardiographic images based on pre-processing

    Energy Technology Data Exchange (ETDEWEB)

    Hussein, Zinah Rajab; Rahmat, Rahmita Wirza; Abdullah, Lili Nurliyana [Department of Multimedia, Faculty of Computer Science and Information Technology, Department of Computer and Communication Systems Engineering, Faculty of Engineering University Putra Malaysia 43400 Serdang, Selangor (Malaysia); Zamrin, D M [Department of Surgery, Faculty of Medicine, National University of Malaysia, 56000 Cheras, Kuala Lumpur (Malaysia); Saripan, M Iqbal

    2011-02-15

    In this work we present a technique to extract the heart contours from noisy echocardiograph images. Our technique is based on improving the image before applying contours detection to reduce heavy noise and get better image quality. To perform that, we combine many pre-processing techniques (filtering, morphological operations, and contrast adjustment) to avoid unclear edges and enhance low contrast of echocardiograph images, after implementing these techniques we can get legible detection for heart boundaries and valves movement by traditional edge detection methods.

  17. Contour extraction of echocardiographic images based on pre-processing

    International Nuclear Information System (INIS)

    Hussein, Zinah Rajab; Rahmat, Rahmita Wirza; Abdullah, Lili Nurliyana; Zamrin, D M; Saripan, M Iqbal

    2011-01-01

    In this work we present a technique to extract the heart contours from noisy echocardiograph images. Our technique is based on improving the image before applying contours detection to reduce heavy noise and get better image quality. To perform that, we combine many pre-processing techniques (filtering, morphological operations, and contrast adjustment) to avoid unclear edges and enhance low contrast of echocardiograph images, after implementing these techniques we can get legible detection for heart boundaries and valves movement by traditional edge detection methods.

  18. Parallel preprocessing in a nuclear data acquisition system

    International Nuclear Information System (INIS)

    Pichot, G.; Auriol, E.; Lemarchand, G.; Millaud, J.

    1977-01-01

    The appearance of microprocessors and large memory chips has somewhat modified the spectrum of tools usable by the data acquisition system designer. This is particular true in the nuclear research field where the data flow has been continuously growing as a consequence of the increasing capabilities of new detectors. This paper deals with the insertion, between a data acquisition system and a computer, of a preprocessing structure based on microprocessors and large capacity high speed memories. The results shows a significant improvement on several aspects in the operation of the system with returns paying back the investments in 18 months

  19. Pre-Processing and Modeling Tools for Bigdata

    Directory of Open Access Journals (Sweden)

    Hashem Hadi

    2016-09-01

    Full Text Available Modeling tools and operators help the user / developer to identify the processing field on the top of the sequence and to send into the computing module only the data related to the requested result. The remaining data is not relevant and it will slow down the processing. The biggest challenge nowadays is to get high quality processing results with a reduced computing time and costs. To do so, we must review the processing sequence, by adding several modeling tools. The existing processing models do not take in consideration this aspect and focus on getting high calculation performances which will increase the computing time and costs. In this paper we provide a study of the main modeling tools for BigData and a new model based on pre-processing.

  20. Preprocessing in a Tiered Sensor Network for Habitat Monitoring

    Directory of Open Access Journals (Sweden)

    Hanbiao Wang

    2003-03-01

    Full Text Available We investigate task decomposition and collaboration in a two-tiered sensor network for habitat monitoring. The system recognizes and localizes a specified type of birdcalls. The system has a few powerful macronodes in the first tier, and many less powerful micronodes in the second tier. Each macronode combines data collected by multiple micronodes for target classification and localization. We describe two types of lightweight preprocessing which significantly reduce data transmission from micronodes to macronodes. Micronodes classify events according to their cross-zero rates and discard irrelevant events. Data about events of interest is reduced and compressed before being transmitted to macronodes for target localization. Preliminary experiments illustrate the effectiveness of event filtering and data reduction at micronodes.

  1. Textural Analysis of Fatique Crack Surfaces: Image Pre-processing

    Directory of Open Access Journals (Sweden)

    H. Lauschmann

    2000-01-01

    Full Text Available For the fatique crack history reconstitution, new methods of quantitative microfractography are beeing developed based on the image processing and textural analysis. SEM magnifications between micro- and macrofractography are used. Two image pre-processing operatins were suggested and proved to prepare the crack surface images for analytical treatment: 1. Normalization is used to transform the image to a stationary form. Compared to the generally used equalization, it conserves the shape of brightness distribution and saves the character of the texture. 2. Binarization is used to transform the grayscale image to a system of thick fibres. An objective criterion for the threshold brightness value was found as that resulting into the maximum number of objects. Both methods were succesfully applied together with the following textural analysis.

  2. Piecewise Polynomial Aggregation as Preprocessing for Data Numerical Modeling

    Science.gov (United States)

    Dobronets, B. S.; Popova, O. A.

    2018-05-01

    Data aggregation issues for numerical modeling are reviewed in the present study. The authors discuss data aggregation procedures as preprocessing for subsequent numerical modeling. To calculate the data aggregation, the authors propose using numerical probabilistic analysis (NPA). An important feature of this study is how the authors represent the aggregated data. The study shows that the offered approach to data aggregation can be interpreted as the frequency distribution of a variable. To study its properties, the density function is used. For this purpose, the authors propose using the piecewise polynomial models. A suitable example of such approach is the spline. The authors show that their approach to data aggregation allows reducing the level of data uncertainty and significantly increasing the efficiency of numerical calculations. To demonstrate the degree of the correspondence of the proposed methods to reality, the authors developed a theoretical framework and considered numerical examples devoted to time series aggregation.

  3. Pre-processing of input files for the AZTRAN code

    International Nuclear Information System (INIS)

    Vargas E, S.; Ibarra, G.

    2017-09-01

    The AZTRAN code began to be developed in the Nuclear Engineering Department of the Escuela Superior de Fisica y Matematicas (ESFM) of the Instituto Politecnico Nacional (IPN) with the purpose of numerically solving various models arising from the physics and engineering of nuclear reactors. The code is still under development and is part of the AZTLAN platform: Development of a Mexican platform for the analysis and design of nuclear reactors. Due to the complexity to generate an input file for the code, a script based on D language is developed, with the purpose of making its elaboration easier, based on a new input file format which includes specific cards, which have been divided into two blocks, mandatory cards and optional cards, including a pre-processing of the input file to identify possible errors within it, as well as an image generator for the specific problem based on the python interpreter. (Author)

  4. Statistics in experimental design, preprocessing, and analysis of proteomics data.

    Science.gov (United States)

    Jung, Klaus

    2011-01-01

    High-throughput experiments in proteomics, such as 2-dimensional gel electrophoresis (2-DE) and mass spectrometry (MS), yield usually high-dimensional data sets of expression values for hundreds or thousands of proteins which are, however, observed on only a relatively small number of biological samples. Statistical methods for the planning and analysis of experiments are important to avoid false conclusions and to receive tenable results. In this chapter, the most frequent experimental designs for proteomics experiments are illustrated. In particular, focus is put on studies for the detection of differentially regulated proteins. Furthermore, issues of sample size planning, statistical analysis of expression levels as well as methods for data preprocessing are covered.

  5. Digital soil mapping: strategy for data pre-processing

    Directory of Open Access Journals (Sweden)

    Alexandre ten Caten

    2012-08-01

    Full Text Available The region of greatest variability on soil maps is along the edge of their polygons, causing disagreement among pedologists about the appropriate description of soil classes at these locations. The objective of this work was to propose a strategy for data pre-processing applied to digital soil mapping (DSM. Soil polygons on a training map were shrunk by 100 and 160 m. This strategy prevented the use of covariates located near the edge of the soil classes for the Decision Tree (DT models. Three DT models derived from eight predictive covariates, related to relief and organism factors sampled on the original polygons of a soil map and on polygons shrunk by 100 and 160 m were used to predict soil classes. The DT model derived from observations 160 m away from the edge of the polygons on the original map is less complex and has a better predictive performance.

  6. A New Indicator for Optimal Preprocessing and Wavelengths Selection of Near-Infrared Spectra

    NARCIS (Netherlands)

    Skibsted, E.; Boelens, H.F.M.; Westerhuis, J.A.; Witte, D.T.; Smilde, A.K.

    2004-01-01

    Preprocessing of near-infrared spectra to remove unwanted, i.e., non-related spectral variation and selection of informative wavelengths is considered to be a crucial step prior to the construction of a quantitative calibration model. The standard methodology when comparing various preprocessing

  7. New indicator for optimal preprocessing and wavelength selection of near-infrared spectra

    NARCIS (Netherlands)

    Skibsted, E. T. S.; Boelens, H. F. M.; Westerhuis, J. A.; Witte, D. T.; Smilde, A. K.

    2004-01-01

    Preprocessing of near-infrared spectra to remove unwanted, i.e., non-related spectral variation and selection of informative wavelengths is considered to be a crucial step prior to the construction of a quantitative calibration model. The standard methodology when comparing various preprocessing

  8. Ensemble preprocessing of near-infrared (NIR) spectra for multivariate calibration

    International Nuclear Information System (INIS)

    Xu Lu; Zhou Yanping; Tang Lijuan; Wu Hailong; Jiang Jianhui; Shen Guoli; Yu Ruqin

    2008-01-01

    Preprocessing of raw near-infrared (NIR) spectral data is indispensable in multivariate calibration when the measured spectra are subject to significant noises, baselines and other undesirable factors. However, due to the lack of sufficient prior information and an incomplete knowledge of the raw data, NIR spectra preprocessing in multivariate calibration is still trial and error. How to select a proper method depends largely on both the nature of the data and the expertise and experience of the practitioners. This might limit the applications of multivariate calibration in many fields, where researchers are not very familiar with the characteristics of many preprocessing methods unique in chemometrics and have difficulties to select the most suitable methods. Another problem is many preprocessing methods, when used alone, might degrade the data in certain aspects or lose some useful information while improving certain qualities of the data. In order to tackle these problems, this paper proposes a new concept of data preprocessing, ensemble preprocessing method, where partial least squares (PLSs) models built on differently preprocessed data are combined by Monte Carlo cross validation (MCCV) stacked regression. Little or no prior information of the data and expertise are required. Moreover, fusion of complementary information obtained by different preprocessing methods often leads to a more stable and accurate calibration model. The investigation of two real data sets has demonstrated the advantages of the proposed method

  9. Software for Preprocessing Data from Rocket-Engine Tests

    Science.gov (United States)

    Cheng, Chiu-Fu

    2004-01-01

    Three computer programs have been written to preprocess digitized outputs of sensors during rocket-engine tests at Stennis Space Center (SSC). The programs apply exclusively to the SSC E test-stand complex and utilize the SSC file format. The programs are the following: Engineering Units Generator (EUGEN) converts sensor-output-measurement data to engineering units. The inputs to EUGEN are raw binary test-data files, which include the voltage data, a list identifying the data channels, and time codes. EUGEN effects conversion by use of a file that contains calibration coefficients for each channel. QUICKLOOK enables immediate viewing of a few selected channels of data, in contradistinction to viewing only after post-test processing (which can take 30 minutes to several hours depending on the number of channels and other test parameters) of data from all channels. QUICKLOOK converts the selected data into a form in which they can be plotted in engineering units by use of Winplot (a free graphing program written by Rick Paris). EUPLOT provides a quick means for looking at data files generated by EUGEN without the necessity of relying on the PV-WAVE based plotting software.

  10. Zseq: An Approach for Preprocessing Next-Generation Sequencing Data.

    Science.gov (United States)

    Alkhateeb, Abedalrhman; Rueda, Luis

    2017-08-01

    Next-generation sequencing technology generates a huge number of reads (short sequences), which contain a vast amount of genomic data. The sequencing process, however, comes with artifacts. Preprocessing of sequences is mandatory for further downstream analysis. We present Zseq, a linear method that identifies the most informative genomic sequences and reduces the number of biased sequences, sequence duplications, and ambiguous nucleotides. Zseq finds the complexity of the sequences by counting the number of unique k-mers in each sequence as its corresponding score and also takes into the account other factors such as ambiguous nucleotides or high GC-content percentage in k-mers. Based on a z-score threshold, Zseq sweeps through the sequences again and filters those with a z-score less than the user-defined threshold. Zseq algorithm is able to provide a better mapping rate; it reduces the number of ambiguous bases significantly in comparison with other methods. Evaluation of the filtered reads has been conducted by aligning the reads and assembling the transcripts using the reference genome as well as de novo assembly. The assembled transcripts show a better discriminative ability to separate cancer and normal samples in comparison with another state-of-the-art method. Moreover, de novo assembled transcripts from the reads filtered by Zseq have longer genomic sequences than other tested methods. Estimating the threshold of the cutoff point is introduced using labeling rules with optimistic results.

  11. Road Sign Recognition with Fuzzy Adaptive Pre-Processing Models

    Science.gov (United States)

    Lin, Chien-Chuan; Wang, Ming-Shi

    2012-01-01

    A road sign recognition system based on adaptive image pre-processing models using two fuzzy inference schemes has been proposed. The first fuzzy inference scheme is to check the changes of the light illumination and rich red color of a frame image by the checking areas. The other is to check the variance of vehicle's speed and angle of steering wheel to select an adaptive size and position of the detection area. The Adaboost classifier was employed to detect the road sign candidates from an image and the support vector machine technique was employed to recognize the content of the road sign candidates. The prohibitory and warning road traffic signs are the processing targets in this research. The detection rate in the detection phase is 97.42%. In the recognition phase, the recognition rate is 93.04%. The total accuracy rate of the system is 92.47%. For video sequences, the best accuracy rate is 90.54%, and the average accuracy rate is 80.17%. The average computing time is 51.86 milliseconds per frame. The proposed system can not only overcome low illumination and rich red color around the road sign problems but also offer high detection rates and high computing performance. PMID:22778650

  12. Neural Online Filtering Based on Preprocessed Calorimeter Data

    CERN Document Server

    Torres, R C; The ATLAS collaboration; Simas Filho, E F; De Seixas, J M

    2009-01-01

    Among LHC detectors, ATLAS aims at coping with such high event rate by designing a three-level online triggering system. The first level trigger output will be ~75 kHz. This level will mark the regions where relevant events were found. The second level will validate LVL1 decision by looking only at the approved data using full granularity. At the level two output, the event rate will be reduced to ~2 kHz. Finally, the third level will look at full event information and a rate of ~200 Hz events is expected to be approved, and stored in persistent media for further offline analysis. Many interesting events decay into electrons, which have to be identified from the huge background noise (jets). This work proposes a high-efficient LVL2 electron / jet discrimination system based on neural networks fed from preprocessed calorimeter information. The feature extraction part of the proposed system performs a ring structure of data description. A set of concentric rings centered at the highest energy cell is generated ...

  13. Data preprocessing methods for robust Fourier ptychographic microscopy

    Science.gov (United States)

    Zhang, Yan; Pan, An; Lei, Ming; Yao, Baoli

    2017-12-01

    Fourier ptychographic microscopy (FPM) is a recently developed computational imaging technique that achieves gigapixel images with both high resolution and large field-of-view. In the current FPM experimental setup, the dark-field images with high-angle illuminations are easily overwhelmed by stray lights and background noises due to the low signal-to-noise ratio, thus significantly degrading the achievable resolution of the FPM approach. We provide an overall and systematic data preprocessing scheme to enhance the FPM's performance, which involves sampling analysis, underexposed/overexposed treatments, background noises suppression, and stray lights elimination. It is demonstrated experimentally with both US Air Force (USAF) 1951 resolution target and biological samples that the benefit of the noise removal by these methods far outweighs the defect of the accompanying signal loss, as part of the lost signals can be compensated by the improved consistencies among the captured raw images. In addition, the reported nonparametric scheme could be further cooperated with the existing state-of-the-art algorithms with a great flexibility, facilitating a stronger noise-robust capability of the FPM approach in various applications.

  14. Arabic text preprocessing for the natural language processing applications

    International Nuclear Information System (INIS)

    Awajan, A.

    2007-01-01

    A new approach for processing vowelized and unvowelized Arabic texts in order to prepare them for Natural Language Processing (NLP) purposes is described. The developed approach is rule-based and made up of four phases: text tokenization, word light stemming, word's morphological analysis and text annotation. The first phase preprocesses the input text in order to isolate the words and represent them in a formal way. The second phase applies a light stemmer in order to extract the stem of each word by eliminating the prefixes and suffixes. The third phase is a rule-based morphological analyzer that determines the root and the morphological pattern for each extracted stem. The last phase produces an annotated text where each word is tagged with its morphological attributes. The preprocessor presented in this paper is capable of dealing with vowelized and unvowelized words, and provides the input words along with relevant linguistics information needed by different applications. It is designed to be used with different NLP applications such as machine translation text summarization, text correction, information retrieval and automatic vowelization of Arabic Text. (author)

  15. ASAP: an environment for automated preprocessing of sequencing data

    Directory of Open Access Journals (Sweden)

    Torstenson Eric S

    2013-01-01

    Full Text Available Abstract Background Next-generation sequencing (NGS has yielded an unprecedented amount of data for genetics research. It is a daunting task to process the data from raw sequence reads to variant calls and manually processing this data can significantly delay downstream analysis and increase the possibility for human error. The research community has produced tools to properly prepare sequence data for analysis and established guidelines on how to apply those tools to achieve the best results, however, existing pipeline programs to automate the process through its entirety are either inaccessible to investigators, or web-based and require a certain amount of administrative expertise to set up. Findings Advanced Sequence Automated Pipeline (ASAP was developed to provide a framework for automating the translation of sequencing data into annotated variant calls with the goal of minimizing user involvement without the need for dedicated hardware or administrative rights. ASAP works both on computer clusters and on standalone machines with minimal human involvement and maintains high data integrity, while allowing complete control over the configuration of its component programs. It offers an easy-to-use interface for submitting and tracking jobs as well as resuming failed jobs. It also provides tools for quality checking and for dividing jobs into pieces for maximum throughput. Conclusions ASAP provides an environment for building an automated pipeline for NGS data preprocessing. This environment is flexible for use and future development. It is freely available at http://biostat.mc.vanderbilt.edu/ASAP.

  16. ASAP: an environment for automated preprocessing of sequencing data.

    Science.gov (United States)

    Torstenson, Eric S; Li, Bingshan; Li, Chun

    2013-01-04

    Next-generation sequencing (NGS) has yielded an unprecedented amount of data for genetics research. It is a daunting task to process the data from raw sequence reads to variant calls and manually processing this data can significantly delay downstream analysis and increase the possibility for human error. The research community has produced tools to properly prepare sequence data for analysis and established guidelines on how to apply those tools to achieve the best results, however, existing pipeline programs to automate the process through its entirety are either inaccessible to investigators, or web-based and require a certain amount of administrative expertise to set up. Advanced Sequence Automated Pipeline (ASAP) was developed to provide a framework for automating the translation of sequencing data into annotated variant calls with the goal of minimizing user involvement without the need for dedicated hardware or administrative rights. ASAP works both on computer clusters and on standalone machines with minimal human involvement and maintains high data integrity, while allowing complete control over the configuration of its component programs. It offers an easy-to-use interface for submitting and tracking jobs as well as resuming failed jobs. It also provides tools for quality checking and for dividing jobs into pieces for maximum throughput. ASAP provides an environment for building an automated pipeline for NGS data preprocessing. This environment is flexible for use and future development. It is freely available at http://biostat.mc.vanderbilt.edu/ASAP.

  17. ASAP: an environment for automated preprocessing of sequencing data

    Science.gov (United States)

    2013-01-01

    Background Next-generation sequencing (NGS) has yielded an unprecedented amount of data for genetics research. It is a daunting task to process the data from raw sequence reads to variant calls and manually processing this data can significantly delay downstream analysis and increase the possibility for human error. The research community has produced tools to properly prepare sequence data for analysis and established guidelines on how to apply those tools to achieve the best results, however, existing pipeline programs to automate the process through its entirety are either inaccessible to investigators, or web-based and require a certain amount of administrative expertise to set up. Findings Advanced Sequence Automated Pipeline (ASAP) was developed to provide a framework for automating the translation of sequencing data into annotated variant calls with the goal of minimizing user involvement without the need for dedicated hardware or administrative rights. ASAP works both on computer clusters and on standalone machines with minimal human involvement and maintains high data integrity, while allowing complete control over the configuration of its component programs. It offers an easy-to-use interface for submitting and tracking jobs as well as resuming failed jobs. It also provides tools for quality checking and for dividing jobs into pieces for maximum throughput. Conclusions ASAP provides an environment for building an automated pipeline for NGS data preprocessing. This environment is flexible for use and future development. It is freely available at http://biostat.mc.vanderbilt.edu/ASAP. PMID:23289815

  18. AVHRR Polar 1 Km Level 1B Data Set

    Data.gov (United States)

    National Aeronautics and Space Administration — Please note that the machine on which these AVHRR data are processed has reached its life expectancy and will no longer be available as of 02 June 2008 until further...

  19. On-Board, Real-Time Preprocessing System for Optical Remote-Sensing Imagery.

    Science.gov (United States)

    Qi, Baogui; Shi, Hao; Zhuang, Yin; Chen, He; Chen, Liang

    2018-04-25

    With the development of remote-sensing technology, optical remote-sensing imagery processing has played an important role in many application fields, such as geological exploration and natural disaster prevention. However, relative radiation correction and geometric correction are key steps in preprocessing because raw image data without preprocessing will cause poor performance during application. Traditionally, remote-sensing data are downlinked to the ground station, preprocessed, and distributed to users. This process generates long delays, which is a major bottleneck in real-time applications for remote-sensing data. Therefore, on-board, real-time image preprocessing is greatly desired. In this paper, a real-time processing architecture for on-board imagery preprocessing is proposed. First, a hierarchical optimization and mapping method is proposed to realize the preprocessing algorithm in a hardware structure, which can effectively reduce the computation burden of on-board processing. Second, a co-processing system using a field-programmable gate array (FPGA) and a digital signal processor (DSP; altogether, FPGA-DSP) based on optimization is designed to realize real-time preprocessing. The experimental results demonstrate the potential application of our system to an on-board processor, for which resources and power consumption are limited.

  20. On-Board, Real-Time Preprocessing System for Optical Remote-Sensing Imagery

    Science.gov (United States)

    Qi, Baogui; Zhuang, Yin; Chen, He; Chen, Liang

    2018-01-01

    With the development of remote-sensing technology, optical remote-sensing imagery processing has played an important role in many application fields, such as geological exploration and natural disaster prevention. However, relative radiation correction and geometric correction are key steps in preprocessing because raw image data without preprocessing will cause poor performance during application. Traditionally, remote-sensing data are downlinked to the ground station, preprocessed, and distributed to users. This process generates long delays, which is a major bottleneck in real-time applications for remote-sensing data. Therefore, on-board, real-time image preprocessing is greatly desired. In this paper, a real-time processing architecture for on-board imagery preprocessing is proposed. First, a hierarchical optimization and mapping method is proposed to realize the preprocessing algorithm in a hardware structure, which can effectively reduce the computation burden of on-board processing. Second, a co-processing system using a field-programmable gate array (FPGA) and a digital signal processor (DSP; altogether, FPGA-DSP) based on optimization is designed to realize real-time preprocessing. The experimental results demonstrate the potential application of our system to an on-board processor, for which resources and power consumption are limited. PMID:29693585

  1. Switched Flip-Flop based Preprocessing Circuit for ISFETs

    Directory of Open Access Journals (Sweden)

    Martin Kollár

    2005-03-01

    Full Text Available In this paper, a preprocessing circuit for ISFETs (Ion-sensitive field-effecttransistors to measure hydrogen-ion concentration in electrolyte is presented. A modifiedflip-flop is the main part of the circuit. The modification consists in replacing the standardtransistors by ISFETs and periodically switching the supply voltage on and off.Concentration of hydrogen ions to be measured discontinues the flip-flop value symmetry,which means that by switching the supply voltage on the flip-flop goes to one of two stablestates, ‘one’ or ‘zero’. The recovery of the value symmetry can be achieved by changing abalanced voltage, which is incorporated to the flip-flop, to bring the flip-flop to a 50%position (probability of ‘one’ equals to probability of ‘zero’. Thus, the balanced voltagereflects the measured concentration of hydrogen ions. Its magnitude is set automatically byusing a feedback circuit whose input is connected to the flip-flop output. The preprocessingcircuit, as the whole, is the well-known δ modulator in which the switched flip-flop servesas a comparator and a sampling circuit. The advantages of this approach in comparison tothose of standard approaches are discussed. Finally, theoretical results are verified bysimulations with TSPICE and a good agreement is reported.

  2. Automated Pre-processing for NMR Assignments with Reduced Tedium

    Energy Technology Data Exchange (ETDEWEB)

    2004-05-11

    An important rate-limiting step in the reasonance asignment process is accurate identification of resonance peaks in MNR spectra. NMR spectra are noisy. Hence, automatic peak-picking programs must navigate between the Scylla of reliable but incomplete picking, and the Charybdis of noisy but complete picking. Each of these extremes complicates the assignment process: incomplete peak-picking results in the loss of essential connectivities, while noisy picking conceals the true connectivities under a combinatiorial explosion of false positives. Intermediate processing can simplify the assignment process by preferentially removing false peaks from noisy peak lists. This is accomplished by requiring consensus between multiple NMR experiments, exploiting a priori information about NMR spectra, and drawing on empirical statistical distributions of chemical shift extracted from the BioMagResBank. Experienced NMR practitioners currently apply many of these techniques "by hand", which is tedious, and may appear arbitrary to the novice. To increase efficiency, we have created a systematic and automated approach to this process, known as APART. Automated pre-processing has three main advantages: reduced tedium, standardization, and pedagogy. In the hands of experienced spectroscopists, the main advantage is reduced tedium (a rapid increase in the ratio of true peaks to false peaks with minimal effort). When a project is passed from hand to hand, the main advantage is standardization. APART automatically documents the peak filtering process by archiving its original recommendations, the accompanying justifications, and whether a user accepted or overrode a given filtering recommendation. In the hands of a novice, this tool can reduce the stumbling block of learning to differentiate between real peaks and noise, by providing real-time examples of how such decisions are made.

  3. Thinning: A Preprocessing Technique for an OCR System for the Brahmi Script

    Directory of Open Access Journals (Sweden)

    H. K. Anasuya Devi

    2006-12-01

    Full Text Available In this paper we study the methodology employed for preprocessing the archaeological images. We present the various algorithms used in the low level processing stage of image analysis for Optical Character Recognition System for Brahmi Script. The image preprocessing technique covered in this paper include Thinning method. We also try to analyze the results obtained by the pixel-level processing algorithms.

  4. An Automated, Adaptive Framework for Optimizing Preprocessing Pipelines in Task-Based Functional MRI.

    Directory of Open Access Journals (Sweden)

    Nathan W Churchill

    Full Text Available BOLD fMRI is sensitive to blood-oxygenation changes correlated with brain function; however, it is limited by relatively weak signal and significant noise confounds. Many preprocessing algorithms have been developed to control noise and improve signal detection in fMRI. Although the chosen set of preprocessing and analysis steps (the "pipeline" significantly affects signal detection, pipelines are rarely quantitatively validated in the neuroimaging literature, due to complex preprocessing interactions. This paper outlines and validates an adaptive resampling framework for evaluating and optimizing preprocessing choices by optimizing data-driven metrics of task prediction and spatial reproducibility. Compared to standard "fixed" preprocessing pipelines, this optimization approach significantly improves independent validation measures of within-subject test-retest, and between-subject activation overlap, and behavioural prediction accuracy. We demonstrate that preprocessing choices function as implicit model regularizers, and that improvements due to pipeline optimization generalize across a range of simple to complex experimental tasks and analysis models. Results are shown for brief scanning sessions (<3 minutes each, demonstrating that with pipeline optimization, it is possible to obtain reliable results and brain-behaviour correlations in relatively small datasets.

  5. Comparison of pre-processing methods for multiplex bead-based immunoassays.

    Science.gov (United States)

    Rausch, Tanja K; Schillert, Arne; Ziegler, Andreas; Lüking, Angelika; Zucht, Hans-Dieter; Schulz-Knappe, Peter

    2016-08-11

    High throughput protein expression studies can be performed using bead-based protein immunoassays, such as the Luminex® xMAP® technology. Technical variability is inherent to these experiments and may lead to systematic bias and reduced power. To reduce technical variability, data pre-processing is performed. However, no recommendations exist for the pre-processing of Luminex® xMAP® data. We compared 37 different data pre-processing combinations of transformation and normalization methods in 42 samples on 384 analytes obtained from a multiplex immunoassay based on the Luminex® xMAP® technology. We evaluated the performance of each pre-processing approach with 6 different performance criteria. Three performance criteria were plots. All plots were evaluated by 15 independent and blinded readers. Four different combinations of transformation and normalization methods performed well as pre-processing procedure for this bead-based protein immunoassay. The following combinations of transformation and normalization were suitable for pre-processing Luminex® xMAP® data in this study: weighted Box-Cox followed by quantile or robust spline normalization (rsn), asinh transformation followed by loess normalization and Box-Cox followed by rsn.

  6. Effect of packaging on physicochemical characteristics of irradiated pre-processed chicken

    International Nuclear Information System (INIS)

    Jiang Xiujie; Zhang Dongjie; Zhang Dequan; Li Shurong; Gao Meixu; Wang Zhidong

    2011-01-01

    To explore the effect of modified atmosphere packaging and antioxidants on the physicochemical characteristics of irradiated pre-processed chicken, the pre-processed chicken was added antioxidants first, and then packaged in common, vacuum and gas respectively, and finally irradiated at 5 kGy dosage. All samples was stored at 4 ℃. The pH, TBA, TVB-N and color deviation were evaluated after 0, 3, 7, 10, 14, 18 and 21 d of storage. The results showed that pH value of pre-processed chicken with antioxidants and vacuum packaged increased with the storage time but not significantly among different treatments. The TBA value was also increased but not significantly (P > 0.05), which indicated that vacuum package inhibited the lipid oxidation. TVB-N value increased with storage time, TVB-N value of vacuum package samples reached 14.29 mg/100 g at 21 d storage, which did not exceeded the reference indexes of fresh meat. a * value of the pre-processed chicken of vacuum package and non-oxygen package samples increased significantly during storage (P > 0.05), and chicken color kept bright red after 21 d storage with vacuum package It is concluded that vacuum packaging of irradiated pre-processed chicken is effective on ensuring its physical and chemical properties during storage. (authors)

  7. Examination of Speed Contribution of Parallelization for Several Fingerprint Pre-Processing Algorithms

    Directory of Open Access Journals (Sweden)

    GORGUNOGLU, S.

    2014-05-01

    Full Text Available In analysis of minutiae based fingerprint systems, fingerprints needs to be pre-processed. The pre-processing is carried out to enhance the quality of the fingerprint and to obtain more accurate minutiae points. Reducing the pre-processing time is important for identification and verification in real time systems and especially for databases holding large fingerprints information. Parallel processing and parallel CPU computing can be considered as distribution of processes over multi core processor. This is done by using parallel programming techniques. Reducing the execution time is the main objective in parallel processing. In this study, pre-processing of minutiae based fingerprint system is implemented by parallel processing on multi core computers using OpenMP and on graphics processor using CUDA to improve execution time. The execution times and speedup ratios are compared with the one that of single core processor. The results show that by using parallel processing, execution time is substantially improved. The improvement ratios obtained for different pre-processing algorithms allowed us to make suggestions on the more suitable approaches for parallelization.

  8. Comparative performance evaluation of transform coding in image pre-processing

    Science.gov (United States)

    Menon, Vignesh V.; NB, Harikrishnan; Narayanan, Gayathri; CK, Niveditha

    2017-07-01

    We are in the midst of a communication transmute which drives the development as largely as dissemination of pioneering communication systems with ever-increasing fidelity and resolution. Distinguishable researches have been appreciative in image processing techniques crazed by a growing thirst for faster and easier encoding, storage and transmission of visual information. In this paper, the researchers intend to throw light on many techniques which could be worn at the transmitter-end in order to ease the transmission and reconstruction of the images. The researchers investigate the performance of different image transform coding schemes used in pre-processing, their comparison, and effectiveness, the necessary and sufficient conditions, properties and complexity in implementation. Whimsical by prior advancements in image processing techniques, the researchers compare various contemporary image pre-processing frameworks- Compressed Sensing, Singular Value Decomposition, Integer Wavelet Transform on performance. The paper exposes the potential of Integer Wavelet transform to be an efficient pre-processing scheme.

  9. Performance of Pre-processing Schemes with Imperfect Channel State Information

    DEFF Research Database (Denmark)

    Christensen, Søren Skovgaard; Kyritsi, Persa; De Carvalho, Elisabeth

    2006-01-01

    Pre-processing techniques have several benefits when the CSI is perfect. In this work we investigate three linear pre-processing filters, assuming imperfect CSI caused by noise degradation and channel temporal variation. Results indicate, that the LMMSE filter achieves the lowest BER and the high......Pre-processing techniques have several benefits when the CSI is perfect. In this work we investigate three linear pre-processing filters, assuming imperfect CSI caused by noise degradation and channel temporal variation. Results indicate, that the LMMSE filter achieves the lowest BER...... and the highest SINR when the CSI is perfect, whereas the simple matched filter may be a good choice when the CSI is imperfect. Additionally the results give insight into the inherent trade-off between robustness against CSI imperfections and spatial focusing ability....

  10. Comparison of classification algorithms for various methods of preprocessing radar images of the MSTAR base

    Science.gov (United States)

    Borodinov, A. A.; Myasnikov, V. V.

    2018-04-01

    The present work is devoted to comparing the accuracy of the known qualification algorithms in the task of recognizing local objects on radar images for various image preprocessing methods. Preprocessing involves speckle noise filtering and normalization of the object orientation in the image by the method of image moments and by a method based on the Hough transform. In comparison, the following classification algorithms are used: Decision tree; Support vector machine, AdaBoost, Random forest. The principal component analysis is used to reduce the dimension. The research is carried out on the objects from the base of radar images MSTAR. The paper presents the results of the conducted studies.

  11. A Real-Time Embedded System for Stereo Vision Preprocessing Using an FPGA

    DEFF Research Database (Denmark)

    Kjær-Nielsen, Anders; Jensen, Lars Baunegaard With; Sørensen, Anders Stengaard

    2008-01-01

    In this paper a low level vision processing node for use in existing IEEE 1394 camera setups is presented. The processing node is a small embedded system, that utilizes an FPGA to perform stereo vision preprocessing at rates limited by the bandwidth of IEEE 1394a (400Mbit). The system is used...

  12. Poisson pre-processing of nonstationary photonic signals: Signals with equality between mean and variance.

    Science.gov (United States)

    Poplová, Michaela; Sovka, Pavel; Cifra, Michal

    2017-01-01

    Photonic signals are broadly exploited in communication and sensing and they typically exhibit Poisson-like statistics. In a common scenario where the intensity of the photonic signals is low and one needs to remove a nonstationary trend of the signals for any further analysis, one faces an obstacle: due to the dependence between the mean and variance typical for a Poisson-like process, information about the trend remains in the variance even after the trend has been subtracted, possibly yielding artifactual results in further analyses. Commonly available detrending or normalizing methods cannot cope with this issue. To alleviate this issue we developed a suitable pre-processing method for the signals that originate from a Poisson-like process. In this paper, a Poisson pre-processing method for nonstationary time series with Poisson distribution is developed and tested on computer-generated model data and experimental data of chemiluminescence from human neutrophils and mung seeds. The presented method transforms a nonstationary Poisson signal into a stationary signal with a Poisson distribution while preserving the type of photocount distribution and phase-space structure of the signal. The importance of the suggested pre-processing method is shown in Fano factor and Hurst exponent analysis of both computer-generated model signals and experimental photonic signals. It is demonstrated that our pre-processing method is superior to standard detrending-based methods whenever further signal analysis is sensitive to variance of the signal.

  13. Scene matching based on non-linear pre-processing on reference image and sensed image

    Institute of Scientific and Technical Information of China (English)

    Zhong Sheng; Zhang Tianxu; Sang Nong

    2005-01-01

    To solve the heterogeneous image scene matching problem, a non-linear pre-processing method for the original images before intensity-based correlation is proposed. The result shows that the proper matching probability is raised greatly. Especially for the low S/N image pairs, the effect is more remarkable.

  14. Data pre-processing: a case study in predicting student's retention in ...

    African Journals Online (AJOL)

    dataset with features that are ready for data mining task. The study also proposed a process model and suggestions, which can be applied to support more comprehensible tools for educational domain who is the end user. Subsequently, the data pre-processing become more efficient for predicting student's retention in ...

  15. Summary of ENDF/B Pre-Processing Codes June 1983

    International Nuclear Information System (INIS)

    Cullen, D.E.

    1983-06-01

    This is the summary documentation for the 1983 version of the ENDF/B Pre-Processing Codes LINEAR, RECENT, SIGMA1, GROUPIE, EVALPLOT, MERGER, DICTION, COMPLOT, CONVERT. This summary documentation is merely a copy of the comment cards that appear at the beginning of each programme; these comment cards always reflect the latest status of input options, etc

  16. Evaluation of Microarray Preprocessing Algorithms Based on Concordance with RT-PCR in Clinical Samples

    DEFF Research Database (Denmark)

    Hansen, Kasper Lage; Szallasi, Zoltan Imre; Eklund, Aron Charles

    2009-01-01

    evaluated consistency using the Pearson correlation between measurements obtained on the two platforms. Also, we introduce the log-ratio discrepancy as a more relevant measure of discordance between gene expression platforms. Of nine preprocessing algorithms tested, PLIER+16 produced expression values...

  17. Pre-processing data using wavelet transform and PCA based on ...

    Indian Academy of Sciences (India)

    Abazar Solgi

    2017-07-14

    Jul 14, 2017 ... Pre-processing data using wavelet transform and PCA based on support vector regression and gene expression programming for river flow simulation. Abazar Solgi1,*, Amir Pourhaghi1, Ramin Bahmani2 and Heidar Zarei3. 1. Department of Water Resources Engineering, Shahid Chamran University of ...

  18. Preprocessing for Optimization of Probabilistic-Logic Models for Sequence Analysis

    DEFF Research Database (Denmark)

    Christiansen, Henning; Lassen, Ole Torp

    2009-01-01

    and approximation are needed. The first steps are taken towards a methodology for optimizing such models by approximations using auxiliary models for preprocessing or splitting them into submodels. Evaluation of such approximating models is challenging as authoritative test data may be sparse. On the other hand...

  19. Data preprocessing methods of FT-NIR spectral data for the classification cooking oil

    Science.gov (United States)

    Ruah, Mas Ezatul Nadia Mohd; Rasaruddin, Nor Fazila; Fong, Sim Siong; Jaafar, Mohd Zuli

    2014-12-01

    This recent work describes the data pre-processing method of FT-NIR spectroscopy datasets of cooking oil and its quality parameters with chemometrics method. Pre-processing of near-infrared (NIR) spectral data has become an integral part of chemometrics modelling. Hence, this work is dedicated to investigate the utility and effectiveness of pre-processing algorithms namely row scaling, column scaling and single scaling process with Standard Normal Variate (SNV). The combinations of these scaling methods have impact on exploratory analysis and classification via Principle Component Analysis plot (PCA). The samples were divided into palm oil and non-palm cooking oil. The classification model was build using FT-NIR cooking oil spectra datasets in absorbance mode at the range of 4000cm-1-14000cm-1. Savitzky Golay derivative was applied before developing the classification model. Then, the data was separated into two sets which were training set and test set by using Duplex method. The number of each class was kept equal to 2/3 of the class that has the minimum number of sample. Then, the sample was employed t-statistic as variable selection method in order to select which variable is significant towards the classification models. The evaluation of data pre-processing were looking at value of modified silhouette width (mSW), PCA and also Percentage Correctly Classified (%CC). The results show that different data processing strategies resulting to substantial amount of model performances quality. The effects of several data pre-processing i.e. row scaling, column standardisation and single scaling process with Standard Normal Variate indicated by mSW and %CC. At two PCs model, all five classifier gave high %CC except Quadratic Distance Analysis.

  20. Value of Distributed Preprocessing of Biomass Feedstocks to a Bioenergy Industry

    Energy Technology Data Exchange (ETDEWEB)

    Christopher T Wright

    2006-07-01

    Biomass preprocessing is one of the primary operations in the feedstock assembly system and the front-end of a biorefinery. Its purpose is to chop, grind, or otherwise format the biomass into a suitable feedstock for conversion to ethanol and other bioproducts. Many variables such as equipment cost and efficiency, and feedstock moisture content, particle size, bulk density, compressibility, and flowability affect the location and implementation of this unit operation. Previous conceptual designs show this operation to be located at the front-end of the biorefinery. However, data are presented that show distributed preprocessing at the field-side or in a fixed preprocessing facility can provide significant cost benefits by producing a higher value feedstock with improved handling, transporting, and merchandising potential. In addition, data supporting the preferential deconstruction of feedstock materials due to their bio-composite structure identifies the potential for significant improvements in equipment efficiencies and compositional quality upgrades. Theses data are collected from full-scale low and high capacity hammermill grinders with various screen sizes. Multiple feedstock varieties with a range of moisture values were used in the preprocessing tests. The comparative values of the different grinding configurations, feedstock varieties, and moisture levels are assessed through post-grinding analysis of the different particle fractions separated with a medium-scale forage particle separator and a Rototap separator. The results show that distributed preprocessing produces a material that has bulk flowable properties and fractionation benefits that can improve the ease of transporting, handling and conveying the material to the biorefinery and improve the biochemical and thermochemical conversion processes.

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

    Science.gov (United States)

    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

  2. Reproducible cancer biomarker discovery in SELDI-TOF MS using different pre-processing algorithms.

    Directory of Open Access Journals (Sweden)

    Jinfeng Zou

    Full Text Available BACKGROUND: There has been much interest in differentiating diseased and normal samples using biomarkers derived from mass spectrometry (MS studies. However, biomarker identification for specific diseases has been hindered by irreproducibility. Specifically, a peak profile extracted from a dataset for biomarker identification depends on a data pre-processing algorithm. Until now, no widely accepted agreement has been reached. RESULTS: In this paper, we investigated the consistency of biomarker identification using differentially expressed (DE peaks from peak profiles produced by three widely used average spectrum-dependent pre-processing algorithms based on SELDI-TOF MS data for prostate and breast cancers. Our results revealed two important factors that affect the consistency of DE peak identification using different algorithms. One factor is that some DE peaks selected from one peak profile were not detected as peaks in other profiles, and the second factor is that the statistical power of identifying DE peaks in large peak profiles with many peaks may be low due to the large scale of the tests and small number of samples. Furthermore, we demonstrated that the DE peak detection power in large profiles could be improved by the stratified false discovery rate (FDR control approach and that the reproducibility of DE peak detection could thereby be increased. CONCLUSIONS: Comparing and evaluating pre-processing algorithms in terms of reproducibility can elucidate the relationship among different algorithms and also help in selecting a pre-processing algorithm. The DE peaks selected from small peak profiles with few peaks for a dataset tend to be reproducibly detected in large peak profiles, which suggests that a suitable pre-processing algorithm should be able to produce peaks sufficient for identifying useful and reproducible biomarkers.

  3. Input data preprocessing method for exchange rate forecasting via neural network

    Directory of Open Access Journals (Sweden)

    Antić Dragan S.

    2014-01-01

    Full Text Available The aim of this paper is to present a method for neural network input parameters selection and preprocessing. The purpose of this network is to forecast foreign exchange rates using artificial intelligence. Two data sets are formed for two different economic systems. Each system is represented by six categories with 70 economic parameters which are used in the analysis. Reduction of these parameters within each category was performed by using the principal component analysis method. Component interdependencies are established and relations between them are formed. Newly formed relations were used to create input vectors of a neural network. The multilayer feed forward neural network is formed and trained using batch training. Finally, simulation results are presented and it is concluded that input data preparation method is an effective way for preprocessing neural network data. [Projekat Ministarstva nauke Republike Srbije, br.TR 35005, br. III 43007 i br. III 44006

  4. Parallel finite elements with domain decomposition and its pre-processing

    International Nuclear Information System (INIS)

    Yoshida, A.; Yagawa, G.; Hamada, S.

    1993-01-01

    This paper describes a parallel finite element analysis using a domain decomposition method, and the pre-processing for the parallel calculation. Computer simulations are about to replace experiments in various fields, and the scale of model to be simulated tends to be extremely large. On the other hand, computational environment has drastically changed in these years. Especially, parallel processing on massively parallel computers or computer networks is considered to be promising techniques. In order to achieve high efficiency on such parallel computation environment, large granularity of tasks, a well-balanced workload distribution are key issues. It is also important to reduce the cost of pre-processing in such parallel FEM. From the point of view, the authors developed the domain decomposition FEM with the automatic and dynamic task-allocation mechanism and the automatic mesh generation/domain subdivision system for it. (author)

  5. Protein from preprocessed waste activated sludge as a nutritional supplement in chicken feed.

    Science.gov (United States)

    Chirwa, Evans M N; Lebitso, Moses T

    2014-01-01

    Five groups of broiler chickens were raised on feed containing varying substitutions of single cell protein from preprocessed waste activated sludge (pWAS) in varying compositions of 0:100, 25:75, 50:50, 75:25, and 100:0 pWAS: fishmeal by mass. Forty chickens per batch were evaluated for growth rate, mortality rate, and feed conversion efficiency (ηє). The initial mass gain rate, mortality rate, initial and operational cost analyses showed that protein from pWAS could successfully replace the commercial feed supplements with a significant cost saving without adversely affecting the health of the birds. The chickens raised on preprocessed WAS weighed 19% more than those raised on fishmeal protein supplement over a 45 day test period. Growing chickens on pWAS translated into a 46% cost saving due to the fast growth rate and minimal death losses before maturity.

  6. Application of preprocessing filtering on Decision Tree C4.5 and rough set theory

    Science.gov (United States)

    Chan, Joseph C. C.; Lin, Tsau Y.

    2001-03-01

    This paper compares two artificial intelligence methods: the Decision Tree C4.5 and Rough Set Theory on the stock market data. The Decision Tree C4.5 is reviewed with the Rough Set Theory. An enhanced window application is developed to facilitate the pre-processing filtering by introducing the feature (attribute) transformations, which allows users to input formulas and create new attributes. Also, the application produces three varieties of data set with delaying, averaging, and summation. The results prove the improvement of pre-processing by applying feature (attribute) transformations on Decision Tree C4.5. Moreover, the comparison between Decision Tree C4.5 and Rough Set Theory is based on the clarity, automation, accuracy, dimensionality, raw data, and speed, which is supported by the rules sets generated by both algorithms on three different sets of data.

  7. Acoustic Biometric System Based on Preprocessing Techniques and Linear Support Vector Machines.

    Science.gov (United States)

    del Val, Lara; Izquierdo-Fuente, Alberto; Villacorta, Juan J; Raboso, Mariano

    2015-06-17

    Drawing on the results of an acoustic biometric system based on a MSE classifier, a new biometric system has been implemented. This new system preprocesses acoustic images, extracts several parameters and finally classifies them, based on Support Vector Machine (SVM). The preprocessing techniques used are spatial filtering, segmentation-based on a Gaussian Mixture Model (GMM) to separate the person from the background, masking-to reduce the dimensions of images-and binarization-to reduce the size of each image. An analysis of classification error and a study of the sensitivity of the error versus the computational burden of each implemented algorithm are presented. This allows the selection of the most relevant algorithms, according to the benefits required by the system. A significant improvement of the biometric system has been achieved by reducing the classification error, the computational burden and the storage requirements.

  8. ENDF/B Pre-Processing Codes: Implementing and testing on a Personal Computer

    International Nuclear Information System (INIS)

    McLaughlin, P.K.

    1987-05-01

    This document describes the contents of the diskettes containing the ENDF/B Pre-Processing codes by D.E. Cullen, and example data for use in implementing and testing these codes on a Personal Computer of the type IBM-PC/AT. Upon request the codes are available from the IAEA Nuclear Data Section, free of charge, on a series of 7 diskettes. (author)

  9. The Influence of Preprocessing Steps on Graph Theory Measures Derived from Resting State fMRI.

    Science.gov (United States)

    Gargouri, Fatma; Kallel, Fathi; Delphine, Sebastien; Ben Hamida, Ahmed; Lehéricy, Stéphane; Valabregue, Romain

    2018-01-01

    Resting state functional MRI (rs-fMRI) is an imaging technique that allows the spontaneous activity of the brain to be measured. Measures of functional connectivity highly depend on the quality of the BOLD signal data processing. In this study, our aim was to study the influence of preprocessing steps and their order of application on small-world topology and their efficiency in resting state fMRI data analysis using graph theory. We applied the most standard preprocessing steps: slice-timing, realign, smoothing, filtering, and the tCompCor method. In particular, we were interested in how preprocessing can retain the small-world economic properties and how to maximize the local and global efficiency of a network while minimizing the cost. Tests that we conducted in 54 healthy subjects showed that the choice and ordering of preprocessing steps impacted the graph measures. We found that the csr (where we applied realignment, smoothing, and tCompCor as a final step) and the scr (where we applied realignment, tCompCor and smoothing as a final step) strategies had the highest mean values of global efficiency (eg) . Furthermore, we found that the fscr strategy (where we applied realignment, tCompCor, smoothing, and filtering as a final step), had the highest mean local efficiency (el) values. These results confirm that the graph theory measures of functional connectivity depend on the ordering of the processing steps, with the best results being obtained using smoothing and tCompCor as the final steps for global efficiency with additional filtering for local efficiency.

  10. Effect of pre-processing on the physico-chemical properties of ...

    African Journals Online (AJOL)

    The findings indicated that the pre-processing treatments produced significant differences (p < 0.05) in protein (1.50 ± 0.18g/100g) and carbohydrate (1.09 ± 0.94g/100g) composition of the baking soda blanched milk sample. The viscosity of the baking soda blanched milk (18.91 ± 3.38cps) was significantly higher than that ...

  11. A clinical evaluation of the RNCA study using Fourier filtering as a preprocessing method

    Energy Technology Data Exchange (ETDEWEB)

    Robeson, W.; Alcan, K.E.; Graham, M.C.; Palestro, C.; Oliver, F.H.; Benua, R.S.

    1984-06-01

    Forty-one patients (25 male, 16 female) were studied by Radionuclide Cardangiography (RNCA) in our institution. There were 42 rest studies and 24 stress studies (66 studies total). Sixteen patients were normal, 15 had ASHD, seven had a cardiomyopathy, and three had left-sided valvular regurgitation. Each study was preprocessed using both the standard nine-point smoothing method and Fourier filtering. Amplitude and phase images were also generated. Both preprocessing methods were compared with respect to image quality, border definition, reliability and reproducibility of the LVEF, and cine wall motion interpretation. Image quality and border definition were judged superior by the consensus of two independent observers in 65 of 66 studies (98%) using Fourier filtered data. The LVEF differed between the two processes by greater than .05 in 17 of 66 studies (26%) including five studies in which the LVEF could not be determined using nine-point smoothed data. LV wall motion was normal by both techniques in all control patients by cine analysis. However, cine wall motion analysis using Fourier filtered data demonstrated additional abnormalities in 17 of 25 studies (68%) in the ASHD group, including three uninterpretable studies using nine-point smoothed data. In the cardiomyopathy/valvular heart disease group, ten of 18 studies (56%) had additional wall motion abnormalities using Fourier filtered data (including four uninterpretable studies using nine-point smoothed data). We conclude that Fourier filtering is superior to the nine-point smooth preprocessing method now in general use in terms of image quality, border definition, generation of an LVEF, and cine wall motion analysis. The advent of the array processor makes routine preprocessing by Fourier filtering a feasible technologic advance in the development of the RNCA study.

  12. Review of Data Preprocessing Methods for Sign Language Recognition Systems based on Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Zorins Aleksejs

    2016-12-01

    Full Text Available The article presents an introductory analysis of relevant research topic for Latvian deaf society, which is the development of the Latvian Sign Language Recognition System. More specifically the data preprocessing methods are discussed in the paper and several approaches are shown with a focus on systems based on artificial neural networks, which are one of the most successful solutions for sign language recognition task.

  13. Evaluation of a Stereo Music Preprocessing Scheme for Cochlear Implant Users.

    Science.gov (United States)

    Buyens, Wim; van Dijk, Bas; Moonen, Marc; Wouters, Jan

    2018-01-01

    Although for most cochlear implant (CI) users good speech understanding is reached (at least in quiet environments), the perception and the appraisal of music are generally unsatisfactory. The improvement in music appraisal was evaluated in CI participants by using a stereo music preprocessing scheme implemented on a take-home device, in a comfortable listening environment. The preprocessing allowed adjusting the balance among vocals/bass/drums and other instruments, and was evaluated for different genres of music. The correlation between the preferred settings and the participants' speech and pitch detection performance was investigated. During the initial visit preceding the take-home test, the participants' speech-in-noise perception and pitch detection performance were measured, and a questionnaire about their music involvement was completed. The take-home device was provided, including the stereo music preprocessing scheme and seven playlists with six songs each. The participants were asked to adjust the balance by means of a turning wheel to make the music sound most enjoyable, and to repeat this three times for all songs. Twelve postlingually deafened CI users participated in the study. The data were collected by means of a take-home device, which preserved all the preferred settings for the different songs. Statistical analysis was done with a Friedman test (with post hoc Wilcoxon signed-rank test) to check the effect of "Genre." The correlations were investigated with Pearson's and Spearman's correlation coefficients. All participants preferred a balance significantly different from the original balance. Differences across participants were observed which could not be explained by perceptual abilities. An effect of "Genre" was found, showing significantly smaller preferred deviation from the original balance for Golden Oldies compared to the other genres. The stereo music preprocessing scheme showed an improvement in music appraisal with complex music and

  14. Hyperspectral imaging in medicine: image pre-processing problems and solutions in Matlab.

    Science.gov (United States)

    Koprowski, Robert

    2015-11-01

    The paper presents problems and solutions related to hyperspectral image pre-processing. New methods of preliminary image analysis are proposed. The paper shows problems occurring in Matlab when trying to analyse this type of images. Moreover, new methods are discussed which provide the source code in Matlab that can be used in practice without any licensing restrictions. The proposed application and sample result of hyperspectral image analysis. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  15. A clinical evaluation of the RNCA study using Fourier filtering as a preprocessing method

    International Nuclear Information System (INIS)

    Robeson, W.; Alcan, K.E.; Graham, M.C.; Palestro, C.; Oliver, F.H.; Benua, R.S.

    1984-01-01

    Forty-one patients (25 male, 16 female) were studied by Radionuclide Cardangiography (RNCA) in our institution. There were 42 rest studies and 24 stress studies (66 studies total). Sixteen patients were normal, 15 had ASHD, seven had a cardiomyopathy, and three had left-sided valvular regurgitation. Each study was preprocessed using both the standard nine-point smoothing method and Fourier filtering. Amplitude and phase images were also generated. Both preprocessing methods were compared with respect to image quality, border definition, reliability and reproducibility of the LVEF, and cine wall motion interpretation. Image quality and border definition were judged superior by the consensus of two independent observers in 65 of 66 studies (98%) using Fourier filtered data. The LVEF differed between the two processes by greater than .05 in 17 of 66 studies (26%) including five studies in which the LVEF could not be determined using nine-point smoothed data. LV wall motion was normal by both techniques in all control patients by cine analysis. However, cine wall motion analysis using Fourier filtered data demonstrated additional abnormalities in 17 of 25 studies (68%) in the ASHD group, including three uninterpretable studies using nine-point smoothed data. In the cardiomyopathy/valvular heart disease group, ten of 18 studies (56%) had additional wall motion abnormalities using Fourier filtered data (including four uninterpretable studies using nine-point smoothed data). We conclude that Fourier filtering is superior to the nine-point smooth preprocessing method now in general use in terms of image quality, border definition, generation of an LVEF, and cine wall motion analysis. The advent of the array processor makes routine preprocessing by Fourier filtering a feasible technologic advance in the development of the RNCA study

  16. The Influence of Preprocessing Steps on Graph Theory Measures Derived from Resting State fMRI

    Directory of Open Access Journals (Sweden)

    Fatma Gargouri

    2018-02-01

    Full Text Available Resting state functional MRI (rs-fMRI is an imaging technique that allows the spontaneous activity of the brain to be measured. Measures of functional connectivity highly depend on the quality of the BOLD signal data processing. In this study, our aim was to study the influence of preprocessing steps and their order of application on small-world topology and their efficiency in resting state fMRI data analysis using graph theory. We applied the most standard preprocessing steps: slice-timing, realign, smoothing, filtering, and the tCompCor method. In particular, we were interested in how preprocessing can retain the small-world economic properties and how to maximize the local and global efficiency of a network while minimizing the cost. Tests that we conducted in 54 healthy subjects showed that the choice and ordering of preprocessing steps impacted the graph measures. We found that the csr (where we applied realignment, smoothing, and tCompCor as a final step and the scr (where we applied realignment, tCompCor and smoothing as a final step strategies had the highest mean values of global efficiency (eg. Furthermore, we found that the fscr strategy (where we applied realignment, tCompCor, smoothing, and filtering as a final step, had the highest mean local efficiency (el values. These results confirm that the graph theory measures of functional connectivity depend on the ordering of the processing steps, with the best results being obtained using smoothing and tCompCor as the final steps for global efficiency with additional filtering for local efficiency.

  17. The Influence of Preprocessing Steps on Graph Theory Measures Derived from Resting State fMRI

    Science.gov (United States)

    Gargouri, Fatma; Kallel, Fathi; Delphine, Sebastien; Ben Hamida, Ahmed; Lehéricy, Stéphane; Valabregue, Romain

    2018-01-01

    Resting state functional MRI (rs-fMRI) is an imaging technique that allows the spontaneous activity of the brain to be measured. Measures of functional connectivity highly depend on the quality of the BOLD signal data processing. In this study, our aim was to study the influence of preprocessing steps and their order of application on small-world topology and their efficiency in resting state fMRI data analysis using graph theory. We applied the most standard preprocessing steps: slice-timing, realign, smoothing, filtering, and the tCompCor method. In particular, we were interested in how preprocessing can retain the small-world economic properties and how to maximize the local and global efficiency of a network while minimizing the cost. Tests that we conducted in 54 healthy subjects showed that the choice and ordering of preprocessing steps impacted the graph measures. We found that the csr (where we applied realignment, smoothing, and tCompCor as a final step) and the scr (where we applied realignment, tCompCor and smoothing as a final step) strategies had the highest mean values of global efficiency (eg). Furthermore, we found that the fscr strategy (where we applied realignment, tCompCor, smoothing, and filtering as a final step), had the highest mean local efficiency (el) values. These results confirm that the graph theory measures of functional connectivity depend on the ordering of the processing steps, with the best results being obtained using smoothing and tCompCor as the final steps for global efficiency with additional filtering for local efficiency. PMID:29497372

  18. Supervised pre-processing approaches in multiple class variables classification for fish recruitment forecasting

    KAUST Repository

    Fernandes, José Antonio

    2013-02-01

    A multi-species approach to fisheries management requires taking into account the interactions between species in order to improve recruitment forecasting of the fish species. Recent advances in Bayesian networks direct the learning of models with several interrelated variables to be forecasted simultaneously. These models are known as multi-dimensional Bayesian network classifiers (MDBNs). Pre-processing steps are critical for the posterior learning of the model in these kinds of domains. Therefore, in the present study, a set of \\'state-of-the-art\\' uni-dimensional pre-processing methods, within the categories of missing data imputation, feature discretization and feature subset selection, are adapted to be used with MDBNs. A framework that includes the proposed multi-dimensional supervised pre-processing methods, coupled with a MDBN classifier, is tested with synthetic datasets and the real domain of fish recruitment forecasting. The correctly forecasting of three fish species (anchovy, sardine and hake) simultaneously is doubled (from 17.3% to 29.5%) using the multi-dimensional approach in comparison to mono-species models. The probability assessments also show high improvement reducing the average error (estimated by means of Brier score) from 0.35 to 0.27. Finally, these differences are superior to the forecasting of species by pairs. © 2012 Elsevier Ltd.

  19. Preprocessing with Photoshop Software on Microscopic Images of A549 Cells in Epithelial-Mesenchymal Transition.

    Science.gov (United States)

    Ren, Zhou-Xin; Yu, Hai-Bin; Shen, Jun-Ling; Li, Ya; Li, Jian-Sheng

    2015-06-01

    To establish a preprocessing method for cell morphometry in microscopic images of A549 cells in epithelial-mesenchymal transition (EMT). Adobe Photoshop CS2 (Adobe Systems, Inc.) was used for preprocessing the images. First, all images were processed for size uniformity and high distinguishability between the cell and background area. Then, a blank image with the same size and grids was established and cross points of the grids were added into a distinct color. The blank image was merged into a processed image. In the merged images, the cells with 1 or more cross points were chosen, and then the cell areas were enclosed and were replaced in a distinct color. Except for chosen cellular areas, all areas were changed into a unique hue. Three observers quantified roundness of cells in images with the image preprocess (IPP) or without the method (Controls), respectively. Furthermore, 1 observer measured the roundness 3 times with the 2 methods, respectively. The results between IPPs and Controls were compared for repeatability and reproducibility. As compared with the Control method, among 3 observers, use of the IPP method resulted in a higher number and a higher percentage of same-chosen cells in an image. The relative average deviation values of roundness, either for 3 observers or 1 observer, were significantly higher in Controls than in IPPs (p Photoshop, a chosen cell from an image was more objective, regular, and accurate, creating an increase of reproducibility and repeatability on morphometry of A549 cells in epithelial to mesenchymal transition.

  20. Characterizing the continuously acquired cardiovascular time series during hemodialysis, using median hybrid filter preprocessing noise reduction

    Directory of Open Access Journals (Sweden)

    Wilson S

    2015-01-01

    Full Text Available Scott Wilson,1,2 Andrea Bowyer,3 Stephen B Harrap4 1Department of Renal Medicine, The Alfred Hospital, 2Baker IDI, Melbourne, 3Department of Anaesthesia, Royal Melbourne Hospital, 4University of Melbourne, Parkville, VIC, Australia Abstract: The clinical characterization of cardiovascular dynamics during hemodialysis (HD has important pathophysiological implications in terms of diagnostic, cardiovascular risk assessment, and treatment efficacy perspectives. Currently the diagnosis of significant intradialytic systolic blood pressure (SBP changes among HD patients is imprecise and opportunistic, reliant upon the presence of hypotensive symptoms in conjunction with coincident but isolated noninvasive brachial cuff blood pressure (NIBP readings. Considering hemodynamic variables as a time series makes a continuous recording approach more desirable than intermittent measures; however, in the clinical environment, the data signal is susceptible to corruption due to both impulsive and Gaussian-type noise. Signal preprocessing is an attractive solution to this problem. Prospectively collected continuous noninvasive SBP data over the short-break intradialytic period in ten patients was preprocessed using a novel median hybrid filter (MHF algorithm and compared with 50 time-coincident pairs of intradialytic NIBP measures from routine HD practice. The median hybrid preprocessing technique for continuously acquired cardiovascular data yielded a dynamic regression without significant noise and artifact, suitable for high-level profiling of time-dependent SBP behavior. Signal accuracy is highly comparable with standard NIBP measurement, with the added clinical benefit of dynamic real-time hemodynamic information. Keywords: continuous monitoring, blood pressure

  1. Characterizing the continuously acquired cardiovascular time series during hemodialysis, using median hybrid filter preprocessing noise reduction.

    Science.gov (United States)

    Wilson, Scott; Bowyer, Andrea; Harrap, Stephen B

    2015-01-01

    The clinical characterization of cardiovascular dynamics during hemodialysis (HD) has important pathophysiological implications in terms of diagnostic, cardiovascular risk assessment, and treatment efficacy perspectives. Currently the diagnosis of significant intradialytic systolic blood pressure (SBP) changes among HD patients is imprecise and opportunistic, reliant upon the presence of hypotensive symptoms in conjunction with coincident but isolated noninvasive brachial cuff blood pressure (NIBP) readings. Considering hemodynamic variables as a time series makes a continuous recording approach more desirable than intermittent measures; however, in the clinical environment, the data signal is susceptible to corruption due to both impulsive and Gaussian-type noise. Signal preprocessing is an attractive solution to this problem. Prospectively collected continuous noninvasive SBP data over the short-break intradialytic period in ten patients was preprocessed using a novel median hybrid filter (MHF) algorithm and compared with 50 time-coincident pairs of intradialytic NIBP measures from routine HD practice. The median hybrid preprocessing technique for continuously acquired cardiovascular data yielded a dynamic regression without significant noise and artifact, suitable for high-level profiling of time-dependent SBP behavior. Signal accuracy is highly comparable with standard NIBP measurement, with the added clinical benefit of dynamic real-time hemodynamic information.

  2. Validation of DWI pre-processing procedures for reliable differentiation between human brain gliomas.

    Science.gov (United States)

    Vellmer, Sebastian; Tonoyan, Aram S; Suter, Dieter; Pronin, Igor N; Maximov, Ivan I

    2018-02-01

    Diffusion magnetic resonance imaging (dMRI) is a powerful tool in clinical applications, in particular, in oncology screening. dMRI demonstrated its benefit and efficiency in the localisation and detection of different types of human brain tumours. Clinical dMRI data suffer from multiple artefacts such as motion and eddy-current distortions, contamination by noise, outliers etc. In order to increase the image quality of the derived diffusion scalar metrics and the accuracy of the subsequent data analysis, various pre-processing approaches are actively developed and used. In the present work we assess the effect of different pre-processing procedures such as a noise correction, different smoothing algorithms and spatial interpolation of raw diffusion data, with respect to the accuracy of brain glioma differentiation. As a set of sensitive biomarkers of the glioma malignancy grades we chose the derived scalar metrics from diffusion and kurtosis tensor imaging as well as the neurite orientation dispersion and density imaging (NODDI) biophysical model. Our results show that the application of noise correction, anisotropic diffusion filtering, and cubic-order spline interpolation resulted in the highest sensitivity and specificity for glioma malignancy grading. Thus, these pre-processing steps are recommended for the statistical analysis in brain tumour studies. Copyright © 2017. Published by Elsevier GmbH.

  3. [Study of near infrared spectral preprocessing and wavelength selection methods for endometrial cancer tissue].

    Science.gov (United States)

    Zhao, Li-Ting; Xiang, Yu-Hong; Dai, Yin-Mei; Zhang, Zhuo-Yong

    2010-04-01

    Near infrared spectroscopy was applied to measure the tissue slice of endometrial tissues for collecting the spectra. A total of 154 spectra were obtained from 154 samples. The number of normal, hyperplasia, and malignant samples was 36, 60, and 58, respectively. Original near infrared spectra are composed of many variables, for example, interference information including instrument errors and physical effects such as particle size and light scatter. In order to reduce these influences, original spectra data should be performed with different spectral preprocessing methods to compress variables and extract useful information. So the methods of spectral preprocessing and wavelength selection have played an important role in near infrared spectroscopy technique. In the present paper the raw spectra were processed using various preprocessing methods including first derivative, multiplication scatter correction, Savitzky-Golay first derivative algorithm, standard normal variate, smoothing, and moving-window median. Standard deviation was used to select the optimal spectral region of 4 000-6 000 cm(-1). Then principal component analysis was used for classification. Principal component analysis results showed that three types of samples could be discriminated completely and the accuracy almost achieved 100%. This study demonstrated that near infrared spectroscopy technology and chemometrics method could be a fast, efficient, and novel means to diagnose cancer. The proposed methods would be a promising and significant diagnosis technique of early stage cancer.

  4. Data pre-processing for web log mining: Case study of commercial bank website usage analysis

    Directory of Open Access Journals (Sweden)

    Jozef Kapusta

    2013-01-01

    Full Text Available We use data cleaning, integration, reduction and data conversion methods in the pre-processing level of data analysis. Data processing techniques improve the overall quality of the patterns mined. The paper describes using of standard pre-processing methods for preparing data of the commercial bank website in the form of the log file obtained from the web server. Data cleaning, as the simplest step of data pre-processing, is non–trivial as the analysed content is highly specific. We had to deal with the problem of frequent changes of the content and even frequent changes of the structure. Regular changes in the structure make use of the sitemap impossible. We presented approaches how to deal with this problem. We were able to create the sitemap dynamically just based on the content of the log file. In this case study, we also examined just the one part of the website over the standard analysis of an entire website, as we did not have access to all log files for the security reason. As the result, the traditional practices had to be adapted for this special case. Analysing just the small fraction of the website resulted in the short session time of regular visitors. We were not able to use recommended methods to determine the optimal value of session time. Therefore, we proposed new methods based on outliers identification for raising the accuracy of the session length in this paper.

  5. Thresholding: A Pixel-Level Image Processing Methodology Preprocessing Technique for an OCR System for the Brahmi Script

    Directory of Open Access Journals (Sweden)

    H. K. Anasuya Devi

    2006-12-01

    Full Text Available In this paper we study the methodology employed for preprocessing the archaeological images. We present the various algorithms used in the low-level processing stage of image analysis for Optical Character Recognition System for Brahmi Script. The image preprocessing technique covered in this paper is thresholding. We also try to analyze the results obtained by the pixel-level processing algorithms.

  6. Optimal preprocessing of serum and urine metabolomic data fusion for staging prostate cancer through design of experiment

    International Nuclear Information System (INIS)

    Zheng, Hong; Cai, Aimin; Zhou, Qi; Xu, Pengtao; Zhao, Liangcai; Li, Chen; Dong, Baijun; Gao, Hongchang

    2017-01-01

    Accurate classification of cancer stages will achieve precision treatment for cancer. Metabolomics presents biological phenotypes at the metabolite level and holds a great potential for cancer classification. Since metabolomic data can be obtained from different samples or analytical techniques, data fusion has been applied to improve classification accuracy. Data preprocessing is an essential step during metabolomic data analysis. Therefore, we developed an innovative optimization method to select a proper data preprocessing strategy for metabolomic data fusion using a design of experiment approach for improving the classification of prostate cancer (PCa) stages. In this study, urine and serum samples were collected from participants at five phases of PCa and analyzed using a 1 H NMR-based metabolomic approach. Partial least squares-discriminant analysis (PLS-DA) was used as a classification model and its performance was assessed by goodness of fit (R 2 ) and predictive ability (Q 2 ). Results show that data preprocessing significantly affect classification performance and depends on data properties. Using the fused metabolomic data from urine and serum, PLS-DA model with the optimal data preprocessing (R 2  = 0.729, Q 2  = 0.504, P < 0.0001) can effectively improve model performance and achieve a better classification result for PCa stages as compared with that without data preprocessing (R 2  = 0.139, Q 2  = 0.006, P = 0.450). Therefore, we propose that metabolomic data fusion integrated with an optimal data preprocessing strategy can significantly improve the classification of cancer stages for precision treatment. - Highlights: • NMR metabolomic analysis of body fluids can be used for staging prostate cancer. • Data preprocessing is an essential step for metabolomic analysis. • Data fusion improves information recovery for cancer classification. • Design of experiment achieves optimal preprocessing of metabolomic data fusion.

  7. Optimal production scheduling for energy efficiency improvement in biofuel feedstock preprocessing considering work-in-process particle separation

    International Nuclear Information System (INIS)

    Li, Lin; Sun, Zeyi; Yao, Xufeng; Wang, Donghai

    2016-01-01

    Biofuel is considered a promising alternative to traditional liquid transportation fuels. The large-scale substitution of biofuel can greatly enhance global energy security and mitigate greenhouse gas emissions. One major concern of the broad adoption of biofuel is the intensive energy consumption in biofuel manufacturing. This paper focuses on the energy efficiency improvement of biofuel feedstock preprocessing, a major process of cellulosic biofuel manufacturing. An improved scheme of the feedstock preprocessing considering work-in-process particle separation is introduced to reduce energy waste and improve energy efficiency. A scheduling model based on the improved scheme is also developed to identify an optimal production schedule that can minimize the energy consumption of the feedstock preprocessing under production target constraint. A numerical case study is used to illustrate the effectiveness of the proposed method. The research outcome is expected to improve the energy efficiency and enhance the environmental sustainability of biomass feedstock preprocessing. - Highlights: • A novel method to schedule production in biofuel feedstock preprocessing process. • Systems modeling approach is used. • Capable of optimize preprocessing to reduce energy waste and improve energy efficiency. • A numerical case is used to illustrate the effectiveness of the method. • Energy consumption per unit production can be significantly reduced.

  8. Discrete pre-processing step effects in registration-based pipelines, a preliminary volumetric study on T1-weighted images.

    Science.gov (United States)

    Muncy, Nathan M; Hedges-Muncy, Ariana M; Kirwan, C Brock

    2017-01-01

    Pre-processing MRI scans prior to performing volumetric analyses is common practice in MRI studies. As pre-processing steps adjust the voxel intensities, the space in which the scan exists, and the amount of data in the scan, it is possible that the steps have an effect on the volumetric output. To date, studies have compared between and not within pipelines, and so the impact of each step is unknown. This study aims to quantify the effects of pre-processing steps on volumetric measures in T1-weighted scans within a single pipeline. It was our hypothesis that pre-processing steps would significantly impact ROI volume estimations. One hundred fifteen participants from the OASIS dataset were used, where each participant contributed three scans. All scans were then pre-processed using a step-wise pipeline. Bilateral hippocampus, putamen, and middle temporal gyrus volume estimations were assessed following each successive step, and all data were processed by the same pipeline 5 times. Repeated-measures analyses tested for a main effects of pipeline step, scan-rescan (for MRI scanner consistency) and repeated pipeline runs (for algorithmic consistency). A main effect of pipeline step was detected, and interestingly an interaction between pipeline step and ROI exists. No effect for either scan-rescan or repeated pipeline run was detected. We then supply a correction for noise in the data resulting from pre-processing.

  9. EARLINET Single Calculus Chain - technical - Part 1: Pre-processing of raw lidar data

    Science.gov (United States)

    D'Amico, Giuseppe; Amodeo, Aldo; Mattis, Ina; Freudenthaler, Volker; Pappalardo, Gelsomina

    2016-02-01

    In this paper we describe an automatic tool for the pre-processing of aerosol lidar data called ELPP (EARLINET Lidar Pre-Processor). It is one of two calculus modules of the EARLINET Single Calculus Chain (SCC), the automatic tool for the analysis of EARLINET data. ELPP is an open source module that executes instrumental corrections and data handling of the raw lidar signals, making the lidar data ready to be processed by the optical retrieval algorithms. According to the specific lidar configuration, ELPP automatically performs dead-time correction, atmospheric and electronic background subtraction, gluing of lidar signals, and trigger-delay correction. Moreover, the signal-to-noise ratio of the pre-processed signals can be improved by means of configurable time integration of the raw signals and/or spatial smoothing. ELPP delivers the statistical uncertainties of the final products by means of error propagation or Monte Carlo simulations. During the development of ELPP, particular attention has been payed to make the tool flexible enough to handle all lidar configurations currently used within the EARLINET community. Moreover, it has been designed in a modular way to allow an easy extension to lidar configurations not yet implemented. The primary goal of ELPP is to enable the application of quality-assured procedures in the lidar data analysis starting from the raw lidar data. This provides the added value of full traceability of each delivered lidar product. Several tests have been performed to check the proper functioning of ELPP. The whole SCC has been tested with the same synthetic data sets, which were used for the EARLINET algorithm inter-comparison exercise. ELPP has been successfully employed for the automatic near-real-time pre-processing of the raw lidar data measured during several EARLINET inter-comparison campaigns as well as during intense field campaigns.

  10. Cloudy Solar Software - Enhanced Capabilities for Finding, Pre-processing, and Visualizing Solar Data

    Science.gov (United States)

    Istvan Etesi, Laszlo; Tolbert, K.; Schwartz, R.; Zarro, D.; Dennis, B.; Csillaghy, A.

    2010-05-01

    In our project "Extending the Virtual Solar Observatory (VSO)” we have combined some of the features available in Solar Software (SSW) to produce an integrated environment for data analysis, supporting the complete workflow from data location, retrieval, preparation, and analysis to creating publication-quality figures. Our goal is an integrated analysis experience in IDL, easy-to-use but flexible enough to allow more sophisticated procedures such as multi-instrument analysis. To that end, we have made the transition from a locally oriented setting where all the analysis is done on the user's computer, to an extended analysis environment where IDL has access to services available on the Internet. We have implemented a form of Cloud Computing that uses the VSO search and a new data retrieval and pre-processing server (PrepServer) that provides remote execution of instrument-specific data preparation. We have incorporated the interfaces to the VSO search and the PrepServer into an IDL widget (SHOW_SYNOP) that provides user-friendly searching and downloading of raw solar data and optionally sends search results for pre-processing to the PrepServer prior to downloading the data. The raw and pre-processed data can be displayed with our plotting suite, PLOTMAN, which can handle different data types (light curves, images, and spectra) and perform basic data operations such as zooming, image overlays, solar rotation, etc. PLOTMAN is highly configurable and suited for visual data analysis and for creating publishable figures. PLOTMAN and SHOW_SYNOP work hand-in-hand for a convenient working environment. Our environment supports a growing number of solar instruments that currently includes RHESSI, SOHO/EIT, TRACE, SECCHI/EUVI, HINODE/XRT, and HINODE/EIS.

  11. Fast randomized point location without preprocessing in two- and three-dimensional Delaunay triangulations

    Energy Technology Data Exchange (ETDEWEB)

    Muecke, E.P.; Saias, I.; Zhu, B.

    1996-05-01

    This paper studies the point location problem in Delaunay triangulations without preprocessing and additional storage. The proposed procedure finds the query point simply by walking through the triangulation, after selecting a good starting point by random sampling. The analysis generalizes and extends a recent result of d = 2 dimensions by proving this procedure to take expected time close to O(n{sup 1/(d+1)}) for point location in Delaunay triangulations of n random points in d = 3 dimensions. Empirical results in both two and three dimensions show that this procedure is efficient in practice.

  12. Preprocessing Raw Data in Clinical Medicine for a Data Mining Purpose

    Directory of Open Access Journals (Sweden)

    Peterková Andrea

    2016-12-01

    Full Text Available Dealing with data from the field of medicine is nowadays very current and difficult. On a global scale, a large amount of medical data is produced on an everyday basis. For the purpose of our research, we understand medical data as data about patients like results from laboratory analysis, results from screening examinations (CT, ECHO and clinical parameters. This data is usually in a raw format, difficult to understand, non-standard and not suitable for further processing or analysis. This paper aims to describe the possible method of data preparation and preprocessing of such raw medical data into a form, where further analysis algorithms can be applied.

  13. Classification-based comparison of pre-processing methods for interpretation of mass spectrometry generated clinical datasets

    Directory of Open Access Journals (Sweden)

    Hoefsloot Huub CJ

    2009-05-01

    Full Text Available Abstract Background Mass spectrometry is increasingly being used to discover proteins or protein profiles associated with disease. Experimental design of mass-spectrometry studies has come under close scrutiny and the importance of strict protocols for sample collection is now understood. However, the question of how best to process the large quantities of data generated is still unanswered. Main challenges for the analysis are the choice of proper pre-processing and classification methods. While these two issues have been investigated in isolation, we propose to use the classification of patient samples as a clinically relevant benchmark for the evaluation of pre-processing methods. Results Two in-house generated clinical SELDI-TOF MS datasets are used in this study as an example of high throughput mass-spectrometry data. We perform a systematic comparison of two commonly used pre-processing methods as implemented in Ciphergen ProteinChip Software and in the Cromwell package. With respect to reproducibility, Ciphergen and Cromwell pre-processing are largely comparable. We find that the overlap between peaks detected by either Ciphergen ProteinChip Software or Cromwell is large. This is especially the case for the more stringent peak detection settings. Moreover, similarity of the estimated intensities between matched peaks is high. We evaluate the pre-processing methods using five different classification methods. Classification is done in a double cross-validation protocol using repeated random sampling to obtain an unbiased estimate of classification accuracy. No pre-processing method significantly outperforms the other for all peak detection settings evaluated. Conclusion We use classification of patient samples as a clinically relevant benchmark for the evaluation of pre-processing methods. Both pre-processing methods lead to similar classification results on an ovarian cancer and a Gaucher disease dataset. However, the settings for pre-processing

  14. Effects of Preprocessing on Multi-Direction Properties of Aluminum Alloy Cold-Spray Deposits

    Science.gov (United States)

    Rokni, M. R.; Nardi, A. T.; Champagne, V. K.; Nutt, S. R.

    2018-05-01

    The effects of powder preprocessing (degassing at 400 °C for 6 h) on microstructure and mechanical properties of 5056 aluminum deposits produced by high-pressure cold spray were investigated. To investigate directionality of the mechanical properties, microtensile coupons were excised from different directions of the deposit, i.e., longitudinal, short transverse, long transverse, and diagonal and then tested. The results were compared to properties of wrought 5056 and the coating deposited with as-received 5056 Al powder and correlated with the observed microstructures. Preprocessing softened the particles and eliminated the pores within them, resulting in more extensive and uniform deformation upon impact with the substrate and with underlying deposited material. Microstructural characterization and finite element simulation indicated that upon particle impact, the peripheral regions experienced more extensive deformation and higher temperatures than the central contact zone. This led to more recrystallization and stronger bonding at peripheral regions relative to the contact zone area and yielded superior properties in the longitudinal direction compared with the short transverse direction. Fractography revealed that crack propagation takes place along the particle-particle interfaces in the transverse directions (caused by insufficient bonding and recrystallization), whereas through the deposited particles, fracture is dominant in the longitudinal direction.

  15. A review of blood sample handling and pre-processing for metabolomics studies.

    Science.gov (United States)

    Hernandes, Vinicius Veri; Barbas, Coral; Dudzik, Danuta

    2017-09-01

    Metabolomics has been found to be applicable to a wide range of clinical studies, bringing a new era for improving clinical diagnostics, early disease detection, therapy prediction and treatment efficiency monitoring. A major challenge in metabolomics, particularly untargeted studies, is the extremely diverse and complex nature of biological specimens. Despite great advances in the field there still exist fundamental needs for considering pre-analytical variability that can introduce bias to the subsequent analytical process and decrease the reliability of the results and moreover confound final research outcomes. Many researchers are mainly focused on the instrumental aspects of the biomarker discovery process, and sample related variables sometimes seem to be overlooked. To bridge the gap, critical information and standardized protocols regarding experimental design and sample handling and pre-processing are highly desired. Characterization of a range variation among sample collection methods is necessary to prevent results misinterpretation and to ensure that observed differences are not due to an experimental bias caused by inconsistencies in sample processing. Herein, a systematic discussion of pre-analytical variables affecting metabolomics studies based on blood derived samples is performed. Furthermore, we provide a set of recommendations concerning experimental design, collection, pre-processing procedures and storage conditions as a practical review that can guide and serve for the standardization of protocols and reduction of undesirable variation. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  16. Influence of Averaging Preprocessing on Image Analysis with a Markov Random Field Model

    Science.gov (United States)

    Sakamoto, Hirotaka; Nakanishi-Ohno, Yoshinori; Okada, Masato

    2018-02-01

    This paper describes our investigations into the influence of averaging preprocessing on the performance of image analysis. Averaging preprocessing involves a trade-off: image averaging is often undertaken to reduce noise while the number of image data available for image analysis is decreased. We formulated a process of generating image data by using a Markov random field (MRF) model to achieve image analysis tasks such as image restoration and hyper-parameter estimation by a Bayesian approach. According to the notions of Bayesian inference, posterior distributions were analyzed to evaluate the influence of averaging. There are three main results. First, we found that the performance of image restoration with a predetermined value for hyper-parameters is invariant regardless of whether averaging is conducted. We then found that the performance of hyper-parameter estimation deteriorates due to averaging. Our analysis of the negative logarithm of the posterior probability, which is called the free energy based on an analogy with statistical mechanics, indicated that the confidence of hyper-parameter estimation remains higher without averaging. Finally, we found that when the hyper-parameters are estimated from the data, the performance of image restoration worsens as averaging is undertaken. We conclude that averaging adversely influences the performance of image analysis through hyper-parameter estimation.

  17. Statistical Downscaling Output GCM Modeling with Continuum Regression and Pre-Processing PCA Approach

    Directory of Open Access Journals (Sweden)

    Sutikno Sutikno

    2010-08-01

    Full Text Available One of the climate models used to predict the climatic conditions is Global Circulation Models (GCM. GCM is a computer-based model that consists of different equations. It uses numerical and deterministic equation which follows the physics rules. GCM is a main tool to predict climate and weather, also it uses as primary information source to review the climate change effect. Statistical Downscaling (SD technique is used to bridge the large-scale GCM with a small scale (the study area. GCM data is spatial and temporal data most likely to occur where the spatial correlation between different data on the grid in a single domain. Multicollinearity problems require the need for pre-processing of variable data X. Continuum Regression (CR and pre-processing with Principal Component Analysis (PCA methods is an alternative to SD modelling. CR is one method which was developed by Stone and Brooks (1990. This method is a generalization from Ordinary Least Square (OLS, Principal Component Regression (PCR and Partial Least Square method (PLS methods, used to overcome multicollinearity problems. Data processing for the station in Ambon, Pontianak, Losarang, Indramayu and Yuntinyuat show that the RMSEP values and R2 predict in the domain 8x8 and 12x12 by uses CR method produces results better than by PCR and PLS.

  18. Automated pre-processing and multivariate vibrational spectra analysis software for rapid results in clinical settings

    Science.gov (United States)

    Bhattacharjee, T.; Kumar, P.; Fillipe, L.

    2018-02-01

    Vibrational spectroscopy, especially FTIR and Raman, has shown enormous potential in disease diagnosis, especially in cancers. Their potential for detecting varied pathological conditions are regularly reported. However, to prove their applicability in clinics, large multi-center multi-national studies need to be undertaken; and these will result in enormous amount of data. A parallel effort to develop analytical methods, including user-friendly software that can quickly pre-process data and subject them to required multivariate analysis is warranted in order to obtain results in real time. This study reports a MATLAB based script that can automatically import data, preprocess spectra— interpolation, derivatives, normalization, and then carry out Principal Component Analysis (PCA) followed by Linear Discriminant Analysis (LDA) of the first 10 PCs; all with a single click. The software has been verified on data obtained from cell lines, animal models, and in vivo patient datasets, and gives results comparable to Minitab 16 software. The software can be used to import variety of file extensions, asc, .txt., .xls, and many others. Options to ignore noisy data, plot all possible graphs with PCA factors 1 to 5, and save loading factors, confusion matrices and other parameters are also present. The software can provide results for a dataset of 300 spectra within 0.01 s. We believe that the software will be vital not only in clinical trials using vibrational spectroscopic data, but also to obtain rapid results when these tools get translated into clinics.

  19. 3-D image pre-processing algorithms for improved automated tracing of neuronal arbors.

    Science.gov (United States)

    Narayanaswamy, Arunachalam; Wang, Yu; Roysam, Badrinath

    2011-09-01

    The accuracy and reliability of automated neurite tracing systems is ultimately limited by image quality as reflected in the signal-to-noise ratio, contrast, and image variability. This paper describes a novel combination of image processing methods that operate on images of neurites captured by confocal and widefield microscopy, and produce synthetic images that are better suited to automated tracing. The algorithms are based on the curvelet transform (for denoising curvilinear structures and local orientation estimation), perceptual grouping by scalar voting (for elimination of non-tubular structures and improvement of neurite continuity while preserving branch points), adaptive focus detection, and depth estimation (for handling widefield images without deconvolution). The proposed methods are fast, and capable of handling large images. Their ability to handle images of unlimited size derives from automated tiling of large images along the lateral dimension, and processing of 3-D images one optical slice at a time. Their speed derives in part from the fact that the core computations are formulated in terms of the Fast Fourier Transform (FFT), and in part from parallel computation on multi-core computers. The methods are simple to apply to new images since they require very few adjustable parameters, all of which are intuitive. Examples of pre-processing DIADEM Challenge images are used to illustrate improved automated tracing resulting from our pre-processing methods.

  20. Safe and sensible preprocessing and baseline correction of pupil-size data.

    Science.gov (United States)

    Mathôt, Sebastiaan; Fabius, Jasper; Van Heusden, Elle; Van der Stigchel, Stefan

    2018-02-01

    Measurement of pupil size (pupillometry) has recently gained renewed interest from psychologists, but there is little agreement on how pupil-size data is best analyzed. Here we focus on one aspect of pupillometric analyses: baseline correction, i.e., analyzing changes in pupil size relative to a baseline period. Baseline correction is useful in experiments that investigate the effect of some experimental manipulation on pupil size. In such experiments, baseline correction improves statistical power by taking into account random fluctuations in pupil size over time. However, we show that baseline correction can also distort data if unrealistically small pupil sizes are recorded during the baseline period, which can easily occur due to eye blinks, data loss, or other distortions. Divisive baseline correction (corrected pupil size = pupil size/baseline) is affected more strongly by such distortions than subtractive baseline correction (corrected pupil size = pupil size - baseline). We discuss the role of baseline correction as a part of preprocessing of pupillometric data, and make five recommendations: (1) before baseline correction, perform data preprocessing to mark missing and invalid data, but assume that some distortions will remain in the data; (2) use subtractive baseline correction; (3) visually compare your corrected and uncorrected data; (4) be wary of pupil-size effects that emerge faster than the latency of the pupillary response allows (within ±220 ms after the manipulation that induces the effect); and (5) remove trials on which baseline pupil size is unrealistically small (indicative of blinks and other distortions).

  1. THE IMAGE REGISTRATION OF FOURIER-MELLIN BASED ON THE COMBINATION OF PROJECTION AND GRADIENT PREPROCESSING

    Directory of Open Access Journals (Sweden)

    D. Gao

    2017-09-01

    Full Text Available Image registration is one of the most important applications in the field of image processing. The method of Fourier Merlin transform, which has the advantages of high precision and good robustness to change in light and shade, partial blocking, noise influence and so on, is widely used. However, not only this method can’t obtain the unique mutual power pulse function for non-parallel image pairs, even part of image pairs also can’t get the mutual power function pulse. In this paper, an image registration method based on Fourier-Mellin transformation in the view of projection-gradient preprocessing is proposed. According to the projection conformational equation, the method calculates the matrix of image projection transformation to correct the tilt image; then, gradient preprocessing and Fourier-Mellin transformation are performed on the corrected image to obtain the registration parameters. Eventually, the experiment results show that the method makes the image registration of Fourier-Mellin transformation not only applicable to the registration of the parallel image pairs, but also to the registration of non-parallel image pairs. What’s more, the better registration effect can be obtained

  2. Applying Enhancement Filters in the Pre-processing of Images of Lymphoma

    International Nuclear Information System (INIS)

    Silva, Sérgio Henrique; Do Nascimento, Marcelo Zanchetta; Neves, Leandro Alves; Batista, Valério Ramos

    2015-01-01

    Lymphoma is a type of cancer that affects the immune system, and is classified as Hodgkin or non-Hodgkin. It is one of the ten types of cancer that are the most common on earth. Among all malignant neoplasms diagnosed in the world, lymphoma ranges from three to four percent of them. Our work presents a study of some filters devoted to enhancing images of lymphoma at the pre-processing step. Here the enhancement is useful for removing noise from the digital images. We have analysed the noise caused by different sources like room vibration, scraps and defocusing, and in the following classes of lymphoma: follicular, mantle cell and B-cell chronic lymphocytic leukemia. The filters Gaussian, Median and Mean-Shift were applied to different colour models (RGB, Lab and HSV). Afterwards, we performed a quantitative analysis of the images by means of the Structural Similarity Index. This was done in order to evaluate the similarity between the images. In all cases we have obtained a certainty of at least 75%, which rises to 99% if one considers only HSV. Namely, we have concluded that HSV is an important choice of colour model at pre-processing histological images of lymphoma, because in this case the resulting image will get the best enhancement

  3. Automated cleaning and pre-processing of immunoglobulin gene sequences from high-throughput sequencing

    Directory of Open Access Journals (Sweden)

    Miri eMichaeli

    2012-12-01

    Full Text Available High throughput sequencing (HTS yields tens of thousands to millions of sequences that require a large amount of pre-processing work to clean various artifacts. Such cleaning cannot be performed manually. Existing programs are not suitable for immunoglobulin (Ig genes, which are variable and often highly mutated. This paper describes Ig-HTS-Cleaner (Ig High Throughput Sequencing Cleaner, a program containing a simple cleaning procedure that successfully deals with pre-processing of Ig sequences derived from HTS, and Ig-Indel-Identifier (Ig Insertion – Deletion Identifier, a program for identifying legitimate and artifact insertions and/or deletions (indels. Our programs were designed for analyzing Ig gene sequences obtained by 454 sequencing, but they are applicable to all types of sequences and sequencing platforms. Ig-HTS-Cleaner and Ig-Indel-Identifier have been implemented in Java and saved as executable JAR files, supported on Linux and MS Windows. No special requirements are needed in order to run the programs, except for correctly constructing the input files as explained in the text. The programs' performance has been tested and validated on real and simulated data sets.

  4. A Technical Review on Biomass Processing: Densification, Preprocessing, Modeling and Optimization

    Energy Technology Data Exchange (ETDEWEB)

    Jaya Shankar Tumuluru; Christopher T. Wright

    2010-06-01

    It is now a well-acclaimed fact that burning fossil fuels and deforestation are major contributors to climate change. Biomass from plants can serve as an alternative renewable and carbon-neutral raw material for the production of bioenergy. Low densities of 40–60 kg/m3 for lignocellulosic and 200–400 kg/m3 for woody biomass limits their application for energy purposes. Prior to use in energy applications these materials need to be densified. The densified biomass can have bulk densities over 10 times the raw material helping to significantly reduce technical limitations associated with storage, loading and transportation. Pelleting, briquetting, or extrusion processing are commonly used methods for densification. The aim of the present research is to develop a comprehensive review of biomass processing that includes densification, preprocessing, modeling and optimization. The specific objective include carrying out a technical review on (a) mechanisms of particle bonding during densification; (b) methods of densification including extrusion, briquetting, pelleting, and agglomeration; (c) effects of process and feedstock variables and biomass biochemical composition on the densification (d) effects of preprocessing such as grinding, preheating, steam explosion, and torrefaction on biomass quality and binding characteristics; (e) models for understanding the compression characteristics; and (f) procedures for response surface modeling and optimization.

  5. Preprocessing of A-scan GPR data based on energy features

    Science.gov (United States)

    Dogan, Mesut; Turhan-Sayan, Gonul

    2016-05-01

    There is an increasing demand for noninvasive real-time detection and classification of buried objects in various civil and military applications. The problem of detection and annihilation of landmines is particularly important due to strong safety concerns. The requirement for a fast real-time decision process is as important as the requirements for high detection rates and low false alarm rates. In this paper, we introduce and demonstrate a computationally simple, timeefficient, energy-based preprocessing approach that can be used in ground penetrating radar (GPR) applications to eliminate reflections from the air-ground boundary and to locate the buried objects, simultaneously, at one easy step. The instantaneous power signals, the total energy values and the cumulative energy curves are extracted from the A-scan GPR data. The cumulative energy curves, in particular, are shown to be useful to detect the presence and location of buried objects in a fast and simple way while preserving the spectral content of the original A-scan data for further steps of physics-based target classification. The proposed method is demonstrated using the GPR data collected at the facilities of IPA Defense, Ankara at outdoor test lanes. Cylindrically shaped plastic containers were buried in fine-medium sand to simulate buried landmines. These plastic containers were half-filled by ammonium nitrate including metal pins. Results of this pilot study are demonstrated to be highly promising to motivate further research for the use of energy-based preprocessing features in landmine detection problem.

  6. Change detection using landsat time series: A review of frequencies, preprocessing, algorithms, and applications

    Science.gov (United States)

    Zhu, Zhe

    2017-08-01

    The free and open access to all archived Landsat images in 2008 has completely changed the way of using Landsat data. Many novel change detection algorithms based on Landsat time series have been developed We present a comprehensive review of four important aspects of change detection studies based on Landsat time series, including frequencies, preprocessing, algorithms, and applications. We observed the trend that the more recent the study, the higher the frequency of Landsat time series used. We reviewed a series of image preprocessing steps, including atmospheric correction, cloud and cloud shadow detection, and composite/fusion/metrics techniques. We divided all change detection algorithms into six categories, including thresholding, differencing, segmentation, trajectory classification, statistical boundary, and regression. Within each category, six major characteristics of different algorithms, such as frequency, change index, univariate/multivariate, online/offline, abrupt/gradual change, and sub-pixel/pixel/spatial were analyzed. Moreover, some of the widely-used change detection algorithms were also discussed. Finally, we reviewed different change detection applications by dividing these applications into two categories, change target and change agent detection.

  7. The effects of pre-processing strategies in sentiment analysis of online movie reviews

    Science.gov (United States)

    Zin, Harnani Mat; Mustapha, Norwati; Murad, Masrah Azrifah Azmi; Sharef, Nurfadhlina Mohd

    2017-10-01

    With the ever increasing of internet applications and social networking sites, people nowadays can easily express their feelings towards any products and services. These online reviews act as an important source for further analysis and improved decision making. These reviews are mostly unstructured by nature and thus, need processing like sentiment analysis and classification to provide a meaningful information for future uses. In text analysis tasks, the appropriate selection of words/features will have a huge impact on the effectiveness of the classifier. Thus, this paper explores the effect of the pre-processing strategies in the sentiment analysis of online movie reviews. In this paper, supervised machine learning method was used to classify the reviews. The support vector machine (SVM) with linear and non-linear kernel has been considered as classifier for the classification of the reviews. The performance of the classifier is critically examined based on the results of precision, recall, f-measure, and accuracy. Two different features representations were used which are term frequency and term frequency-inverse document frequency. Results show that the pre-processing strategies give a significant impact on the classification process.

  8. Data Acquisition and Preprocessing in Studies on Humans: What Is Not Taught in Statistics Classes?

    Science.gov (United States)

    Zhu, Yeyi; Hernandez, Ladia M; Mueller, Peter; Dong, Yongquan; Forman, Michele R

    2013-01-01

    The aim of this paper is to address issues in research that may be missing from statistics classes and important for (bio-)statistics students. In the context of a case study, we discuss data acquisition and preprocessing steps that fill the gap between research questions posed by subject matter scientists and statistical methodology for formal inference. Issues include participant recruitment, data collection training and standardization, variable coding, data review and verification, data cleaning and editing, and documentation. Despite the critical importance of these details in research, most of these issues are rarely discussed in an applied statistics program. One reason for the lack of more formal training is the difficulty in addressing the many challenges that can possibly arise in the course of a study in a systematic way. This article can help to bridge this gap between research questions and formal statistical inference by using an illustrative case study for a discussion. We hope that reading and discussing this paper and practicing data preprocessing exercises will sensitize statistics students to these important issues and achieve optimal conduct, quality control, analysis, and interpretation of a study.

  9. Comparison of planar images and SPECT with bayesean preprocessing for the demonstration of facial anatomy and craniomandibular disorders

    International Nuclear Information System (INIS)

    Kircos, L.T.; Ortendahl, D.A.; Hattner, R.S.; Faulkner, D.; Taylor, R.L.

    1984-01-01

    Craniomandiublar disorders involving the facial anatomy may be difficult to demonstrate in planar images. Although bone scanning is generally more sensitive than radiography, facial bone anatomy is complex and focal areas of increased or decreased radiotracer may become obscured by overlapping structures in planar images. Thus SPECT appears ideally suited to examination of the facial skeleton. A series of patients with craniomandibular disorders of unknown origin were imaged using 20 mCi Tc-99m MDP. Planar and SPECT (Siemens 7500 ZLC Orbiter) images were obtained four hours after injection. The SPECT images were reconstructed with a filtered back-projection algorithm. In order to improve image contrast and resolution in SPECT images, the rotation views were pre-processed with a Bayesean deblurring algorithm which has previously been show to offer improved contrast and resolution in planar images. SPECT images using the pre-processed rotation views were obtained and compared to the SPECT images without pre-processing and the planar images. TMJ arthropathy involving either the glenoid fossa or the mandibular condyle, orthopedic changes involving the mandible or maxilla, localized dental pathosis, as well as changes in structures peripheral to the facial skeleton were identified. Bayesean pre-processed SPECT depicted the facial skeleton more clearly as well as providing a more obvious demonstration of the bony changes associated with craniomandibular disorders than either planar images or SPECT without pre-processing

  10. Nuclear data for fusion: Validation of typical pre-processing methods for radiation transport calculations

    International Nuclear Information System (INIS)

    Hutton, T.; Sublet, J.C.; Morgan, L.; Leadbeater, T.W.

    2015-01-01

    Highlights: • We quantify the effect of processing nuclear data from ENDF to ACE format. • We consider the differences between fission and fusion angular distributions. • C-nat(n,el) at 2.0 MeV has a 0.6% deviation between original and processed data. • Fe-56(n,el) at 14.1 MeV has a 11.0% deviation between original and processed data. • Processed data do not accurately depict ENDF distributions for fusion energies. - Abstract: Nuclear data form the basis of the radiation transport codes used to design and simulate the behaviour of nuclear facilities, such as the ITER and DEMO fusion reactors. Typically these data and codes are biased towards fission and high-energy physics applications yet are still applied to fusion problems. With increasing interest in fusion applications, the lack of fusion specific codes and relevant data libraries is becoming increasingly apparent. Industry standard radiation transport codes require pre-processing of the evaluated data libraries prior to use in simulation. Historically these methods focus on speed of simulation at the cost of accurate data representation. For legacy applications this has not been a major concern, but current fusion needs differ significantly. Pre-processing reconstructs the differential and double differential interaction cross sections with a coarse binned structure, or more recently as a tabulated cumulative distribution function. This work looks at the validity of applying these processing methods to data used in fusion specific calculations in comparison to fission. The relative effects of applying this pre-processing mechanism, to both fission and fusion relevant reaction channels are demonstrated, and as such the poor representation of these distributions for the fusion energy regime. For the nat C(n,el) reaction at 2.0 MeV, the binned differential cross section deviates from the original data by 0.6% on average. For the 56 Fe(n,el) reaction at 14.1 MeV, the deviation increases to 11.0%. We

  11. Bayesian Optimization for Neuroimaging Pre-processing in Brain Age Classification and Prediction

    Directory of Open Access Journals (Sweden)

    Jenessa Lancaster

    2018-02-01

    Full Text Available Neuroimaging-based age prediction using machine learning is proposed as a biomarker of brain aging, relating to cognitive performance, health outcomes and progression of neurodegenerative disease. However, even leading age-prediction algorithms contain measurement error, motivating efforts to improve experimental pipelines. T1-weighted MRI is commonly used for age prediction, and the pre-processing of these scans involves normalization to a common template and resampling to a common voxel size, followed by spatial smoothing. Resampling parameters are often selected arbitrarily. Here, we sought to improve brain-age prediction accuracy by optimizing resampling parameters using Bayesian optimization. Using data on N = 2003 healthy individuals (aged 16–90 years we trained support vector machines to (i distinguish between young (<22 years and old (>50 years brains (classification and (ii predict chronological age (regression. We also evaluated generalisability of the age-regression model to an independent dataset (CamCAN, N = 648, aged 18–88 years. Bayesian optimization was used to identify optimal voxel size and smoothing kernel size for each task. This procedure adaptively samples the parameter space to evaluate accuracy across a range of possible parameters, using independent sub-samples to iteratively assess different parameter combinations to arrive at optimal values. When distinguishing between young and old brains a classification accuracy of 88.1% was achieved, (optimal voxel size = 11.5 mm3, smoothing kernel = 2.3 mm. For predicting chronological age, a mean absolute error (MAE of 5.08 years was achieved, (optimal voxel size = 3.73 mm3, smoothing kernel = 3.68 mm. This was compared to performance using default values of 1.5 mm3 and 4mm respectively, resulting in MAE = 5.48 years, though this 7.3% improvement was not statistically significant. When assessing generalisability, best performance was achieved when applying the entire Bayesian

  12. A simpler method of preprocessing MALDI-TOF MS data for differential biomarker analysis: stem cell and melanoma cancer studies

    Directory of Open Access Journals (Sweden)

    Tong Dong L

    2011-09-01

    Full Text Available Abstract Introduction Raw spectral data from matrix-assisted laser desorption/ionisation time-of-flight (MALDI-TOF with MS profiling techniques usually contains complex information not readily providing biological insight into disease. The association of identified features within raw data to a known peptide is extremely difficult. Data preprocessing to remove uncertainty characteristics in the data is normally required before performing any further analysis. This study proposes an alternative yet simple solution to preprocess raw MALDI-TOF-MS data for identification of candidate marker ions. Two in-house MALDI-TOF-MS data sets from two different sample sources (melanoma serum and cord blood plasma are used in our study. Method Raw MS spectral profiles were preprocessed using the proposed approach to identify peak regions in the spectra. The preprocessed data was then analysed using bespoke machine learning algorithms for data reduction and ion selection. Using the selected ions, an ANN-based predictive model was constructed to examine the predictive power of these ions for classification. Results Our model identified 10 candidate marker ions for both data sets. These ion panels achieved over 90% classification accuracy on blind validation data. Receiver operating characteristics analysis was performed and the area under the curve for melanoma and cord blood classifiers was 0.991 and 0.986, respectively. Conclusion The results suggest that our data preprocessing technique removes unwanted characteristics of the raw data, while preserving the predictive components of the data. Ion identification analysis can be carried out using MALDI-TOF-MS data with the proposed data preprocessing technique coupled with bespoke algorithms for data reduction and ion selection.

  13. Evaluation of the robustness of the preprocessing technique improving reversible compressibility of CT images: Tested on various CT examinations

    Energy Technology Data Exchange (ETDEWEB)

    Jeon, Chang Ho; Kim, Bohyoung; Gu, Bon Seung; Lee, Jong Min [Department of Radiology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, 300 Gumi-ro, Bundang-gu, Seongnam-si, Gyeonggi-do 463-707 (Korea, Republic of); Kim, Kil Joong [Department of Radiology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, 300 Gumi-ro, Bundang-gu, Seongnam-si, Gyeonggi-do 463-707, South Korea and Department of Radiation Applied Life Science, Seoul National University College of Medicine, 103 Daehak-ro, Jongno-gu, Seoul 110-799 (Korea, Republic of); Lee, Kyoung Ho [Department of Radiology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, 300 Gumi-ro, Bundang-gu, Seongnam-si, Gyeonggi-do 463-707, South Korea and Institute of Radiation Medicine, Seoul National University Medical Research Center, and Clinical Research Institute, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul 110-744 (Korea, Republic of); Kim, Tae Ki [Medical Information Center, Seoul National University Bundang Hospital, Seoul National University College of Medicine, 300 Gumi-ro, Bundang-gu, Seongnam-si, Gyeonggi-do 463-707 (Korea, Republic of)

    2013-10-15

    Purpose: To modify the preprocessing technique, which was previously proposed, improving compressibility of computed tomography (CT) images to cover the diversity of three dimensional configurations of different body parts and to evaluate the robustness of the technique in terms of segmentation correctness and increase in reversible compression ratio (CR) for various CT examinations.Methods: This study had institutional review board approval with waiver of informed patient consent. A preprocessing technique was previously proposed to improve the compressibility of CT images by replacing pixel values outside the body region with a constant value resulting in maximizing data redundancy. Since the technique was developed aiming at only chest CT images, the authors modified the segmentation method to cover the diversity of three dimensional configurations of different body parts. The modified version was evaluated as follows. In randomly selected 368 CT examinations (352 787 images), each image was preprocessed by using the modified preprocessing technique. Radiologists visually confirmed whether the segmented region covers the body region or not. The images with and without the preprocessing were reversibly compressed using Joint Photographic Experts Group (JPEG), JPEG2000 two-dimensional (2D), and JPEG2000 three-dimensional (3D) compressions. The percentage increase in CR per examination (CR{sub I}) was measured.Results: The rate of correct segmentation was 100.0% (95% CI: 99.9%, 100.0%) for all the examinations. The median of CR{sub I} were 26.1% (95% CI: 24.9%, 27.1%), 40.2% (38.5%, 41.1%), and 34.5% (32.7%, 36.2%) in JPEG, JPEG2000 2D, and JPEG2000 3D, respectively.Conclusions: In various CT examinations, the modified preprocessing technique can increase in the CR by 25% or more without concerning about degradation of diagnostic information.

  14. Image Processing of Welding Procedure Specification and Pre-process program development for Finite Element Modelling

    International Nuclear Information System (INIS)

    Kim, K. S.; Lee, H. J.

    2009-11-01

    PRE-WELD program, which generates automatically the input file for the finite element analysis on the 2D butt welding at the dissimilar metal weld part, was developed. This program is pre-process program of the FEM code for analyzing the residual stress at the welding parts. Even if the users have not the detail knowledge for the FEM modelling, the users can make the ABAQUS INPUT easily by inputting the shape data of welding part, the weld current and voltage of welding parameters. By using PRE-WELD program, we can save the time and the effort greatly for preparing the ABAQUS INPUT for the residual stress analysis at the welding parts, and make the exact input without the human error

  15. Joint preprocesser-based detector for cooperative networks with limited hardware processing capability

    KAUST Repository

    Abuzaid, Abdulrahman I.

    2015-02-01

    In this letter, a joint detector for cooperative communication networks is proposed when the destination has limited hardware processing capability. The transmitter sends its symbols with the help of L relays. As the destination has limited hardware, only U out of L signals are processed and the energy of the remaining relays is lost. To solve this problem, a joint preprocessing based detector is proposed. This joint preprocessor based detector operate on the principles of minimizing the symbol error rate (SER). For a realistic assessment, pilot symbol aided channel estimation is incorporated for this proposed detector. From our simulations, it can be observed that our proposed detector achieves the same SER performance as that of the maximum likelihood (ML) detector with all participating relays. Additionally, our detector outperforms selection combining (SC), channel shortening (CS) scheme and reduced-rank techniques when using the same U. Our proposed scheme has low computational complexity.

  16. Flexible high-speed FASTBUS master for data read-out and preprocessing

    International Nuclear Information System (INIS)

    Wurz, A.; Manner, R.

    1990-01-01

    This paper describes a single slot FASTBUS master module. It can be used for read-out and preprocessing of data that are read out from FASTBUS modules, e.g., and ADC system. The module consists of a 25 MHz, 32-bit processor MC 68030 with cache memory and memory management, a floating point coprocessor MC68882, 4 MBytes of main memory, and FASTBUS master and slave interfaces. In addition, a DMA controller for read-out of FASTBUS data is provided. The processor allows I/O via serial ports, a 16-bit parallel port, and a transputer link. Additional interfaces are planned. The main memory is multi-ported and can be accessed directly by the CPU, the FASTBUS, and external masters via the high-speed local bus that is accessible by way of a connector. The FASTBUS interface supports most of the standard operations in master and slave mode

  17. Combined principal component preprocessing and n-tuple neural networks for improved classification

    DEFF Research Database (Denmark)

    Høskuldsson, Agnar; Linneberg, Christian

    2000-01-01

    We present a combined principal component analysis/neural network scheme for classification. The data used to illustrate the method consist of spectral fluorescence recordings from seven different production facilities, and the task is to relate an unknown sample to one of these seven factories....... The data are first preprocessed by performing an individual principal component analysis on each of the seven groups of data. The components found are then used for classifying the data, but instead of making a single multiclass classifier, we follow the ideas of turning a multiclass problem into a number...... of two-class problems. For each possible pair of classes we further apply a transformation to the calculated principal components in order to increase the separation between the classes. Finally we apply the so-called n-tuple neural network to the transformed data in order to give the classification...

  18. Image preprocessing for improving computational efficiency in implementation of restoration and superresolution algorithms.

    Science.gov (United States)

    Sundareshan, Malur K; Bhattacharjee, Supratik; Inampudi, Radhika; Pang, Ho-Yuen

    2002-12-10

    Computational complexity is a major impediment to the real-time implementation of image restoration and superresolution algorithms in many applications. Although powerful restoration algorithms have been developed within the past few years utilizing sophisticated mathematical machinery (based on statistical optimization and convex set theory), these algorithms are typically iterative in nature and require a sufficient number of iterations to be executed to achieve the desired resolution improvement that may be needed to meaningfully perform postprocessing image exploitation tasks in practice. Additionally, recent technological breakthroughs have facilitated novel sensor designs (focal plane arrays, for instance) that make it possible to capture megapixel imagery data at video frame rates. A major challenge in the processing of these large-format images is to complete the execution of the image processing steps within the frame capture times and to keep up with the output rate of the sensor so that all data captured by the sensor can be efficiently utilized. Consequently, development of novel methods that facilitate real-time implementation of image restoration and superresolution algorithms is of significant practical interest and is the primary focus of this study. The key to designing computationally efficient processing schemes lies in strategically introducing appropriate preprocessing steps together with the superresolution iterations to tailor optimized overall processing sequences for imagery data of specific formats. For substantiating this assertion, three distinct methods for tailoring a preprocessing filter and integrating it with the superresolution processing steps are outlined. These methods consist of a region-of-interest extraction scheme, a background-detail separation procedure, and a scene-derived information extraction step for implementing a set-theoretic restoration of the image that is less demanding in computation compared with the

  19. A base composition analysis of natural patterns for the preprocessing of metagenome sequences.

    Science.gov (United States)

    Bonham-Carter, Oliver; Ali, Hesham; Bastola, Dhundy

    2013-01-01

    On the pretext that sequence reads and contigs often exhibit the same kinds of base usage that is also observed in the sequences from which they are derived, we offer a base composition analysis tool. Our tool uses these natural patterns to determine relatedness across sequence data. We introduce spectrum sets (sets of motifs) which are permutations of bacterial restriction sites and the base composition analysis framework to measure their proportional content in sequence data. We suggest that this framework will increase the efficiency during the pre-processing stages of metagenome sequencing and assembly projects. Our method is able to differentiate organisms and their reads or contigs. The framework shows how to successfully determine the relatedness between these reads or contigs by comparison of base composition. In particular, we show that two types of organismal-sequence data are fundamentally different by analyzing their spectrum set motif proportions (coverage). By the application of one of the four possible spectrum sets, encompassing all known restriction sites, we provide the evidence to claim that each set has a different ability to differentiate sequence data. Furthermore, we show that the spectrum set selection having relevance to one organism, but not to the others of the data set, will greatly improve performance of sequence differentiation even if the fragment size of the read, contig or sequence is not lengthy. We show the proof of concept of our method by its application to ten trials of two or three freshly selected sequence fragments (reads and contigs) for each experiment across the six organisms of our set. Here we describe a novel and computationally effective pre-processing step for metagenome sequencing and assembly tasks. Furthermore, our base composition method has applications in phylogeny where it can be used to infer evolutionary distances between organisms based on the notion that related organisms often have much conserved code.

  20. chipPCR: an R package to pre-process raw data of amplification curves.

    Science.gov (United States)

    Rödiger, Stefan; Burdukiewicz, Michał; Schierack, Peter

    2015-09-01

    Both the quantitative real-time polymerase chain reaction (qPCR) and quantitative isothermal amplification (qIA) are standard methods for nucleic acid quantification. Numerous real-time read-out technologies have been developed. Despite the continuous interest in amplification-based techniques, there are only few tools for pre-processing of amplification data. However, a transparent tool for precise control of raw data is indispensable in several scenarios, for example, during the development of new instruments. chipPCR is an R: package for the pre-processing and quality analysis of raw data of amplification curves. The package takes advantage of R: 's S4 object model and offers an extensible environment. chipPCR contains tools for raw data exploration: normalization, baselining, imputation of missing values, a powerful wrapper for amplification curve smoothing and a function to detect the start and end of an amplification curve. The capabilities of the software are enhanced by the implementation of algorithms unavailable in R: , such as a 5-point stencil for derivative interpolation. Simulation tools, statistical tests, plots for data quality management, amplification efficiency/quantification cycle calculation, and datasets from qPCR and qIA experiments are part of the package. Core functionalities are integrated in GUIs (web-based and standalone shiny applications), thus streamlining analysis and report generation. http://cran.r-project.org/web/packages/chipPCR. Source code: https://github.com/michbur/chipPCR. stefan.roediger@b-tu.de Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  1. The Evaluation of Preprocessing Choices in Single-Subject BOLD fMRI Using NPAIRS Performance Metrics

    DEFF Research Database (Denmark)

    Stephen, LaConte; Rottenberg, David; Strother, Stephen

    2003-01-01

    to obtain cross-validation-based model performance estimates of prediction accuracy and global reproducibility for various degrees of model complexity. We rely on the concept of an analysis chain meta-model in which all parameters of the preprocessing steps along with the final statistical model are treated...

  2. The recursive combination filter approach of pre-processing for the estimation of standard deviation of RR series.

    Science.gov (United States)

    Mishra, Alok; Swati, D

    2015-09-01

    Variation in the interval between the R-R peaks of the electrocardiogram represents the modulation of the cardiac oscillations by the autonomic nervous system. This variation is contaminated by anomalous signals called ectopic beats, artefacts or noise which mask the true behaviour of heart rate variability. In this paper, we have proposed a combination filter of recursive impulse rejection filter and recursive 20% filter, with recursive application and preference of replacement over removal of abnormal beats to improve the pre-processing of the inter-beat intervals. We have tested this novel recursive combinational method with median method replacement to estimate the standard deviation of normal to normal (SDNN) beat intervals of congestive heart failure (CHF) and normal sinus rhythm subjects. This work discusses the improvement in pre-processing over single use of impulse rejection filter and removal of abnormal beats for heart rate variability for the estimation of SDNN and Poncaré plot descriptors (SD1, SD2, and SD1/SD2) in detail. We have found the 22 ms value of SDNN and 36 ms value of SD2 descriptor of Poincaré plot as clinical indicators in discriminating the normal cases from CHF cases. The pre-processing is also useful in calculation of Lyapunov exponent which is a nonlinear index as Lyapunov exponents calculated after proposed pre-processing modified in a way that it start following the notion of less complex behaviour of diseased states.

  3. Preprocessing of 18F-DMFP-PET Data Based on Hidden Markov Random Fields and the Gaussian Distribution

    Directory of Open Access Journals (Sweden)

    Fermín Segovia

    2017-10-01

    Full Text Available 18F-DMFP-PET is an emerging neuroimaging modality used to diagnose Parkinson's disease (PD that allows us to examine postsynaptic dopamine D2/3 receptors. Like other neuroimaging modalities used for PD diagnosis, most of the total intensity of 18F-DMFP-PET images is concentrated in the striatum. However, other regions can also be useful for diagnostic purposes. An appropriate delimitation of the regions of interest contained in 18F-DMFP-PET data is crucial to improve the automatic diagnosis of PD. In this manuscript we propose a novel methodology to preprocess 18F-DMFP-PET data that improves the accuracy of computer aided diagnosis systems for PD. First, the data were segmented using an algorithm based on Hidden Markov Random Field. As a result, each neuroimage was divided into 4 maps according to the intensity and the neighborhood of the voxels. The maps were then individually normalized so that the shape of their histograms could be modeled by a Gaussian distribution with equal parameters for all the neuroimages. This approach was evaluated using a dataset with neuroimaging data from 87 parkinsonian patients. After these preprocessing steps, a Support Vector Machine classifier was used to separate idiopathic and non-idiopathic PD. Data preprocessed by the proposed method provided higher accuracy results than the ones preprocessed with previous approaches.

  4. On image pre-processing for PIV of sinlge- and two-phase flows over reflecting objects

    NARCIS (Netherlands)

    Deen, N.G.; Willems, P.; van Sint Annaland, M.; Kuipers, J.A.M.; Lammertink, Rob G.H.; Kemperman, Antonius J.B.; Wessling, Matthias; van der Meer, Walterus Gijsbertus Joseph

    2010-01-01

    A novel image pre-processing scheme for PIV of single- and two-phase flows over reflecting objects which does not require the use of additional hardware is discussed. The approach for single-phase flow consists of image normalization and intensity stretching followed by background subtraction. For

  5. Conversation on data mining strategies in LC-MS untargeted metabolomics: pre-processing and pre-treatment steps

    CSIR Research Space (South Africa)

    Tugizimana, F

    2016-11-01

    Full Text Available -MS)-based untargeted metabolomic dataset, this study explored the influence of collection parameters in the data pre-processing step, scaling and data transformation on the statistical models generated, and feature selection, thereafter. Data obtained in positive mode...

  6. CudaPre3D: An Alternative Preprocessing Algorithm for Accelerating 3D Convex Hull Computation on the GPU

    Directory of Open Access Journals (Sweden)

    MEI, G.

    2015-05-01

    Full Text Available In the calculating of convex hulls for point sets, a preprocessing procedure that is to filter the input points by discarding non-extreme points is commonly used to improve the computational efficiency. We previously proposed a quite straightforward preprocessing approach for accelerating 2D convex hull computation on the GPU. In this paper, we extend that algorithm to being used in 3D cases. The basic ideas behind these two preprocessing algorithms are similar: first, several groups of extreme points are found according to the original set of input points and several rotated versions of the input set; then, a convex polyhedron is created using the found extreme points; and finally those interior points locating inside the formed convex polyhedron are discarded. Experimental results show that: when employing the proposed preprocessing algorithm, it achieves the speedups of about 4x on average and 5x to 6x in the best cases over the cases where the proposed approach is not used. In addition, more than 95 percent of the input points can be discarded in most experimental tests.

  7. Acquiring and preprocessing leaf images for automated plant identification: understanding the tradeoff between effort and information gain

    Directory of Open Access Journals (Sweden)

    Michael Rzanny

    2017-11-01

    Full Text Available Abstract Background Automated species identification is a long term research subject. Contrary to flowers and fruits, leaves are available throughout most of the year. Offering margin and texture to characterize a species, they are the most studied organ for automated identification. Substantially matured machine learning techniques generate the need for more training data (aka leaf images. Researchers as well as enthusiasts miss guidance on how to acquire suitable training images in an efficient way. Methods In this paper, we systematically study nine image types and three preprocessing strategies. Image types vary in terms of in-situ image recording conditions: perspective, illumination, and background, while the preprocessing strategies compare non-preprocessed, cropped, and segmented images to each other. Per image type-preprocessing combination, we also quantify the manual effort required for their implementation. We extract image features using a convolutional neural network, classify species using the resulting feature vectors and discuss classification accuracy in relation to the required effort per combination. Results The most effective, non-destructive way to record herbaceous leaves is to take an image of the leaf’s top side. We yield the highest classification accuracy using destructive back light images, i.e., holding the plucked leaf against the sky for image acquisition. Cropping the image to the leaf’s boundary substantially improves accuracy, while precise segmentation yields similar accuracy at a substantially higher effort. The permanent use or disuse of a flash light has negligible effects. Imaging the typically stronger textured backside of a leaf does not result in higher accuracy, but notably increases the acquisition cost. Conclusions In conclusion, the way in which leaf images are acquired and preprocessed does have a substantial effect on the accuracy of the classifier trained on them. For the first time, this

  8. Scientific data products and the data pre-processing subsystem of the Chang'e-3 mission

    International Nuclear Information System (INIS)

    Tan Xu; Liu Jian-Jun; Li Chun-Lai; Feng Jian-Qing; Ren Xin; Wang Fen-Fei; Yan Wei; Zuo Wei; Wang Xiao-Qian; Zhang Zhou-Bin

    2014-01-01

    The Chang'e-3 (CE-3) mission is China's first exploration mission on the surface of the Moon that uses a lander and a rover. Eight instruments that form the scientific payloads have the following objectives: (1) investigate the morphological features and geological structures at the landing site; (2) integrated in-situ analysis of minerals and chemical compositions; (3) integrated exploration of the structure of the lunar interior; (4) exploration of the lunar-terrestrial space environment, lunar surface environment and acquire Moon-based ultraviolet astronomical observations. The Ground Research and Application System (GRAS) is in charge of data acquisition and pre-processing, management of the payload in orbit, and managing the data products and their applications. The Data Pre-processing Subsystem (DPS) is a part of GRAS. The task of DPS is the pre-processing of raw data from the eight instruments that are part of CE-3, including channel processing, unpacking, package sorting, calibration and correction, identification of geographical location, calculation of probe azimuth angle, probe zenith angle, solar azimuth angle, and solar zenith angle and so on, and conducting quality checks. These processes produce Level 0, Level 1 and Level 2 data. The computing platform of this subsystem is comprised of a high-performance computing cluster, including a real-time subsystem used for processing Level 0 data and a post-time subsystem for generating Level 1 and Level 2 data. This paper describes the CE-3 data pre-processing method, the data pre-processing subsystem, data classification, data validity and data products that are used for scientific studies

  9. Automatic pre-processing for an object-oriented distributed hydrological model using GRASS-GIS

    Science.gov (United States)

    Sanzana, P.; Jankowfsky, S.; Branger, F.; Braud, I.; Vargas, X.; Hitschfeld, N.

    2012-04-01

    Landscapes are very heterogeneous, which impact the hydrological processes occurring in the catchments, especially in the modeling of peri-urban catchments. The Hydrological Response Units (HRUs), resulting from the intersection of different maps, such as land use, soil types and geology, and flow networks, allow the representation of these elements in an explicit way, preserving natural and artificial contours of the different layers. These HRUs are used as model mesh in some distributed object-oriented hydrological models, allowing the application of a topological oriented approach. The connectivity between polygons and polylines provides a detailed representation of the water balance and overland flow in these distributed hydrological models, based on irregular hydro-landscape units. When computing fluxes between these HRUs, the geometrical parameters, such as the distance between the centroid of gravity of the HRUs and the river network, and the length of the perimeter, can impact the realism of the calculated overland, sub-surface and groundwater fluxes. Therefore, it is necessary to process the original model mesh in order to avoid these numerical problems. We present an automatic pre-processing implemented in the open source GRASS-GIS software, for which several Python scripts or some algorithms already available were used, such as the Triangle software. First, some scripts were developed to improve the topology of the various elements, such as snapping of the river network to the closest contours. When data are derived with remote sensing, such as vegetation areas, their perimeter has lots of right angles that were smoothed. Second, the algorithms more particularly address bad-shaped elements of the model mesh such as polygons with narrow shapes, marked irregular contours and/or the centroid outside of the polygons. To identify these elements we used shape descriptors. The convexity index was considered the best descriptor to identify them with a threshold

  10. Pre-processing, registration and selection of adaptive optics corrected retinal images.

    Science.gov (United States)

    Ramaswamy, Gomathy; Devaney, Nicholas

    2013-07-01

    In this paper, the aim is to demonstrate enhanced processing of sequences of fundus images obtained using a commercial AO flood illumination system. The purpose of the work is to (1) correct for uneven illumination at the retina (2) automatically select the best quality images and (3) precisely register the best images. Adaptive optics corrected retinal images are pre-processed to correct uneven illumination using different methods; subtracting or dividing by the average filtered image, homomorphic filtering and a wavelet based approach. These images are evaluated to measure the image quality using various parameters, including sharpness, variance, power spectrum kurtosis and contrast. We have carried out the registration in two stages; a coarse stage using cross-correlation followed by fine registration using two approaches; parabolic interpolation on the peak of the cross-correlation and maximum-likelihood estimation. The angle of rotation of the images is measured using a combination of peak tracking and Procrustes transformation. We have found that a wavelet approach (Daubechies 4 wavelet at 6th level decomposition) provides good illumination correction with clear improvement in image sharpness and contrast. The assessment of image quality using a 'Designer metric' works well when compared to visual evaluation, although it is highly correlated with other metrics. In image registration, sub-pixel translation measured using parabolic interpolation on the peak of the cross-correlation function and maximum-likelihood estimation are found to give very similar results (RMS difference 0.047 pixels). We have confirmed that correcting rotation of the images provides a significant improvement, especially at the edges of the image. We observed that selecting the better quality frames (e.g. best 75% images) for image registration gives improved resolution, at the expense of poorer signal-to-noise. The sharpness map of the registered and de-rotated images shows increased

  11. Tools and Databases of the KOMICS Web Portal for Preprocessing, Mining, and Dissemination of Metabolomics Data

    Directory of Open Access Journals (Sweden)

    Nozomu Sakurai

    2014-01-01

    Full Text Available A metabolome—the collection of comprehensive quantitative data on metabolites in an organism—has been increasingly utilized for applications such as data-intensive systems biology, disease diagnostics, biomarker discovery, and assessment of food quality. A considerable number of tools and databases have been developed to date for the analysis of data generated by various combinations of chromatography and mass spectrometry. We report here a web portal named KOMICS (The Kazusa Metabolomics Portal, where the tools and databases that we developed are available for free to academic users. KOMICS includes the tools and databases for preprocessing, mining, visualization, and publication of metabolomics data. Improvements in the annotation of unknown metabolites and dissemination of comprehensive metabolomic data are the primary aims behind the development of this portal. For this purpose, PowerGet and FragmentAlign include a manual curation function for the results of metabolite feature alignments. A metadata-specific wiki-based database, Metabolonote, functions as a hub of web resources related to the submitters' work. This feature is expected to increase citation of the submitters' work, thereby promoting data publication. As an example of the practical use of KOMICS, a workflow for a study on Jatropha curcas is presented. The tools and databases available at KOMICS should contribute to enhanced production, interpretation, and utilization of metabolomic Big Data.

  12. A new approach to pre-processing digital image for wavelet-based watermark

    Science.gov (United States)

    Agreste, Santa; Andaloro, Guido

    2008-11-01

    The growth of the Internet has increased the phenomenon of digital piracy, in multimedia objects, like software, image, video, audio and text. Therefore it is strategic to individualize and to develop methods and numerical algorithms, which are stable and have low computational cost, that will allow us to find a solution to these problems. We describe a digital watermarking algorithm for color image protection and authenticity: robust, not blind, and wavelet-based. The use of Discrete Wavelet Transform is motivated by good time-frequency features and a good match with Human Visual System directives. These two combined elements are important for building an invisible and robust watermark. Moreover our algorithm can work with any image, thanks to the step of pre-processing of the image that includes resize techniques that adapt to the size of the original image for Wavelet transform. The watermark signal is calculated in correlation with the image features and statistic properties. In the detection step we apply a re-synchronization between the original and watermarked image according to the Neyman-Pearson statistic criterion. Experimentation on a large set of different images has been shown to be resistant against geometric, filtering, and StirMark attacks with a low rate of false alarm.

  13. An Advanced Pre-Processing Pipeline to Improve Automated Photogrammetric Reconstructions of Architectural Scenes

    Directory of Open Access Journals (Sweden)

    Marco Gaiani

    2016-02-01

    Full Text Available Automated image-based 3D reconstruction methods are more and more flooding our 3D modeling applications. Fully automated solutions give the impression that from a sample of randomly acquired images we can derive quite impressive visual 3D models. Although the level of automation is reaching very high standards, image quality is a fundamental pre-requisite to produce successful and photo-realistic 3D products, in particular when dealing with large datasets of images. This article presents an efficient pipeline based on color enhancement, image denoising, color-to-gray conversion and image content enrichment. The pipeline stems from an analysis of various state-of-the-art algorithms and aims to adjust the most promising methods, giving solutions to typical failure causes. The assessment evaluation proves how an effective image pre-processing, which considers the entire image dataset, can improve the automated orientation procedure and dense 3D point cloud reconstruction, even in the case of poor texture scenarios.

  14. A comparative analysis of pre-processing techniques in colour retinal images

    International Nuclear Information System (INIS)

    Salvatelli, A; Bizai, G; Barbosa, G; Drozdowicz, B; Delrieux, C

    2007-01-01

    Diabetic retinopathy (DR) is a chronic disease of the ocular retina, which most of the times is only discovered when the disease is on an advanced stage and most of the damage is irreversible. For that reason, early diagnosis is paramount for avoiding the most severe consequences of the DR, of which complete blindness is not uncommon. Unsupervised or supervised image processing of retinal images emerges as a feasible tool for this diagnosis. The preprocessing stages are the key for any further assessment, since these images exhibit several defects, including non uniform illumination, sampling noise, uneven contrast due to pigmentation loss during sampling, and many others. Any feasible diagnosis system should work with images where these defects were compensated. In this work we analyze and test several correction techniques. Non uniform illumination is compensated using morphology and homomorphic filtering; uneven contrast is compensated using morphology and local enhancement. We tested our processing stages using Fuzzy C-Means, and local Hurst (self correlation) coefficient for unsupervised segmentation of the abnormal blood vessels. The results over a standard set of DR images are more than promising

  15. Voice preprocessing system incorporating a real-time spectrum analyzer with programmable switched-capacitor filters

    Science.gov (United States)

    Knapp, G.

    1984-01-01

    As part of a speaker verification program for BISS (Base Installation Security System), a test system is being designed with a flexible preprocessing system for the evaluation of voice spectrum/verification algorithm related problems. The main part of this report covers the design, construction, and testing of a voice analyzer with 16 integrating real-time frequency channels ranging from 300 Hz to 3 KHz. The bandpass filter response of each channel is programmable by NMOS switched capacitor quad filter arrays. Presently, the accuracy of these units is limited to a moderate precision by the finite steps of programming. However, repeatability of characteristics between filter units and sections seems to be excellent for the implemented fourth-order Butterworth bandpass responses. We obtained a 0.1 dB linearity error of signal detection and measured a signal-to-noise ratio of approximately 70 dB. The proprocessing system discussed includes preemphasis filter design, gain normalizer design, and data acquisition system design as well as test results.

  16. Robust preprocessing for stimulus-based functional MRI of the moving fetus.

    Science.gov (United States)

    You, Wonsang; Evangelou, Iordanis E; Zun, Zungho; Andescavage, Nickie; Limperopoulos, Catherine

    2016-04-01

    Fetal motion manifests as signal degradation and image artifact in the acquired time series of blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) studies. We present a robust preprocessing pipeline to specifically address fetal and placental motion-induced artifacts in stimulus-based fMRI with slowly cycled block design in the living fetus. In the proposed pipeline, motion correction is optimized to the experimental paradigm, and it is performed separately in each phase as well as in each region of interest (ROI), recognizing that each phase and organ experiences different types of motion. To obtain the averaged BOLD signals for each ROI, both misaligned volumes and noisy voxels are automatically detected and excluded, and the missing data are then imputed by statistical estimation based on local polynomial smoothing. Our experimental results demonstrate that the proposed pipeline was effective in mitigating the motion-induced artifacts in stimulus-based fMRI data of the fetal brain and placenta.

  17. The PREP Pipeline: Standardized preprocessing for large-scale EEG analysis

    Directory of Open Access Journals (Sweden)

    Nima eBigdelys Shamlo

    2015-06-01

    Full Text Available The technology to collect brain imaging and physiological measures has become portable and ubiquitous, opening the possibility of large-scale analysis of real-world human imaging. By its nature, such data is large and complex, making automated processing essential. This paper shows how lack of attention to the very early stages of an EEG preprocessing pipeline can reduce the signal-to-noise ratio and introduce unwanted artifacts into the data, particularly for computations done in single precision. We demonstrate that ordinary average referencing improves the signal-to-noise ratio, but that noisy channels can contaminate the results. We also show that identification of noisy channels depends on the reference and examine the complex interaction of filtering, noisy channel identification, and referencing. We introduce a multi-stage robust referencing scheme to deal with the noisy channel-reference interaction. We propose a standardized early-stage EEG processing pipeline (PREP and discuss the application of the pipeline to more than 600 EEG datasets. The pipeline includes an automatically generated report for each dataset processed. Users can download the PREP pipeline as a freely available MATLAB library from http://eegstudy.org/prepcode/.

  18. Improving the performance of streamflow forecasting model using data-preprocessing technique in Dungun River Basin

    Science.gov (United States)

    Khai Tiu, Ervin Shan; Huang, Yuk Feng; Ling, Lloyd

    2018-03-01

    An accurate streamflow forecasting model is important for the development of flood mitigation plan as to ensure sustainable development for a river basin. This study adopted Variational Mode Decomposition (VMD) data-preprocessing technique to process and denoise the rainfall data before putting into the Support Vector Machine (SVM) streamflow forecasting model in order to improve the performance of the selected model. Rainfall data and river water level data for the period of 1996-2016 were used for this purpose. Homogeneity tests (Standard Normal Homogeneity Test, the Buishand Range Test, the Pettitt Test and the Von Neumann Ratio Test) and normality tests (Shapiro-Wilk Test, Anderson-Darling Test, Lilliefors Test and Jarque-Bera Test) had been carried out on the rainfall series. Homogenous and non-normally distributed data were found in all the stations, respectively. From the recorded rainfall data, it was observed that Dungun River Basin possessed higher monthly rainfall from November to February, which was during the Northeast Monsoon. Thus, the monthly and seasonal rainfall series of this monsoon would be the main focus for this research as floods usually happen during the Northeast Monsoon period. The predicted water levels from SVM model were assessed with the observed water level using non-parametric statistical tests (Biased Method, Kendall's Tau B Test and Spearman's Rho Test).

  19. A data preprocessing strategy for metabolomics to reduce the mask effect in data analysis

    Directory of Open Access Journals (Sweden)

    Jun eYang

    2015-02-01

    Full Text Available Metabolomics is a booming research field. Its success highly relies on the discovery of differential metabolites by comparing different data sets (for example, patients vs. controls. One of the challenges is that differences of the low abundant metabolites between groups are often masked by the high variation of abundant metabolites -. In order to solve this challenge, a novel data preprocessing strategy consisting of 3 steps was proposed in this study. In step 1, a ‘modified 80%’ rule was used to reduce effect of missing values; in step 2, unit-variance and Pareto scaling methods were used to reduce the mask effect from the abundant metabolites. In step 3, in order to fix the adverse effect of scaling, stability information of the variables deduced from intensity information and the class information, was used to assign suitable weights to the variables. When applying to an LC/MS based metabolomics dataset from chronic hepatitis B patients study and two simulated datasets, the mask effect was found to be partially eliminated and several new low abundant differential metabolites were rescued.

  20. An Application for Data Preprocessing and Models Extractions in Web Usage Mining

    Directory of Open Access Journals (Sweden)

    Claudia Elena DINUCA

    2011-11-01

    Full Text Available Web servers worldwide generate a vast amount of information on web users’ browsing activities. Several researchers have studied these so-called clickstream or web access log data to better understand and characterize web users. The goal of this application is to analyze user behaviour by mining enriched web access log data. With the continued growth and proliferation of e-commerce, Web services, and Web-based information systems, the volumes of click stream and user data collected by Web-based organizations in their daily operations has reached astronomical proportions. This information can be exploited in various ways, such as enhancing the effectiveness of websites or developing directed web marketing campaigns. The discovered patterns are usually represented as collections of pages, objects, or re-sources that are frequently accessed by groups of users with common needs or interests. In this paper we will focus on displaying the way how it was implemented the application for data preprocessing and extracting different data models from web logs data, finding association as a data mining technique to extract potentially useful knowledge from web usage data. We find different data models navigation patterns by analysing the log files of the web-site. I implemented the application in Java using NetBeans IDE. For exemplification, I used the log files data from a commercial web site www.nice-layouts.com.

  1. A comparative analysis of pre-processing techniques in colour retinal images

    Energy Technology Data Exchange (ETDEWEB)

    Salvatelli, A [Artificial Intelligence Group, Facultad de Ingenieria, Universidad Nacional de Entre Rios (Argentina); Bizai, G [Artificial Intelligence Group, Facultad de Ingenieria, Universidad Nacional de Entre Rios (Argentina); Barbosa, G [Artificial Intelligence Group, Facultad de Ingenieria, Universidad Nacional de Entre Rios (Argentina); Drozdowicz, B [Artificial Intelligence Group, Facultad de Ingenieria, Universidad Nacional de Entre Rios (Argentina); Delrieux, C [Electric and Computing Engineering Department, Universidad Nacional del Sur, Alem 1253, BahIa Blanca, (Partially funded by SECyT-UNS) (Argentina)], E-mail: claudio@acm.org

    2007-11-15

    Diabetic retinopathy (DR) is a chronic disease of the ocular retina, which most of the times is only discovered when the disease is on an advanced stage and most of the damage is irreversible. For that reason, early diagnosis is paramount for avoiding the most severe consequences of the DR, of which complete blindness is not uncommon. Unsupervised or supervised image processing of retinal images emerges as a feasible tool for this diagnosis. The preprocessing stages are the key for any further assessment, since these images exhibit several defects, including non uniform illumination, sampling noise, uneven contrast due to pigmentation loss during sampling, and many others. Any feasible diagnosis system should work with images where these defects were compensated. In this work we analyze and test several correction techniques. Non uniform illumination is compensated using morphology and homomorphic filtering; uneven contrast is compensated using morphology and local enhancement. We tested our processing stages using Fuzzy C-Means, and local Hurst (self correlation) coefficient for unsupervised segmentation of the abnormal blood vessels. The results over a standard set of DR images are more than promising.

  2. Tools and databases of the KOMICS web portal for preprocessing, mining, and dissemination of metabolomics data.

    Science.gov (United States)

    Sakurai, Nozomu; Ara, Takeshi; Enomoto, Mitsuo; Motegi, Takeshi; Morishita, Yoshihiko; Kurabayashi, Atsushi; Iijima, Yoko; Ogata, Yoshiyuki; Nakajima, Daisuke; Suzuki, Hideyuki; Shibata, Daisuke

    2014-01-01

    A metabolome--the collection of comprehensive quantitative data on metabolites in an organism--has been increasingly utilized for applications such as data-intensive systems biology, disease diagnostics, biomarker discovery, and assessment of food quality. A considerable number of tools and databases have been developed to date for the analysis of data generated by various combinations of chromatography and mass spectrometry. We report here a web portal named KOMICS (The Kazusa Metabolomics Portal), where the tools and databases that we developed are available for free to academic users. KOMICS includes the tools and databases for preprocessing, mining, visualization, and publication of metabolomics data. Improvements in the annotation of unknown metabolites and dissemination of comprehensive metabolomic data are the primary aims behind the development of this portal. For this purpose, PowerGet and FragmentAlign include a manual curation function for the results of metabolite feature alignments. A metadata-specific wiki-based database, Metabolonote, functions as a hub of web resources related to the submitters' work. This feature is expected to increase citation of the submitters' work, thereby promoting data publication. As an example of the practical use of KOMICS, a workflow for a study on Jatropha curcas is presented. The tools and databases available at KOMICS should contribute to enhanced production, interpretation, and utilization of metabolomic Big Data.

  3. The PREP pipeline: standardized preprocessing for large-scale EEG analysis.

    Science.gov (United States)

    Bigdely-Shamlo, Nima; Mullen, Tim; Kothe, Christian; Su, Kyung-Min; Robbins, Kay A

    2015-01-01

    The technology to collect brain imaging and physiological measures has become portable and ubiquitous, opening the possibility of large-scale analysis of real-world human imaging. By its nature, such data is large and complex, making automated processing essential. This paper shows how lack of attention to the very early stages of an EEG preprocessing pipeline can reduce the signal-to-noise ratio and introduce unwanted artifacts into the data, particularly for computations done in single precision. We demonstrate that ordinary average referencing improves the signal-to-noise ratio, but that noisy channels can contaminate the results. We also show that identification of noisy channels depends on the reference and examine the complex interaction of filtering, noisy channel identification, and referencing. We introduce a multi-stage robust referencing scheme to deal with the noisy channel-reference interaction. We propose a standardized early-stage EEG processing pipeline (PREP) and discuss the application of the pipeline to more than 600 EEG datasets. The pipeline includes an automatically generated report for each dataset processed. Users can download the PREP pipeline as a freely available MATLAB library from http://eegstudy.org/prepcode.

  4. Constant time distance queries in planar unweighted graphs with subquadratic preprocessing time

    DEFF Research Database (Denmark)

    Wulff-Nilsen, C.

    2013-01-01

    Let G be an n-vertex planar, undirected, and unweighted graph. It was stated as open problems whether the Wiener index, defined as the sum of all-pairs shortest path distances, and the diameter of G can be computed in o(n(2)) time. We show that both problems can be solved in O(n(2) log log n/log n......) time with O(n) space. The techniques that we apply allow us to build, within the same time bound, an oracle for exact distance queries in G. More generally, for any parameter S is an element of [(log n/log log n)(2), n(2/5)], distance queries can be answered in O (root S log S/log n) time per query...... with O(n(2)/root S) preprocessing time and space requirement. With respect to running time, this is better than previous algorithms when log S = o(log n). All algorithms have linear space requirement. Our results generalize to a larger class of graphs including those with a fixed excluded minor. (C) 2012...

  5. Fast data preprocessing for chromatographic fingerprints of tomato cell wall polysaccharides using chemometric methods.

    Science.gov (United States)

    Quéméner, Bernard; Bertrand, Dominique; Marty, Isabelle; Causse, Mathilde; Lahaye, Marc

    2007-02-02

    The variability in the chemistry of cell wall polysaccharides in pericarp tissue of red-ripe tomato fruit (Solanum lycopersicon Mill.) was characterized by chemical methods and enzymatic degradations coupled to high performance anion exchange chromatography (HPAEC) and mass spectrometry analysis. Large fruited line, Levovil (LEV) carrying introgressed chromosome fragments from a cherry tomato line Cervil (CER) on chromosomes 4 (LC4), 9 (LC9), or on chromosomes 1, 2, 4 and 9 (LCX) and containing quantitative trait loci (QTLs) for texture traits, was studied. In order to differentiate cell wall polysaccharide modifications in the tomato fruit collection by multivariate analysis, chromatograms were corrected for baseline drift and shift of the component elution time using an approach derived from image analysis and mathematical morphology. The baseline was first corrected by using a "moving window" approach while the peak-matching method developed was based upon location of peaks as local maxima within a window of a definite size. The fast chromatographic data preprocessing proposed was a prerequisite for the different chemometric treatments, such as variance and principal component analysis applied herein to the analysis. Applied to the tomato collection, the combined enzymatic degradations and HPAEC analyses revealed that the firm LCX and CER genotypes showed a higher proportion of glucuronoxylans and pectic arabinan side chains while the mealy LC9 genotype demonstrated the highest content of pectic galactan side chains. QTLs on tomato chromosomes 1, 2, 4 and 9 contain important genes controlling glucuronoxylan and pectic neutral side chains biosynthesis and/or metabolism.

  6. Min st-cut oracle for planar graphs with near-linear preprocessing time

    DEFF Research Database (Denmark)

    Borradaile, Glencora; Sankowski, Piotr; Wulff-Nilsen, Christian

    2010-01-01

    For an undirected n-vertex planar graph G with non-negative edge-weights, we consider the following type of query: given two vertices s and t in G, what is the weight of a min st-cut in G? We show how to answer such queries in constant time with O(n log5 n) preprocessing time and O(n log n) space....... We use a Gomory-Hu tree to represent all the pairwise min st-cuts implicitly. Previously, no subquadratic time algorithm was known for this problem. Our oracle can be extended to report the min st-cuts in time proportional to their size. Since all-pairs min st-cut and the minimum cycle basis are dual...... problems in planar graphs, we also obtain an implicit representation of a minimum cycle basis in O(n log5 n) time and O(n log n) space and an explicit representation with additional O(C) time and space where C is the size of the basis. To obtain our results, we require that shortest paths be unique...

  7. lop-DWI: A Novel Scheme for Pre-Processing of Diffusion-Weighted Images in the Gradient Direction Domain.

    Science.gov (United States)

    Sepehrband, Farshid; Choupan, Jeiran; Caruyer, Emmanuel; Kurniawan, Nyoman D; Gal, Yaniv; Tieng, Quang M; McMahon, Katie L; Vegh, Viktor; Reutens, David C; Yang, Zhengyi

    2014-01-01

    We describe and evaluate a pre-processing method based on a periodic spiral sampling of diffusion-gradient directions for high angular resolution diffusion magnetic resonance imaging. Our pre-processing method incorporates prior knowledge about the acquired diffusion-weighted signal, facilitating noise reduction. Periodic spiral sampling of gradient direction encodings results in an acquired signal in each voxel that is pseudo-periodic with characteristics that allow separation of low-frequency signal from high frequency noise. Consequently, it enhances local reconstruction of the orientation distribution function used to define fiber tracks in the brain. Denoising with periodic spiral sampling was tested using synthetic data and in vivo human brain images. The level of improvement in signal-to-noise ratio and in the accuracy of local reconstruction of fiber tracks was significantly improved using our method.

  8. PRACTICAL RECOMMENDATIONS OF DATA PREPROCESSING AND GEOSPATIAL MEASURES FOR OPTIMIZING THE NEUROLOGICAL AND OTHER PEDIATRIC EMERGENCIES MANAGEMENT

    Directory of Open Access Journals (Sweden)

    Ionela MANIU

    2017-08-01

    Full Text Available Time management, optimal and timed determination of emergency severity as well as optimizing the use of available human and material resources are crucial areas of emergency services. A starting point for achieving these optimizations can be considered the analysis and preprocess of real data from the emergency services. The benefits of performing this method consist in exposing more useful structures to data modelling algorithms which consequently will reduce overfitting and improves accuracy. This paper aims to offer practical recommendations for data preprocessing measures including feature selection and discretization of numeric attributes regarding age, duration of the case, season, period, week period (workday, weekend and geospatial location of neurological and other pediatric emergencies. An analytical, retrospective study was conducted on a sample consisting of 933 pediatric cases, from UPU-SMURD Sibiu, 01.01.2014 – 27.02.2017 period.

  9. Novel low-power ultrasound digital preprocessing architecture for wireless display.

    Science.gov (United States)

    Levesque, Philippe; Sawan, Mohamad

    2010-03-01

    A complete hardware-based ultrasound preprocessing unit (PPU) is presented as an alternative to available power-hungry devices. Intended to expand the ultrasonic applications, the proposed unit allows replacement of the cable of the ultrasonic probe by a wireless link to transfer data from the probe to a remote monitor. The digital back-end architecture of this PPU is fully pipelined, which permits sampling of ultrasonic signals at a frequency equal to the field-programmable gate array-based system clock, up to 100 MHz. Experimental results show that the proposed processing unit has an excellent performance, an equivalent 53.15 Dhrystone 2.1 MIPS/ MHz (DMIPS/MHz), compared with other software-based architectures that allow a maximum of 1.6 DMIPS/MHz. In addition, an adaptive subsampling method is proposed to operate the pixel compressor, which allows real-time image zooming and, by removing high-frequency noise, the lateral and axial resolutions are enhanced by 25% and 33%, respectively. Realtime images, acquired from a reference phantom, validated the feasibility of the proposed architecture. For a display rate of 15 frames per second, and a 5-MHz single-element piezoelectric transducer, the proposed digital PPU requires a dynamic power of only 242 mW, which represents around 20% of the best-available software-based system. Furthermore, composed by the ultrasound processor and the image interpolation unit, the digital processing core of the PPU presents good power-performance ratios of 26 DMIPS/mW and 43.9 DMIPS/mW at a 20-MHz and 100-MHz sample frequency, respectively.

  10. Joint Preprocesser-Based Detectors for One-Way and Two-Way Cooperative Communication Networks

    KAUST Repository

    Abuzaid, Abdulrahman I.

    2014-05-01

    Efficient receiver designs for cooperative communication networks are becoming increasingly important. In previous work, cooperative networks communicated with the use of L relays. As the receiver is constrained, channel shortening and reduced-rank techniques were employed to design the preprocessing matrix that reduces the length of the received vector from L to U. In the first part of the work, a receiver structure is proposed which combines our proposed threshold selection criteria with the joint iterative optimization (JIO) algorithm that is based on the mean square error (MSE). Our receiver assists in determining the optimal U. Furthermore, this receiver provides the freedom to choose U for each frame depending on the tolerable difference allowed for MSE. Our study and simulation results show that by choosing an appropriate threshold, it is possible to gain in terms of complexity savings while having no or minimal effect on the BER performance of the system. Furthermore, the effect of channel estimation on the performance of the cooperative system is investigated. In the second part of the work, a joint preprocessor-based detector for cooperative communication networks is proposed for one-way and two-way relaying. This joint preprocessor-based detector operates on the principles of minimizing the symbol error rate (SER) instead of minimizing MSE. For a realistic assessment, pilot symbols are used to estimate the channel. From our simulations, it can be observed that our proposed detector achieves the same SER performance as that of the maximum likelihood (ML) detector with all participating relays. Additionally, our detector outperforms selection combining (SC), channel shortening (CS) scheme and reduced-rank techniques when using the same U. Finally, our proposed scheme has the lowest computational complexity.

  11. Hardware Design and Implementation of a Wavelet De-Noising Procedure for Medical Signal Preprocessing

    Directory of Open Access Journals (Sweden)

    Szi-Wen Chen

    2015-10-01

    Full Text Available In this paper, a discrete wavelet transform (DWT based de-noising with its applications into the noise reduction for medical signal preprocessing is introduced. This work focuses on the hardware realization of a real-time wavelet de-noising procedure. The proposed de-noising circuit mainly consists of three modules: a DWT, a thresholding, and an inverse DWT (IDWT modular circuits. We also proposed a novel adaptive thresholding scheme and incorporated it into our wavelet de-noising procedure. Performance was then evaluated on both the architectural designs of the software and. In addition, the de-noising circuit was also implemented by downloading the Verilog codes to a field programmable gate array (FPGA based platform so that its ability in noise reduction may be further validated in actual practice. Simulation experiment results produced by applying a set of simulated noise-contaminated electrocardiogram (ECG signals into the de-noising circuit showed that the circuit could not only desirably meet the requirement of real-time processing, but also achieve satisfactory performance for noise reduction, while the sharp features of the ECG signals can be well preserved. The proposed de-noising circuit was further synthesized using the Synopsys Design Compiler with an Artisan Taiwan Semiconductor Manufacturing Company (TSMC, Hsinchu, Taiwan 40 nm standard cell library. The integrated circuit (IC synthesis simulation results showed that the proposed design can achieve a clock frequency of 200 MHz and the power consumption was only 17.4 mW, when operated at 200 MHz.

  12. Hardware design and implementation of a wavelet de-noising procedure for medical signal preprocessing.

    Science.gov (United States)

    Chen, Szi-Wen; Chen, Yuan-Ho

    2015-10-16

    In this paper, a discrete wavelet transform (DWT) based de-noising with its applications into the noise reduction for medical signal preprocessing is introduced. This work focuses on the hardware realization of a real-time wavelet de-noising procedure. The proposed de-noising circuit mainly consists of three modules: a DWT, a thresholding, and an inverse DWT (IDWT) modular circuits. We also proposed a novel adaptive thresholding scheme and incorporated it into our wavelet de-noising procedure. Performance was then evaluated on both the architectural designs of the software and. In addition, the de-noising circuit was also implemented by downloading the Verilog codes to a field programmable gate array (FPGA) based platform so that its ability in noise reduction may be further validated in actual practice. Simulation experiment results produced by applying a set of simulated noise-contaminated electrocardiogram (ECG) signals into the de-noising circuit showed that the circuit could not only desirably meet the requirement of real-time processing, but also achieve satisfactory performance for noise reduction, while the sharp features of the ECG signals can be well preserved. The proposed de-noising circuit was further synthesized using the Synopsys Design Compiler with an Artisan Taiwan Semiconductor Manufacturing Company (TSMC, Hsinchu, Taiwan) 40 nm standard cell library. The integrated circuit (IC) synthesis simulation results showed that the proposed design can achieve a clock frequency of 200 MHz and the power consumption was only 17.4 mW, when operated at 200 MHz.

  13. Preprocessing of gravity gradients at the GOCE high-level processing facility

    Science.gov (United States)

    Bouman, Johannes; Rispens, Sietse; Gruber, Thomas; Koop, Radboud; Schrama, Ernst; Visser, Pieter; Tscherning, Carl Christian; Veicherts, Martin

    2009-07-01

    One of the products derived from the gravity field and steady-state ocean circulation explorer (GOCE) observations are the gravity gradients. These gravity gradients are provided in the gradiometer reference frame (GRF) and are calibrated in-flight using satellite shaking and star sensor data. To use these gravity gradients for application in Earth scienes and gravity field analysis, additional preprocessing needs to be done, including corrections for temporal gravity field signals to isolate the static gravity field part, screening for outliers, calibration by comparison with existing external gravity field information and error assessment. The temporal gravity gradient corrections consist of tidal and nontidal corrections. These are all generally below the gravity gradient error level, which is predicted to show a 1/ f behaviour for low frequencies. In the outlier detection, the 1/ f error is compensated for by subtracting a local median from the data, while the data error is assessed using the median absolute deviation. The local median acts as a high-pass filter and it is robust as is the median absolute deviation. Three different methods have been implemented for the calibration of the gravity gradients. All three methods use a high-pass filter to compensate for the 1/ f gravity gradient error. The baseline method uses state-of-the-art global gravity field models and the most accurate results are obtained if star sensor misalignments are estimated along with the calibration parameters. A second calibration method uses GOCE GPS data to estimate a low-degree gravity field model as well as gravity gradient scale factors. Both methods allow to estimate gravity gradient scale factors down to the 10-3 level. The third calibration method uses high accurate terrestrial gravity data in selected regions to validate the gravity gradient scale factors, focussing on the measurement band. Gravity gradient scale factors may be estimated down to the 10-2 level with this

  14. Impact of functional MRI data preprocessing pipeline on default-mode network detectability in patients with disorders of consciousness

    Directory of Open Access Journals (Sweden)

    Adrian eAndronache

    2013-08-01

    Full Text Available An emerging application of resting-state functional MRI is the study of patients with disorders of consciousness (DoC, where integrity of default-mode network (DMN activity is associated to the clinical level of preservation of consciousness. Due to the inherent inability to follow verbal instructions, arousal induced by scanning noise and postural pain, these patients tend to exhibit substantial levels of movement. This results in spurious, non-neural fluctuations of the blood-oxygen level-dependent (BOLD signal, which impair the evaluation of residual functional connectivity. Here, the effect of data preprocessing choices on the detectability of the DMN was systematically evaluated in a representative cohort of 30 clinically and etiologically heterogeneous DoC patients and 33 healthy controls. Starting from a standard preprocessing pipeline, additional steps were gradually inserted, namely band-pass filtering, removal of co-variance with the movement vectors, removal of co-variance with the global brain parenchyma signal, rejection of realignment outlier volumes and ventricle masking. Both independent-component analysis (ICA and seed-based analysis (SBA were performed, and DMN detectability was assessed quantitatively as well as visually. The results of the present study strongly show that the detection of DMN activity in the sub-optimal fMRI series acquired on DoC patients is contingent on the use of adequate filtering steps. ICA and SBA are differently affected but give convergent findings for high-grade preprocessing. We propose that future studies in this area should adopt the described preprocessing procedures as a minimum standard to reduce the probability of wrongly inferring that DMN activity is absent.

  15. Integrated fMRI Preprocessing Framework Using Extended Kalman Filter for Estimation of Slice-Wise Motion

    OpenAIRE

    Basile Pinsard; Basile Pinsard; Basile Pinsard; Arnaud Boutin; Arnaud Boutin; Julien Doyon; Julien Doyon; Habib Benali; Habib Benali; Habib Benali

    2018-01-01

    Functional MRI acquisition is sensitive to subjects' motion that cannot be fully constrained. Therefore, signal corrections have to be applied a posteriori in order to mitigate the complex interactions between changing tissue localization and magnetic fields, gradients and readouts. To circumvent current preprocessing strategies limitations, we developed an integrated method that correct motion and spatial low-frequency intensity fluctuations at the level of each slice in order to better fit ...

  16. TargetSearch - a Bioconductor package for the efficient preprocessing of GC-MS metabolite profiling data

    Science.gov (United States)

    2009-01-01

    Background Metabolite profiling, the simultaneous quantification of multiple metabolites in an experiment, is becoming increasingly popular, particularly with the rise of systems-level biology. The workhorse in this field is gas-chromatography hyphenated with mass spectrometry (GC-MS). The high-throughput of this technology coupled with a demand for large experiments has led to data pre-processing, i.e. the quantification of metabolites across samples, becoming a major bottleneck. Existing software has several limitations, including restricted maximum sample size, systematic errors and low flexibility. However, the biggest limitation is that the resulting data usually require extensive hand-curation, which is subjective and can typically take several days to weeks. Results We introduce the TargetSearch package, an open source tool which is a flexible and accurate method for pre-processing even very large numbers of GC-MS samples within hours. We developed a novel strategy to iteratively correct and update retention time indices for searching and identifying metabolites. The package is written in the R programming language with computationally intensive functions written in C for speed and performance. The package includes a graphical user interface to allow easy use by those unfamiliar with R. Conclusions TargetSearch allows fast and accurate data pre-processing for GC-MS experiments and overcomes the sample number limitations and manual curation requirements of existing software. We validate our method by carrying out an analysis against both a set of known chemical standard mixtures and of a biological experiment. In addition we demonstrate its capabilities and speed by comparing it with other GC-MS pre-processing tools. We believe this package will greatly ease current bottlenecks and facilitate the analysis of metabolic profiling data. PMID:20015393

  17. TargetSearch - a Bioconductor package for the efficient preprocessing of GC-MS metabolite profiling data

    Directory of Open Access Journals (Sweden)

    Lisec Jan

    2009-12-01

    Full Text Available Abstract Background Metabolite profiling, the simultaneous quantification of multiple metabolites in an experiment, is becoming increasingly popular, particularly with the rise of systems-level biology. The workhorse in this field is gas-chromatography hyphenated with mass spectrometry (GC-MS. The high-throughput of this technology coupled with a demand for large experiments has led to data pre-processing, i.e. the quantification of metabolites across samples, becoming a major bottleneck. Existing software has several limitations, including restricted maximum sample size, systematic errors and low flexibility. However, the biggest limitation is that the resulting data usually require extensive hand-curation, which is subjective and can typically take several days to weeks. Results We introduce the TargetSearch package, an open source tool which is a flexible and accurate method for pre-processing even very large numbers of GC-MS samples within hours. We developed a novel strategy to iteratively correct and update retention time indices for searching and identifying metabolites. The package is written in the R programming language with computationally intensive functions written in C for speed and performance. The package includes a graphical user interface to allow easy use by those unfamiliar with R. Conclusions TargetSearch allows fast and accurate data pre-processing for GC-MS experiments and overcomes the sample number limitations and manual curation requirements of existing software. We validate our method by carrying out an analysis against both a set of known chemical standard mixtures and of a biological experiment. In addition we demonstrate its capabilities and speed by comparing it with other GC-MS pre-processing tools. We believe this package will greatly ease current bottlenecks and facilitate the analysis of metabolic profiling data.

  18. TargetSearch--a Bioconductor package for the efficient preprocessing of GC-MS metabolite profiling data.

    Science.gov (United States)

    Cuadros-Inostroza, Alvaro; Caldana, Camila; Redestig, Henning; Kusano, Miyako; Lisec, Jan; Peña-Cortés, Hugo; Willmitzer, Lothar; Hannah, Matthew A

    2009-12-16

    Metabolite profiling, the simultaneous quantification of multiple metabolites in an experiment, is becoming increasingly popular, particularly with the rise of systems-level biology. The workhorse in this field is gas-chromatography hyphenated with mass spectrometry (GC-MS). The high-throughput of this technology coupled with a demand for large experiments has led to data pre-processing, i.e. the quantification of metabolites across samples, becoming a major bottleneck. Existing software has several limitations, including restricted maximum sample size, systematic errors and low flexibility. However, the biggest limitation is that the resulting data usually require extensive hand-curation, which is subjective and can typically take several days to weeks. We introduce the TargetSearch package, an open source tool which is a flexible and accurate method for pre-processing even very large numbers of GC-MS samples within hours. We developed a novel strategy to iteratively correct and update retention time indices for searching and identifying metabolites. The package is written in the R programming language with computationally intensive functions written in C for speed and performance. The package includes a graphical user interface to allow easy use by those unfamiliar with R. TargetSearch allows fast and accurate data pre-processing for GC-MS experiments and overcomes the sample number limitations and manual curation requirements of existing software. We validate our method by carrying out an analysis against both a set of known chemical standard mixtures and of a biological experiment. In addition we demonstrate its capabilities and speed by comparing it with other GC-MS pre-processing tools. We believe this package will greatly ease current bottlenecks and facilitate the analysis of metabolic profiling data.

  19. THE EFFECT OF DECOMPOSITION METHOD AS DATA PREPROCESSING ON NEURAL NETWORKS MODEL FOR FORECASTING TREND AND SEASONAL TIME SERIES

    Directory of Open Access Journals (Sweden)

    Subanar Subanar

    2006-01-01

    Full Text Available Recently, one of the central topics for the neural networks (NN community is the issue of data preprocessing on the use of NN. In this paper, we will investigate this topic particularly on the effect of Decomposition method as data processing and the use of NN for modeling effectively time series with both trend and seasonal patterns. Limited empirical studies on seasonal time series forecasting with neural networks show that some find neural networks are able to model seasonality directly and prior deseasonalization is not necessary, and others conclude just the opposite. In this research, we study particularly on the effectiveness of data preprocessing, including detrending and deseasonalization by applying Decomposition method on NN modeling and forecasting performance. We use two kinds of data, simulation and real data. Simulation data are examined on multiplicative of trend and seasonality patterns. The results are compared to those obtained from the classical time series model. Our result shows that a combination of detrending and deseasonalization by applying Decomposition method is the effective data preprocessing on the use of NN for forecasting trend and seasonal time series.

  20. Performance Comparison of Several Pre-Processing Methods in a Hand Gesture Recognition System based on Nearest Neighbor for Different Background Conditions

    Directory of Open Access Journals (Sweden)

    Iwan Setyawan

    2012-12-01

    Full Text Available This paper presents a performance analysis and comparison of several pre-processing methods used in a hand gesture recognition system. The pre-processing methods are based on the combinations of several image processing operations, namely edge detection, low pass filtering, histogram equalization, thresholding and desaturation. The hand gesture recognition system is designed to classify an input image into one of six possible classes. The input images are taken with various background conditions. Our experiments showed that the best result is achieved when the pre-processing method consists of only a desaturation operation, achieving a classification accuracy of up to 83.15%.

  1. A Conversation on Data Mining Strategies in LC-MS Untargeted Metabolomics: Pre-Processing and Pre-Treatment Steps

    Directory of Open Access Journals (Sweden)

    Fidele Tugizimana

    2016-11-01

    Full Text Available Untargeted metabolomic studies generate information-rich, high-dimensional, and complex datasets that remain challenging to handle and fully exploit. Despite the remarkable progress in the development of tools and algorithms, the “exhaustive” extraction of information from these metabolomic datasets is still a non-trivial undertaking. A conversation on data mining strategies for a maximal information extraction from metabolomic data is needed. Using a liquid chromatography-mass spectrometry (LC-MS-based untargeted metabolomic dataset, this study explored the influence of collection parameters in the data pre-processing step, scaling and data transformation on the statistical models generated, and feature selection, thereafter. Data obtained in positive mode generated from a LC-MS-based untargeted metabolomic study (sorghum plants responding dynamically to infection by a fungal pathogen were used. Raw data were pre-processed with MarkerLynxTM software (Waters Corporation, Manchester, UK. Here, two parameters were varied: the intensity threshold (50–100 counts and the mass tolerance (0.005–0.01 Da. After the pre-processing, the datasets were imported into SIMCA (Umetrics, Umea, Sweden for more data cleaning and statistical modeling. In addition, different scaling (unit variance, Pareto, etc. and data transformation (log and power methods were explored. The results showed that the pre-processing parameters (or algorithms influence the output dataset with regard to the number of defined features. Furthermore, the study demonstrates that the pre-treatment of data prior to statistical modeling affects the subspace approximation outcome: e.g., the amount of variation in X-data that the model can explain and predict. The pre-processing and pre-treatment steps subsequently influence the number of statistically significant extracted/selected features (variables. Thus, as informed by the results, to maximize the value of untargeted metabolomic data

  2. A Probabilistic Approach to Network Event Formation from Pre-Processed Waveform Data

    Science.gov (United States)

    Kohl, B. C.; Given, J.

    2017-12-01

    The current state of the art for seismic event detection still largely depends on signal detection at individual sensor stations, including picking accurate arrivals times and correctly identifying phases, and relying on fusion algorithms to associate individual signal detections to form event hypotheses. But increasing computational capability has enabled progress toward the objective of fully utilizing body-wave recordings in an integrated manner to detect events without the necessity of previously recorded ground truth events. In 2011-2012 Leidos (then SAIC) operated a seismic network to monitor activity associated with geothermal field operations in western Nevada. We developed a new association approach for detecting and quantifying events by probabilistically combining pre-processed waveform data to deal with noisy data and clutter at local distance ranges. The ProbDet algorithm maps continuous waveform data into continuous conditional probability traces using a source model (e.g. Brune earthquake or Mueller-Murphy explosion) to map frequency content and an attenuation model to map amplitudes. Event detection and classification is accomplished by combining the conditional probabilities from the entire network using a Bayesian formulation. This approach was successful in producing a high-Pd, low-Pfa automated bulletin for a local network and preliminary tests with regional and teleseismic data show that it has promise for global seismic and nuclear monitoring applications. The approach highlights several features that we believe are essential to achieving low-threshold automated event detection: Minimizes the utilization of individual seismic phase detections - in traditional techniques, errors in signal detection, timing, feature measurement and initial phase ID compound and propagate into errors in event formation, Has a formalized framework that utilizes information from non-detecting stations, Has a formalized framework that utilizes source information, in

  3. PreP+07: improvements of a user friendly tool to preprocess and analyse microarray data

    Directory of Open Access Journals (Sweden)

    Claros M Gonzalo

    2009-01-01

    Full Text Available Abstract Background Nowadays, microarray gene expression analysis is a widely used technology that scientists handle but whose final interpretation usually requires the participation of a specialist. The need for this participation is due to the requirement of some background in statistics that most users lack or have a very vague notion of. Moreover, programming skills could also be essential to analyse these data. An interactive, easy to use application seems therefore necessary to help researchers to extract full information from data and analyse them in a simple, powerful and confident way. Results PreP+07 is a standalone Windows XP application that presents a friendly interface for spot filtration, inter- and intra-slide normalization, duplicate resolution, dye-swapping, error removal and statistical analyses. Additionally, it contains two unique implementation of the procedures – double scan and Supervised Lowess-, a complete set of graphical representations – MA plot, RG plot, QQ plot, PP plot, PN plot – and can deal with many data formats, such as tabulated text, GenePix GPR and ArrayPRO. PreP+07 performance has been compared with the equivalent functions in Bioconductor using a tomato chip with 13056 spots. The number of differentially expressed genes considering p-values coming from the PreP+07 and Bioconductor Limma packages were statistically identical when the data set was only normalized; however, a slight variability was appreciated when the data was both normalized and scaled. Conclusion PreP+07 implementation provides a high degree of freedom in selecting and organizing a small set of widely used data processing protocols, and can handle many data formats. Its reliability has been proven so that a laboratory researcher can afford a statistical pre-processing of his/her microarray results and obtain a list of differentially expressed genes using PreP+07 without any programming skills. All of this gives support to scientists

  4. Stack Characterization in CryoSat Level1b SAR/SARin Baseline C

    Science.gov (United States)

    Scagliola, Michele; Fornari, Marco; Di Giacinto, Andrea; Bouffard, Jerome; Féménias, Pierre; Parrinello, Tommaso

    2015-04-01

    CryoSat was launched on the 8th April 2010 and is the first European ice mission dedicated to the monitoring of precise changes in the thickness of polar ice sheets and floating sea ice. CryoSat is the first altimetry mission operating in SAR mode and it carries an innovative radar altimeter called the Synthetic Aperture Interferometric Altimeter (SIRAL), that transmits pulses at a high pulse repetition frequency thus making the received echoes phase coherent and suitable for azimuth processing. The current CryoSat IPF (Instrument Processing Facility), Baseline B, was released in operation in February 2012. After more than 2 years of development, the release in operations of the Baseline C is expected in the first half of 2015. It is worth recalling here that the CryoSat SAR/SARin IPF1 generates 20Hz waveforms in correspondence of an approximately equally spaced set of ground locations on the Earth surface, i.e. surface samples, and that a surface sample gathers a collection of single-look echoes coming from the processed bursts during the time of visibility. Thus, for a given surface sample, the stack can be defined as the collection of all the single-look echoes pointing to the current surface sample, after applying all the necessary range corrections. The L1B product contains the power average of all the single-look echoes in the stack: the multi-looked L1B waveform. This reduces the data volume, while removing some information contained in the single looks, useful for characterizing the surface and modelling the L1B waveform. To recover such information, a set of parameters has been added to the L1B product: the stack characterization or beam behaviour parameters. The stack characterization, already included in previous Baselines, has been reviewed and expanded in Baseline C. This poster describes all the stack characterization parameters, detailing what they represent and how they have been computed. In details, such parameters can be summarized in: - Stack statistical parameters, such as skewness and kurtosis - Look angle (i.e. the angle at which the surfaces sample is seen with respect to the nadir direction of the satellite) and Doppler angle (i.e. the angle at which the surfaces sample is seen with respect to the normal to the velocity vector) for the first and the last single-look echoes in the stack. - Number of single-looks averaged in the stack (in Baseline C a stack-weighting has been applied that reduces the number of looks). With the correct use of these parameters, users will be able to retrieve some of the 'lost' information contained within the stack and fully exploit the L1B product.

  5. AIRS/Aqua Level 1B HSB geolocated and calibrated brightness temperatures V005

    Data.gov (United States)

    National Aeronautics and Space Administration — The Atmospheric Infrared Sounder (AIRS) is a facility instrument aboard the second Earth Observing System (EOS) polar-orbiting platform, EOS Aqua. In combination...

  6. NOAA GOES-R Series Advanced Baseline Imager (ABI) Level 1b Radiances

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Advanced Baseline Imager (ABI) instrument samples the radiance of the Earth in sixteen spectral bands using several arrays of detectors in the instrument’s...

  7. AIRS/Aqua Level 1B Infrared (IR) quality assurance subset V005

    Data.gov (United States)

    National Aeronautics and Space Administration — The Atmospheric Infrared Sounder (AIRS) is a facility instrument aboard the second Earth Observing System (EOS) polar-orbiting platform, EOS Aqua. In combination...

  8. The Python Spectral Analysis Tool (PySAT) for Powerful, Flexible, and Easy Preprocessing and Machine Learning with Point Spectral Data

    Science.gov (United States)

    Anderson, R. B.; Finch, N.; Clegg, S. M.; Graff, T.; Morris, R. V.; Laura, J.

    2018-04-01

    The PySAT point spectra tool provides a flexible graphical interface, enabling scientists to apply a wide variety of preprocessing and machine learning methods to point spectral data, with an emphasis on multivariate regression.

  9. Status of pre-processing of waste electrical and electronic equipment in Germany and its influence on the recovery of gold.

    Science.gov (United States)

    Chancerel, Perrine; Bolland, Til; Rotter, Vera Susanne

    2011-03-01

    Waste electrical and electronic equipment (WEEE) contains gold in low but from an environmental and economic point of view relevant concentration. After collection, WEEE is pre-processed in order to generate appropriate material fractions that are sent to the subsequent end-processing stages (recovery, reuse or disposal). The goal of this research is to quantify the overall recovery rates of pre-processing technologies used in Germany for the reference year 2007. To achieve this goal, facilities operating in Germany were listed and classified according to the technology they apply. Information on their processing capacity was gathered by evaluating statistical databases. Based on a literature review of experimental results for gold recovery rates of different pre-processing technologies, the German overall recovery rate of gold at the pre-processing level was quantified depending on the characteristics of the treated WEEE. The results reveal that - depending on the equipment groups - pre-processing recovery rates of gold of 29 to 61% are achieved in Germany. Some practical recommendations to reduce the losses during pre-processing could be formulated. Defining mass-based recovery targets in the legislation does not set incentives to recover trace elements. Instead, the priorities for recycling could be defined based on other parameters like the environmental impacts of the materials. The implementation of measures to reduce the gold losses would also improve the recovery of several other non-ferrous metals like tin, nickel, and palladium.

  10. Current breathomics-a review on data pre-processing techniques and machine learning in metabolomics breath analysis

    DEFF Research Database (Denmark)

    Smolinska, A.; Hauschild, A. C.; Fijten, R. R. R.

    2014-01-01

    been extensively developed. Yet, the application of machine learning methods for fingerprinting VOC profiles in the breathomics is still in its infancy. Therefore, in this paper, we describe the current state of the art in data pre-processing and multivariate analysis of breathomics data. We start...... different conditions (e.g. disease stage, treatment). Independently of the utilized analytical method, the most important question, 'which VOCs are discriminatory?', remains the same. Answers can be given by several modern machine learning techniques (multivariate statistics) and, therefore, are the focus...

  11. Predicting prices of agricultural commodities in Thailand using combined approach emphasizing on data pre-processing technique

    Directory of Open Access Journals (Sweden)

    Thoranin Sujjaviriyasup

    2018-02-01

    Full Text Available In this research, a combined approach emphasizing on data pre-processing technique is developed to forecast prices of agricultural commodities in Thailand. The future prices play significant role in decision making to cultivate crops in next year. The proposed model takes ability of MODWT to decompose original time series data into more stable and explicit subseries, and SVR model to formulate complex function of forecasting. The experimental results indicated that the proposed model outperforms traditional forecasting models based on MAE and MAPE criteria. Furthermore, the proposed model reveals that it is able to be a useful forecasting tool for prices of agricultural commodities in Thailand

  12. Quality assessment of baby food made of different pre-processed organic raw materials under industrial processing conditions.

    Science.gov (United States)

    Seidel, Kathrin; Kahl, Johannes; Paoletti, Flavio; Birlouez, Ines; Busscher, Nicolaas; Kretzschmar, Ursula; Särkkä-Tirkkonen, Marjo; Seljåsen, Randi; Sinesio, Fiorella; Torp, Torfinn; Baiamonte, Irene

    2015-02-01

    The market for processed food is rapidly growing. The industry needs methods for "processing with care" leading to high quality products in order to meet consumers' expectations. Processing influences the quality of the finished product through various factors. In carrot baby food, these are the raw material, the pre-processing and storage treatments as well as the processing conditions. In this study, a quality assessment was performed on baby food made from different pre-processed raw materials. The experiments were carried out under industrial conditions using fresh, frozen and stored organic carrots as raw material. Statistically significant differences were found for sensory attributes among the three autoclaved puree samples (e.g. overall odour F = 90.72, p processed from frozen carrots show increased moisture content and decrease of several chemical constituents. Biocrystallization identified changes between replications of the cooking. Pre-treatment of raw material has a significant influence on the final quality of the baby food.

  13. An efficient depth map preprocessing method based on structure-aided domain transform smoothing for 3D view generation.

    Directory of Open Access Journals (Sweden)

    Wei Liu

    Full Text Available Depth image-based rendering (DIBR, which is used to render virtual views with a color image and the corresponding depth map, is one of the key techniques in the 2D to 3D conversion process. Due to the absence of knowledge about the 3D structure of a scene and its corresponding texture, DIBR in the 2D to 3D conversion process, inevitably leads to holes in the resulting 3D image as a result of newly-exposed areas. In this paper, we proposed a structure-aided depth map preprocessing framework in the transformed domain, which is inspired by recently proposed domain transform for its low complexity and high efficiency. Firstly, our framework integrates hybrid constraints including scene structure, edge consistency and visual saliency information in the transformed domain to improve the performance of depth map preprocess in an implicit way. Then, adaptive smooth localization is cooperated and realized in the proposed framework to further reduce over-smoothness and enhance optimization in the non-hole regions. Different from the other similar methods, the proposed method can simultaneously achieve the effects of hole filling, edge correction and local smoothing for typical depth maps in a united framework. Thanks to these advantages, it can yield visually satisfactory results with less computational complexity for high quality 2D to 3D conversion. Numerical experimental results demonstrate the excellent performances of the proposed method.

  14. Web Log Pre-processing and Analysis for Generation of Learning Profiles in Adaptive E-learning

    Directory of Open Access Journals (Sweden)

    Radhika M. Pai

    2016-03-01

    Full Text Available Adaptive E-learning Systems (AESs enhance the efficiency of online courses in education by providing personalized contents and user interfaces that changes according to learner’s requirements and usage patterns. This paper presents the approach to generate learning profile of each learner which helps to identify the learning styles and provide Adaptive User Interface which includes adaptive learning components and learning material. The proposed method analyzes the captured web usage data to identify the learning profile of the learners. The learning profiles are identified by an algorithmic approach that is based on the frequency of accessing the materials and the time spent on the various learning components on the portal. The captured log data is pre-processed and converted into standard XML format to generate learners sequence data corresponding to the different sessions and time spent. The learning style model adopted in this approach is Felder-Silverman Learning Style Model (FSLSM. This paper also presents the analysis of learner’s activities, preprocessed XML files and generated sequences.

  15. Web Log Pre-processing and Analysis for Generation of Learning Profiles in Adaptive E-learning

    Directory of Open Access Journals (Sweden)

    Radhika M. Pai

    2016-04-01

    Full Text Available Adaptive E-learning Systems (AESs enhance the efficiency of online courses in education by providing personalized contents and user interfaces that changes according to learner’s requirements and usage patterns. This paper presents the approach to generate learning profile of each learner which helps to identify the learning styles and provide Adaptive User Interface which includes adaptive learning components and learning material. The proposed method analyzes the captured web usage data to identify the learning profile of the learners. The learning profiles are identified by an algorithmic approach that is based on the frequency of accessing the materials and the time spent on the various learning components on the portal. The captured log data is pre-processed and converted into standard XML format to generate learners sequence data corresponding to the different sessions and time spent. The learning style model adopted in this approach is Felder-Silverman Learning Style Model (FSLSM. This paper also presents the analysis of learner’s activities, preprocessed XML files and generated sequences.

  16. Research of high speed data readout and pre-processing system based on xTCA for silicon pixel detector

    International Nuclear Information System (INIS)

    Zhao Jingzhou; Lin Haichuan; Guo Fang; Liu Zhen'an; Xu Hao; Gong Wenxuan; Liu Zhao

    2012-01-01

    As the development of the detector, Silicon pixel detectors have been widely used in high energy physics experiments. It needs data processing system with high speed, high bandwidth and high availability to read data from silicon pixel detectors which generate more large data. The same question occurs on Belle II Pixel Detector which is a new style silicon pixel detector used in SuperKEKB accelerator with high luminance. The paper describes the research of High speed data readout and pre-processing system based on xTCA for silicon pixel detector. The system consists of High Performance Computer Node (HPCN) based on xTCA and ATCA frame. The HPCN consists of 4XFPs based on AMC, 1 AMC Carrier ATCA Board (ACAB) and 1 Rear Transmission Module. It characterized by 5 high performance FPGAs, 16 fiber links based on RocketIO, 5 Gbit Ethernet ports and DDR2 with capacity up to 18GB. In a ATCA frame, 14 HPCNs make up a system using the high speed backplane to achieve the function of data pre-processing and trigger. This system will be used on the trigger and data acquisition system of Belle II Pixel detector. (authors)

  17. Integrated fMRI Preprocessing Framework Using Extended Kalman Filter for Estimation of Slice-Wise Motion

    Directory of Open Access Journals (Sweden)

    Basile Pinsard

    2018-04-01

    Full Text Available Functional MRI acquisition is sensitive to subjects' motion that cannot be fully constrained. Therefore, signal corrections have to be applied a posteriori in order to mitigate the complex interactions between changing tissue localization and magnetic fields, gradients and readouts. To circumvent current preprocessing strategies limitations, we developed an integrated method that correct motion and spatial low-frequency intensity fluctuations at the level of each slice in order to better fit the acquisition processes. The registration of single or multiple simultaneously acquired slices is achieved online by an Iterated Extended Kalman Filter, favoring the robust estimation of continuous motion, while an intensity bias field is non-parametrically fitted. The proposed extraction of gray-matter BOLD activity from the acquisition space to an anatomical group template space, taking into account distortions, better preserves fine-scale patterns of activity. Importantly, the proposed unified framework generalizes to high-resolution multi-slice techniques. When tested on simulated and real data the latter shows a reduction of motion explained variance and signal variability when compared to the conventional preprocessing approach. These improvements provide more stable patterns of activity, facilitating investigation of cerebral information representation in healthy and/or clinical populations where motion is known to impact fine-scale data.

  18. Combined data preprocessing and multivariate statistical analysis characterizes fed-batch culture of mouse hybridoma cells for rational medium design.

    Science.gov (United States)

    Selvarasu, Suresh; Kim, Do Yun; Karimi, Iftekhar A; Lee, Dong-Yup

    2010-10-01

    We present an integrated framework for characterizing fed-batch cultures of mouse hybridoma cells producing monoclonal antibody (mAb). This framework systematically combines data preprocessing, elemental balancing and statistical analysis technique. Initially, specific rates of cell growth, glucose/amino acid consumptions and mAb/metabolite productions were calculated via curve fitting using logistic equations, with subsequent elemental balancing of the preprocessed data indicating the presence of experimental measurement errors. Multivariate statistical analysis was then employed to understand physiological characteristics of the cellular system. The results from principal component analysis (PCA) revealed three major clusters of amino acids with similar trends in their consumption profiles: (i) arginine, threonine and serine, (ii) glycine, tyrosine, phenylalanine, methionine, histidine and asparagine, and (iii) lysine, valine and isoleucine. Further analysis using partial least square (PLS) regression identified key amino acids which were positively or negatively correlated with the cell growth, mAb production and the generation of lactate and ammonia. Based on these results, the optimal concentrations of key amino acids in the feed medium can be inferred, potentially leading to an increase in cell viability and productivity, as well as a decrease in toxic waste production. The study demonstrated how the current methodological framework using multivariate statistical analysis techniques can serve as a potential tool for deriving rational medium design strategies. Copyright © 2010 Elsevier B.V. All rights reserved.

  19. Development and integration of block operations for data invariant automation of digital preprocessing and analysis of biological and biomedical Raman spectra.

    Science.gov (United States)

    Schulze, H Georg; Turner, Robin F B

    2015-06-01

    High-throughput information extraction from large numbers of Raman spectra is becoming an increasingly taxing problem due to the proliferation of new applications enabled using advances in instrumentation. Fortunately, in many of these applications, the entire process can be automated, yielding reproducibly good results with significant time and cost savings. Information extraction consists of two stages, preprocessing and analysis. We focus here on the preprocessing stage, which typically involves several steps, such as calibration, background subtraction, baseline flattening, artifact removal, smoothing, and so on, before the resulting spectra can be further analyzed. Because the results of some of these steps can affect the performance of subsequent ones, attention must be given to the sequencing of steps, the compatibility of these sequences, and the propensity of each step to generate spectral distortions. We outline here important considerations to effect full automation of Raman spectral preprocessing: what is considered full automation; putative general principles to effect full automation; the proper sequencing of processing and analysis steps; conflicts and circularities arising from sequencing; and the need for, and approaches to, preprocessing quality control. These considerations are discussed and illustrated with biological and biomedical examples reflecting both successful and faulty preprocessing.

  20. Speech perception for adult cochlear implant recipients in a realistic background noise: effectiveness of preprocessing strategies and external options for improving speech recognition in noise.

    Science.gov (United States)

    Gifford, René H; Revit, Lawrence J

    2010-01-01

    Although cochlear implant patients are achieving increasingly higher levels of performance, speech perception in noise continues to be problematic. The newest generations of implant speech processors are equipped with preprocessing and/or external accessories that are purported to improve listening in noise. Most speech perception measures in the clinical setting, however, do not provide a close approximation to real-world listening environments. To assess speech perception for adult cochlear implant recipients in the presence of a realistic restaurant simulation generated by an eight-loudspeaker (R-SPACE) array in order to determine whether commercially available preprocessing strategies and/or external accessories yield improved sentence recognition in noise. Single-subject, repeated-measures design with two groups of participants: Advanced Bionics and Cochlear Corporation recipients. Thirty-four subjects, ranging in age from 18 to 90 yr (mean 54.5 yr), participated in this prospective study. Fourteen subjects were Advanced Bionics recipients, and 20 subjects were Cochlear Corporation recipients. Speech reception thresholds (SRTs) in semidiffuse restaurant noise originating from an eight-loudspeaker array were assessed with the subjects' preferred listening programs as well as with the addition of either Beam preprocessing (Cochlear Corporation) or the T-Mic accessory option (Advanced Bionics). In Experiment 1, adaptive SRTs with the Hearing in Noise Test sentences were obtained for all 34 subjects. For Cochlear Corporation recipients, SRTs were obtained with their preferred everyday listening program as well as with the addition of Focus preprocessing. For Advanced Bionics recipients, SRTs were obtained with the integrated behind-the-ear (BTE) mic as well as with the T-Mic. Statistical analysis using a repeated-measures analysis of variance (ANOVA) evaluated the effects of the preprocessing strategy or external accessory in reducing the SRT in noise. In addition

  1. Simultaneous data pre-processing and SVM classification model selection based on a parallel genetic algorithm applied to spectroscopic data of olive oils.

    Science.gov (United States)

    Devos, Olivier; Downey, Gerard; Duponchel, Ludovic

    2014-04-01

    Classification is an important task in chemometrics. For several years now, support vector machines (SVMs) have proven to be powerful for infrared spectral data classification. However such methods require optimisation of parameters in order to control the risk of overfitting and the complexity of the boundary. Furthermore, it is established that the prediction ability of classification models can be improved using pre-processing in order to remove unwanted variance in the spectra. In this paper we propose a new methodology based on genetic algorithm (GA) for the simultaneous optimisation of SVM parameters and pre-processing (GENOPT-SVM). The method has been tested for the discrimination of the geographical origin of Italian olive oil (Ligurian and non-Ligurian) on the basis of near infrared (NIR) or mid infrared (FTIR) spectra. Different classification models (PLS-DA, SVM with mean centre data, GENOPT-SVM) have been tested and statistically compared using McNemar's statistical test. For the two datasets, SVM with optimised pre-processing give models with higher accuracy than the one obtained with PLS-DA on pre-processed data. In the case of the NIR dataset, most of this accuracy improvement (86.3% compared with 82.8% for PLS-DA) occurred using only a single pre-processing step. For the FTIR dataset, three optimised pre-processing steps are required to obtain SVM model with significant accuracy improvement (82.2%) compared to the one obtained with PLS-DA (78.6%). Furthermore, this study demonstrates that even SVM models have to be developed on the basis of well-corrected spectral data in order to obtain higher classification rates. Copyright © 2013 Elsevier Ltd. All rights reserved.

  2. Pre-processing of input files for the AZTRAN code; Pre procesamiento de archivos de entrada para el codigo AZTRAN

    Energy Technology Data Exchange (ETDEWEB)

    Vargas E, S. [ININ, Carretera Mexico-Toluca s/n, 52750 Ocoyoacac, Estado de Mexico (Mexico); Ibarra, G., E-mail: samuel.vargas@inin.gob.mx [IPN, Av. Instituto Politecnico Nacional s/n, 07738 Ciudad de Mexico (Mexico)

    2017-09-15

    The AZTRAN code began to be developed in the Nuclear Engineering Department of the Escuela Superior de Fisica y Matematicas (ESFM) of the Instituto Politecnico Nacional (IPN) with the purpose of numerically solving various models arising from the physics and engineering of nuclear reactors. The code is still under development and is part of the AZTLAN platform: Development of a Mexican platform for the analysis and design of nuclear reactors. Due to the complexity to generate an input file for the code, a script based on D language is developed, with the purpose of making its elaboration easier, based on a new input file format which includes specific cards, which have been divided into two blocks, mandatory cards and optional cards, including a pre-processing of the input file to identify possible errors within it, as well as an image generator for the specific problem based on the python interpreter. (Author)

  3. Pre-processing of Fourier transform infrared spectra by means of multivariate analysis implemented in the R environment.

    Science.gov (United States)

    Banas, Krzysztof; Banas, Agnieszka; Gajda, Mariusz; Pawlicki, Bohdan; Kwiatek, Wojciech M; Breese, Mark B H

    2015-04-21

    Pre-processing of Fourier transform infrared (FTIR) spectra is typically the first and crucial step in data analysis. Very often hyperspectral datasets include the regions characterized by the spectra of very low intensity, for example two-dimensional (2D) maps where the areas with only support materials (like mylar foil) are present. In that case segmentation of the complete dataset is required before subsequent evaluation. The method proposed in this contribution is based on a multivariate approach (hierarchical cluster analysis), and shows its superiority when compared to the standard method of cutting-off by using only the mean spectral intensity. Both techniques were implemented and their performance was tested in the R statistical environment - open-source platform - that is a favourable solution if the repeatability and transparency are the key aspects.

  4. Study on Construction of a Medical X-Ray Direct Digital Radiography System and Hybrid Preprocessing Methods

    Directory of Open Access Journals (Sweden)

    Yong Ren

    2014-01-01

    Full Text Available We construct a medical X-ray direct digital radiography (DDR system based on a CCD (charge-coupled devices camera. For the original images captured from X-ray exposure, computer first executes image flat-field correction and image gamma correction, and then carries out image contrast enhancement. A hybrid image contrast enhancement algorithm which is based on sharp frequency localization-contourlet transform (SFL-CT and contrast limited adaptive histogram equalization (CLAHE, is proposed and verified by the clinical DDR images. Experimental results show that, for the medical X-ray DDR images, the proposed comprehensive preprocessing algorithm can not only greatly enhance the contrast and detail information, but also improve the resolution capability of DDR system.

  5. Use of apparent thickness for preprocessing of low-frequency electromagnetic data in inversion-based multibarrier evaluation workflow

    Science.gov (United States)

    Omar, Saad; Omeragic, Dzevat

    2018-04-01

    The concept of apparent thicknesses is introduced for the inversion-based, multicasing evaluation interpretation workflow using multifrequency and multispacing electromagnetic measurements. A thickness value is assigned to each measurement, enabling the development of two new preprocessing algorithms to remove casing collar artifacts. First, long-spacing apparent thicknesses are used to remove, from the pipe sections, artifacts ("ghosts") caused by the transmitter crossing a casing collar or corrosion. Second, a collar identification, localization, and assignment algorithm is developed to enable robust inversion in collar sections. Last, casing eccentering can also be identified on the basis of opposite deviation of short-spacing phase and magnitude apparent thicknesses from the nominal value. The proposed workflow can handle an arbitrary number of nested casings and has been validated on synthetic and field data.

  6. Effect of interpolation error in pre-processing codes on calculations of self-shielding factors and their temperature derivatives

    International Nuclear Information System (INIS)

    Ganesan, S.; Gopalakrishnan, V.; Ramanadhan, M.M.; Cullan, D.E.

    1986-01-01

    We investigate the effect of interpolation error in the pre-processing codes LINEAR, RECENT and SIGMA1 on calculations of self-shielding factors and their temperature derivatives. We consider the 2.0347 to 3.3546 keV energy region for 238 U capture, which is the NEACRP benchmark exercise on unresolved parameters. The calculated values of temperature derivatives of self-shielding factors are significantly affected by interpolation error. The sources of problems in both evaluated data and codes are identified and eliminated in the 1985 version of these codes. This paper helps to (1) inform code users to use only 1985 versions of LINEAR, RECENT, and SIGMA1 and (2) inform designers of other code systems where they may have problems and what to do to eliminate their problems. (author)

  7. Effect of interpolation error in pre-processing codes on calculations of self-shielding factors and their temperature derivatives

    International Nuclear Information System (INIS)

    Ganesan, S.; Gopalakrishnan, V.; Ramanadhan, M.M.; Cullen, D.E.

    1985-01-01

    The authors investigate the effect of interpolation error in the pre-processing codes LINEAR, RECENT and SIGMA1 on calculations of self-shielding factors and their temperature derivatives. They consider the 2.0347 to 3.3546 keV energy region for /sup 238/U capture, which is the NEACRP benchmark exercise on unresolved parameters. The calculated values of temperature derivatives of self-shielding factors are significantly affected by interpolation error. The sources of problems in both evaluated data and codes are identified and eliminated in the 1985 version of these codes. This paper helps to (1) inform code users to use only 1985 versions of LINEAR, RECENT, and SIGMA1 and (2) inform designers of other code systems where they may have problems and what to do to eliminate their problems

  8. QSpike Tools: a Generic Framework for Parallel Batch Preprocessing of Extracellular Neuronal Signals Recorded by Substrate Microelectrode Arrays

    Directory of Open Access Journals (Sweden)

    Mufti eMahmud

    2014-03-01

    Full Text Available Micro-Electrode Arrays (MEAs have emerged as a mature technique to investigate brain (dysfunctions in vivo and in in vitro animal models. Often referred to as smart Petri dishes, MEAs has demonstrated a great potential particularly for medium-throughput studies in vitro, both in academic and pharmaceutical industrial contexts. Enabling rapid comparison of ionic/pharmacological/genetic manipulations with control conditions, MEAs are often employed to screen compounds by monitoring non-invasively the spontaneous and evoked neuronal electrical activity in longitudinal studies, with relatively inexpensive equipment. However, in order to acquire sufficient statistical significance, recordings last up to tens of minutes and generate large amount of raw data (e.g., 60 channels/MEA, 16 bits A/D conversion, 20kHz sampling rate: ~8GB/MEA,h uncompressed. Thus, when the experimental conditions to be tested are numerous, the availability of fast, standardized, and automated signal preprocessing becomes pivotal for any subsequent analysis and data archiving. To this aim, we developed an in-house cloud-computing system, named QSpike Tools, where CPU-intensive operations, required for preprocessing of each recorded channel (e.g., filtering, multi-unit activity detection, spike-sorting, etc., are decomposed and batch-queued to a multi-core architecture or to computer cluster. With the commercial availability of new and inexpensive high-density MEAs, we believe that disseminating QSpike Tools might facilitate its wide adoption and customization, and possibly inspire the creation of community-supported cloud-computing facilities for MEAs users.

  9. Achieving Accurate Automatic Sleep Staging on Manually Pre-processed EEG Data Through Synchronization Feature Extraction and Graph Metrics.

    Science.gov (United States)

    Chriskos, Panteleimon; Frantzidis, Christos A; Gkivogkli, Polyxeni T; Bamidis, Panagiotis D; Kourtidou-Papadeli, Chrysoula

    2018-01-01

    Sleep staging, the process of assigning labels to epochs of sleep, depending on the stage of sleep they belong, is an arduous, time consuming and error prone process as the initial recordings are quite often polluted by noise from different sources. To properly analyze such data and extract clinical knowledge, noise components must be removed or alleviated. In this paper a pre-processing and subsequent sleep staging pipeline for the sleep analysis of electroencephalographic signals is described. Two novel methods of functional connectivity estimation (Synchronization Likelihood/SL and Relative Wavelet Entropy/RWE) are comparatively investigated for automatic sleep staging through manually pre-processed electroencephalographic recordings. A multi-step process that renders signals suitable for further analysis is initially described. Then, two methods that rely on extracting synchronization features from electroencephalographic recordings to achieve computerized sleep staging are proposed, based on bivariate features which provide a functional overview of the brain network, contrary to most proposed methods that rely on extracting univariate time and frequency features. Annotation of sleep epochs is achieved through the presented feature extraction methods by training classifiers, which are in turn able to accurately classify new epochs. Analysis of data from sleep experiments on a randomized, controlled bed-rest study, which was organized by the European Space Agency and was conducted in the "ENVIHAB" facility of the Institute of Aerospace Medicine at the German Aerospace Center (DLR) in Cologne, Germany attains high accuracy rates, over 90% based on ground truth that resulted from manual sleep staging by two experienced sleep experts. Therefore, it can be concluded that the above feature extraction methods are suitable for semi-automatic sleep staging.

  10. QSpike tools: a generic framework for parallel batch preprocessing of extracellular neuronal signals recorded by substrate microelectrode arrays.

    Science.gov (United States)

    Mahmud, Mufti; Pulizzi, Rocco; Vasilaki, Eleni; Giugliano, Michele

    2014-01-01

    Micro-Electrode Arrays (MEAs) have emerged as a mature technique to investigate brain (dys)functions in vivo and in in vitro animal models. Often referred to as "smart" Petri dishes, MEAs have demonstrated a great potential particularly for medium-throughput studies in vitro, both in academic and pharmaceutical industrial contexts. Enabling rapid comparison of ionic/pharmacological/genetic manipulations with control conditions, MEAs are employed to screen compounds by monitoring non-invasively the spontaneous and evoked neuronal electrical activity in longitudinal studies, with relatively inexpensive equipment. However, in order to acquire sufficient statistical significance, recordings last up to tens of minutes and generate large amount of raw data (e.g., 60 channels/MEA, 16 bits A/D conversion, 20 kHz sampling rate: approximately 8 GB/MEA,h uncompressed). Thus, when the experimental conditions to be tested are numerous, the availability of fast, standardized, and automated signal preprocessing becomes pivotal for any subsequent analysis and data archiving. To this aim, we developed an in-house cloud-computing system, named QSpike Tools, where CPU-intensive operations, required for preprocessing of each recorded channel (e.g., filtering, multi-unit activity detection, spike-sorting, etc.), are decomposed and batch-queued to a multi-core architecture or to a computers cluster. With the commercial availability of new and inexpensive high-density MEAs, we believe that disseminating QSpike Tools might facilitate its wide adoption and customization, and inspire the creation of community-supported cloud-computing facilities for MEAs users.

  11. Using primary care electronic health record data for comparative effectiveness research : experience of data quality assessment and preprocessing in The Netherlands

    NARCIS (Netherlands)

    Huang, Yunyu; Voorham, Jaco; Haaijer-Ruskamp, Flora M.

    Aim: Details of data quality and how quality issues were solved have not been reported in published comparative effectiveness studies using electronic health record data. Methods: We developed a conceptual framework of data quality assessment and preprocessing and apply it to a study comparing

  12. Computational Testing for Automated Preprocessing 2: Practical Demonstration of a System for Scientific Data-Processing Workflow Management for High-Volume EEG.

    Science.gov (United States)

    Cowley, Benjamin U; Korpela, Jussi

    2018-01-01

    Existing tools for the preprocessing of EEG data provide a large choice of methods to suitably prepare and analyse a given dataset. Yet it remains a challenge for the average user to integrate methods for batch processing of the increasingly large datasets of modern research, and compare methods to choose an optimal approach across the many possible parameter configurations. Additionally, many tools still require a high degree of manual decision making for, e.g., the classification of artifacts in channels, epochs or segments. This introduces extra subjectivity, is slow, and is not reproducible. Batching and well-designed automation can help to regularize EEG preprocessing, and thus reduce human effort, subjectivity, and consequent error. The Computational Testing for Automated Preprocessing (CTAP) toolbox facilitates: (i) batch processing that is easy for experts and novices alike; (ii) testing and comparison of preprocessing methods. Here we demonstrate the application of CTAP to high-resolution EEG data in three modes of use. First, a linear processing pipeline with mostly default parameters illustrates ease-of-use for naive users. Second, a branching pipeline illustrates CTAP's support for comparison of competing methods. Third, a pipeline with built-in parameter-sweeping illustrates CTAP's capability to support data-driven method parameterization. CTAP extends the existing functions and data structure from the well-known EEGLAB toolbox, based on Matlab, and produces extensive quality control outputs. CTAP is available under MIT open-source licence from https://github.com/bwrc/ctap.

  13. A graphical method to evaluate spectral preprocessing in multivariate regression calibrations: example with Savitzky-Golay filters and partial least squares regression.

    Science.gov (United States)

    Delwiche, Stephen R; Reeves, James B

    2010-01-01

    In multivariate regression analysis of spectroscopy data, spectral preprocessing is often performed to reduce unwanted background information (offsets, sloped baselines) or accentuate absorption features in intrinsically overlapping bands. These procedures, also known as pretreatments, are commonly smoothing operations or derivatives. While such operations are often useful in reducing the number of latent variables of the actual decomposition and lowering residual error, they also run the risk of misleading the practitioner into accepting calibration equations that are poorly adapted to samples outside of the calibration. The current study developed a graphical method to examine this effect on partial least squares (PLS) regression calibrations of near-infrared (NIR) reflection spectra of ground wheat meal with two analytes, protein content and sodium dodecyl sulfate sedimentation (SDS) volume (an indicator of the quantity of the gluten proteins that contribute to strong doughs). These two properties were chosen because of their differing abilities to be modeled by NIR spectroscopy: excellent for protein content, fair for SDS sedimentation volume. To further demonstrate the potential pitfalls of preprocessing, an artificial component, a randomly generated value, was included in PLS regression trials. Savitzky-Golay (digital filter) smoothing, first-derivative, and second-derivative preprocess functions (5 to 25 centrally symmetric convolution points, derived from quadratic polynomials) were applied to PLS calibrations of 1 to 15 factors. The results demonstrated the danger of an over reliance on preprocessing when (1) the number of samples used in a multivariate calibration is low (<50), (2) the spectral response of the analyte is weak, and (3) the goodness of the calibration is based on the coefficient of determination (R(2)) rather than a term based on residual error. The graphical method has application to the evaluation of other preprocess functions and various

  14. Chemical pre-processing of cluster galaxies over the past 10 billion years in the IllustrisTNG simulations

    Science.gov (United States)

    Gupta, Anshu; Yuan, Tiantian; Torrey, Paul; Vogelsberger, Mark; Martizzi, Davide; Tran, Kim-Vy H.; Kewley, Lisa J.; Marinacci, Federico; Nelson, Dylan; Pillepich, Annalisa; Hernquist, Lars; Genel, Shy; Springel, Volker

    2018-06-01

    We use the IllustrisTNG simulations to investigate the evolution of the mass-metallicity relation (MZR) for star-forming cluster galaxies as a function of the formation history of their cluster host. The simulations predict an enhancement in the gas-phase metallicities of star-forming cluster galaxies (109 cluster galaxies appears prior to their infall into the central cluster potential, indicating for the first time a systematic `chemical pre-processing' signature for infalling cluster galaxies. Namely, galaxies that will fall into a cluster by z = 0 show a ˜0.05 dex enhancement in the MZR compared to field galaxies at z ≤ 0.5. Based on the inflow rate of gas into cluster galaxies and its metallicity, we identify that the accretion of pre-enriched gas is the key driver of the chemical evolution of such galaxies, particularly in the stellar mass range (109 clusters. Our results motivate future observations looking for pre-enrichment signatures in dense environments.

  15. Forecasting of a ground-coupled heat pump performance using neural networks with statistical data weighting pre-processing

    Energy Technology Data Exchange (ETDEWEB)

    Esen, Hikmet; Esen, Mehmet [Department of Mechanical Education, Faculty of Technical Education, Firat University, 23119 Elazig (Turkey); Inalli, Mustafa [Department of Mechanical Engineering, Faculty of Engineering, Firat University, 23279 Elazig (Turkey); Sengur, Abdulkadir [Department of Electronic and Computer Science, Faculty of Technical Education, Firat University, 23119 Elazig (Turkey)

    2008-04-15

    The objective of this work is to improve the performance of an artificial neural network (ANN) with a statistical weighted pre-processing (SWP) method to learn to predict ground source heat pump (GCHP) systems with the minimum data set. Experimental studies were completed to obtain training and test data. Air temperatures entering/leaving condenser unit, water-antifreeze solution entering/leaving the horizontal ground heat exchangers and ground temperatures (1 and 2 m) were used as input layer, while the output is coefficient of performance (COP) of system. Some statistical methods, such as the root-mean squared (RMS), the coefficient of multiple determinations (R{sup 2}) and the coefficient of variation (cov) is used to compare predicted and actual values for model validation. It is found that RMS value is 0.074, R{sup 2} value is 0.9999 and cov value is 2.22 for SCG6 algorithm of only ANN structure. It is also found that RMS value is 0.002, R{sup 2} value is 0.9999 and cov value is 0.076 for SCG6 algorithm of SWP-ANN structure. The simulation results show that the SWP based networks can be used an alternative way in these systems. Therefore, instead of limited experimental data found in literature, faster and simpler solutions are obtained using hybridized structures such as SWP-ANN. (author)

  16. [Influence of Spectral Pre-Processing on PLS Quantitative Model of Detecting Cu in Navel Orange by LIBS].

    Science.gov (United States)

    Li, Wen-bing; Yao, Lin-tao; Liu, Mu-hua; Huang, Lin; Yao, Ming-yin; Chen, Tian-bing; He, Xiu-wen; Yang, Ping; Hu, Hui-qin; Nie, Jiang-hui

    2015-05-01

    Cu in navel orange was detected rapidly by laser-induced breakdown spectroscopy (LIBS) combined with partial least squares (PLS) for quantitative analysis, then the effect on the detection accuracy of the model with different spectral data ptetreatment methods was explored. Spectral data for the 52 Gannan navel orange samples were pretreated by different data smoothing, mean centralized and standard normal variable transform. Then 319~338 nm wavelength section containing characteristic spectral lines of Cu was selected to build PLS models, the main evaluation indexes of models such as regression coefficient (r), root mean square error of cross validation (RMSECV) and the root mean square error of prediction (RMSEP) were compared and analyzed. Three indicators of PLS model after 13 points smoothing and processing of the mean center were found reaching 0. 992 8, 3. 43 and 3. 4 respectively, the average relative error of prediction model is only 5. 55%, and in one word, the quality of calibration and prediction of this model are the best results. The results show that selecting the appropriate data pre-processing method, the prediction accuracy of PLS quantitative model of fruits and vegetables detected by LIBS can be improved effectively, providing a new method for fast and accurate detection of fruits and vegetables by LIBS.

  17. A New Hybrid Model Based on Data Preprocessing and an Intelligent Optimization Algorithm for Electrical Power System Forecasting

    Directory of Open Access Journals (Sweden)

    Ping Jiang

    2015-01-01

    Full Text Available The establishment of electrical power system cannot only benefit the reasonable distribution and management in energy resources, but also satisfy the increasing demand for electricity. The electrical power system construction is often a pivotal part in the national and regional economic development plan. This paper constructs a hybrid model, known as the E-MFA-BP model, that can forecast indices in the electrical power system, including wind speed, electrical load, and electricity price. Firstly, the ensemble empirical mode decomposition can be applied to eliminate the noise of original time series data. After data preprocessing, the back propagation neural network model is applied to carry out the forecasting. Owing to the instability of its structure, the modified firefly algorithm is employed to optimize the weight and threshold values of back propagation to obtain a hybrid model with higher forecasting quality. Three experiments are carried out to verify the effectiveness of the model. Through comparison with other traditional well-known forecasting models, and models optimized by other optimization algorithms, the experimental results demonstrate that the hybrid model has the best forecasting performance.

  18. Haralick texture features from apparent diffusion coefficient (ADC) MRI images depend on imaging and pre-processing parameters.

    Science.gov (United States)

    Brynolfsson, Patrik; Nilsson, David; Torheim, Turid; Asklund, Thomas; Karlsson, Camilla Thellenberg; Trygg, Johan; Nyholm, Tufve; Garpebring, Anders

    2017-06-22

    In recent years, texture analysis of medical images has become increasingly popular in studies investigating diagnosis, classification and treatment response assessment of cancerous disease. Despite numerous applications in oncology and medical imaging in general, there is no consensus regarding texture analysis workflow, or reporting of parameter settings crucial for replication of results. The aim of this study was to assess how sensitive Haralick texture features of apparent diffusion coefficient (ADC) MR images are to changes in five parameters related to image acquisition and pre-processing: noise, resolution, how the ADC map is constructed, the choice of quantization method, and the number of gray levels in the quantized image. We found that noise, resolution, choice of quantization method and the number of gray levels in the quantized images had a significant influence on most texture features, and that the effect size varied between different features. Different methods for constructing the ADC maps did not have an impact on any texture feature. Based on our results, we recommend using images with similar resolutions and noise levels, using one quantization method, and the same number of gray levels in all quantized images, to make meaningful comparisons of texture feature results between different subjects.

  19. Performance Comparison of Several Pre-Processing Methods in a Hand Gesture Recognition System based on Nearest Neighbor for Different Background Conditions

    Directory of Open Access Journals (Sweden)

    Regina Lionnie

    2013-09-01

    Full Text Available This paper presents a performance analysis and comparison of several pre-processing  methods  used  in  a  hand  gesture  recognition  system.  The  preprocessing methods are based on the combinations ofseveral image processing operations,  namely  edge  detection,  low  pass  filtering,  histogram  equalization, thresholding and desaturation. The hand gesture recognition system is designed to classify an input image into one of six possibleclasses. The input images are taken with various background conditions. Our experiments showed that the best result is achieved when the pre-processing method consists of only a desaturation operation, achieving a classification accuracy of up to 83.15%.

  20. High speed preprocessing system

    Indian Academy of Sciences (India)

    The number of pixels an object occupies in the image plane depends ... these scaling factors, 6890 real number (floating point) multiplications, 2351023 integer additions .... baud frequency, required for USART for transmission and reception.

  1. Investigation of thermochemical biorefinery sizing and environmental sustainability impacts for conventional supply system and distributed preprocessing supply system designs

    Energy Technology Data Exchange (ETDEWEB)

    Muth, jr., David J. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Langholtz, Matthew H. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Tan, Eric [National Renewable Energy Lab. (NREL), Golden, CO (United States); Jacobson, Jacob [Idaho National Lab. (INL), Idaho Falls, ID (United States); Schwab, Amy [National Renewable Energy Lab. (NREL), Golden, CO (United States); Wu, May [Argonne National Lab. (ANL), Argonne, IL (United States); Argo, Andrew [Sundrop Fuels, Golden, CO (United States); Brandt, Craig C. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Cafferty, Kara [Idaho National Lab. (INL), Idaho Falls, ID (United States); Chiu, Yi-Wen [Argonne National Lab. (ANL), Argonne, IL (United States); Dutta, Abhijit [National Renewable Energy Lab. (NREL), Golden, CO (United States); Eaton, Laurence M. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Searcy, Erin [Idaho National Lab. (INL), Idaho Falls, ID (United States)

    2014-03-31

    The 2011 US Billion-Ton Update estimates that by 2030 there will be enough agricultural and forest resources to sustainably provide at least one billion dry tons of biomass annually, enough to displace approximately 30% of the country's current petroleum consumption. A portion of these resources are inaccessible at current cost targets with conventional feedstock supply systems because of their remoteness or low yields. Reliable analyses and projections of US biofuels production depend on assumptions about the supply system and biorefinery capacity, which, in turn, depend upon economic value, feedstock logistics, and sustainability. A cross-functional team has examined combinations of advances in feedstock supply systems and biorefinery capacities with rigorous design information, improved crop yield and agronomic practices, and improved estimates of sustainable biomass availability. A previous report on biochemical refinery capacity noted that under advanced feedstock logistic supply systems that include depots and pre-processing operations there are cost advantages that support larger biorefineries up to 10 000 DMT/day facilities compared to the smaller 2000 DMT/day facilities. This report focuses on analyzing conventional versus advanced depot biomass supply systems for a thermochemical conversion and refinery sizing based on woody biomass. The results of this analysis demonstrate that the economies of scale enabled by advanced logistics offsets much of the added logistics costs from additional depot processing and transportation, resulting in a small overall increase to the minimum ethanol selling price compared to the conventional logistic supply system. While the overall costs do increase slightly for the advanced logistic supply systems, the ability to mitigate moisture and ash in the system will improve the storage and conversion processes. In addition, being able to draw on feedstocks from further distances will decrease the risk of biomass supply to

  2. Rapid prototyping of SoC-based real-time vision system: application to image preprocessing and face detection

    Science.gov (United States)

    Jridi, Maher; Alfalou, Ayman

    2017-05-01

    By this paper, the major goal is to investigate the Multi-CPU/FPGA SoC (System on Chip) design flow and to transfer a know-how and skills to rapidly design embedded real-time vision system. Our aim is to show how the use of these devices can be benefit for system level integration since they make possible simultaneous hardware and software development. We take the facial detection and pretreatments as case study since they have a great potential to be used in several applications such as video surveillance, building access control and criminal identification. The designed system use the Xilinx Zedboard platform. The last is the central element of the developed vision system. The video acquisition is performed using either standard webcam connected to the Zedboard via USB interface or several camera IP devices. The visualization of video content and intermediate results are possible with HDMI interface connected to HD display. The treatments embedded in the system are as follow: (i) pre-processing such as edge detection implemented in the ARM and in the reconfigurable logic, (ii) software implementation of motion detection and face detection using either ViolaJones or LBP (Local Binary Pattern), and (iii) application layer to select processing application and to display results in a web page. One uniquely interesting feature of the proposed system is that two functions have been developed to transmit data from and to the VDMA port. With the proposed optimization, the hardware implementation of the Sobel filter takes 27 ms and 76 ms for 640x480, and 720p resolutions, respectively. Hence, with the FPGA implementation, an acceleration of 5 times is obtained which allow the processing of 37 fps and 13 fps for 640x480, and 720p resolutions, respectively.

  3. A Comparative Investigation of the Combined Effects of Pre-Processing, Wavelength Selection, and Regression Methods on Near-Infrared Calibration Model Performance.

    Science.gov (United States)

    Wan, Jian; Chen, Yi-Chieh; Morris, A Julian; Thennadil, Suresh N

    2017-07-01

    Near-infrared (NIR) spectroscopy is being widely used in various fields ranging from pharmaceutics to the food industry for analyzing chemical and physical properties of the substances concerned. Its advantages over other analytical techniques include available physical interpretation of spectral data, nondestructive nature and high speed of measurements, and little or no need for sample preparation. The successful application of NIR spectroscopy relies on three main aspects: pre-processing of spectral data to eliminate nonlinear variations due to temperature, light scattering effects and many others, selection of those wavelengths that contribute useful information, and identification of suitable calibration models using linear/nonlinear regression . Several methods have been developed for each of these three aspects and many comparative studies of different methods exist for an individual aspect or some combinations. However, there is still a lack of comparative studies for the interactions among these three aspects, which can shed light on what role each aspect plays in the calibration and how to combine various methods of each aspect together to obtain the best calibration model. This paper aims to provide such a comparative study based on four benchmark data sets using three typical pre-processing methods, namely, orthogonal signal correction (OSC), extended multiplicative signal correction (EMSC) and optical path-length estimation and correction (OPLEC); two existing wavelength selection methods, namely, stepwise forward selection (SFS) and genetic algorithm optimization combined with partial least squares regression for spectral data (GAPLSSP); four popular regression methods, namely, partial least squares (PLS), least absolute shrinkage and selection operator (LASSO), least squares support vector machine (LS-SVM), and Gaussian process regression (GPR). The comparative study indicates that, in general, pre-processing of spectral data can play a significant

  4. Use of spectral pre-processing methods to compensate for the presence of packaging film in visible–near infrared hyperspectral images of food products

    Directory of Open Access Journals (Sweden)

    A.A. Gowen

    2010-10-01

    Full Text Available The presence of polymeric packaging film in images of food products may modify spectra obtained in hyperspectral imaging (HSI experiments, leading to undesirable image artefacts which may impede image classification. Some pre-processing of the image is typically required to reduce the presence of such artefacts. The objective of this research was to investigate the use of spectral pre-processing techniques to compensate for the presence of packaging film in hyperspectral images obtained in the visible–near infrared wavelength range (445–945 nm, with application in food quality assessment. A selection of commonly used pre-processing methods, used individually and in combination, were applied to hyperspectral images of flat homogeneous samples, imaged in the presence and absence of different packaging films (polyvinyl chloride and polyethylene terephthalate. Effects of the selected pre-treatments on variation due to the film’s presence were examined in principal components score space. The results show that the combination of first derivative Savitzky–Golay followed by standard normal variate transformation was useful in reducing variations in spectral response caused by the presence of packaging film. Compared to other methods examined, this combination has the benefits of being computationally fast and not requiring a priori knowledge about the sample or film used.

  5. Detailed Investigation and Comparison of the XCMS and MZmine 2 Chromatogram Construction and Chromatographic Peak Detection Methods for Preprocessing Mass Spectrometry Metabolomics Data.

    Science.gov (United States)

    Myers, Owen D; Sumner, Susan J; Li, Shuzhao; Barnes, Stephen; Du, Xiuxia

    2017-09-05

    XCMS and MZmine 2 are two widely used software packages for preprocessing untargeted LC/MS metabolomics data. Both construct extracted ion chromatograms (EICs) and detect peaks from the EICs, the first two steps in the data preprocessing workflow. While both packages have performed admirably in peak picking, they also detect a problematic number of false positive EIC peaks and can also fail to detect real EIC peaks. The former and latter translate downstream into spurious and missing compounds and present significant limitations with most existing software packages that preprocess untargeted mass spectrometry metabolomics data. We seek to understand the specific reasons why XCMS and MZmine 2 find the false positive EIC peaks that they do and in what ways they fail to detect real compounds. We investigate differences of EIC construction methods in XCMS and MZmine 2 and find several problems in the XCMS centWave peak detection algorithm which we show are partly responsible for the false positive and false negative compound identifications. In addition, we find a problem with MZmine 2's use of centWave. We hope that a detailed understanding of the XCMS and MZmine 2 algorithms will allow users to work with them more effectively and will also help with future algorithmic development.

  6. LoCuSS: THE SLOW QUENCHING OF STAR FORMATION IN CLUSTER GALAXIES AND THE NEED FOR PRE-PROCESSING

    Energy Technology Data Exchange (ETDEWEB)

    Haines, C. P. [Departamento de Astronomía, Universidad de Chile, Casilla 36-D, Correo Central, Santiago (Chile); Pereira, M. J.; Egami, E.; Rawle, T. D. [Steward Observatory, University of Arizona, 933 North Cherry Avenue, Tucson, AZ 85721 (United States); Smith, G. P.; Ziparo, F.; McGee, S. L. [School of Physics and Astronomy, University of Birmingham, Edgbaston, Birmingham, B15 2TT (United Kingdom); Babul, A. [Department of Physics and Astronomy, University of Victoria, 3800 Finnerty Road, Victoria, BC, V8P 1A1 (Canada); Finoguenov, A. [Department of Physics, University of Helsinki, Gustaf Hällströmin katu 2a, FI-0014 Helsinki (Finland); Okabe, N. [Academia Sinica Institute of Astronomy and Astrophysics (ASIAA), P.O. Box 23-141, Taipei 10617, Taiwan (China); Moran, S. M., E-mail: cphaines@das.uchile.cl [Smithsonian Astrophysical Observatory, 60 Garden Street, Cambridge, MA 02138 (United States)

    2015-06-10

    We present a study of the spatial distribution and kinematics of star-forming galaxies in 30 massive clusters at 0.15 < z < 0.30, combining wide-field Spitzer 24 μm and GALEX near-ultraviolet imaging with highly complete spectroscopy of cluster members. The fraction (f{sub SF}) of star-forming cluster galaxies rises steadily with cluster-centric radius, increasing fivefold by 2r{sub 200}, but remains well below field values even at 3r{sub 200}. This suppression of star formation at large radii cannot be reproduced by models in which star formation is quenched in infalling field galaxies only once they pass within r{sub 200} of the cluster, but is consistent with some of them being first pre-processed within galaxy groups. Despite the increasing f{sub SF}-radius trend, the surface density of star-forming galaxies actually declines steadily with radius, falling ∼15× from the core to 2r{sub 200}. This requires star formation to survive within recently accreted spirals for 2–3 Gyr to build up the apparent over-density of star-forming galaxies within clusters. The velocity dispersion profile of the star-forming galaxy population shows a sharp peak of 1.44 σ{sub ν} at 0.3r{sub 500}, and is 10%–35% higher than that of the inactive cluster members at all cluster-centric radii, while their velocity distribution shows a flat, top-hat profile within r{sub 500}. All of these results are consistent with star-forming cluster galaxies being an infalling population, but one that must also survive ∼0.5–2 Gyr beyond passing within r{sub 200}. By comparing the observed distribution of star-forming galaxies in the stacked caustic diagram with predictions from the Millennium simulation, we obtain a best-fit model in which star formation rates decline exponentially on quenching timescales of 1.73 ± 0.25 Gyr upon accretion into the cluster.

  7. 基于延时相关预处理的MUSIC算法%MUSIC algorithm based on delay correlation preprocessing

    Institute of Scientific and Technical Information of China (English)

    初萍; 司伟建

    2013-01-01

    针对MUSIC算法的分辨力受信噪比、快拍数及阵元数等因素限制的问题,利用各阵元接收数据的延时相关函数重新构造协方差矩阵,提出了基于延时相关预处理的MUSIC算法.根据阵元间的延时相关函数与原阵列流型及信号延时相关函数的关系,推导了4个与原阵列流型相同(共轭)的延时相关函数矩阵,分别对各矩阵求协方差并按规则求和得到新的协方差矩阵,之后对协方差矩阵进行特征分解,根据信号子空间处理稳健性高和噪声子空间处理估计精度高的特点构造谱函数进行谱峰搜索,实现DOA估计.通过仿真实验验证了本文算法的可行性和有效性.%To solve the problem that the resolution of MUSIC algorithm is limited by such factors as signal to noise ratio (SNR), number of snapshots and number of array elements, the covariance matrix was reconstructed with the delay correlation function of data received from each array element, and the MUSIC algorithm based on the delay correlation preprocessing was proposed. According to the relationship between the delay correlation function of array elements as well as the delay correlation function of original array manifold and signals, four delay correlation function matrixes which are as the same as the original array manifold were derived. The covariance of each matrix was attained, and the summation was performed according to the rules to obtain a new covariance matrix. Then the eigen-decomposition of covariance matrix was carried out. In addition; the spectrum function was established according to the characteristics of both high robustness of signal subspace processing and high estimation accuracy of noise subspace processing. Furthermore, the searching of spectrum peaks was performed, and the DOA estimation was realized. The feasibility and validity of the proposed algorithm are testified with the simulation experiments.

  8. Implications of different digital elevation models and preprocessing techniques to delineate debris flow inundation hazard zones in El Salvador

    Science.gov (United States)

    Anderson, E. R.; Griffin, R.; Irwin, D.

    2013-12-01

    Heavy rains and steep, volcanic slopes in El Salvador cause numerous landslides every year, posing a persistent threat to the population, economy and environment. Although potential debris inundation hazard zones have been delineated using digital elevation models (DEMs), some disparities exist between the simulated zones and actual affected areas. Moreover, these hazard zones have only been identified for volcanic lahars and not the shallow landslides that occur nearly every year. This is despite the availability of tools to delineate a variety of landslide types (e.g., the USGS-developed LAHARZ software). Limitations in DEM spatial resolution, age of the data, and hydrological preprocessing techniques can contribute to inaccurate hazard zone definitions. This study investigates the impacts of using different elevation models and pit filling techniques in the final debris hazard zone delineations, in an effort to determine which combination of methods most closely agrees with observed landslide events. In particular, a national DEM digitized from topographic sheets from the 1970s and 1980s provide an elevation product at a 10 meter resolution. Both natural and anthropogenic modifications of the terrain limit the accuracy of current landslide hazard assessments derived from this source. Global products from the Shuttle Radar Topography Mission (SRTM) and the Advanced Spaceborne Thermal Emission and Reflection Radiometer Global DEM (ASTER GDEM) offer more recent data but at the cost of spatial resolution. New data derived from the NASA Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) in 2013 provides the opportunity to update hazard zones at a higher spatial resolution (approximately 6 meters). Hydrological filling of sinks or pits for current hazard zone simulation has previously been achieved through ArcInfo spatial analyst. Such hydrological processing typically only fills pits and can lead to drastic modifications of original elevation values

  9. The Python Spectral Analysis Tool (PySAT): A Powerful, Flexible, Preprocessing and Machine Learning Library and Interface

    Science.gov (United States)

    Anderson, R. B.; Finch, N.; Clegg, S. M.; Graff, T. G.; Morris, R. V.; Laura, J.; Gaddis, L. R.

    2017-12-01

    Machine learning is a powerful but underutilized approach that can enable planetary scientists to derive meaningful results from the rapidly-growing quantity of available spectral data. For example, regression methods such as Partial Least Squares (PLS) and Least Absolute Shrinkage and Selection Operator (LASSO), can be used to determine chemical concentrations from ChemCam and SuperCam Laser-Induced Breakdown Spectroscopy (LIBS) data [1]. Many scientists are interested in testing different spectral data processing and machine learning methods, but few have the time or expertise to write their own software to do so. We are therefore developing a free open-source library of software called the Python Spectral Analysis Tool (PySAT) along with a flexible, user-friendly graphical interface to enable scientists to process and analyze point spectral data without requiring significant programming or machine-learning expertise. A related but separately-funded effort is working to develop a graphical interface for orbital data [2]. The PySAT point-spectra tool includes common preprocessing steps (e.g. interpolation, normalization, masking, continuum removal, dimensionality reduction), plotting capabilities, and capabilities to prepare data for machine learning such as creating stratified folds for cross validation, defining training and test sets, and applying calibration transfer so that data collected on different instruments or under different conditions can be used together. The tool leverages the scikit-learn library [3] to enable users to train and compare the results from a variety of multivariate regression methods. It also includes the ability to combine multiple "sub-models" into an overall model, a method that has been shown to improve results and is currently used for ChemCam data [4]. Although development of the PySAT point-spectra tool has focused primarily on the analysis of LIBS spectra, the relevant steps and methods are applicable to any spectral data. The

  10. AIRS/Aqua Level 1B Visible/Near Infrared (VIS/NIR) geolocated and calibrated radiances V005

    Data.gov (United States)

    National Aeronautics and Space Administration — The Atmospheric Infrared Sounder (AIRS) is a facility instrument aboard the second Earth Observing System (EOS) polar-orbiting platform, EOS Aqua. In combination...

  11. AIRS/Aqua Level 1B Visible/Near Infrared (VIS/NIR) quality assurance subset V005

    Data.gov (United States)

    National Aeronautics and Space Administration — The Atmospheric Infrared Sounder (AIRS) is a facility instrument aboard the second Earth Observing System (EOS) polar-orbiting platform, EOS Aqua. In combination...

  12. AIRS/Aqua Near Real Time (NRT) Level 1B Infrared (IR) quality assurance subset V005

    Data.gov (United States)

    National Aeronautics and Space Administration — The Atmospheric Infrared Sounder (AIRS) is a facility instrument aboard the second Earth Observing System (EOS) polar-orbiting platform, EOS Aqua. In combination...

  13. AIRS/Aqua Level 1B AMSU (A1/A2) geolocated and calibrated brightness temperatures V005

    Data.gov (United States)

    National Aeronautics and Space Administration — The Atmospheric Infrared Sounder (AIRS) is a facility instrument aboard the second Earth Observing System (EOS) polar-orbiting platform, EOS Aqua. In combination...

  14. Unsharp masking technique as a preprocessing filter for improvement of 3D-CT image of bony structure in the maxillofacial region

    International Nuclear Information System (INIS)

    Harada, Takuya; Nishikawa, Keiichi; Kuroyanagi, Kinya

    1998-01-01

    We evaluated the usefulness of the unsharp masking technique as a preprocessing filter to improve 3D-CT images of bony structure in the maxillofacial region. The effect of the unsharp masking technique with several combinations of mask size and weighting factor on image resolution was investigated using a spatial frequency phantom made of bone-equivalent material. The 3D-CT images were obtained with scans perpendicular to and parallel to the phantom plates. The contrast transfer function (CTF) and the full width at half maximum (FWHM) of each spatial frequency component were measured. The FWHM was expressed as a ratio against the actual thickness of phantom plate. The effect on pseudoforamina was assessed using sliced CT images obtained in clinical bony 3D-CT examinations. The effect of the unsharp masking technique on image quality was also visually evaluated using five clinical fracture cases. CTFs did not change. FWHM ratios of original 3D-CT images were smaller than 1.0, regardless of the scanning direction. Those in scans perpendicular to the phantom plates were not changed by the unsharp masking technique. Those in parallel scanning were increased by mask size and weighting factor. The area of pseudoforamina decreased with increases in mask size and weighting factor. The combination of mask size 3 x 3 pixels and weighting factor 5 was optimal. Visual evaluation indicated that preprocessing with the unsharp masking technique improved the image quality of the 3D-CT images. The unsharp masking technique is useful as a preprocessing filter to improve the 3D-CT image of bony structure in the maxillofacial region. (author)

  15. Parallelizing flow-accumulation calculations on graphics processing units—From iterative DEM preprocessing algorithm to recursive multiple-flow-direction algorithm

    Science.gov (United States)

    Qin, Cheng-Zhi; Zhan, Lijun

    2012-06-01

    As one of the important tasks in digital terrain analysis, the calculation of flow accumulations from gridded digital elevation models (DEMs) usually involves two steps in a real application: (1) using an iterative DEM preprocessing algorithm to remove the depressions and flat areas commonly contained in real DEMs, and (2) using a recursive flow-direction algorithm to calculate the flow accumulation for every cell in the DEM. Because both algorithms are computationally intensive, quick calculation of the flow accumulations from a DEM (especially for a large area) presents a practical challenge to personal computer (PC) users. In recent years, rapid increases in hardware capacity of the graphics processing units (GPUs) provided in modern PCs have made it possible to meet this challenge in a PC environment. Parallel computing on GPUs using a compute-unified-device-architecture (CUDA) programming model has been explored to speed up the execution of the single-flow-direction algorithm (SFD). However, the parallel implementation on a GPU of the multiple-flow-direction (MFD) algorithm, which generally performs better than the SFD algorithm, has not been reported. Moreover, GPU-based parallelization of the DEM preprocessing step in the flow-accumulation calculations has not been addressed. This paper proposes a parallel approach to calculate flow accumulations (including both iterative DEM preprocessing and a recursive MFD algorithm) on a CUDA-compatible GPU. For the parallelization of an MFD algorithm (MFD-md), two different parallelization strategies using a GPU are explored. The first parallelization strategy, which has been used in the existing parallel SFD algorithm on GPU, has the problem of computing redundancy. Therefore, we designed a parallelization strategy based on graph theory. The application results show that the proposed parallel approach to calculate flow accumulations on a GPU performs much faster than either sequential algorithms or other parallel GPU

  16. International Best Practices for Pre-Processing and Co-Processing Municipal Solid Waste and Sewage Sludge in the Cement Industry

    Energy Technology Data Exchange (ETDEWEB)

    Hasanbeigi, Ali [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Lu, Hongyou [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Williams, Christopher [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Price, Lynn [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2012-07-01

    The purpose of this report is to describe international best practices for pre-processing and coprocessing of MSW and sewage sludge in cement plants, for the benefit of countries that wish to develop co-processing capacity. The report is divided into three main sections. Section 2 describes the fundamentals of co-processing, Section 3 describes exemplary international regulatory and institutional frameworks for co-processing, and Section 4 describes international best practices related to the technological aspects of co-processing.

  17. Contribution of the microprocessors in the study and development of a pre-processing unit involved in a nuclear physics experiment

    International Nuclear Information System (INIS)

    Pichot, G.

    1980-01-01

    The pre-processing unit has its place between the electronic output of the detector and the experiment control system, its role is 3-fold: a real-time role to provide adequate data to the control system allowing feedback, a basic role of selecting and reducing the volume of data and a role of managing the programs necessary to the first 2 roles. This work can be divided in 3 parts. First the analysis of the needs and limitations of the present system, secondly the meeting of the needs with on-the-shelf equipment, and thirdly validation and future improvements [fr

  18. An Innovative Hybrid Model Based on Data Pre-Processing and Modified Optimization Algorithm and Its Application in Wind Speed Forecasting

    Directory of Open Access Journals (Sweden)

    Ping Jiang

    2017-07-01

    Full Text Available Wind speed forecasting has an unsuperseded function in the high-efficiency operation of wind farms, and is significant in wind-related engineering studies. Back-propagation (BP algorithms have been comprehensively employed to forecast time series that are nonlinear, irregular, and unstable. However, the single model usually overlooks the importance of data pre-processing and parameter optimization of the model, which results in weak forecasting performance. In this paper, a more precise and robust model that combines data pre-processing, BP neural network, and a modified artificial intelligence optimization algorithm was proposed, which succeeded in avoiding the limitations of the individual algorithm. The novel model not only improves the forecasting accuracy but also retains the advantages of the firefly algorithm (FA and overcomes the disadvantage of the FA while optimizing in the later stage. To verify the forecasting performance of the presented hybrid model, 10-min wind speed data from Penglai city, Shandong province, China, were analyzed in this study. The simulations revealed that the proposed hybrid model significantly outperforms other single metaheuristics.

  19. INFLUENCE OF RAW IMAGE PREPROCESSING AND OTHER SELECTED PROCESSES ON ACCURACY OF CLOSE-RANGE PHOTOGRAMMETRIC SYSTEMS ACCORDING TO VDI 2634

    Directory of Open Access Journals (Sweden)

    J. Reznicek

    2016-06-01

    Full Text Available This paper examines the influence of raw image preprocessing and other selected processes on the accuracy of close-range photogrammetric measurement. The examined processes and features includes: raw image preprocessing, sensor unflatness, distance-dependent lens distortion, extending the input observations (image measurements by incorporating all RGB colour channels, ellipse centre eccentricity and target detecting. The examination of each effect is carried out experimentally by performing the validation procedure proposed in the German VDI guideline 2634/1. The validation procedure is based on performing standard photogrammetric measurements of high-accurate calibrated measuring lines (multi-scale bars with known lengths (typical uncertainty = 5 μm at 2 sigma. The comparison of the measured lengths with the known values gives the maximum length measurement error LME, which characterize the accuracy of the validated photogrammetric system. For higher reliability the VDI test field was photographed ten times independently with the same configuration and camera settings. The images were acquired with the metric ALPA 12WA camera. The tests are performed on all ten measurements which gives the possibility to measure the repeatability of the estimated parameters as well. The influences are examined by comparing the quality characteristics of the reference and tested settings.

  20. Neural network-based preprocessing to estimate the parameters of the X-ray emission of a single-temperature thermal plasma

    Science.gov (United States)

    Ichinohe, Y.; Yamada, S.; Miyazaki, N.; Saito, S.

    2018-04-01

    We present data preprocessing based on an artificial neural network to estimate the parameters of the X-ray emission spectra of a single-temperature thermal plasma. The method finds appropriate parameters close to the global optimum. The neural network is designed to learn the parameters of the thermal plasma (temperature, abundance, normalization and redshift) of the input spectra. After training using 9000 simulated X-ray spectra, the network has grown to predict all the unknown parameters with uncertainties of about a few per cent. The performance dependence on the network structure has been studied. We applied the neural network to an actual high-resolution spectrum obtained with Hitomi. The predicted plasma parameters agree with the known best-fitting parameters of the Perseus cluster within uncertainties of ≲10 per cent. The result shows that neural networks trained by simulated data might possibly be used to extract a feature built in the data. This would reduce human-intensive preprocessing costs before detailed spectral analysis, and would help us make the best use of the large quantities of spectral data that will be available in the coming decades.

  1. Berry ripening, pre-processing and thermal treatments affect the phenolic composition and antioxidant capacity of grape (Vitis vinifera L.) juice.

    Science.gov (United States)

    Genova, Giuseppe; Tosetti, Roberta; Tonutti, Pietro

    2016-01-30

    Grape juice is an important dietary source of health-promoting antioxidant molecules. Different factors may affect juice composition and nutraceutical properties. The effects of some of these factors (harvest time, pre-processing ethylene treatment of grapes and juice thermal pasteurization) were here evaluated, considering in particular the phenolic composition and antioxidant capacity. Grapes (Vitis vinifera L., red-skinned variety Sangiovese) were collected twice in relation to the technological harvest (TH) and 12 days before TH (early harvest, EH) and treated with gaseous ethylene (1000 ppm) or air for 48 h. Fresh and pasteurized (78 °C for 30 min) juices were produced using a water bath. Three-way analysis of variance showed that the harvest date had the strongest impact on total polyphenols, hydroxycinnamates, flavonols, and especially on total flavonoids. Pre-processing ethylene treatment significantly increased the proanthocyanidin, anthocyanin and flavan-3-ol content in the juices. Pasteurization induced a significant increase in anthocyanin concentration. Antioxidant capacity was enhanced by ethylene treatment and pasteurization in juices from both TH and EH grapes. These results suggest that an appropriate management of grape harvesting date, postharvest and processing may lead to an improvement in nutraceutical quality of juices. Further research is needed to study the effect of the investigated factors on juice organoleptic properties. © 2015 Society of Chemical Industry.

  2. Clinical data miner: an electronic case report form system with integrated data preprocessing and machine-learning libraries supporting clinical diagnostic model research.

    Science.gov (United States)

    Installé, Arnaud Jf; Van den Bosch, Thierry; De Moor, Bart; Timmerman, Dirk

    2014-10-20

    Using machine-learning techniques, clinical diagnostic model research extracts diagnostic models from patient data. Traditionally, patient data are often collected using electronic Case Report Form (eCRF) systems, while mathematical software is used for analyzing these data using machine-learning techniques. Due to the lack of integration between eCRF systems and mathematical software, extracting diagnostic models is a complex, error-prone process. Moreover, due to the complexity of this process, it is usually only performed once, after a predetermined number of data points have been collected, without insight into the predictive performance of the resulting models. The objective of the study of Clinical Data Miner (CDM) software framework is to offer an eCRF system with integrated data preprocessing and machine-learning libraries, improving efficiency of the clinical diagnostic model research workflow, and to enable optimization of patient inclusion numbers through study performance monitoring. The CDM software framework was developed using a test-driven development (TDD) approach, to ensure high software quality. Architecturally, CDM's design is split over a number of modules, to ensure future extendability. The TDD approach has enabled us to deliver high software quality. CDM's eCRF Web interface is in active use by the studies of the International Endometrial Tumor Analysis consortium, with over 4000 enrolled patients, and more studies planned. Additionally, a derived user interface has been used in six separate interrater agreement studies. CDM's integrated data preprocessing and machine-learning libraries simplify some otherwise manual and error-prone steps in the clinical diagnostic model research workflow. Furthermore, CDM's libraries provide study coordinators with a method to monitor a study's predictive performance as patient inclusions increase. To our knowledge, CDM is the only eCRF system integrating data preprocessing and machine-learning libraries

  3. Data Pre-Processing Method to Remove Interference of Gas Bubbles and Cell Clusters During Anaerobic and Aerobic Yeast Fermentations in a Stirred Tank Bioreactor

    Science.gov (United States)

    Princz, S.; Wenzel, U.; Miller, R.; Hessling, M.

    2014-11-01

    One aerobic and four anaerobic batch fermentations of the yeast Saccharomyces cerevisiae were conducted in a stirred bioreactor and monitored inline by NIR spectroscopy and a transflectance dip probe. From the acquired NIR spectra, chemometric partial least squares regression (PLSR) models for predicting biomass, glucose and ethanol were constructed. The spectra were directly measured in the fermentation broth and successfully inspected for adulteration using our novel data pre-processing method. These adulterations manifested as strong fluctuations in the shape and offset of the absorption spectra. They resulted from cells, cell clusters, or gas bubbles intercepting the optical path of the dip probe. In the proposed data pre-processing method, adulterated signals are removed by passing the time-scanned non-averaged spectra through two filter algorithms with a 5% quantile cutoff. The filtered spectra containing meaningful data are then averaged. A second step checks whether the whole time scan is analyzable. If true, the average is calculated and used to prepare the PLSR models. This new method distinctly improved the prediction results. To dissociate possible correlations between analyte concentrations, such as glucose and ethanol, the feeding analytes were alternately supplied at different concentrations (spiking) at the end of the four anaerobic fermentations. This procedure yielded low-error (anaerobic) PLSR models for predicting analyte concentrations of 0.31 g/l for biomass, 3.41 g/l for glucose, and 2.17 g/l for ethanol. The maximum concentrations were 14 g/l biomass, 167 g/l glucose, and 80 g/l ethanol. Data from the aerobic fermentation, carried out under high agitation and high aeration, were incorporated to realize combined PLSR models, which have not been previously reported to our knowledge.

  4. Effects of different correlation metrics and preprocessing factors on small-world brain functional networks: a resting-state functional MRI study.

    Science.gov (United States)

    Liang, Xia; Wang, Jinhui; Yan, Chaogan; Shu, Ni; Xu, Ke; Gong, Gaolang; He, Yong

    2012-01-01

    Graph theoretical analysis of brain networks based on resting-state functional MRI (R-fMRI) has attracted a great deal of attention in recent years. These analyses often involve the selection of correlation metrics and specific preprocessing steps. However, the influence of these factors on the topological properties of functional brain networks has not been systematically examined. Here, we investigated the influences of correlation metric choice (Pearson's correlation versus partial correlation), global signal presence (regressed or not) and frequency band selection [slow-5 (0.01-0.027 Hz) versus slow-4 (0.027-0.073 Hz)] on the topological properties of both binary and weighted brain networks derived from them, and we employed test-retest (TRT) analyses for further guidance on how to choose the "best" network modeling strategy from the reliability perspective. Our results show significant differences in global network metrics associated with both correlation metrics and global signals. Analysis of nodal degree revealed differing hub distributions for brain networks derived from Pearson's correlation versus partial correlation. TRT analysis revealed that the reliability of both global and local topological properties are modulated by correlation metrics and the global signal, with the highest reliability observed for Pearson's-correlation-based brain networks without global signal removal (WOGR-PEAR). The nodal reliability exhibited a spatially heterogeneous distribution wherein regions in association and limbic/paralimbic cortices showed moderate TRT reliability in Pearson's-correlation-based brain networks. Moreover, we found that there were significant frequency-related differences in topological properties of WOGR-PEAR networks, and brain networks derived in the 0.027-0.073 Hz band exhibited greater reliability than those in the 0.01-0.027 Hz band. Taken together, our results provide direct evidence regarding the influences of correlation metrics and specific

  5. Effects of different correlation metrics and preprocessing factors on small-world brain functional networks: a resting-state functional MRI study.

    Directory of Open Access Journals (Sweden)

    Xia Liang

    Full Text Available Graph theoretical analysis of brain networks based on resting-state functional MRI (R-fMRI has attracted a great deal of attention in recent years. These analyses often involve the selection of correlation metrics and specific preprocessing steps. However, the influence of these factors on the topological properties of functional brain networks has not been systematically examined. Here, we investigated the influences of correlation metric choice (Pearson's correlation versus partial correlation, global signal presence (regressed or not and frequency band selection [slow-5 (0.01-0.027 Hz versus slow-4 (0.027-0.073 Hz] on the topological properties of both binary and weighted brain networks derived from them, and we employed test-retest (TRT analyses for further guidance on how to choose the "best" network modeling strategy from the reliability perspective. Our results show significant differences in global network metrics associated with both correlation metrics and global signals. Analysis of nodal degree revealed differing hub distributions for brain networks derived from Pearson's correlation versus partial correlation. TRT analysis revealed that the reliability of both global and local topological properties are modulated by correlation metrics and the global signal, with the highest reliability observed for Pearson's-correlation-based brain networks without global signal removal (WOGR-PEAR. The nodal reliability exhibited a spatially heterogeneous distribution wherein regions in association and limbic/paralimbic cortices showed moderate TRT reliability in Pearson's-correlation-based brain networks. Moreover, we found that there were significant frequency-related differences in topological properties of WOGR-PEAR networks, and brain networks derived in the 0.027-0.073 Hz band exhibited greater reliability than those in the 0.01-0.027 Hz band. Taken together, our results provide direct evidence regarding the influences of correlation metrics

  6. Predictive analysis of the influence of the chemical composition and pre-processing regimen on structural properties of steel alloys using machine learning techniques

    Science.gov (United States)

    Krishnamurthy, Narayanan; Maddali, Siddharth; Romanov, Vyacheslav; Hawk, Jeffrey

    We present some structural properties of multi-component steel alloys as predicted by a random forest machine-learning model. These non-parametric models are trained on high-dimensional data sets defined by features such as chemical composition, pre-processing temperatures and environmental influences, the latter of which are based upon standardized testing procedures for tensile, creep and rupture properties as defined by the American Society of Testing and Materials (ASTM). We quantify the goodness of fit of these models as well as the inferred relative importance of each of these features, all with a conveniently defined metric and scale. The models are tested with synthetic data points, generated subject to the appropriate mathematical constraints for the various features. By this we highlight possible trends in the increase or degradation of the structural properties with perturbations in the features of importance. This work is presented as part of the Data Science Initiative at the National Energy Technology Laboratory, directed specifically towards the computational design of steel alloys.

  7. Image-preprocessing method for near-wall particle image velocimetry (PIV) image interrogation with very large in-plane displacement

    International Nuclear Information System (INIS)

    Zhu, Yiding; Yuan, Huijing; Zhang, Chuanhong; Lee, Cunbiao

    2013-01-01

    Accurate particle image velocimetry (PIV) measurements very near the wall are still a great challenge. The problem is compounded by the very large in-plane displacement on PIV images commonly encountered in measurements in hypersonic boundary layers. An improved image-preprocessing method is presented in this paper which expands the traditional window deformation iterative multigrid scheme to PIV images with very large displacement. Before the interrogation, stationary artificial particles of uniform size are added homogeneously in the wall region. The mean squares of the intensities of signals in the flow and in the wall region are postulated to be equal when half the initial interrogation window overlaps the wall region. The initial estimation near the wall is then smoothed by data from both sides of the shear layer to reduce the large random uncertainties. Interrogations in the following iterative steps then converge to the correct results to provide accurate predictions for particle tracking velocimetries. Significant improvement is seen in Monte Carlo simulations and experimental tests. The algorithm successfully extracted the small flow structures of the second-mode wave in the hypersonic boundary layer from PIV images with low signal-noise-ratios when the traditional method was not successful. (paper)

  8. Making the most of RNA-seq: Pre-processing sequencing data with Opossum for reliable SNP variant detection [version 2; referees: 2 approved, 1 approved with reservations

    Directory of Open Access Journals (Sweden)

    Laura Oikkonen

    2017-03-01

    Full Text Available Identifying variants from RNA-seq (transcriptome sequencing data is a cost-effective and versatile complement to whole-exome (WES and whole-genome sequencing (WGS analysis. RNA-seq (transcriptome sequencing is primarily considered a method of gene expression analysis but it can also be used to detect DNA variants in expressed regions of the genome. However, current variant callers do not generally behave well with RNA-seq data due to reads encompassing intronic regions. We have developed a software programme called Opossum to address this problem. Opossum pre-processes RNA-seq reads prior to variant calling, and although it has been designed to work specifically with Platypus, it can be used equally well with other variant callers such as GATK HaplotypeCaller. In this work, we show that using Opossum in conjunction with either Platypus or GATK HaplotypeCaller maintains precision and improves the sensitivity for SNP detection compared to the GATK Best Practices pipeline. In addition, using it in combination with Platypus offers a substantial reduction in run times compared to the GATK pipeline so it is ideal when there are only limited time or computational resources available.

  9. Making the most of RNA-seq: Pre-processing sequencing data with Opossum for reliable SNP variant detection [version 1; referees: 2 approved, 1 approved with reservations

    Directory of Open Access Journals (Sweden)

    Laura Oikkonen

    2017-01-01

    Full Text Available Identifying variants from RNA-seq (transcriptome sequencing data is a cost-effective and versatile alternative to whole-genome sequencing. However, current variant callers do not generally behave well with RNA-seq data due to reads encompassing intronic regions. We have developed a software programme called Opossum to address this problem. Opossum pre-processes RNA-seq reads prior to variant calling, and although it has been designed to work specifically with Platypus, it can be used equally well with other variant callers such as GATK HaplotypeCaller. In this work, we show that using Opossum in conjunction with either Platypus or GATK HaplotypeCaller maintains precision and improves the sensitivity for SNP detection compared to the GATK Best Practices pipeline. In addition, using it in combination with Platypus offers a substantial reduction in run times compared to the GATK pipeline so it is ideal when there are only limited time or computational resources available.

  10. Optimized image processing with modified preprocessing of image data sets of a transparent imaging plate by way of the lateral view of the cervical spine

    International Nuclear Information System (INIS)

    Reissberg, S.; Hoeschen, C.; Redlich, U.; Scherlach, C.; Preuss, H.; Kaestner, A.; Doehring, W.; Woischneck, D.; Schuetze, M.; Reichardt, K.; Firsching, R.

    2002-01-01

    Purpose: To improve the diagnostic quality of lateral radiographs of the cervical spine by pre-processing the image data sets produced by a transparent imaging plate with both-side reading and to evaluate any possible impact on minimizing the number of additional radiographs and supplementary investigations. Material and Methods: One hundred lateral digital radiographs of the cervical spine were processed with two different methods: processing of each data set using the system-imminent parameters and using the manual model. The difference between the two types of processing is the level of the latitude value. Hard copies of the processed images were judged by five radiologists and three neurosurgeons. The evaluation applied the image criteria score (ICS) without conventional reference images. Results: In 99% of the lateral radiographs of the cervical spine, all vertebral bodies could be completed delineated using the manual mode, but only 76% of the images processed by the system-imminent parameters showed all vertebral bodies. Thus, the manual mode enabled the evaluation of up to two additional more caudal vertebral bodies. The manual mode processing was significantly better concerning object size and processing artifacts. This optimized image processing and the resultant minimization of supplementary investigations was calculated to correspond to a theoretical dose reduction of about 50%. (orig.) [de

  11. Data preprocessing for data mining

    OpenAIRE

    Ren, Yifei

    2013-01-01

    People have increasing amounts data in the current prosperous information age. In order to improve competitive power and work efficiency, discovering knowledge from data is becoming more and more important. Data mining, as an emerging interdisciplinary applications field, plays a significant role in various trades’ and industries' decision making. However, it is known that original data is always dirty and not suitable for further analysis which have become a major obstacle of finding knowled...

  12. Sample Preprocessing For Atomic Spectrometry

    International Nuclear Information System (INIS)

    Kim, Sun Tae

    2004-08-01

    This book gives descriptions of atomic spectrometry, which deals with atomic absorption spectrometry such as Maxwell-Boltzmann equation and Beer-Lambert law, atomic absorption spectrometry for solvent extraction, HGAAS, ETASS, and CVAAS and inductively coupled plasma emission spectrometer, such as basic principle, generative principle of plasma and device and equipment, and interferences, and inductively coupled plasma mass spectrometry like device, pros and cons of ICP/MS, sample analysis, reagent, water, acid, flux, materials of experiments, sample and sampling and disassembling of sample and pollution and loss in open system and closed system.

  13. Investigation of thermochemical biorefinery sizing and environmental sustainability impacts for conventional supply system and distributed pre-processing supply system designs

    Energy Technology Data Exchange (ETDEWEB)

    David J. Muth, Jr.; Matthew H. Langholtz; Eric C. D. Tan; Jacob J. Jacobson; Amy Schwab; May M. Wu; Andrew Argo; Craig C. Brandt; Kara G. Cafferty; Yi-Wen Chiu; Abhijit Dutta; Laurence M. Eaton; Erin M. Searcy

    2014-08-01

    The 2011 US Billion-Ton Update estimates that by 2030 there will be enough agricultural and forest resources to sustainably provide at least one billion dry tons of biomass annually, enough to displace approximately 30% of the country's current petroleum consumption. A portion of these resources are inaccessible at current cost targets with conventional feedstock supply systems because of their remoteness or low yields. Reliable analyses and projections of US biofuels production depend on assumptions about the supply system and biorefinery capacity, which, in turn, depend upon economic value, feedstock logistics, and sustainability. A cross-functional team has examined combinations of advances in feedstock supply systems and biorefinery capacities with rigorous design information, improved crop yield and agronomic practices, and improved estimates of sustainable biomass availability. A previous report on biochemical refinery capacity noted that under advanced feedstock logistic supply systems that include depots and pre-processing operations there are cost advantages that support larger biorefineries up to 10 000 DMT/day facilities compared to the smaller 2000 DMT/day facilities. This report focuses on analyzing conventional versus advanced depot biomass supply systems for a thermochemical conversion and refinery sizing based on woody biomass. The results of this analysis demonstrate that the economies of scale enabled by advanced logistics offsets much of the added logistics costs from additional depot processing and transportation, resulting in a small overall increase to the minimum ethanol selling price compared to the conventional logistic supply system. While the overall costs do increase slightly for the advanced logistic supply systems, the ability to mitigate moisture and ash in the system will improve the storage and conversion processes. In addition, being able to draw on feedstocks from further distances will decrease the risk of biomass supply to

  14. Saving Grace - A Climate Change Documentary Education Program

    Science.gov (United States)

    Byrne, J. M.; McDaniel, S.; Graham, J.; Little, L.; Hoggan, J. C.

    2012-12-01

    Saving Grace conveys climate change knowledge from the best international scientists and social scientists using a series of new media formats. An Education and Communication Plan (ECP) has been developed to disseminate climate change knowledge on impacts, mitigation and adaptation for individuals, and for all sectors of society. The research team is seeking contacts with science and social science colleagues around the world to provide the knowledge base for the ECP. Poverty enslaves…and climate change has, and will, spread and deepen poverty to hundreds of millions of people, primarily in the developing world. And make no mistake; we are enslaving hundreds of millions of people in a depressing and debilitating poverty that in numbers will far surpass the horrors of the slave trade of past centuries. Saving Grace is the story of that poverty - and minimizing that poverty. Saving Grace stars the best of the world's climate researchers. Saving Grace presents the science; who, where and why of greenhouse gases that drive climate change; current and projected impacts of a changing climate around the world; and most important, solutions to the climate change challenges we face.

  15. AIRS/Aqua Near Real Time (NRT) Level 1B AMSU (A1/A2) geolocated and calibrated brightness temperatures V005

    Data.gov (United States)

    National Aeronautics and Space Administration — The Atmospheric Infrared Sounder (AIRS) is a facility instrument aboard the second Earth Observing System (EOS) polar-orbiting platform, EOS Aqua. In combination...

  16. AIRS/Aqua Near Real Time (NRT) Level 1B Visible/Near Infrared (VIS/NIR) geolocated and calibrated radiances V005

    Data.gov (United States)

    National Aeronautics and Space Administration — The Atmospheric Infrared Sounder (AIRS) is a facility instrument aboard the second Earth Observing System (EOS) polar-orbiting platform, EOS Aqua. In combination...

  17. AIRS/Aqua Near Real Time (NRT) Level 1B Visible/Near Infrared (VIS/NIR) quality assurance subset V005

    Data.gov (United States)

    National Aeronautics and Space Administration — The Atmospheric Infrared Sounder (AIRS) is a facility instrument aboard the second Earth Observing System (EOS) polar-orbiting platform, EOS Aqua. In combination...

  18. Use of neural network based auto-associative memory as a data compressor for pre-processing optical emission spectra in gas thermometry with the help of neural network

    International Nuclear Information System (INIS)

    Dolenko, S.A.; Filippov, A.V.; Pal, A.F.; Persiantsev, I.G.; Serov, A.O.

    2003-01-01

    Determination of temperature from optical emission spectra is an inverse problem that is often very difficult to solve, especially when substantial noise is present. One of the means that can be used to solve such a problem is a neural network trained on the results of modeling of spectra at different temperatures (Dolenko, et al., in: I.C. Parmee (Ed.), Adaptive Computing in Design and Manufacture, Springer, London, 1998, p. 345). Reducing the dimensionality of the input data prior to application of neural network can increase the accuracy and stability of temperature determination. In this study, such pre-processing is performed with another neural network working as an auto-associative memory with a narrow bottleneck in the hidden layer. The improvement in the accuracy and stability of temperature determination in presence of noise is demonstrated on model spectra similar to those recorded in a DC-discharge CVD reactor

  19. [Application of N-isopropyl-p-[123I] iodoamphetamine quantification of regional cerebral blood flow using iterative reconstruction methods: selection of the optimal reconstruction method and optimization of the cutoff frequency of the preprocessing filter].

    Science.gov (United States)

    Asazu, Akira; Hayashi, Masuo; Arai, Mami; Kumai, Yoshiaki; Akagi, Hiroyuki; Okayama, Katsuyoshi; Narumi, Yoshifumi

    2013-05-01

    In cerebral blood flow tests using N-Isopropyl-p-[123I] Iodoamphetamine "I-IMP, quantitative results of greater accuracy than possible using the autoradiography (ARG) method can be obtained with attenuation and scatter correction and image reconstruction by filtered back projection (FBP). However, the cutoff frequency of the preprocessing Butterworth filter affects the quantitative value; hence, we sought an optimal cutoff frequency, derived from the correlation between the FBP method and Xenon-enhanced computed tomography (XeCT)/cerebral blood flow (CBF). In this study, we reconstructed images using ordered subsets expectation maximization (OSEM), a method of successive approximation which has recently come into wide use, and also three-dimensional (3D)-OSEM, a method by which the resolution can be corrected with the addition of collimator broad correction, to examine the effects on the regional cerebral blood flow (rCBF) quantitative value of changing the cutoff frequency, and to determine whether successive approximation is applicable to cerebral blood flow quantification. Our results showed that quantification of greater accuracy was obtained with reconstruction employing the 3D-OSEM method and using a cutoff frequency set near 0.75-0.85 cycles/cm, which is higher than the frequency used in image reconstruction by the ordinary FBP method.

  20. Application of N-isopropyl-p-[123I] iodoamphetamine quantification of regional cerebral blood flow using iterative reconstruction methods. Selection of the optimal reconstruction method and optimization of the cutoff frequency of the preprocessing filter

    International Nuclear Information System (INIS)

    Asazu, Akira; Hayashi, Masuo; Arai, Mami; Kumai, Yoshiaki; Akagi, Hiroyuki; Okayama, Katsuyoshi; Narumi, Yoshifumi

    2013-01-01

    In cerebral blood flow tests using N-Isopropyl-p-[ 123 I] Iodoamphetamine 123 I-IMP, quantitative results of greater accuracy than possible using the autoradiography (ARG) method can be obtained with attenuation and scatter correction and image reconstruction by filtered back projection (FBP). However, the cutoff frequency of the preprocessing Butterworth filter affects the quantitative value; hence, we sought an optimal cutoff frequency, derived from the correlation between the FBP method and Xenon-enhanced computed tomography (XeCT)/cerebral blood flow (CBF). In this study, we reconstructed images using ordered subsets expectation maximization (OSEM), a method of successive approximation which has recently come into wide use, and also three-dimensional (3D)-OSEM, a method by which the resolution can be corrected with the addition of collimator broad correction, to examine the effects on the regional cerebral blood flow (rCBF) quantitative value of changing the cutoff frequency, and to determine whether successive approximation is applicable to cerebral blood flow quantification. Our results showed that quantification of greater accuracy was obtained with reconstruction employing the 3D-OSEM method and using a cutoff frequency set near 0.75-0.85 cycles/cm, which is higher than the frequency used in image reconstruction by the ordinary FBP method. (author)

  1. Does HDR Pre-Processing Improve the Accuracy of 3D Models Obtained by Means of two Conventional SfM-MVS Software Packages? The Case of the Corral del Veleta Rock Glacier

    Directory of Open Access Journals (Sweden)

    Álvaro Gómez-Gutiérrez

    2015-08-01

    Full Text Available The accuracy of different workflows using Structure-from-Motion and Multi-View-Stereo techniques (SfM-MVS is tested. Twelve point clouds of the Corral del Veleta rock glacier, in Spain, were produced with two different software packages (123D Catch and Agisoft Photoscan, using Low Dynamic Range images and High Dynamic Range compositions (HDR for three different years (2011, 2012 and 2014. The accuracy of the resulting point clouds was assessed using benchmark models acquired every year with a Terrestrial Laser Scanner. Three parameters were used to estimate the accuracy of each point cloud: the RMSE, the Cloud-to-Cloud distance (C2C and the Multiscale-Model-to-Model comparison (M3C2. The M3C2 mean error ranged from 0.084 m (standard deviation of 0.403 m to 1.451 m (standard deviation of 1.625 m. Agisoft Photoscan overcome 123D Catch, producing more accurate and denser point clouds in 11 out 12 cases, being this work, the first available comparison between both software packages in the literature. No significant improvement was observed using HDR pre-processing. To our knowledge, this is the first time that the geometrical accuracy of 3D models obtained using LDR and HDR compositions are compared. These findings may be of interest for researchers who wish to estimate geomorphic changes using SfM-MVS approaches.

  2. Evaluation of the efficiency of continuous wavelet transform as processing and preprocessing algorithm for resolution of overlapped signals in univariate and multivariate regression analyses; an application to ternary and quaternary mixtures

    Science.gov (United States)

    Hegazy, Maha A.; Lotfy, Hayam M.; Mowaka, Shereen; Mohamed, Ekram Hany

    2016-07-01

    Wavelets have been adapted for a vast number of signal-processing applications due to the amount of information that can be extracted from a signal. In this work, a comparative study on the efficiency of continuous wavelet transform (CWT) as a signal processing tool in univariate regression and a pre-processing tool in multivariate analysis using partial least square (CWT-PLS) was conducted. These were applied to complex spectral signals of ternary and quaternary mixtures. CWT-PLS method succeeded in the simultaneous determination of a quaternary mixture of drotaverine (DRO), caffeine (CAF), paracetamol (PAR) and p-aminophenol (PAP, the major impurity of paracetamol). While, the univariate CWT failed to simultaneously determine the quaternary mixture components and was able to determine only PAR and PAP, the ternary mixtures of DRO, CAF, and PAR and CAF, PAR, and PAP. During the calculations of CWT, different wavelet families were tested. The univariate CWT method was validated according to the ICH guidelines. While for the development of the CWT-PLS model a calibration set was prepared by means of an orthogonal experimental design and their absorption spectra were recorded and processed by CWT. The CWT-PLS model was constructed by regression between the wavelet coefficients and concentration matrices and validation was performed by both cross validation and external validation sets. Both methods were successfully applied for determination of the studied drugs in pharmaceutical formulations.

  3. Data pre-processing for database marketing

    OpenAIRE

    Pinto, Filipe; Santos, Manuel Filipe; Cortez, Paulo; Quintela, Hélder

    2004-01-01

    To increase effectiveness in their marketing and Customer Relationship Manager activities, many organizations are adopting strategies of Database Marketing (DBM). Nowadays, DBM faces new challenges in business knowledge since current strategies are mainly approached by classical statistical inference, which may fail when complex, multi-dimensional and incomplete data is available. An alternative is to use Knowledge Discovery from Databases (KDD), which aims at automatic extraction of useful p...

  4. Preprocessing Greek Papyri for Linguistic Annotation

    Directory of Open Access Journals (Sweden)

    Vierros, Marja

    2017-08-01

    Full Text Available Greek documentary papyri form an important direct source for Ancient Greek. It has been exploited surprisingly little in Greek linguistics due to a lack of good tools for searching linguistic structures. This article presents a new tool and digital platform, “Sematia”, which enables transforming the digital texts available in TEI EpiDoc XML format to a format which can be morphologically and syntactically annotated (treebanked, and where the user can add new metadata concerning the text type, writer and handwriting of each act of writing. An important aspect in this process is to take into account the original surviving writing vs. the standardization of language and supplements made by the editors. This is performed by creating two different layers of the same text. The platform is in its early development phase. Ongoing and future developments, such as tagging linguistic variation phenomena as well as queries performed within Sematia, are discussed at the end of the article.

  5. On Using Entropy for Enhancing Handwriting Preprocessing

    Directory of Open Access Journals (Sweden)

    Bernhard Peischl

    2012-11-01

    Full Text Available Handwriting is an important modality for Human-Computer Interaction. For medical professionals, handwriting is (still the preferred natural method of documentation. Handwriting recognition has long been a primary research area in Computer Science. With the tremendous ubiquity of smartphones, along with the renaissance of the stylus, handwriting recognition has become a new impetus. However, recognition rates are still not 100% perfect, and researchers still are constantly improving handwriting algorithms. In this paper we evaluate the performance of entropy based slant- and skew-correction, and compare the results to other methods. We selected 3700 words of 23 writers out of the Unipen-ICROW-03 benchmark set, which we annotated with their associated error angles by hand. Our results show that the entropy-based slant correction method outperforms a window based approach with an average precision of 6:02 for the entropy-based method, compared with the 7:85 for the alternative. On the other hand, the entropy-based skew correction yields a lower average precision of 2:86, compared with the average precision of 2:13 for the alternative LSM based approach.

  6. Comparing Binaural Pre-processing Strategies II

    Directory of Open Access Journals (Sweden)

    Regina M. Baumgärtel

    2015-12-01

    Full Text Available Several binaural audio signal enhancement algorithms were evaluated with respect to their potential to improve speech intelligibility in noise for users of bilateral cochlear implants (CIs. 50% speech reception thresholds (SRT50 were assessed using an adaptive procedure in three distinct, realistic noise scenarios. All scenarios were highly nonstationary, complex, and included a significant amount of reverberation. Other aspects, such as the perfectly frontal target position, were idealized laboratory settings, allowing the algorithms to perform better than in corresponding real-world conditions. Eight bilaterally implanted CI users, wearing devices from three manufacturers, participated in the study. In all noise conditions, a substantial improvement in SRT50 compared to the unprocessed signal was observed for most of the algorithms tested, with the largest improvements generally provided by binaural minimum variance distortionless response (MVDR beamforming algorithms. The largest overall improvement in speech intelligibility was achieved by an adaptive binaural MVDR in a spatially separated, single competing talker noise scenario. A no-pre-processing condition and adaptive differential microphones without a binaural link served as the two baseline conditions. SRT50 improvements provided by the binaural MVDR beamformers surpassed the performance of the adaptive differential microphones in most cases. Speech intelligibility improvements predicted by instrumental measures were shown to account for some but not all aspects of the perceptually obtained SRT50 improvements measured in bilaterally implanted CI users.

  7. Data preprocessing techniques for classification without discrimination

    NARCIS (Netherlands)

    Kamiran, F.; Calders, T.G.K.

    2012-01-01

    Recently, the following Discrimination-Aware Classification Problem was introduced: Suppose we are given training data that exhibit unlawful discrimination; e.g., toward sensitive attributes such as gender or ethnicity. The task is to learn a classifier that optimizes accuracy, but does not have

  8. Project GRACE A grid based search tool for the global digital library

    CERN Document Server

    Scholze, Frank; Vigen, Jens; Prazak, Petra; The Seventh International Conference on Electronic Theses and Dissertations

    2004-01-01

    The paper will report on the progress of an ongoing EU project called GRACE - Grid Search and Categorization Engine (http://www.grace-ist.org). The project participants are CERN, Sheffield Hallam University, Stockholm University, Stuttgart University, GL 2006 and Telecom Italia. The project started in 2002 and will finish in 2005, resulting in a Grid based search engine that will search across a variety of content sources including a number of electronic thesis and dissertation repositories. The Open Archives Initiative (OAI) is expanding and is clearly an interesting movement for a community advocating open access to ETD. However, the OAI approach alone may not be sufficiently scalable to achieve a truly global ETD Digital Library. Many universities simply offer their collections to the world via their local web services without being part of any federated system for archiving and even those dissertations that are provided with OAI compliant metadata will not necessarily be picked up by a centralized OAI Ser...

  9. Aging gracefully: a comparative study of Japanese and Malaysian women aged 65-75.

    Science.gov (United States)

    Kok, Jin Kuan; Yap, Yuet Ngor

    2014-12-01

    Longer lives and extended retirement have created a 'young old age' stage of life. How people spend their "young old age" has become increasingly important. This research aims to investigate the different ageing experiences of Japanese and Malaysian women and the activities they engaged in their "young old age". In-depth interviews were conducted to collect data and an adapted grounded theory approach was used for data analysis. Findings reveal many common characteristics for both groups of research participants. The emerging themes show that Japanese and Malaysian Chinese have different life missions evident in their daily activities, one passing on culture and the other passing on family values and life experience. They also differ in their choice of living arrangement (independent versus dependent/interdependent), attitudes to life (fighting versus accepting) and activities in which to engage (aesthetic pursuits versus family oriented activities). Copyright © 2014 Elsevier Inc. All rights reserved.

  10. Data Security by Preprocessing the Text with Secret Hiding

    OpenAIRE

    Ajit Singh; Upasana Jauhari

    2012-01-01

    With the advent of the Internet, an open forum, the massive increase in the data travel across networkmake an issue for secure transmission. Cryptography is the term that involves many encryption method to make data secure. But the transmission of the secure data is an intricate task. Steganography here comes with effect of transmission without revealing the secure data. The research paper provide the mechanism which enhance the security of data by using a crypto+stegano combination to increa...

  11. Prediction of speech intelligibility based on an auditory preprocessing model

    DEFF Research Database (Denmark)

    Christiansen, Claus Forup Corlin; Pedersen, Michael Syskind; Dau, Torsten

    2010-01-01

    in noise experiment was used for training and an ideal binary mask experiment was used for evaluation. All three models were able to capture the trends in the speech in noise training data well, but the proposed model provides a better prediction of the binary mask test data, particularly when the binary...... masks degenerate to a noise vocoder....

  12. Method for pre-processing LWR spent fuel

    International Nuclear Information System (INIS)

    Otsuka, Katsuyuki; Ebihara, Hikoe.

    1986-01-01

    Purpose: To facilitate the decladding of spent fuel, cladding tube processing, and waste gas recovery, and to enable the efficient execution of main re-processing process thereafter. Constitution: Spent fuel assemblies are sent to a cutting process where they are cut into chips of easy-to-process size. The chips, in a thermal decladding process, undergo a thermal cycle processing in air with the processing temperatures increased and decreased within the range of from 700 deg C to 1200 deg C, oxidizing zircaloy comprising the cladding tubes into zirconia. The oxidized cladding tubes have a number of fine cracks and become very brittle and easy to loosen off from fuel pellets when even a slight mechanical force is applied thereto, thus changing into a form of powder. Processed products are then separated into zirconia sand and fuel pellets by a gravitational selection method or by a sifting method, the zirconia sand being sent to a waste processing process and the fuel pellets to a melting-refining process. (Yoshino, Y.)

  13. LEDAPS Landsat Calibration, Reflectance, Atmospheric Correction Preprocessing Code

    Data.gov (United States)

    National Aeronautics and Space Administration — ABSTRACT: The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) is a NASA project to map disturbance, regrowth, and permanent forest conversion...

  14. Comparing Binaural Pre-processing Strategies I: Instrumental Evaluation.

    Science.gov (United States)

    Baumgärtel, Regina M; Krawczyk-Becker, Martin; Marquardt, Daniel; Völker, Christoph; Hu, Hongmei; Herzke, Tobias; Coleman, Graham; Adiloğlu, Kamil; Ernst, Stephan M A; Gerkmann, Timo; Doclo, Simon; Kollmeier, Birger; Hohmann, Volker; Dietz, Mathias

    2015-12-30

    In a collaborative research project, several monaural and binaural noise reduction algorithms have been comprehensively evaluated. In this article, eight selected noise reduction algorithms were assessed using instrumental measures, with a focus on the instrumental evaluation of speech intelligibility. Four distinct, reverberant scenarios were created to reflect everyday listening situations: a stationary speech-shaped noise, a multitalker babble noise, a single interfering talker, and a realistic cafeteria noise. Three instrumental measures were employed to assess predicted speech intelligibility and predicted sound quality: the intelligibility-weighted signal-to-noise ratio, the short-time objective intelligibility measure, and the perceptual evaluation of speech quality. The results show substantial improvements in predicted speech intelligibility as well as sound quality for the proposed algorithms. The evaluated coherence-based noise reduction algorithm was able to provide improvements in predicted audio signal quality. For the tested single-channel noise reduction algorithm, improvements in intelligibility-weighted signal-to-noise ratio were observed in all but the nonstationary cafeteria ambient noise scenario. Binaural minimum variance distortionless response beamforming algorithms performed particularly well in all noise scenarios. © The Author(s) 2015.

  15. Ash Reduction of Corn Stover by Mild Hydrothermal Preprocessing

    Energy Technology Data Exchange (ETDEWEB)

    M. Toufiq Reza; Rachel Emerson; M. Helal Uddin; Garold Gresham; Charles J. Coronella

    2014-04-22

    Lignocellulosic biomass such as corn stover can contain high ash content, which may act as an inhibitor in downstream conversion processes. Most of the structural ash in biomass is located in the cross-linked structure of lignin, which is mildly reactive in basic solutions. Four organic acids (formic, oxalic, tartaric, and citric) were evaluated for effectiveness in ash reduction, with limited success. Because of sodium citrate’s chelating and basic characteristics, it is effective in ash removal. More than 75 % of structural and 85 % of whole ash was removed from the biomass by treatment with 0.1 g of sodium citrate per gram of biomass at 130 °C and 2.7 bar. FTIR, fiber analysis, and chemical analyses show that cellulose and hemicellulose were unaffected by the treatment. ICP–AES showed that all inorganics measured were reduced within the biomass feedstock, except sodium due to the addition of Na through the treatment. Sodium citrate addition to the preconversion process of corn stover is an effective way to reduced physiological ash content of the feedstock without negatively impacting carbohydrate and lignin content.

  16. Towards reproducible MSMS data preprocessing, quality control and quantification

    OpenAIRE

    Gatto, Laurent; Lilley, Kathryn S.

    2010-01-01

    The development of MSnbase aims at providing researchers dealing with labelled quantitative proteomics data with a transparent, portable, extensible and open-source collaborative framework to easily manipulate and analyse MS2-level raw tandem mass spectrometry data. The implementation in R gives users and developers a great variety of powerful tools to be used in a controlled and reproducible way. Furthermore, MSnbase has been developed following an object-oriented programming paradigm: all i...

  17. Pre-process desilication of wheat straw with citrate

    DEFF Research Database (Denmark)

    Le, Duy Michael; Sorensen, Hanne R.; Meyer, Anne S.

    2017-01-01

    in the residual biomass and treatment temperature was observed up to 170 degrees C, yielding a Si removal of up to 97.7%. This high Si removal came at the expense of a low mass yield (down to 45%) in the insoluble lignocellulosic fraction. Optimum process conditions for high Si removal and high total mass yield...... were: 100mM sodium citrate, 130 degrees C, 60 min, 2% w/v solids, and pH of similar to 6.5 during extraction. Using the proposed process conditions, silica removal of up to 77% was achieved with a mass yield of 72.8%. This Si removal from the insoluble lignocellulosic fraction did not affect...

  18. The pre-processing technique and parameter adjustment influences ...

    African Journals Online (AJOL)

    based BPSO structure for time-varying water temperature modelling. N Hambali, M.N. Taib, I.M. Yassin, M.H.F. Rahiman. Abstract. No Abstract. Keywords: identification; NARX; particle swarm optimization; distillation colum; temperature. Full Text:.

  19. Grouping preprocess for haplotype inference from SNP and CNV data

    International Nuclear Information System (INIS)

    Shindo, Hiroyuki; Chigira, Hiroshi; Nagaoka, Tomoyo; Inoue, Masato; Kamatani, Naoyuki

    2009-01-01

    The method of statistical haplotype inference is an indispensable technique in the field of medical science. The authors previously reported Hardy-Weinberg equilibrium-based haplotype inference that could manage single nucleotide polymorphism (SNP) data. We recently extended the method to cover copy number variation (CNV) data. Haplotype inference from mixed data is important because SNPs and CNVs are occasionally in linkage disequilibrium. The idea underlying the proposed method is simple, but the algorithm for it needs to be quite elaborate to reduce the calculation cost. Consequently, we have focused on the details on the algorithm in this study. Although the main advantage of the method is accuracy, in that it does not use any approximation, its main disadvantage is still the calculation cost, which is sometimes intractable for large data sets with missing values.

  20. Grouping preprocess for haplotype inference from SNP and CNV data

    Energy Technology Data Exchange (ETDEWEB)

    Shindo, Hiroyuki; Chigira, Hiroshi; Nagaoka, Tomoyo; Inoue, Masato [Department of Electrical Engineering and Bioscience, School of Advanced Science and Engineering, Waseda University, 3-4-1, Okubo, Shinjuku-ku, Tokyo 169-8555 (Japan); Kamatani, Naoyuki, E-mail: masato.inoue@eb.waseda.ac.j [Institute of Rheumatology, Tokyo Women' s Medical University, 10-22, Kawada-cho, Shinjuku-ku, Tokyo 162-0054 (Japan)

    2009-12-01

    The method of statistical haplotype inference is an indispensable technique in the field of medical science. The authors previously reported Hardy-Weinberg equilibrium-based haplotype inference that could manage single nucleotide polymorphism (SNP) data. We recently extended the method to cover copy number variation (CNV) data. Haplotype inference from mixed data is important because SNPs and CNVs are occasionally in linkage disequilibrium. The idea underlying the proposed method is simple, but the algorithm for it needs to be quite elaborate to reduce the calculation cost. Consequently, we have focused on the details on the algorithm in this study. Although the main advantage of the method is accuracy, in that it does not use any approximation, its main disadvantage is still the calculation cost, which is sometimes intractable for large data sets with missing values.

  1. A Data Pre-Processing Model for the Topsis Method

    Directory of Open Access Journals (Sweden)

    Kobryń Andrzej

    2016-12-01

    Full Text Available TOPSIS is one of the most popular methods of multi-criteria decision making (MCDM. Its fundamental role is the establishment of chosen alternatives ranking based on their distance from the ideal and negative-ideal solution. There are three primary versions of the TOPSIS method distinguished: classical, interval and fuzzy, where calculation algorithms are adjusted to the character of input rating decision-making alternatives (real numbers, interval data or fuzzy numbers. Various, specialist publications present descriptions on the use of particular versions of the TOPSIS method in the decision-making process, particularly popular is the fuzzy version. However, it should be noticed, that depending on the character of accepted criteria – rating of alternatives can have a heterogeneous character. The present paper suggests the means of proceeding in the situation when the set of criteria covers characteristic criteria for each of the mentioned versions of TOPSIS, as a result of which the rating of the alternatives is vague. The calculation procedure has been illustrated by an adequate numerical example.

  2. Experimental variability and data pre-processing as factors affecting the discrimination power of some chemometric approaches (PCA, CA and a new algorithm based on linear regression) applied to (+/-)ESI/MS and RPLC/UV data: Application on green tea extracts.

    Science.gov (United States)

    Iorgulescu, E; Voicu, V A; Sârbu, C; Tache, F; Albu, F; Medvedovici, A

    2016-08-01

    The influence of the experimental variability (instrumental repeatability, instrumental intermediate precision and sample preparation variability) and data pre-processing (normalization, peak alignment, background subtraction) on the discrimination power of multivariate data analysis methods (Principal Component Analysis -PCA- and Cluster Analysis -CA-) as well as a new algorithm based on linear regression was studied. Data used in the study were obtained through positive or negative ion monitoring electrospray mass spectrometry (+/-ESI/MS) and reversed phase liquid chromatography/UV spectrometric detection (RPLC/UV) applied to green tea extracts. Extractions in ethanol and heated water infusion were used as sample preparation procedures. The multivariate methods were directly applied to mass spectra and chromatograms, involving strictly a holistic comparison of shapes, without assignment of any structural identity to compounds. An alternative data interpretation based on linear regression analysis mutually applied to data series is also discussed. Slopes, intercepts and correlation coefficients produced by the linear regression analysis applied on pairs of very large experimental data series successfully retain information resulting from high frequency instrumental acquisition rates, obviously better defining the profiles being compared. Consequently, each type of sample or comparison between samples produces in the Cartesian space an ellipsoidal volume defined by the normal variation intervals of the slope, intercept and correlation coefficient. Distances between volumes graphically illustrates (dis)similarities between compared data. The instrumental intermediate precision had the major effect on the discrimination power of the multivariate data analysis methods. Mass spectra produced through ionization from liquid state in atmospheric pressure conditions of bulk complex mixtures resulting from extracted materials of natural origins provided an excellent data

  3. Improving Human Effectiveness Through Embedded Virtual Simulation (Amelioration de l’efficacite humaine grace a la simulation virtuelle integree)

    Science.gov (United States)

    2014-01-01

    blocks by the US Army Research, Development and Engineering Command (RDECOM) as a development that enables armoured crew the ability to observe...behavioral and physiological sensors, past performance and other competency measures, demographic information, human observations and/or self...tutoring systems may include demographics , input from behavioral and physiological sensors, self-reported and observed data and/or historical

  4. Seasonal changes in the European gravity field from GRACE: A comparison with superconducting gravimeters and hydrology model predictions

    Science.gov (United States)

    Hinderer, Jacques; Andersen, Ole; Lemoine, Frank; Crossley, David; Boy, Jean-Paul

    2006-01-01

    This paper is devoted to the investigation of seasonal changes of the Earth's gravity field from GRACE satellites and the comparison with surface gravity measurements in Europe from the Global Geodynamics Project (GGP) sub-network, as well as with recent hydrology models for continental soil moisture and snow. We used gravity maps in Europe retrieved from the initial GRACE monthly solutions spanning a 21-month duration from April 2002 to December 2003 for various truncation levels of the initial spherical harmonic decomposition of the field. The transfer function between satellite-derived and ground gravity changes due to continental hydrology is studied and we also compute the theoretical ratio of gravity versus radial displacement (in μGal/mm) involved in the hydrological loading process. The 'mean' value (averaged in time and in space over Europe) from hydrologic forward modeling is found to be close to -1.0 μGal/mm and we show that this value can be explained by a strong low degree ( n = 5-6) peak in the hydrology amplitude spectrum. The dominant time-variable signal from GRACE is found to be annual with an amplitude and a phase both of which are in fair agreement with predictions in Europe from recent hydrology models. Initial results suggest that all three data sets (GRACE, hydrology and GGP) respond to annual changes in near-surface water in Europe of a few μGal (at length scales of ˜1000 km) that show a high value in winter and a summer minimum. Despite the limited time span of our analysis and the uncertainties in separating purely local effects from regional ones in superconducting gravimeter data, the calibration and validation aspects of the GRACE data processing based on the annual hydrology cycle in Europe are in progress.

  5. Seasonal changes in the European gravity field from GRACE: A comparison with superconducting gravimeters and hydrology model predictions

    DEFF Research Database (Denmark)

    Hinderer, J.; Andersen, Ole Baltazar; Lemoine, F.

    2006-01-01

    This paper is devoted to the investigation of seasonal changes of the Earth's gravity field from GRACE satellites and the comparison with surface gravity measurements in Europe from the Global Geodynamics Project (GGP) sub-network, as well as with recent hydrology models for continental soil...... moisture and snow. We used gravity maps in Europe retrieved from the initial GRACE monthly solutions spanning a 21 -month duration from April 2002 to December 2003 for various truncation levels of the initial spherical harmonic decomposition of the field. The transfer function between satellite......-derived and ground gravity changes due to continental hydrology is studied and we also compute the theoretical ratio of gravity versus radial displacement (in mu Gal/mm) involved in the hydrological loading process. The 'mean' value (averaged in time and in space over Europe) from hydrologic forward modeling...

  6. Belly button piercings: a saving grace? A patent urachus presenting in a 17-year-old girl.

    Science.gov (United States)

    Bannon, Aidan; Black, Patrick; Turner, Joanna; Gray, Sam; Kirk, Stephen

    2014-06-10

    We report the case of a 17-year-old girl who presented to the accident and emergency department with dysuria and foul smelling, bloody discharge from her umbilicus. The definitive diagnosis was that of a patent urachus, which is a fistulous communication between the bladder and the umbilicus, usually diagnosed in early infancy. The incidence of a patent urachus is approximately 1 in 70,000 in the general population. It is highly likely that removal of a recent belly button piercing resulted in the acute presentation by completing the fistulous tract to the skin. This case is of clinical relevance as the diagnosis was missed 18 months prior with a milder presentation. The recommended treatment option is surgical excision due to the potential risk of malignant change, with urachal adenocarcinoma accounting for 0.3% of all bladder cancers. 2014 BMJ Publishing Group Ltd.

  7. Time Changes of the European Gravity Field from GRACE: A Comparison with Ground Measurements from Superconducting Gravimeters and with Hydrology Model Predictions

    Science.gov (United States)

    Hinderer, J.; Lemoine, Frank G.; Crossley, D.; Boy, J.-P.

    2004-01-01

    We investigate the time-variable gravity changes in Europe retrieved from the initial GRACE monthly solutions spanning a 18 month duration from April 2002 to October 2003. Gravity anomaly maps are retrieved in Central Europe from the monthly satellite solutions we compare the fields according to various truncation levels (typically between degree 10 and 20) of the initial fields (expressed in spherical harmonics to degree 120). For these different degrees, an empirical orthogonal function (EOF) decomposition of the time-variable gravity field leads us to its main spatial and temporal characteristics. We show that the dominant signal is found to be annual with an amplitude and a phase both in agreement with predictions in Europe modeled using snow and soil-moisture variations from recent hydrology models. We compare these GRACE gravity field changes to surface gravity observations from 6 superconducting gravimeters of the GGP (Global Geodynamics Project) European sub-network, with a special attention to loading corrections. Initial results suggest that all 3 data sets (GRACE, hydrology and GGP) are responding to annual changes in near-surface water in Europe of a few microGal (at length scales of approx.1000 km) that show a high value in winter and a summer minimum. We also point out that the GRACE gravity field evolution seems to indicate that there is a trend in gravity between summer 2002 and summer 2003 which can be related to the 2003 heatwave in Europe and its hydrological consequences (drought). Despite the limited time span of our analysis and the uncertainties in retrieving a regional solution from the network of gravimeters, the calibration and validation aspects of the GRACE data processing based on the annual hydrology cycle in Europe are in progress.

  8. Antarctic Glacial Isostatic Adjustment and Ice Sheet Mass Balance using GRACE: A Report from the Ice-sheet Mass Balance Exercise (IMBIE)

    Science.gov (United States)

    Ivins, E. R.; Wahr, J. M.; Schrama, E. J.; Milne, G. A.; Barletta, V.; Horwath, M.; Whitehouse, P.

    2012-12-01

    In preparation for the Inter-govermental Panel on Climate Change: Assessment Report 5 (IPCC AR5), ESA and NASA have formed a committee of experts to perform a formal set of comparative experiments concerning space observations of ice sheet mass balance. This project began in August of 2011 and has now concluded with a report submitted for Science (Shepherd et al., 2012). The focus of the work conducted is to re-evaluate scientific reports on the mass balance of Greenland ice sheet (GIS) and Antarctic ice sheet (AIS). The most serious discrepancies have been reported for the AIS, amounting to as much as 0.9 mm/yr in discrepant sea level contribution. A direct method of determining the AIS is by space gravimetry. However, for this method to contribute to our understanding of sea level change, we require knowledge of present-day non-elastic vertical movements of bedrock in Antarctica. Quantifying the uncertainty and bias caused by lack of observational control on models of regional glacial isostatic adjustment (GIA), was a major focus for our experiments. This regional process is the most problematic error source for GRACE-determinations of ice mass balance in Antarctica. While GIA likely dominates some large vertical motions in Antarctica that are now observed with GPS (Thomas et al., 2011, GRL), interpretations still require models. The reported uncertainty for space gravimetric (GRACE) based sea level sourcing is roughly 0.20 to 0.35 mm/yr. The uncertainty is also part of the error budget for mass balances derived from altimetry measurements, though at a much lower level. Analysis of the GRACE time series using CSR RL04 (2003.0-2010.10) for AIS mass balance reveals a small trend of order +1 to -24 Gt/yr without a GIA correction. Three periods were selected over which to perform inter-comparisons (see Table). One class of GIA models, that relies primarily on far field sea level reconstructions (e.g. ICE-5G), provide a GIA correction that places AIS mass imbalance (δM) as high as -160 Gt/yr. IMBIE used an average of new models IJ05_R2 and W12a for new corrections. This new class of models is constrained by a variety of Antarctic data sets (e.g. proxy reconstructions of past ice extent, GPS estimates of vertical land motion) and provides a correction that is approximately one half to one third of that obtained from the far-field based models. As a consequence, this newer class of models gives Antarctic ice mass balance of approximately -81 ± 33 Gt/yr, or 0.225 ± 0.092 mm/yr contribution to sea-level rise. The new class of GIA models for Antarctica enhances the value of all GRACE Follow-On mission data.Mass Balance of AIS δM (Gt/yr);

  9. Comparison of precise orbit determination methods of zero-difference kinematic, dynamic and reduced-dynamic of GRACE-A satellite using SHORDE software

    Science.gov (United States)

    Li, Kai; Zhou, Xuhua; Guo, Nannan; Zhao, Gang; Xu, Kexin; Lei, Weiwei

    2017-09-01

    Zero-difference kinematic, dynamic and reduced-dynamic precise orbit determination (POD) are three methods to obtain the precise orbits of Low Earth Orbit satellites (LEOs) by using the on-board GPS observations. Comparing the differences between those methods have great significance to establish the mathematical model and is usefull for us to select a suitable method to determine the orbit of the satellite. Based on the zero-difference GPS carrier-phase measurements, Shanghai Astronomical Observatory (SHAO) has improved the early version of SHORDE and then developed it as an integrated software system, which can perform the POD of LEOs by using the above three methods. In order to introduce the function of the software, we take the Gravity Recovery And Climate Experiment (GRACE) on-board GPS observations in January 2008 as example, then we compute the corresponding orbits of GRACE by using the SHORDE software. In order to evaluate the accuracy, we compare the orbits with the precise orbits provided by Jet Propulsion Laboratory (JPL). The results show that: (1) If we use the dynamic POD method, and the force models are used to represent the non-conservative forces, the average accuracy of the GRACE orbit is 2.40cm, 3.91cm, 2.34cm and 5.17cm in radial (R), along-track (T), cross-track (N) and 3D directions respectively; If we use the accelerometer observation instead of non-conservative perturbation model, the average accuracy of the orbit is 1.82cm, 2.51cm, 3.48cm and 4.68cm in R, T, N and 3D directions respectively. The result shows that if we use accelerometer observation instead of the non-conservative perturbation model, the accuracy of orbit is better. (2) When we use the reduced-dynamic POD method to get the orbits, the average accuracy of the orbit is 0.80cm, 1.36cm, 2.38cm and 2.87cm in R, T, N and 3D directions respectively. This method is carried out by setting up the pseudo-stochastic pulses to absorb the errors of atmospheric drag and other perturbations. (3) If we use the kinematic POD method, the accuracy of the GRACE orbit is 2.92cm, 2.48cm, 2.76cm and 4.75cm in R, T, N and 3D directions respectively. In conclusion, it can be seen that the POD of GRACE satellite is practicable by using different strategies and methods. The orbit solution is well and stable, they all can obtain the GRACE orbits with centimeter-level precision.

  10. Reprezentace homosexuality v americkém sitcomu na příkladu Will a Grace a Taková moderní rodinka

    OpenAIRE

    Hofmanová, Zuzana

    2017-01-01

    The diploma theses "Representation of Homosexuality in American Sitcom, as exemplified by Will & Grace and Modern Family" examines the portrayal of minority groups on television. Initially vilified as perverts and abominations, homosexual individuals are now seen as complex characters that buck older stigmatization and stereotypes. These changes can be exemplified and documented across different popular genres currently on television. However, a sitcom is a genre defined by specific rules. Th...

  11. Project GRACE: a staged approach to development of a community-academic partnership to address HIV in rural African American communities.

    Science.gov (United States)

    Corbie-Smith, Giselle; Adimora, Adaora A; Youmans, Selena; Muhammad, Melvin; Blumenthal, Connie; Ellison, Arlinda; Akers, Aletha; Council, Barbara; Thigpen, Yolanda; Wynn, Mysha; Lloyd, Stacey W

    2011-03-01

    The HIV epidemic is a health crisis in rural African American communities in the Southeast United States; however, to date little attention has been paid to community-academic collaborations to address HIV in these communities. Interventions that use a community-based participatory research (CBPR) approach to address individual, social, and physical environmental factors have great potential for improving community health. Project GRACE (Growing, Reaching, Advocating for Change and Empowerment) uses a CBPR approach to develop culturally sensitive, feasible, and sustainable interventions to prevent the spread of HIV in rural African American communities. This article describes a staged approach to community-academic partnership: initial mobilization, establishment of organizational structure, capacity building for action, and planning for action. Strategies for engaging rural community members at each stage are discussed; challenges faced and lessons learned are also described. Careful attention to partnership development has resulted in a collaborative approach that has mutually benefited both the academic and community partners.

  12. Preprocessing of PHERMEX flash radiographic images with Haar and adaptive filtering

    International Nuclear Information System (INIS)

    Brolley, J.E.

    1978-11-01

    Work on image preparation has continued with the application of high-sequency boosting via Haar filtering. This is useful in developing line or edge structures. Widrow LMS adaptive filtering has also been shown to be useful in developing edge structure in special problems. Shadow effects can be obtained with the latter which may be useful for some problems. Combined Haar and adaptive filtering is illustrated for a PHERMEX image

  13. Preprocessing of gravity gradients at the GOCE high-level processing facility

    NARCIS (Netherlands)

    Bouman, J.; Rispens, S.; Gruber, T.; Koop, R.; Schrama, E.; Visser, P.; Tscherning, C.C.; Veicherts, M.

    2008-01-01

    One of the products derived from the gravity field and steady-state ocean circulation explorer (GOCE) observations are the gravity gradients. These gravity gradients are provided in the gradiometer reference frame (GRF) and are calibrated in-flight using satellite shaking and star sensor data. To

  14. Impact of an innovated storage technology on the quality of preprocessed switchgrass bales

    Directory of Open Access Journals (Sweden)

    Christopher N. Boyer

    2016-03-01

    Full Text Available The purpose of this study was to determine the effects of three particle sizes of feedstock and two types of novel bale wraps on the quality of switchgrass by monitoring the chemical changes in cellulose, hemicellulose, lignin, extractives, and ash over a 225-day period. Using NIR (Near-infrared modeling to predict the chemical composition of the treated biomass, differences were found in cellulose, lignin, and ash content across switchgrass bales with different particle sizes. Enclosing bales in a net and film impacted the cellulose, lignin, and ash content. Cellulose, hemicellulose, lignin, extractives, and ash were different across the 225-day storage period. A quadratic response function made better prediction about cellulose, lignin, and ash response to storage, and a linear response function best described hemicellulose and extractives response to storage. This study yields valuable information regarding the quality of switchgrass at different intervals between the start and end date of storage, which is important to conversion facilities when determining optimal storage strategies to improve quality of the biomass feedstock, based on potential output yield of a bale over time.

  15. A Fuzzy Preprocessing Module for Optimizing the Access Network Selection in Wireless Networks

    Directory of Open Access Journals (Sweden)

    Faisal Kaleem

    2013-01-01

    Full Text Available A heterogeneous wireless network is characterized by the presence of different wireless access technologies that coexist in an overlay fashion. These wireless access technologies usually differ in terms of their operating parameters. On the other hand, Mobile Stations (MSs in a heterogeneous wireless network are equipped with multiple interfaces to access different types of services from these wireless access technologies. The ultimate goal of these heterogeneous wireless networks is to provide global connectivity with efficient ubiquitous computing to these MSs based on the Always Best Connected (ABC principle. This is where the need for intelligent and efficient Vertical Handoffs (VHOs between wireless technologies in a heterogeneous environment becomes apparent. This paper presents the design and implementation of a fuzzy multicriteria based Vertical Handoff Necessity Estimation (VHONE scheme that determines the proper time for VHO, while considering the continuity and quality of the currently utilized service, and the end-users' satisfaction.

  16. Cryofracture as a tool for preprocessing retrieved buried and stored transuranic waste

    International Nuclear Information System (INIS)

    Loomis, G.G.; Winberg, M.R.; Ancho, M.L.; Osborne, D.

    1992-01-01

    This paper summarizes important features of an experimental demonstration of applying the Cryofracture process to size-reduce retrieved buried and stored transuranic-contaminated wastes. By size reducing retrieved buried and stored waste, treatment technologies such as thermal treatment can be expedited. Additionally, size reduction of the waste can decrease the amount of storage space required by reducing the volume requirements of storage containers. A demonstration program was performed at the Cryofracture facility by Nuclear Remedial Technologies for the Idaho National Engineering Laboratory. Cryofracture is a size-reducing process whereby objects are frozen to liquid nitrogen temperatures and crushed in a large hydraulic press. Material s at cryogenic temperatures have low ductility and are easily size-reduced by fracturing. Six 55-gallon drums and six 2 x 2 x 8 ft boxes containing simulated waste with tracers were subjected to the Cryofracture process. Data was obtained on (a) cool-down time, (b) yield strength of the containers, (c) size distribution of the waste before and after the Cryofracture process, (d) volume reduction of the waste, and (e) sampling of air and surface dusts for spread of tracers to evaluate potential contamination spread. The Cryofracture process was compared to conventional shredders and detailed cost estimates were established for construction of a Cryofracture facility at the Idaho National Engineering Laboratory

  17. Joint Preprocesser-Based Detectors for One-Way and Two-Way Cooperative Communication Networks

    KAUST Repository

    Abuzaid, Abdulrahman I.

    2014-01-01

    Efficient receiver designs for cooperative communication networks are becoming increasingly important. In previous work, cooperative networks communicated with the use of L relays. As the receiver is constrained, channel shortening and reduced

  18. Depth Value Pre-Processing for Accurate Transfer Learning Based RGB-D Object Recognition

    DEFF Research Database (Denmark)

    Aakerberg, Andreas; Nasrollahi, Kamal; Rasmussen, Christoffer Bøgelund

    2017-01-01

    of an existing deeplearning based RGB-D object recognition model, namely the FusionNet proposed by Eitel et al. First, we showthat encoding the depth values as colorized surface normals is beneficial, when the model is initialized withweights learned from training on ImageNet data. Additionally, we show...

  19. Pre-Processing Data Using Wavelet Transform and PCA Based on ...

    Indian Academy of Sciences (India)

    5

    wavelet theory in the last century, using this tool in the hydrology has been an ... These models are based on Statistical Learning Theory, which is ...... Hutcheson G and Nick S 1999 The multivariate social scientist: Introductory statistics using.

  20. Sabah snake grass extract pre-processing: Preliminary studies in drying and fermentation

    Science.gov (United States)

    Solibun, A.; Sivakumar, K.

    2016-06-01

    Clinacanthus nutans (Burm. F.) Lindau which also known as ‘Sabah Snake Grass’ among Malaysians have been studied in terms of its medicinal and chemical properties in Asian countries which is used to treat various diseases from cancer to viral-related diseases such as varicella-zoster virus lesions. Traditionally, this plant has been used by the locals to treat insect and snake bites, skin rashes, diabetes and dysentery. In Malaysia, the fresh leaves of this plant are usually boiled with water and consumed as herbal tea. The objectives of this study are to determine the key process parameters for Sabah Snake Grass fermentation which affect the chemical and biological constituent concentrations within the tea, extraction kinetics of fermented and unfermented tea and the optimal process parameters for the fermentation of this tea. Experimental methods such as drying, fermenting and extraction of C.nutans leaves were conducted before subjecting them to analysis of antioxidant capacity. Conventional oven- dried (40, 45 and 50°C) and fermented (6, 12 and 18 hours) whole C.nutans leaves were subjected to tea infusion extraction (water temperature was 80°C, duration was 90 minutes) and the sample liquid was extracted for every 5th, 10th, 15th, 25th, 40th, 60th and 90th minute. Analysis for antioxidant capacity and total phenolic content (TPC) were conducted by using 2, 2-diphenyl-1-pycryl-hydrazyl (DPPH) and Folin-Ciocaltheu reagent, respectively. The 40°C dried leaves sample produced the highest phenolic content at 0.1344 absorbance value in 15 minutes of extraction while 50°C dried leaves sample produced 0.1298 absorbance value in 10 minutes of extraction. The highest antioxidant content was produced by 50°C dried leaves sample with absorbance value of 1.6299 in 5 minutes of extraction. For 40°C dried leaves sample, the highest antioxidant content could be observed in 25 minutes of extraction with the absorbance value of 1.1456. The largest diameter of disc that could be observed at 18 hours of fermentation sample had a pile size of 3 cm that had expanded to 5.9 cm of diameter which indicated the microbe's growth.

  1. CNNs flag recognition preprocessing scheme based on gray scale stretching and local binary pattern

    Science.gov (United States)

    Gong, Qian; Qu, Zhiyi; Hao, Kun

    2017-07-01

    Flag is a rather special recognition target in image recognition because of its non-rigid features with the location, scale and rotation characteristics. The location change can be handled well by the depth learning algorithm Convolutional Neural Networks (CNNs), but the scale and rotation changes are quite a challenge for CNNs. Since it has good rotation and gray scale invariance, the local binary pattern (LBP) is combined with grayscale stretching and CNNs to make LBP and grayscale stretching as CNNs pretreatment, which can not only significantly improve the efficiency of flag recognition, but can also evaluate the recognition effect through ROC, accuracy, MSE and quality factor.

  2. Atmospheric dispersion models and pre-processing of meteorological data for real-time application

    DEFF Research Database (Denmark)

    Mikkelsen, T.; Desiato, F.

    1993-01-01

    RODOS is a real-time and on-line decision support system for assisting emergency response in the case of a nuclear emergency. The system is presently under development within the CEC Radiation Protection Programme as a joint venture between several European institutes. This paper identifies, ranks...

  3. Tomography of images with poisson miose: pre-processing of projections

    International Nuclear Information System (INIS)

    Furuie, S.S.

    1989-01-01

    This work present an alternative approach in order to reconstruct images with low signal to noise ratio. Basically it consist of smoothing projections taking into account that the noise is Poisson. These filtered projections are used to reconstruct the original image, applying direct Fourier method. This approach is compared with convolution back projection and EM (Expectation-Maximization). (author) [pt

  4. Dominant distortion classification for pre-processing of vowels in remote biomedical voice analysis

    DEFF Research Database (Denmark)

    Poorjam, Amir Hossein; Jensen, Jesper Rindom; Little, Max A

    2017-01-01

    for pathological voice assessments and investigate the impact of four major types of distortion that are commonly present during recording or transmission in voice analysis, namely: background noise, reverberation, clipping and compression, on Mel-frequency cepstral coefficients (MFCCs) – the most widely...

  5. Integrated Analytical Evaluation and Optimization of Model Parameters against Preprocessed Measurement Data

    Science.gov (United States)

    1989-06-23

    lags in hours for which these maxima occur. Often the night-side results contain two maxima in their dependence on lag, one at zero lag, and the other...Besides the VMS operating system sofware , the workstation also includes a User Interface Services graphics package, which is a collectio;. of FORTRAN

  6. Marine sediment sample pre-processing for macroinvertebrates metabarcoding: mechanical enrichment and homogenization

    Directory of Open Access Journals (Sweden)

    Eva Aylagas

    2016-10-01

    Full Text Available Metabarcoding is an accurate and cost-effective technique that allows for simultaneous taxonomic identification of multiple environmental samples. Application of this technique to marine benthic macroinvertebrate biodiversity assessment for biomonitoring purposes requires standardization of laboratory and data analysis procedures. In this context, protocols for creation and sequencing of amplicon libraries and their related bioinformatics analysis have been recently published. However, a standardized protocol describing all previous steps (i.e. processing and manipulation of environmental samples for macroinvertebrate community characterization is lacking. Here, we provide detailed procedures for benthic environmental sample collection, processing, enrichment for macroinvertebrates, homogenization, and subsequent DNA extraction for metabarcoding analysis. Since this is the first protocol of this kind, it should be of use to any researcher in this field, having the potential for improvement.

  7. Poisson pre-processing of nonstationary photonic signals: Signals with equality between mean and variance

    Czech Academy of Sciences Publication Activity Database

    Poplová, Michaela; Sovka, P.; Cifra, Michal

    2017-01-01

    Roč. 12, č. 12 (2017), č. článku e0188622. E-ISSN 1932-6203 R&D Projects: GA ČR(CZ) GA13-29294S Grant - others:AV ČR(CZ) SAV-15-22 Program:Bilaterální spolupráce Institutional support: RVO:67985882 Keywords : Poisson distribution * Photons * Neutrophils Subject RIV: JB - Sensors, Measurment, Regulation OBOR OECD: Electrical and electronic engineering Impact factor: 2.806, year: 2016

  8. Evaluation of Two Absolute Radiometric Normalization Algorithms for Pre-processing of Landsat Imagery

    Institute of Scientific and Technical Information of China (English)

    Xu Hanqiu

    2006-01-01

    In order to evaluate radiometric normalization techniques, two image normalization algorithms for absolute radiometric correction of Landsat imagery were quantitatively compared in this paper, which are the Illumination Correction Model proposed by Markham and Irish and the Illumination and Atmospheric Correction Model developed by the Remote Sensing and GIS Laboratory of the Utah State University. Relative noise, correlation coefficient and slope value were used as the criteria for the evaluation and comparison, which were derived from pseudo-invariant features identified from multitemtween the normalized multitemporal images were significantly reduced when the seasons of multitemporal images were different. However, there was no significant difference between the normalized and unnormalized images with a similar seasonal condition. Furthermore, the correction results of two algorithms are similar when the images are relatively clear with a uniform atmospheric condition. Therefore, the radiometric normalization procedures should be carried out if the multitemporal images have a significant seasonal difference.

  9. Supervised pre-processing approaches in multiple class variables classification for fish recruitment forecasting

    KAUST Repository

    Fernandes, José Antonio; Lozano, Jose A.; Iñ za, Iñ aki; Irigoien, Xabier; Pé rez, Aritz; Rodrí guez, Juan Diego

    2013-01-01

    A multi-species approach to fisheries management requires taking into account the interactions between species in order to improve recruitment forecasting of the fish species. Recent advances in Bayesian networks direct the learning of models

  10. Viability assessment of regional biomass pre-processing center based bioethanol value chains

    Science.gov (United States)

    Carolan, Joseph E.

    Petroleum accounts for 94% of all liquid fuels and 36% of the total of all energy consumed in the United States. Petroleum dependence is problematic because global petroleum reserves are estimated to last only for 40 to 60 years at current consumption rates; global supplies are often located in politically unstable or unfriendly regions; and fossil fuels have negative environmental footprints. Domestic policies have aimed at promoting alternative, renewable liquid fuels, specifically bio-fuels derived from organic matter. Cellulosic bio-ethanol is one promising alternative fuel that has featured prominently in federal bio-fuel mandates under the Energy Independence and Security Act, 2007. However, the cellulosic bio-ethanol industry faces several technical, physical and industrial organization challenges. This dissertation examines the concept of a network of regional biomass pre-treatment centers (RBPC) that form an extended biomass supply chain feeding into a simplified biorefinery as a way to overcome these challenges. The analyses conducted address the structural and transactional issues facing bio-ethanol value chain establishment; the technical and financial feasibility of a stand alone pre-treatment center (RBPC); the impact of distributed pre-treatment on biomass transport costs; a comparative systems cost evaluation of the performance of the RBPC chain versus a fully integrated biorefinery (gIBRh), followed by application of the analytical framework to three case study regions.

  11. Unmixing-Based Denoising as a Pre-Processing Step for Coral Reef Analysis

    Science.gov (United States)

    Cerra, D.; Traganos, D.; Gege, P.; Reinartz, P.

    2017-05-01

    Coral reefs, among the world's most biodiverse and productive submerged habitats, have faced several mass bleaching events due to climate change during the past 35 years. In the course of this century, global warming and ocean acidification are expected to cause corals to become increasingly rare on reef systems. This will result in a sharp decrease in the biodiversity of reef communities and carbonate reef structures. Coral reefs may be mapped, characterized and monitored through remote sensing. Hyperspectral images in particular excel in being used in coral monitoring, being characterized by very rich spectral information, which results in a strong discrimination power to characterize a target of interest, and separate healthy corals from bleached ones. Being submerged habitats, coral reef systems are difficult to analyse in airborne or satellite images, as relevant information is conveyed in bands in the blue range which exhibit lower signal-to-noise ratio (SNR) with respect to other spectral ranges; furthermore, water is absorbing most of the incident solar radiation, further decreasing the SNR. Derivative features, which are important in coral analysis, result greatly affected by the resulting noise present in relevant spectral bands, justifying the need of new denoising techniques able to keep local spatial and spectral features. In this paper, Unmixing-based Denoising (UBD) is used to enable analysis of a hyperspectral image acquired over a coral reef system in the Red Sea based on derivative features. UBD reconstructs pixelwise a dataset with reduced noise effects, by forcing each spectrum to a linear combination of other reference spectra, exploiting the high dimensionality of hyperspectral datasets. Results show clear enhancements with respect to traditional denoising methods based on spatial and spectral smoothing, facilitating the coral detection task.

  12. Double-Sided Sliding-Paraboloid (DSSP): A new tool for preprocessing GPR data

    Science.gov (United States)

    Rashed, Mohamed; Rashed, Essam A.

    2017-05-01

    Background noise in Ground Penetrating Radar (GPR) data is a nagging problem that degrades the quality of GPR images and increases their ambiguity. There are several methods adopting different strategies to remove background noise. In this study, we present the Double-Sided Sliding-Paraboloid (DSSP) as a new background removal technique. Experiments conducted on field GPR data show that the proposed DSSP technique has several advantages over existing background removal techniques. DSSP removes background noise more efficiently while preserving first arrivals and other strong horizontal reflections. Moreover, DSSP introduces no artifacts to GPR data and corrects data for DC-shift and wow noise.

  13. A novel passive microfluidic device for preprocessing whole blood for point of care diagnostics

    DEFF Research Database (Denmark)

    Shah, Pranjul Jaykumar; Dimaki, Maria; Svendsen, Winnie Edith

    2009-01-01

    integration of electrodes, traps, reservoirs, heaters, etc which is often difficult at microscale [1 – 4]. On the other hand, FACSlyse protocol uses only osmotic pressure to lyse erythrocytes allowing further isolation of leukocytes. This motivated us to develop a novel herringbone based lyser which works...... on the principle of mixing whole blood with pure water in time controlled manner to lyse erythrocytes osmotically on a chip....

  14. Biomass Supply and Trade Opportunities of Preprocessed Biomass for Power Generation

    NARCIS (Netherlands)

    Batidzirai, B.; Junginger, M.; Klemm, M.; Schipfer, F.; Thrän, D.

    2016-01-01

    International trade of solid biomass is expected to increase significantly given the global distribution of biomass resources and anticipated expansion of bioenergy deployment in key global power markets. Given the unique characteristics of biomass, its long-distance trade requires optimized

  15. Erosion risk assessment in the southern Amazon - Data Preprocessing, data base application and process based modelling

    Science.gov (United States)

    Schindewolf, Marcus; Herrmann, Marie-Kristin; Herrmann, Anne-Katrin; Schultze, Nico; Amorim, Ricardo S. S.; Schmidt, Jürgen

    2015-04-01

    The study region along the BR 16 highway belongs to the "Deforestation Arc" at the southern border of the Amazon rainforest. At the same time, it incorporates a land use gradient as colonization started in the 1975-1990 in Central Mato Grosso in 1990 in northern Mato Grosso and most recently in 2004-2005 in southern Pará. Based on present knowledge soil erosion is one of the key driver of soil degradation. Hence, there is a strong need to implement soil erosion control measures in eroding landscapes. Planning and dimensioning of such measures require reliable and detailed information on the temporal and spatial distribution of soil loss, sediment transport and deposition. Soil erosion models are increasingly used, in order to simulate the physical processes involved and to predict the effects of soil erosion control measures. The process based EROSION 3D simulation model is used for surveying soil erosion and deposition on regional catchments. Although EROSION 3D is a widespread, extensively validated model, the application of the model on regional scale remains challenging due to the enormous data requirements and complex data processing operations. In this context the study includes the compilation, validation and generalisation of existing land use and soil data in order to generate a consistent EROSION 3D input datasets. As a part of this process a GIS-linked data base application allows to transfer the original soil and land use data into model specific parameter files. This combined methodology provides different risk assessment maps for certain demands on regional scale. Besides soil loss and sediment transport, sediment pass over points into surface water bodies and particle enrichment can be simulated using the EROSION 3D model. Thus the estimation of particle bound nutrient and pollutant inputs into surface water bodies becomes possible. The study ended up in a user-friendly, timesaving and improved software package for the simulation of soil loss and deposition on a regional scale providing essential information for the planning of soil and water conservation measures particularly under consideration of expected land use and climate changes.

  16. SALOME. A software integration platform for multi-physics, pre-processing and visualisation

    International Nuclear Information System (INIS)

    Bergeaud, Vincent; Lefebvre, Vincent

    2010-01-01

    In order to ease the development of applications integrating simulation codes, CAD modelers and post-processing tools. CEA and EDF R and D have invested in the SALOME platform, a tool dedicated to the environment of the scientific codes. The platform comes in the shape of a toolbox which offers functionalities for CAD, meshing, code coupling, visualization, GUI development. These tools can be combined to create integrated applications that make the scientific codes easier to use and well-interfaced with their environment be it other codes, CAD and meshing tools or visualization software. Many projects in CEA and EDF R and D now use SALOME, bringing technical coherence to the software suites of our institutions. (author)

  17. Comparing Binaural Pre-processing Strategies II: Speech Intelligibility of Bilateral Cochlear Implant Users.

    Science.gov (United States)

    Baumgärtel, Regina M; Hu, Hongmei; Krawczyk-Becker, Martin; Marquardt, Daniel; Herzke, Tobias; Coleman, Graham; Adiloğlu, Kamil; Bomke, Katrin; Plotz, Karsten; Gerkmann, Timo; Doclo, Simon; Kollmeier, Birger; Hohmann, Volker; Dietz, Mathias

    2015-12-30

    Several binaural audio signal enhancement algorithms were evaluated with respect to their potential to improve speech intelligibility in noise for users of bilateral cochlear implants (CIs). 50% speech reception thresholds (SRT50) were assessed using an adaptive procedure in three distinct, realistic noise scenarios. All scenarios were highly nonstationary, complex, and included a significant amount of reverberation. Other aspects, such as the perfectly frontal target position, were idealized laboratory settings, allowing the algorithms to perform better than in corresponding real-world conditions. Eight bilaterally implanted CI users, wearing devices from three manufacturers, participated in the study. In all noise conditions, a substantial improvement in SRT50 compared to the unprocessed signal was observed for most of the algorithms tested, with the largest improvements generally provided by binaural minimum variance distortionless response (MVDR) beamforming algorithms. The largest overall improvement in speech intelligibility was achieved by an adaptive binaural MVDR in a spatially separated, single competing talker noise scenario. A no-pre-processing condition and adaptive differential microphones without a binaural link served as the two baseline conditions. SRT50 improvements provided by the binaural MVDR beamformers surpassed the performance of the adaptive differential microphones in most cases. Speech intelligibility improvements predicted by instrumental measures were shown to account for some but not all aspects of the perceptually obtained SRT50 improvements measured in bilaterally implanted CI users. © The Author(s) 2015.

  18. Safe and sensible preprocessing and baseline correction of pupil-size data

    NARCIS (Netherlands)

    Mathôt, Sebastiaan; Fabius, Jasper; Van Heusden, Elle; Van der Stigchel, Stefan

    Measurement of pupil size (pupillometry) has recently gained renewed interest from psychologists, but there is little agreement on how pupil-size data is best analyzed. Here we focus on one aspect of pupillometric analyses: baseline correction, i.e., analyzing changes in pupil size relative to a

  19. Safe and sensible preprocessing and baseline correction of pupil-size data

    NARCIS (Netherlands)

    Mathôt, Sebastiaan; Fabius, Jasper; Van Heusden, Elle; Van der Stigchel, Stefan

    2018-01-01

    Measurement of pupil size (pupillometry) has recently gained renewed interest from psychologists, but there is little agreement on how pupil-size data is best analyzed. Here we focus on one aspect of pupillometric analyses: baseline correction, that is, analyzing changes in pupil size relative to a

  20. Preprocessing the Nintendo Wii Board Signal to Derive More Accurate Descriptors of Statokinesigrams.

    Science.gov (United States)

    Audiffren, Julien; Contal, Emile

    2016-08-01

    During the past few years, the Nintendo Wii Balance Board (WBB) has been used in postural control research as an affordable but less reliable replacement for laboratory grade force platforms. However, the WBB suffers some limitations, such as a lower accuracy and an inconsistent sampling rate. In this study, we focus on the latter, namely the non uniform acquisition frequency. We show that this problem, combined with the poor signal to noise ratio of the WBB, can drastically decrease the quality of the obtained information if not handled properly. We propose a new resampling method, Sliding Window Average with Relevance Interval Interpolation (SWARII), specifically designed with the WBB in mind, for which we provide an open source implementation. We compare it with several existing methods commonly used in postural control, both on synthetic and experimental data. The results show that some methods, such as linear and piecewise constant interpolations should definitely be avoided, particularly when the resulting signal is differentiated, which is necessary to estimate speed, an important feature in postural control. Other methods, such as averaging on sliding windows or SWARII, perform significantly better on synthetic dataset, and produce results more similar to the laboratory-grade AMTI force plate (AFP) during experiments. Those methods should be preferred when resampling data collected from a WBB.

  1. Preprocessing in Matlab Inconsistent Linear System for a Meaningful Least Squares Solution

    Science.gov (United States)

    Sen, Symal K.; Shaykhian, Gholam Ali

    2011-01-01

    Mathematical models of many physical/statistical problems are systems of linear equations Due to measurement and possible human errors/mistakes in modeling/data, as well as due to certain assumptions to reduce complexity, inconsistency (contradiction) is injected into the model, viz. the linear system. While any inconsistent system irrespective of the degree of inconsistency has always a least-squares solution, one needs to check whether an equation is too much inconsistent or, equivalently too much contradictory. Such an equation will affect/distort the least-squares solution to such an extent that renders it unacceptable/unfit to be used in a real-world application. We propose an algorithm which (i) prunes numerically redundant linear equations from the system as these do not add any new information to the model, (ii) detects contradictory linear equations along with their degree of contradiction (inconsistency index), (iii) removes those equations presumed to be too contradictory, and then (iv) obtain the . minimum norm least-squares solution of the acceptably inconsistent reduced linear system. The algorithm presented in Matlab reduces the computational and storage complexities and also improves the accuracy of the solution. It also provides the necessary warning about the existence of too much contradiction in the model. In addition, we suggest a thorough relook into the mathematical modeling to determine the reason why unacceptable contradiction has occurred thus prompting us to make necessary corrections/modifications to the models - both mathematical and, if necessary, physical.

  2. Application of artificial neural networks for versatile preprocessing of electrocardiogram recordings.

    Science.gov (United States)

    Mateo, J; Rieta, J J

    2012-02-01

    The electrocardiogram (ECG) is the most widely used method for diagnosis of heart diseases, where a good quality of recordings allows the proper interpretation and identification of physiological and pathological phenomena. However, ECG recordings often have interference from noises including thermal, muscle, baseline and powerline noises. These signals severely limit ECG recording utility and, hence, have to be removed. To deal with this problem, the present paper proposes an artificial neural network (ANN) as a filter to remove all kinds of noise in just one step. The method is based on a growing ANN which optimizes both the number of nodes in the hidden layer and the coefficient matrices, which are optimized by means of the Widrow-Hoff delta algorithm. The ANN has been trained with a database comprising all kinds of noise, both from synthesized and real ECG recordings, in order to handle any noise signal present in the ECG. The proposed system improves results yielded by conventional techniques of ECG filtering, such as FIR-based systems, adaptive filtering and wavelet filtering. Therefore, the algorithm could serve as an effective framework to substantially reduce noise in ECG recordings. In addition, the resulting ECG signal distortion is notably more reduced in comparison with conventional methodologies. In summary, the current contribution introduces a new method which is able to suppress all ECG interference signals in only one step with low ECG distortion and a high noise reduction.

  3. Development of integrated superconducting devices for signal preprocessing. Final report; Entwicklung supraleitender Bausteine der Signalvorverarbeitung. Abschlussbericht

    Energy Technology Data Exchange (ETDEWEB)

    Biehl, M.; Koch, R.; Neuhaus, M.; Scherer, T.; Jutzi, W.

    1998-02-01

    SPICE and CADENCE based tools for designing, simulating and optimizing SFQ and RSFQ circuits have been developed as well as a standard cell library corresponding to the fabrication technology established at the IEGI. A 12 bit flux shuttle shift register using Nb/Al Josephson junctions with a new write and readout gate has been fabricated and tested successfully; the power dissipation is 9 nW/bit/GHz. A pseudo random pulse generator was developed correspondingly. Simulations of RSFQ toggle flipflops during a large number of clock cycles demonstrated that the digital performance of counters is limited to clock frequencies below 100 GHz by dynamic effects, especially of parasitic inductances. Therefore dc measurements based on the voltage-frequency Josephson relationship must be followed by real time measurements of single SFQ word pulses. A four stage Nb based RSFQ counter in a coplanar waveguide test jig was tested up to a frequency of 2 GHz, limited by the available 32 bit pattern generator and the bandwith of the sampling oscilloscope, yielding bit error rates of about 10{sup -12}. Using YBCO technology, a 4 bit SFQ shift register (T=40 K) as well as miniaturized coplanar microwave devices for satellite and communication applications at 10 GHz (T=77 K) have been designed and fabricated. A 4 bit instantaneous real time frequency meter (IFM) and a microwave filter with a 3-dB bandwidth of only 1.8% have been mounted on the cold head of a split-cycle Stirling cooler (AEG, 1.5 W rate at 80 K) and tested successfully. Hybrid devices, e.g. amplifiers and oscillators, combining active semiconductor components and low loss coplanar YBCO transmission lines operated at 77 K seem very promising. (orig.) [Deutsch] Werkzeuge der Auslegung, Simulation und Optimierung von SFQ- und RSFQ-Schaltungen auf der Basis von SPICE und CADENCE wurden am IEGI entwickelt und eingesetzt. Eine auf die Technologien des Instituts zugeschnittene Bibliothek von Zellen ist vorhanden. Mit der bewaehrten Niob-Technologie wurde ein 12 bit SFQ-Schieberegister mit einer Schreib- und Leseschaltung und mit extrem kleiner Verlustleistung von 9 nW/bit/GHz hergestellt und impulsmaessig vermessen. Nach dem gleichen Prinzip wurde ein Zufallsimpulsgenerator ausgelegt. Die Simulation von RSFQ-Toggle-Flipflops mit einer grossen Zahl von Eingangsimpulsen zeigte, dass dynamische Effekte besonders durch Streuinduktivitaeten den digitalen Zaehlerbetrieb auf Taktfrequenzen unter 100 GHz begrenzen koennen, obwohl Gleichspannungsmessungen einen einwandfreien Betrieb bei hoeheren Frequenzen erwarten lassen. Daher sind Echtzeitmessungen der einzelnen SFQ-Impulse eines Wortes notwendig. Echtzeitmessungen mit einem Abtastoszillographen an einem 4-stufigen RSFQ-Zaehler der Niob-Technologie mit entsprechend breitbandiger Leitungszufuehrung ergaben bis zur Grenzfrequenz eines vorhandenen 32 bit Wortgenerators bei 2 GHz Bitfehlerraten um 10{sup -12}. Mit der YBCO-Technologie wurden ein 4 bit SFQ-Schieberegister fuer 40 K und miniaturisierte koplanare Mikrowellenschaltungen fuer die Satelliten- und Kommunikationstechnik um 10 GHz fuer 77 K ausgelegt und implementiert. Ein 4 bit Echtzeitfrequenzmesser und ein Filter mit einer 3 dB-Bandbreite von nur 1,8% wurden im IEGI erfolgreich auf dem Kaltkopf eines AEG-Kleinkuehlers ausgemessen. Hybride Schaltungen, z.B. Verstaerker und Oszillatoren, mit aktiven Halbleiterbauelementen und koplanaren YBCO-Verbindungen mit geringen Verlusten koennen bei 77 KJ interessante Eigenschaften besitzen. (orig.)

  4. A new preprocessing parameter estimation based on geodesic active contour model for automatic vestibular neuritis diagnosis.

    Science.gov (United States)

    Ben Slama, Amine; Mouelhi, Aymen; Sahli, Hanene; Manoubi, Sondes; Mbarek, Chiraz; Trabelsi, Hedi; Fnaiech, Farhat; Sayadi, Mounir

    2017-07-01

    The diagnostic of the vestibular neuritis (VN) presents many difficulties to traditional assessment methods This paper deals with a fully automatic VN diagnostic system based on nystagmus parameter estimation using a pupil detection algorithm. A geodesic active contour model is implemented to find an accurate segmentation region of the pupil. Hence, the novelty of the proposed algorithm is to speed up the standard segmentation by using a specific mask located on the region of interest. This allows a drastically computing time reduction and a great performance and accuracy of the obtained results. After using this fast segmentation algorithm, the obtained estimated parameters are represented in temporal and frequency settings. A useful principal component analysis (PCA) selection procedure is then applied to obtain a reduced number of estimated parameters which are used to train a multi neural network (MNN). Experimental results on 90 eye movement videos show the effectiveness and the accuracy of the proposed estimation algorithm versus previous work. Copyright © 2017 Elsevier B.V. All rights reserved.

  5. Sensitivity testing practice on pre-processing parameters in hard and soft coupled modeling

    Directory of Open Access Journals (Sweden)

    Z. Ignaszak

    2010-01-01

    Full Text Available This paper pays attention to the problem of practical applicability of coupled modeling with the use of hard and soft models types and necessity of adapted to that models data base possession. The data base tests results for cylindrical 30 mm diameter casting made of AlSi7Mg alloy were presented. In simulation tests that were applied the Calcosoft system with CAFE (Cellular Automaton Finite Element module. This module which belongs to „multiphysics” models enables structure prediction of complete casting with division of columnar and equiaxed crystals zones of -phase. Sensitivity tests of coupled model on the particular values parameters changing were made. On these basis it was determined the relations of CET (columnar-to-equaiaxed transition zone position influence. The example of virtual structure validation based on real structure with CET zone location and grain size was shown.

  6. Pre-processing of dual-view FIGOS Data: towards operational BRDF retrieval

    OpenAIRE

    Hueni, A; Schopfer, J; Schläpfer, D; Kneubühler, M; Nieke, J

    2008-01-01

    The Bidirectional Reflectance Distribution Function (BRDF) is an inherent property of natural and manmade materials. Its effects depend on the illumination/observation geometry and wavelengths and are apparent in groundbased, airborne and spaceborne imagery. The BRDF is a fundamental quantity from which all other illumination/reflection configurations can be derived. Calibration and validation of hyperspectral images requires knowledge of the BRDF if spectrodirectional effects are to be accou...

  7. Information Pre-Processing using Domain Meta-Ontology and Rule Learning System

    Science.gov (United States)

    Ranganathan, Girish R.; Biletskiy, Yevgen

    Around the globe, extraordinary amounts of documents are being created by Enterprises and by users outside these Enterprises. The documents created in the Enterprises constitute the main focus of the present chapter. These documents are used to perform numerous amounts of machine processing. While using thesedocuments for machine processing, lack of semantics of the information in these documents may cause misinterpretation of the information, thereby inhibiting the productiveness of computer assisted analytical work. Hence, it would be profitable to the Enterprises if they use well defined domain ontologies which will serve as rich source(s) of semantics for the information in the documents. These domain ontologies can be created manually, semi-automatically or fully automatically. The focus of this chapter is to propose an intermediate solution which will enable relatively easy creation of these domain ontologies. The process of extracting and capturing domain ontologies from these voluminous documents requires extensive involvement of domain experts and application of methods of ontology learning that are substantially labor intensive; therefore, some intermediate solutions which would assist in capturing domain ontologies must be developed. This chapter proposes a solution in this direction which involves building a meta-ontology that will serve as an intermediate information source for the main domain ontology. This chapter proposes a solution in this direction which involves building a meta-ontology as a rapid approach in conceptualizing a domain of interest from huge amount of source documents. This meta-ontology can be populated by ontological concepts, attributes and relations from documents, and then refined in order to form better domain ontology either through automatic ontology learning methods or some other relevant ontology building approach.

  8. Identification and verification of ultrafine particle affinity zones in urban neighbourhoods: sample design and data pre-processing.

    LENUS (Irish Health Repository)

    Harris, Paul

    2009-01-01

    A methodology is presented and validated through which long-term fixed site air quality measurements are used to characterise and remove temporal signals in sample-based measurements which have good spatial coverage but poor temporal resolution. The work has been carried out specifically to provide a spatial dataset of atmospheric ultrafine particle (UFP < 100 nm) data for ongoing epidemiologic cohort analysis but the method is readily transferable to wider epidemiologic investigations and research into the health effects of other pollutant species.

  9. A First Step in Learning Analytics: Pre-Processing Low-Level Alice Logging Data of Middle School Students

    Science.gov (United States)

    Werner, Linda; McDowell, Charlie; Denner, Jill

    2013-01-01

    Educational data mining can miss or misidentify key findings about student learning without a transparent process of analyzing the data. This paper describes the first steps in the process of using low-level logging data to understand how middle school students used Alice, an initial programming environment. We describe the steps that were…

  10. Solving the challenges of data preprocessing, uploading, archiving, retrieval, analysis and visualization for large heterogeneous paleo- and rock magnetic datasets

    Science.gov (United States)

    Minnett, R.; Koppers, A. A.; Tauxe, L.; Constable, C.; Jarboe, N. A.

    2011-12-01

    The Magnetics Information Consortium (MagIC) provides an archive for the wealth of rock- and paleomagnetic data and interpretations from studies on natural and synthetic samples. As with many fields, most peer-reviewed paleo- and rock magnetic publications only include high level results. However, access to the raw data from which these results were derived is critical for compilation studies and when updating results based on new interpretation and analysis methods. MagIC provides a detailed metadata model with places for everything from raw measurements to their interpretations. Prior to MagIC, these raw data were extremely cumbersome to collect because they mostly existed in a lab's proprietary format on investigator's personal computers or undigitized in field notebooks. MagIC has developed a suite of offline and online tools to enable the paleomagnetic, rock magnetic, and affiliated scientific communities to easily contribute both their previously published data and data supporting an article undergoing peer-review, to retrieve well-annotated published interpretations and raw data, and to analyze and visualize large collections of published data online. Here we present the technology we chose (including VBA in Excel spreadsheets, Python libraries, FastCGI JSON webservices, Oracle procedures, and jQuery user interfaces) and how we implemented it in order to serve the scientific community as seamlessly as possible. These tools are now in use in labs worldwide, have helped archive many valuable legacy studies and datasets, and routinely enable new contributions to the MagIC Database (http://earthref.org/MAGIC/).

  11. A database application for pre-processing, storage and comparison of mass spectra derived from patients and controls.

    NARCIS (Netherlands)

    M.K. Titulaer (Mark); I. Siccama (Ivar); L.J.M. Dekker (Lennard); A.L. Rijswijk (Angelique); R.M. Heeren (Ron); P.A.E. Sillevis Smitt (Peter); T.M. Luider (Theo)

    2006-01-01

    textabstractBACKGROUND: Statistical comparison of peptide profiles in biomarker discovery requires fast, user-friendly software for high throughput data analysis. Important features are flexibility in changing input variables and statistical analysis of peptides that are differentially expressed

  12. A database application for pre-processing, storage and comparison of mass spectra derived from patients and controls

    Directory of Open Access Journals (Sweden)

    Sillevis Smitt Peter A

    2006-09-01

    Full Text Available Abstract Background Statistical comparison of peptide profiles in biomarker discovery requires fast, user-friendly software for high throughput data analysis. Important features are flexibility in changing input variables and statistical analysis of peptides that are differentially expressed between patient and control groups. In addition, integration the mass spectrometry data with the results of other experiments, such as microarray analysis, and information from other databases requires a central storage of the profile matrix, where protein id's can be added to peptide masses of interest. Results A new database application is presented, to detect and identify significantly differentially expressed peptides in peptide profiles obtained from body fluids of patient and control groups. The presented modular software is capable of central storage of mass spectra and results in fast analysis. The software architecture consists of 4 pillars, 1 a Graphical User Interface written in Java, 2 a MySQL database, which contains all metadata, such as experiment numbers and sample codes, 3 a FTP (File Transport Protocol server to store all raw mass spectrometry files and processed data, and 4 the software package R, which is used for modular statistical calculations, such as the Wilcoxon-Mann-Whitney rank sum test. Statistic analysis by the Wilcoxon-Mann-Whitney test in R demonstrates that peptide-profiles of two patient groups 1 breast cancer patients with leptomeningeal metastases and 2 prostate cancer patients in end stage disease can be distinguished from those of control groups. Conclusion The database application is capable to distinguish patient Matrix Assisted Laser Desorption Ionization (MALDI-TOF peptide profiles from control groups using large size datasets. The modular architecture of the application makes it possible to adapt the application to handle also large sized data from MS/MS- and Fourier Transform Ion Cyclotron Resonance (FT-ICR mass spectrometry experiments. It is expected that the higher resolution and mass accuracy of the FT-ICR mass spectrometry prevents the clustering of peaks of different peptides and allows the identification of differentially expressed proteins from the peptide profiles.

  13. A database application for pre-processing, storage and comparison of mass spectra derived from patients and controls.

    Science.gov (United States)

    Titulaer, Mark K; Siccama, Ivar; Dekker, Lennard J; van Rijswijk, Angelique L C T; Heeren, Ron M A; Sillevis Smitt, Peter A; Luider, Theo M

    2006-09-05

    Statistical comparison of peptide profiles in biomarker discovery requires fast, user-friendly software for high throughput data analysis. Important features are flexibility in changing input variables and statistical analysis of peptides that are differentially expressed between patient and control groups. In addition, integration the mass spectrometry data with the results of other experiments, such as microarray analysis, and information from other databases requires a central storage of the profile matrix, where protein id's can be added to peptide masses of interest. A new database application is presented, to detect and identify significantly differentially expressed peptides in peptide profiles obtained from body fluids of patient and control groups. The presented modular software is capable of central storage of mass spectra and results in fast analysis. The software architecture consists of 4 pillars, 1) a Graphical User Interface written in Java, 2) a MySQL database, which contains all metadata, such as experiment numbers and sample codes, 3) a FTP (File Transport Protocol) server to store all raw mass spectrometry files and processed data, and 4) the software package R, which is used for modular statistical calculations, such as the Wilcoxon-Mann-Whitney rank sum test. Statistic analysis by the Wilcoxon-Mann-Whitney test in R demonstrates that peptide-profiles of two patient groups 1) breast cancer patients with leptomeningeal metastases and 2) prostate cancer patients in end stage disease can be distinguished from those of control groups. The database application is capable to distinguish patient Matrix Assisted Laser Desorption Ionization (MALDI-TOF) peptide profiles from control groups using large size datasets. The modular architecture of the application makes it possible to adapt the application to handle also large sized data from MS/MS- and Fourier Transform Ion Cyclotron Resonance (FT-ICR) mass spectrometry experiments. It is expected that the higher resolution and mass accuracy of the FT-ICR mass spectrometry prevents the clustering of peaks of different peptides and allows the identification of differentially expressed proteins from the peptide profiles.

  14. Resting-state test-retest reliability of a priori defined canonical networks over different preprocessing steps.

    Science.gov (United States)

    Varikuti, Deepthi P; Hoffstaedter, Felix; Genon, Sarah; Schwender, Holger; Reid, Andrew T; Eickhoff, Simon B

    2017-04-01

    Resting-state functional connectivity analysis has become a widely used method for the investigation of human brain connectivity and pathology. The measurement of neuronal activity by functional MRI, however, is impeded by various nuisance signals that reduce the stability of functional connectivity. Several methods exist to address this predicament, but little consensus has yet been reached on the most appropriate approach. Given the crucial importance of reliability for the development of clinical applications, we here investigated the effect of various confound removal approaches on the test-retest reliability of functional-connectivity estimates in two previously defined functional brain networks. Our results showed that gray matter masking improved the reliability of connectivity estimates, whereas denoising based on principal components analysis reduced it. We additionally observed that refraining from using any correction for global signals provided the best test-retest reliability, but failed to reproduce anti-correlations between what have been previously described as antagonistic networks. This suggests that improved reliability can come at the expense of potentially poorer biological validity. Consistent with this, we observed that reliability was proportional to the retained variance, which presumably included structured noise, such as reliable nuisance signals (for instance, noise induced by cardiac processes). We conclude that compromises are necessary between maximizing test-retest reliability and removing variance that may be attributable to non-neuronal sources.

  15. Pre-Processing of Brands Versus Attentional: A Test of the Differences in the Registry of Stimulus by Individuals

    Directory of Open Access Journals (Sweden)

    Tais Pasquotto Andreoli

    2013-12-01

    Full Text Available Due to limited capacity of cognitive resources and to the saturation context of stimuli, becomes probably that a lot of available stimulus in the ambient don´t be actively processed, in a conscious manner, but yes unconsciously, at the preattentive level. Despite of the importance of preattentive processing, are few the studies that address and discuss its implications and function on stimuli reception. In the light of the above, the study has with aim to compare the preattentive and attentive processing in terms of advertiser brand registry, testing, for that, the implicit and explicit memory of individuals and their brand valuation. Methodologically, the study proceeded, initially, to the bibliographic survey, focusing on the follow conceptual bases: the attention process under a complex perspective, subdivided into preattention and attention, and the information registry in light of the processing level. Supported by the bibliographic survey, the study adopted the hypothetical-deduvito method, with the development of a experiment 2 (preattention x attention x 2 (magazine show in slide x impress.As contribution, the study support the traced hypotheses: large incidence of explicit memory of advertiser brands in attentive processing; implicit memory found in both processing; brand valuation effects higher when the preattentive processing happened, instead of when did attentive processing. The results find reinforce the theory about the registry differences according with the attention used on processing, highlighting, yet, the superiority of impress media and preattentive processing in the individual influence capacity.      

  16. Resting-state test-retest reliability of a priori defined canonical networks over different preprocessing steps

    NARCIS (Netherlands)

    Varikuti, D.P.; Hoffstaedter, F.; Genon, S.; Schwender, H.; Reid, A.T.; Eickhoff, S.B.

    2017-01-01

    Resting-state functional connectivity analysis has become a widely used method for the investigation of human brain connectivity and pathology. The measurement of neuronal activity by functional MRI, however, is impeded by various nuisance signals that reduce the stability of functional

  17. PREREM: an interactive data preprocessing code for INREM II. Part I: user's manual. Part II: code structure

    Energy Technology Data Exchange (ETDEWEB)

    Ryan, M.T.; Fields, D.E.

    1981-05-01

    PREREM is an interactive computer code developed as a data preprocessor for the INREM-II (Killough, Dunning, and Pleasant, 1978a) internal dose program. PREREM is intended to provide easy access to current and self-consistent nuclear decay and radionuclide-specific metabolic data sets. Provision is made for revision of metabolic data, and the code is intended for both production and research applications. Documentation for the code is in two parts. Part I is a user's manual which emphasizes interpretation of program prompts and choice of user input. Part II stresses internal structure and flow of program control and is intended to assist the researcher who wishes to revise or modify the code or add to its capabilities. PREREM is written for execution on a Digital Equipment Corporation PDP-10 System and much of the code will require revision before it can be run on other machines. The source program length is 950 lines (116 blocks) and computer core required for execution is 212 K bytes. The user must also have sufficient file space for metabolic and S-factor data sets. Further, 64 100 K byte blocks of computer storage space are required for the nuclear decay data file. Computer storage space must also be available for any output files produced during the PREREM execution. 9 refs., 8 tabs.

  18. mapDIA: Preprocessing and statistical analysis of quantitative proteomics data from data independent acquisition mass spectrometry.

    Science.gov (United States)

    Teo, Guoshou; Kim, Sinae; Tsou, Chih-Chiang; Collins, Ben; Gingras, Anne-Claude; Nesvizhskii, Alexey I; Choi, Hyungwon

    2015-11-03

    Data independent acquisition (DIA) mass spectrometry is an emerging technique that offers more complete detection and quantification of peptides and proteins across multiple samples. DIA allows fragment-level quantification, which can be considered as repeated measurements of the abundance of the corresponding peptides and proteins in the downstream statistical analysis. However, few statistical approaches are available for aggregating these complex fragment-level data into peptide- or protein-level statistical summaries. In this work, we describe a software package, mapDIA, for statistical analysis of differential protein expression using DIA fragment-level intensities. The workflow consists of three major steps: intensity normalization, peptide/fragment selection, and statistical analysis. First, mapDIA offers normalization of fragment-level intensities by total intensity sums as well as a novel alternative normalization by local intensity sums in retention time space. Second, mapDIA removes outlier observations and selects peptides/fragments that preserve the major quantitative patterns across all samples for each protein. Last, using the selected fragments and peptides, mapDIA performs model-based statistical significance analysis of protein-level differential expression between specified groups of samples. Using a comprehensive set of simulation datasets, we show that mapDIA detects differentially expressed proteins with accurate control of the false discovery rates. We also describe the analysis procedure in detail using two recently published DIA datasets generated for 14-3-3β dynamic interaction network and prostate cancer glycoproteome. The software was written in C++ language and the source code is available for free through SourceForge website http://sourceforge.net/projects/mapdia/.This article is part of a Special Issue entitled: Computational Proteomics. Copyright © 2015 Elsevier B.V. All rights reserved.

  19. Geometric and radiometric preprocessing of airborne visible/infrared imaging spectrometer (AVIRIS) data in rugged terrain for quantitative data analysis

    Science.gov (United States)

    Meyer, Peter; Green, Robert O.; Staenz, Karl; Itten, Klaus I.

    1994-01-01

    A geocoding procedure for remotely sensed data of airborne systems in rugged terrain is affected by several factors: buffeting of the aircraft by turbulence, variations in ground speed, changes in altitude, attitude variations, and surface topography. The current investigation was carried out with an Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) scene of central Switzerland (Rigi) from NASA's Multi Aircraft Campaign (MAC) in Europe (1991). The parametric approach reconstructs for every pixel the observation geometry based on the flight line, aircraft attitude, and surface topography. To utilize the data for analysis of materials on the surface, the AVIRIS data are corrected to apparent reflectance using algorithms based on MODTRAN (moderate resolution transfer code).

  20. Preprocessing and Content/Navigational Pages Identification as Premises for an Extended Web Usage Mining Model Development

    Directory of Open Access Journals (Sweden)

    Daniel MICAN

    2009-01-01

    Full Text Available From its appearance until nowadays, the internet saw a spectacular growth not only in terms of websites number and information volume, but also in terms of the number of visitors. Therefore, the need of an overall analysis regarding both the web sites and the content provided by them was required. Thus, a new branch of research was developed, namely web mining, that aims to discover useful information and knowledge, based not only on the analysis of websites and content, but also on the way in which the users interact with them. The aim of the present paper is to design a database that captures only the relevant data from logs in a way that will allow to store and manage large sets of temporal data with common tools in real time. In our work, we rely on different web sites or website sections with known architecture and we test several hypotheses from the literature in order to extend the framework to sites with unknown or chaotic structure, which are non-transparent in determining the type of visited pages. In doing this, we will start from non-proprietary, preexisting raw server logs.

  1. A signal pre-processing algorithm designed for the needs of hardware implementation of neural classifiers used in condition monitoring

    DEFF Research Database (Denmark)

    Dabrowski, Dariusz; Hashemiyan, Zahra; Adamczyk, Jan

    2015-01-01

    Gearboxes have a significant influence on the durability and reliability of a power transmission system. Currently, extensive research studies are being carried out to increase the reliability of gearboxes working in the energy industry, especially with a focus on planetary gears in wind turbines...... is to estimate the features of a vibration signal that are related to failures, e.g. misalignment and unbalance. These features can serve as the components of an input vector for a neural classifier. The approach proposed here has several important benefits: it is resistant to small speed fluctuations up to 7...

  2. Resting-state test-retest reliability of a priori defined canonical networks over different preprocessing steps

    Science.gov (United States)

    Varikuti, Deepthi P.; Hoffstaedter, Felix; Genon, Sarah; Schwender, Holger; Reid, Andrew T.; Eickhoff, Simon B.

    2016-01-01

    Resting-state functional connectivity analysis has become a widely used method for the investigation of human brain connectivity and pathology. The measurement of neuronal activity by functional MRI, however, is impeded by various nuisance signals that reduce the stability of functional connectivity. Several methods exist to address this predicament, but little consensus has yet been reached on the most appropriate approach. Given the crucial importance of reliability for the development of clinical applications, we here investigated the effect of various confound removal approaches on the test-retest reliability of functional-connectivity estimates in two previously defined functional brain networks. Our results showed that grey matter masking improved the reliability of connectivity estimates, whereas de-noising based on principal components analysis reduced it. We additionally observed that refraining from using any correction for global signals provided the best test-retest reliability, but failed to reproduce anti-correlations between what have been previously described as antagonistic networks. This suggests that improved reliability can come at the expense of potentially poorer biological validity. Consistent with this, we observed that reliability was proportional to the retained variance, which presumably included structured noise, such as reliable nuisance signals (for instance, noise induced by cardiac processes). We conclude that compromises are necessary between maximizing test-retest reliability and removing variance that may be attributable to non-neuronal sources. PMID:27550015

  3. Spectral Difference in the Image Domain for Large Neighborhoods, a GEOBIA Pre-Processing Step for High Resolution Imagery

    Directory of Open Access Journals (Sweden)

    Roeland de Kok

    2012-08-01

    Full Text Available Contrast plays an important role in the visual interpretation of imagery. To mimic visual interpretation and using contrast in a Geographic Object Based Image Analysis (GEOBIA environment, it is useful to consider an analysis for single pixel objects. This should be done before applying homogeneity criteria in the aggregation of pixels for the construction of meaningful image objects. The habit or “best practice” to start GEOBIA with pixel aggregation into homogeneous objects should come with the awareness that feature attributes for single pixels are at risk of becoming less accessible for further analysis. Single pixel contrast with image convolution on close neighborhoods is a standard technique, also applied in edge detection. This study elaborates on the analysis of close as well as much larger neighborhoods inside the GEOBIA domain. The applied calculations are limited to the first segmentation step for single pixel objects in order to produce additional feature attributes for objects of interest to be generated in further aggregation processes. The equation presented functions at a level that is considered an intermediary product in the sequential processing of imagery. The procedure requires intensive processor and memory capacity. The resulting feature attributes highlight not only contrasting pixels (edges but also contrasting areas of local pixel groups. The suggested approach can be extended and becomes useful in classifying artificial areas at national scales using high resolution satellite mosaics.

  4. Heterogeneous Optimization Framework: Reproducible Preprocessing of Multi-Spectral Clinical MRI for Neuro-Oncology Imaging Research

    OpenAIRE

    Milchenko, Mikhail; Snyder, Abraham Z.; LaMontagne, Pamela; Shimony, Joshua S; Benzinger, Tammie L.; Fouke, Sarah Jost; Marcus, Daniel S.

    2016-01-01

    Neuroimaging research often relies on clinically acquired magnetic resonance imaging (MRI) datasets that can originate from multiple institutions. Such datasets are characterized by high heterogeneity of modalities and variability of sequence parameters. This heterogeneity complicates the automation of image processing tasks such as spatial co-registration and physiological or functional image analysis.

  5. EVOLUTION IN THE H I GAS CONTENT OF GALAXY GROUPS: PRE-PROCESSING AND MASS ASSEMBLY IN THE CURRENT EPOCH

    Energy Technology Data Exchange (ETDEWEB)

    Hess, Kelley M. [Astrophysics, Cosmology and Gravity Centre (ACGC), Department of Astronomy, University of Cape Town, Rondebosch 7701 (South Africa); Wilcots, Eric M., E-mail: hess@ast.uct.ac.za, E-mail: ewilcots@astro.wisc.edu [Department of Astronomy, University of Wisconsin-Madison, Madison, WI 53706 (United States)

    2013-11-01

    We present an analysis of the neutral hydrogen (H I) content and distribution of galaxies in groups as a function of their parent dark matter halo mass. The Arecibo Legacy Fast ALFA survey α.40 data release allows us, for the first time, to study the H I properties of over 740 galaxy groups in the volume of sky common to the Sloan Digital Sky Survey (SDSS) and ALFALFA surveys. We assigned ALFALFA H I detections a group membership based on an existing magnitude/volume-limited SDSS Data Release 7 group/cluster catalog. Additionally, we assigned group ''proximity' membership to H I detected objects whose optical counterpart falls below the limiting optical magnitude—thereby not contributing substantially to the estimate of the group stellar mass, but significantly to the total group H I mass. We find that only 25% of the H I detected galaxies reside in groups or clusters, in contrast to approximately half of all optically detected galaxies. Further, we plot the relative positions of optical and H I detections in groups as a function of parent dark matter halo mass to reveal strong evidence that H I is being processed in galaxies as a result of the group environment: as optical membership increases, groups become increasingly deficient of H I rich galaxies at their center and the H I distribution of galaxies in the most massive groups starts to resemble the distribution observed in comparatively more extreme cluster environments. We find that the lowest H I mass objects lose their gas first as they are processed in the group environment, and it is evident that the infall of gas rich objects is important to the continuing growth of large scale structure at the present epoch, replenishing the neutral gas supply of groups. Finally, we compare our results to those of cosmological simulations and find that current models cannot simultaneously predict the H I selected halo occupation distribution for both low and high mass halos.

  6. A Comparison of Multivariate and Pre-Processing Methods for Quantitative Laser-Induced Breakdown Spectroscopy of Geologic Samples

    Science.gov (United States)

    Anderson, R. B.; Morris, R. V.; Clegg, S. M.; Bell, J. F., III; Humphries, S. D.; Wiens, R. C.

    2011-01-01

    The ChemCam instrument selected for the Curiosity rover is capable of remote laser-induced breakdown spectroscopy (LIBS).[1] We used a remote LIBS instrument similar to ChemCam to analyze 197 geologic slab samples and 32 pressed-powder geostandards. The slab samples are well-characterized and have been used to validate the calibration of previous instruments on Mars missions, including CRISM [2], OMEGA [3], the MER Pancam [4], Mini-TES [5], and Moessbauer [6] instruments and the Phoenix SSI [7]. The resulting dataset was used to compare multivariate methods for quantitative LIBS and to determine the effect of grain size on calculations. Three multivariate methods - partial least squares (PLS), multilayer perceptron artificial neural networks (MLP ANNs) and cascade correlation (CC) ANNs - were used to generate models and extract the quantitative composition of unknown samples. PLS can be used to predict one element (PLS1) or multiple elements (PLS2) at a time, as can the neural network methods. Although MLP and CC ANNs were successful in some cases, PLS generally produced the most accurate and precise results.

  7. Culvert Analysis Program Graphical User Interface 1.0--A preprocessing and postprocessing tool for estimating flow through culvert

    Science.gov (United States)

    Bradley, D. Nathan

    2013-01-01

    The peak discharge of a flood can be estimated from the elevation of high-water marks near the inlet and outlet of a culvert after the flood has occurred. This type of discharge estimate is called an “indirect measurement” because it relies on evidence left behind by the flood, such as high-water marks on trees or buildings. When combined with the cross-sectional geometry of the channel upstream from the culvert and the culvert size, shape, roughness, and orientation, the high-water marks define a water-surface profile that can be used to estimate the peak discharge by using the methods described by Bodhaine (1968). This type of measurement is in contrast to a “direct” measurement of discharge made during the flood where cross-sectional area is measured and a current meter or acoustic equipment is used to measure the water velocity. When a direct discharge measurement cannot be made at a streamgage during high flows because of logistics or safety reasons, an indirect measurement of a peak discharge is useful for defining the high-flow section of the stage-discharge relation (rating curve) at the streamgage, resulting in more accurate computation of high flows. The Culvert Analysis Program (CAP) (Fulford, 1998) is a command-line program written in Fortran for computing peak discharges and culvert rating surfaces or curves. CAP reads input data from a formatted text file and prints results to another formatted text file. Preparing and correctly formatting the input file may be time-consuming and prone to errors. This document describes the CAP graphical user interface (GUI)—a modern, cross-platform, menu-driven application that prepares the CAP input file, executes the program, and helps the user interpret the output

  8. MetAlign: Interface-Driven, Versatile Metabolomics Tool for Hyphenated Full-Scan Mass Spectrometry Data Preprocessing

    NARCIS (Netherlands)

    Lommen, A.

    2009-01-01

    Hyphenated full-scan MS technology creates large amounts of data. A versatile easy to handle automation tool aiding in the data analysis is very important in handling such a data stream. MetAlign software-as described in this manuscript-handles a broad range of accurate mass and nominal mass GC/MS

  9. A pre-processing strategy for liquid chromatography time-of-flight mass spectrometry metabolic fingerprinting data

    DEFF Research Database (Denmark)

    Nielsen, Nikoline Juul; Tomasi, Giorgio; Frandsen, Rasmus John Normand

    2010-01-01

    . Finally, principal component analysis was used for identification of high discriminatory power mass-to-charge ratios (m/z's) separating over-expression, wildtype and deletion genotypes. Two compounds exhibiting a positive correlation to the expected levels in different genotypes were identified. The two...

  10. Advanced Systems for Preprocessing and Characterizing Coal-Biomass Mixtures as Next-Generation Fuels and Feedstocks

    Energy Technology Data Exchange (ETDEWEB)

    Karmis, Michael [Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States); Luttrell, Gerald [Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States); Ripepi, Nino [Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States); Bratton, Robert [Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States); Dohm, Erich [Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States)

    2014-09-30

    The research activities presented in this report are intended to address the most critical technical challenges pertaining to coal-biomass briquette feedstocks. Several detailed investigations were conducted using a variety of coal and biomass feedstocks on the topics of (1) coal-biomass briquette production and characterization, (2) gasification of coal-biomass mixtures and briquettes, (3) combustion of coal-biomass mixtures and briquettes, and (4) conceptual engineering design and economic feasibility of briquette production. The briquette production studies indicate that strong and durable co-firing feedstocks can be produced by co-briquetting coal and biomass resources commonly available in the United States. It is demonstrated that binderless coal-biomass briquettes produced at optimized conditions exhibit very high strength and durability, which indicates that such briquettes would remain competent in the presence of forces encountered in handling, storage and transportation. The gasification studies conducted demonstrate that coal-biomass mixtures and briquettes are exceptional gasification feedstocks, particularly with regard to the synergistic effects realized during devolatilization of the blended materials. The mixture combustion studies indicate that coal-biomass mixtures are exceptional combustion feedstocks, while the briquette combustion study indicates that the use of blended briquettes reduces NOx, CO2, and CO emissions, and requires the least amount of changes in the operating conditions of an existing coal-fired power plant. Similar results were obtained for the physical durability of the pilot-scale briquettes compared to the bench-scale tests. Finally, the conceptual engineering and feasibility analysis study for a commercial-scale briquetting production facility provides preliminary flowsheet and cost simulations to evaluate the various feedstocks, equipment selection and operating parameters.

  11. Process Simulation and Cost Analysis for Removing Inorganics from Wood Chips using Combined Mechanical and Chemical Preprocessing

    Energy Technology Data Exchange (ETDEWEB)

    Hu, Hongqiang; Westover, Tyler L.; Cherry, Robert; Aston, John E.; Lacey, Jeffrey A.; Thompson, David N.

    2016-10-01

    Naturally occurring and introduced inorganic species (ash) in biomass feedstocks negatively impact thermochemical energy conversion processes such as pyrolysis, hydrothermal liquefaction, gasification and combustion to biopower. As such, it is desirable to better understand the cost:benefit ratios of various ash reduction processes. Here, a novel process simulation model was developed using AspenPlus to reduce the ash content of Loblolly logging residues using both air classification and a dilute-acid leaching process. For costing purposes, a throughput of 25 tons/hour was selected. At this scale, the process cost for a standalone air classification process was $3 per ton for a biomass feedstock. Ash reduction via dilute –acid leaching was simulated based on experimentally determined kinetics of ion diffusion at an acid concentration of 0.5% H2SO4 and temperature of 75°F. The total estimated processing cost for leaching at these conditions was approximately $14/ton of dry biomass. Sensitivity analysis of three parameters on mineral reduction in the leaching process revealed that increasing leaching temperature was not economically feasible, while it was viable to apply a longer retention time in leaching for higher ash removal or achieve a lower water content in final products with reasonable extra costs. In addition, scenarios combining air classification with leaching were examined. A whole process cost of approximately $16/ton of biomass at a biomass feedstock rate of 25 ton/hour considering a 9% of biomass classified as light fraction to be leached. The leaching operating costs constituted 75% of this amount, of which the heating costs of dryer was 44%. This suggests that the process costs would be substantially reduced if more efficient drying methods are applied in future.

  12. READING, PREPROCESSING OF ACCELERATIONS AND CORNERS INCLINATION WITH MPU-6050 I RECORD THEM ON SD-CARD THE ARDUINO DUE

    Directory of Open Access Journals (Sweden)

    V. G. Mikhailov

    2016-01-01

    Full Text Available The short review of microcontrollers of family Arduino, their characteristics and application fields is given. Importance of record of parameters of researched object is marked to produce debugging of control systems on microcontrollers Arduino. Unique possibility of registration of parameters in family Arduino is record on SD a card in an alpha mode with usage of functions print (, write (. The problems connected to record of the binary data on SD a card on microcontroller Arduino Due are considered. The analysis of methods of record of the binary data on SD-card Arduino Due, originating problems with neocleaning of memory from the previous program leading to possibility of duplication of the data on SD to a card, presence of the erratic point of view about restriction of volumes of data record and necessity of usage become outdated SD-cards is carried out. Ways of elimination of the marked lacks are considered. The estimation of high-speed performance of various approaches of a data recording on SD a card is led. On the basis of the led researches the approach of multiplexing of the writeable information at the expense of conversion of the binary data is offered is byte-serial in a character array in code ASCI without magnification of their volume and record by units on 240 byte. It allows to use as much as possible standard function possibilities write ( Arduino and specificity of the organization of memory SD of cards and to increase high-speed performance more than in 1100 times in comparison with record in a character type on one byte.It is marked that usage of decisions of an exception of duplication of the data offered at forums does not provide completeness of their elimination. For Arduino Due for storage cleaning it is necessary usages of the special programmator or setting of the new program of loading.

  13. Computational Methods for Quality Check, Preprocessing and Normalization of RNA-Seq Data for Systems Biology and Analysis

    DEFF Research Database (Denmark)

    Mazzoni, Gianluca; Kadarmideen, Haja N.

    2016-01-01

    quality control, trimming and filtering procedures, alignment, postmapping quality control, counting, normalization and differential expression test. For each step, we present the most common tools and we give a complete description of their main characteristics and advantages focusing on the statistics......The use of RNA sequencing (RNA-Seq) technologies is increasing mainly due to the development of new next-generation sequencing machines that have reduced the costs and the time needed for data generation. Nevertheless, microarrays are still the more common choice and one of the reasons...

  14. The nuisance of nuisance regression: spectral misspecification in a common approach to resting-state fMRI preprocessing reintroduces noise and obscures functional connectivity.

    Science.gov (United States)

    Hallquist, Michael N; Hwang, Kai; Luna, Beatriz

    2013-11-15

    Recent resting-state functional connectivity fMRI (RS-fcMRI) research has demonstrated that head motion during fMRI acquisition systematically influences connectivity estimates despite bandpass filtering and nuisance regression, which are intended to reduce such nuisance variability. We provide evidence that the effects of head motion and other nuisance signals are poorly controlled when the fMRI time series are bandpass-filtered but the regressors are unfiltered, resulting in the inadvertent reintroduction of nuisance-related variation into frequencies previously suppressed by the bandpass filter, as well as suboptimal correction for noise signals in the frequencies of interest. This is important because many RS-fcMRI studies, including some focusing on motion-related artifacts, have applied this approach. In two cohorts of individuals (n=117 and 22) who completed resting-state fMRI scans, we found that the bandpass-regress approach consistently overestimated functional connectivity across the brain, typically on the order of r=.10-.35, relative to a simultaneous bandpass filtering and nuisance regression approach. Inflated correlations under the bandpass-regress approach were associated with head motion and cardiac artifacts. Furthermore, distance-related differences in the association of head motion and connectivity estimates were much weaker for the simultaneous filtering approach. We recommend that future RS-fcMRI studies ensure that the frequencies of nuisance regressors and fMRI data match prior to nuisance regression, and we advocate a simultaneous bandpass filtering and nuisance regression strategy that better controls nuisance-related variability. Copyright © 2013 Elsevier Inc. All rights reserved.

  15. The Nuisance of Nuisance Regression: Spectral Misspecification in a Common Approach to Resting-State fMRI Preprocessing Reintroduces Noise and Obscures Functional Connectivity

    OpenAIRE

    Hallquist, Michael N.; Hwang, Kai; Luna, Beatriz

    2013-01-01

    Recent resting-state functional connectivity fMRI (RS-fcMRI) research has demonstrated that head motion during fMRI acquisition systematically influences connectivity estimates despite bandpass filtering and nuisance regression, which are intended to reduce such nuisance variability. We provide evidence that the effects of head motion and other nuisance signals are poorly controlled when the fMRI time series are bandpass-filtered but the regressors are unfiltered, resulting in the inadvertent...

  16. Meteorological pre-processing of incoming solar radiation and heat flux over a sparse boreal forest at a northern site during winter conditions

    DEFF Research Database (Denmark)

    Gryning, Sven-Erik; Batchvarova, E.

    2001-01-01

    ) was found to be a strong function of the solar elevation. At low solar elevation angles, commonly used expressions for turbidity did not fit the measurements well. A simple energy balance type met-processor performed well during daytime, but it was not satisfactory during night time. Simplifications...

  17. Integration of 4 microprocessors for the pre-processing and control of a nuclear physics experiment d(e,e'p)

    International Nuclear Information System (INIS)

    Ben Hamadou, Abdelmajid.

    1979-01-01

    The purpose of the experiments undertaken is to measure the binding energy and the momentum of a proton in the nucleus; they are carried out in the Saclay electron linear accelerator. The configuration of the data acquisition system was chosen following a study of local requirements implying the need to use the new integrated and fast technologies. The objectives sought are: a) increase the processing speed of the three kinds of occurrences, i.e. the single electron occurrences relating to the 600 spectrometer, the single proton occurrences relating to the 900 spectrometer and the coincident occurrences relating to the two 600 and 900 spectrometers, b) facilitate the control of the acquisition, c) increase the reliability and reduce the down-time that is always taken from the allocated beam time. Several systems were considered and the one finally adopted is a centralized network system. It is a grouping of three micro-computers controlled by a more powerful micro-computer called GIMINI that is in turn connected to the PDP 15 computer with a view to using its resources not available on GIMINI. The on-line processing, acquisition control and memory control are described [fr

  18. Conjunction of wavelet transform and SOM-mutual information data pre-processing approach for AI-based Multi-Station nitrate modeling of watersheds

    Science.gov (United States)

    Nourani, Vahid; Andalib, Gholamreza; Dąbrowska, Dominika

    2017-05-01

    Accurate nitrate load predictions can elevate decision management of water quality of watersheds which affects to environment and drinking water. In this paper, two scenarios were considered for Multi-Station (MS) nitrate load modeling of the Little River watershed. In the first scenario, Markovian characteristics of streamflow-nitrate time series were proposed for the MS modeling. For this purpose, feature extraction criterion of Mutual Information (MI) was employed for input selection of artificial intelligence models (Feed Forward Neural Network, FFNN and least square support vector machine). In the second scenario for considering seasonality-based characteristics of the time series, wavelet transform was used to extract multi-scale features of streamflow-nitrate time series of the watershed's sub-basins to model MS nitrate loads. Self-Organizing Map (SOM) clustering technique which finds homogeneous sub-series clusters was also linked to MI for proper cluster agent choice to be imposed into the models for predicting the nitrate loads of the watershed's sub-basins. The proposed MS method not only considers the prediction of the outlet nitrate but also covers predictions of interior sub-basins nitrate load values. The results indicated that the proposed FFNN model coupled with the SOM-MI improved the performance of MS nitrate predictions compared to the Markovian-based models up to 39%. Overall, accurate selection of dominant inputs which consider seasonality-based characteristics of streamflow-nitrate process could enhance the efficiency of nitrate load predictions.

  19. Surface chemistry of pyrite during the pre-processing for the flotation in alkaline sodium carbonate medium during uranium ore processing

    International Nuclear Information System (INIS)

    Neudert, A.; Sommer, H.; Schubert, H.

    1991-01-01

    It is often necessary during processing of uranium ore to flotate pyrite at sodium carbonate alkaline pH value caused by the subsequent hydrometallurgical process stages. It was found out by ESCA analyses that the pyrite surface changes chemically prior to the addition of flotation agents. FeS 2 becomes FeO within a few hours in the case of storage in process water; limonite and/or geothite result from pyrite. The copper ions of the activator CuSO 4 are exclusively monovalent on the pyrite surface. The resulting heavy metal xanthogenate is Cu(I) xanthogenate. Conclusions are derived for the flotation practice for the intensification of the reagent regime. (orig./HP) [de

  20. A new pre-processing technique to enhance single-user-type DS-CDMA detectors in "blind" space-time rake receivers

    Czech Academy of Sciences Publication Activity Database

    Wong, K. T.; Tichavský, Petr; Cheung, S. K.; Liao, G.

    2006-01-01

    Roč. 5, č. 10 (2006), s. 2932-2944 ISSN 1536-1276 R&D Projects: GA ČR GA102/01/0021 Institutional research plan: CEZ:AV0Z10750506 Keywords : antenna arrays * mobile communications * spread spectrum communications Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 1.184, year: 2006

  1. Three-dimensional brachytherapy optimization techniques in the treatment of patients with cervix cancer; Apport des techniques de curietherapie optimisee grace a l'imagerie tridimensionnelle dans la prise en charge des patientes atteintes d'un cancer du col uterin

    Energy Technology Data Exchange (ETDEWEB)

    Haie-Meder, C.; Mazeron, R.; Verezesan, O.; Monnier, L.; Vieillot, S. [Institut Gustave-Roussy, Service de Curietherapie, 94 - Villejuif (France); Dumas, I. [Institut Gustave-Roussy, Service de Physique, 94 - Villejuif (France); Lhomme, C. [Institut Gustave-Roussy, Service d' Ooncologie Gynecologique, 94 - Villejuif (France); Morice, P. [Institut Gustave-Roussy, Service de Chirurgie Oncologique, 94 - Villejuif (France); Barillot, I. [Centre Regional Universitaire de Cancerologie Henry-S.-Kaplan, Hopital Bretonneau, CHU de Tours, 37 - Tours (France); Universite Francois-Rabelais, 37 - Tours (France)

    2009-10-15

    Traditionally, prescription and treatment planning in intracavitary brachytherapy for cervix cancer have used either reference points (mainly points A and B) or reference isodoses (60 Gy according to ICRU recommendations) to report doses to the target volume. Doses to critical organs were reported at bladder and rectum ICRU points. This practice has been supported by a long-standing clinical experience that has yielded an acceptable therapeutic ratio. The recent development of imaging has contributed to the improvement in target and organs at risk knowledge. In 2005 and 2006, the European group of brachytherapy -European Society for therapeutic radiology and oncology (GEC-E.S.T.R.O.) recommendations publications on 3-D based image brachytherapy have defined the different volumes of interest. These recommendations have been validated with intercomparison delineation studies. With the concomitant development of remote after-loading projectors, provided with miniaturized sources, it is now possible to plan radiation doses by adjusting dwell positions and relative dwell time values. These procedures allow better coverage of the targets while sparing O.A.R.. The recent literature data evidence a significant improvement in local control with no increase in complications. Further studies are needed to better define the dose recommended in both tumour and organs at risk. This is one of the goals of the European study on MRI-guided brachytherapy in locally advanced cervical cancer (E.M.B.R.A.C.E.) protocol (meaning of acronym: an international study on MRI-guided brachytherapy in locally advanced cervical cancer). (authors)

  2. Cyber Foraging for Improving Survivability of Mobile Systems

    Science.gov (United States)

    2016-02-10

    Cyber-Foraging for Improving Survivability of Mobile Systems Sebastián Echeverría ( Universidad de los Andes) Grace A. Lewis James Root Ben...NUMBERS FA8721-05-C-0003 6. AUTHOR(S) Sebastián Echeverría ( Universidad de los Andes), Grace A. Lewis, James Root, & Ben Bradshaw 7. PERFORMING

  3. Slope-Area Computation Program Graphical User Interface 1.0—A Preprocessing and Postprocessing Tool for Estimating Peak Flood Discharge Using the Slope-Area Method

    Science.gov (United States)

    Bradley, D. Nathan

    2012-01-01

    The slope-area method is a technique for estimating the peak discharge of a flood after the water has receded (Dalrymple and Benson, 1967). This type of discharge estimate is called an “indirect measurement” because it relies on evidence left behind by the flood, such as high-water marks (HWMs) on trees or buildings. These indicators of flood stage are combined with measurements of the cross-sectional geometry of the stream, estimates of channel roughness, and a mathematical model that balances the total energy of the flow between cross sections. This is in contrast to a “direct” measurement of discharge during the flood where cross-sectional area is measured and a current meter or acoustic equipment is used to measure the water velocity. When a direct discharge measurement cannot be made at a gage during high flows because of logistics or safety reasons, an indirect measurement of a peak discharge is useful for defining the high-flow section of the stage-discharge relation (rating curve) at the stream gage, resulting in more accurate computation of high flows. The Slope-Area Computation program (SAC; Fulford, 1994) is an implementation of the slope-area method that computes a peak-discharge estimate from inputs of water-surface slope (from surveyed HWMs), channel geometry, and estimated channel roughness. SAC is a command line program written in Fortran that reads input data from a formatted text file and prints results to another formatted text file. Preparing the input file can be time-consuming and prone to errors. This document describes the SAC graphical user interface (GUI), a crossplatform “wrapper” application that prepares the SAC input file, executes the program, and helps the user interpret the output. The SAC GUI is an update and enhancement of the slope-area method (SAM; Hortness, 2004; Berenbrock, 1996), an earlier spreadsheet tool used to aid field personnel in the completion of a slope-area measurement. The SAC GUI reads survey data, develops a plan-view plot, water-surface profile, cross-section plots, and develops the SAC input file. The SAC GUI also develops HEC-2 files that can be imported into HEC–RAS.

  4. The Need for Accurate Geometric and Radiometric Corrections of Drone-Borne Hyperspectral Data for Mineral Exploration: MEPHySTo—A Toolbox for Pre-Processing Drone-Borne Hyperspectral Data

    Directory of Open Access Journals (Sweden)

    Sandra Jakob

    2017-01-01

    Full Text Available Drone-borne hyperspectral imaging is a new and promising technique for fast and precise acquisition, as well as delivery of high-resolution hyperspectral data to a large variety of end-users. Drones can overcome the scale gap between field and air-borne remote sensing, thus providing high-resolution and multi-temporal data. They are easy to use, flexible and deliver data within cm-scale resolution. So far, however, drone-borne imagery has prominently and successfully been almost solely used in precision agriculture and photogrammetry. Drone technology currently mainly relies on structure-from-motion photogrammetry, aerial photography and agricultural monitoring. Recently, a few hyperspectral sensors became available for drones, but complex geometric and radiometric effects complicate their use for geology-related studies. Using two examples, we first show that precise corrections are required for any geological mapping. We then present a processing toolbox for frame-based hyperspectral imaging systems adapted for the complex correction of drone-borne hyperspectral imagery. The toolbox performs sensor- and platform-specific geometric distortion corrections. Furthermore, a topographic correction step is implemented to correct for rough terrain surfaces. We recommend the c-factor-algorithm for geological applications. To our knowledge, we demonstrate for the first time the applicability of the corrected dataset for lithological mapping and mineral exploration.

  5. Apprendre a vivre ensemble grace a l'enseignement de l'histoire et de la geographie. Rapport final du colloque sur le theme. (Learning To Live Together Thanks to the Teaching of History and Geography. Final Report on a Colloquium on That Theme.) Proceedings of a Colloquium Organized Jointly by the International Bureau of Education (UNESCO) and the University of Geneva (Geneva, Switzerland, June 12, 1998).

    Science.gov (United States)

    Andre, Yves, Ed.; Mouzoune, Abdelkrim, Ed.

    These Proceedings contain 14 chapters (or papers) from a colloquium on learning to live together in peaceful co-existence thanks to the teaching of history and geography. All the papers in the Proceedings are in French, but each paper has both an English summary and a Spanish summary. The 14 papers are, as follows: (1) "Introduction"…

  6. Synchronous atmospheric radiation correction of GF-2 satellite multispectral image

    Science.gov (United States)

    Bian, Fuqiang; Fan, Dongdong; Zhang, Yan; Wang, Dandan

    2018-02-01

    GF-2 remote sensing products have been widely used in many fields for its high-quality information, which provides technical support for the the macroeconomic decisions. Atmospheric correction is the necessary part in the data preprocessing of the quantitative high resolution remote sensing, which can eliminate the signal interference in the radiation path caused by atmospheric scattering and absorption, and reducting apparent reflectance into real reflectance of the surface targets. Aiming at the problem that current research lack of atmospheric date which are synchronization and region matching of the surface observation image, this research utilize the MODIS Level 1B synchronous data to simulate synchronized atmospheric condition, and write programs to implementation process of aerosol retrieval and atmospheric correction, then generate a lookup table of the remote sensing image based on the radioactive transfer model of 6S (second simulation of a satellite signal in the solar spectrum) to correct the atmospheric effect of multispectral image from GF-2 satellite PMS-1 payload. According to the correction results, this paper analyzes the pixel histogram of the reflectance spectrum of the 4 spectral bands of PMS-1, and evaluates the correction results of different spectral bands. Then conducted a comparison experiment on the same GF-2 image based on the QUAC. According to the different targets respectively statistics the average value of NDVI, implement a comparative study of NDVI from two different results. The degree of influence was discussed by whether to adopt synchronous atmospheric date. The study shows that the result of the synchronous atmospheric parameters have significantly improved the quantitative application of the GF-2 remote sensing data.

  7. Swarm Data Processing and First Scientific Results

    DEFF Research Database (Denmark)

    Olsen, Nils

    2014-01-01

    , accelerometer, plasma and electric field measurements. These observations will be distributed by ESA as Level-1b data, which are the calibrated and formatted time series of e.g. the magnetic field measurements taken by each of the three Swarm satellites. The talks presents a first scientific validation of Swarm...... Level-1b data products....

  8. New proportional counter for in vivo detection of traces of plutonium in the lungs; Nouveau compteur proportionnel destine a la detection in vivo de traces de plutonium dans les poumons

    Energy Technology Data Exchange (ETDEWEB)

    Morucci, J [Commissariat a l' Energie Atomique, Centre d' Etudes Nucleaires de Saclay, 91 - Gif-sur-Yvette (France)

    1966-07-01

    Development of a multi-wire proportional counter having a uniform response over 250 cm{sup 2} thanks to corrections made for boundary effects, and having a low background per sq. cm. due to the use of two identical counters set in anti-coincidence in the same enclosure is described. (author) [French] Etude et mise au point d'un compteur proportionnel multifils de reponse utile homogene sur une surface de 250 cm{sup 2} grace a la correction des effets de bords et de faible mouvement propre par cm{sup 2} grace a deux compteurs identiques montes en anticoincidence dans la meme enceinte. (auteur)

  9. MODIS/Terra Calibrated Radiances 5-Min L1B Swath 1km V005

    Data.gov (United States)

    National Aeronautics and Space Administration — The MODIS Level 1B data set contains calibrated and geolocated at-aperture radiances for 36 discrete bands located in the 0.4 to 14.4 micron region of...

  10. AIRS-CloudSat cloud mask, radar reflectivities, and cloud classification matchups V3.2

    Data.gov (United States)

    National Aeronautics and Space Administration — This is AIRS-CloudSat collocated subset, in NetCDF 4 format. These data contain collocated: AIRS Level 1b radiances spectra, CloudSat radar reflectivities, and MODIS...

  11. MODIS/Terra Calibrated Radiances 5-Min L1B Swath 1km - NRT

    Data.gov (United States)

    National Aeronautics and Space Administration — The MODIS Level 1B Near Real Time (NRT) data set contains calibrated and geolocated at-aperture radiances for 36 discrete bands located in the 0.4 to 14.4 micron...

  12. TRMM Visible and Infrared Scanner Calibrated Radiances L1B 1.5 hours V7 (TRMM_1B01) at GES DISC

    Data.gov (United States)

    National Aeronautics and Space Administration — This TRMM Visible and Infrared Scanner (VIRS) Level 1B Calibrated Radiance Product (1B01) contains calibrated radiances and auxiliary geolocation information from...

  13. NOAA JPSS Visible Infrared Imaging Radiometer Suite (VIIRS) Sensor Data Record (SDR) from IDPS

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Sensor Data Records (SDRs), or Level 1b data, from the Visible Infrared Imaging Radiometer Suite (VIIRS) are the calibrated and geolocated radiance and reflectance...

  14. PODAAC-QSNON-L1CA1

    Data.gov (United States)

    National Aeronautics and Space Administration — This dataset contains geo-located and averaged Level 1B Sigma-0 measurements and wind retrievals from the SeaWinds on QuikSCAT platform, initiated in the months...

  15. SMAP L1B Radiometer Half-Orbit Time-Ordered Brightness Temperatures V003

    Data.gov (United States)

    National Aeronautics and Space Administration — This Level-1B (L1B) product provides calibrated estimates of time-ordered geolocated brightness temperatures measured by the Soil Moisture Active Passive (SMAP)...

  16. OMI/Aura Surface Reflectance Climatology Level 3 Global 0.5deg Lat/Lon Grid V003

    Data.gov (United States)

    National Aeronautics and Space Administration — The OMI Earth Surface Reflectance Climatology product, OMLER (Global 0.5deg Lat/Lon grid) which is based on Version 003 Level-1B top of atmosphere upwelling radiance...

  17. VIIRS Climate Raw Data Record (C-RDR) from Suomi NPP, Version 1

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Suomi NPP Climate Raw Data Record (C-RDR) developed at the NOAA NCDC is an intermediate product processing level (NOAA Level 1b) between a Raw Data Record (RDR)...

  18. ASTER Expedited L1B Registered Radiance at the Sensor V003

    Data.gov (United States)

    National Aeronautics and Space Administration — The Expedited ASTER Level-1B Registered Radiance at the Sensor data set is produced with the express purpose of providing ASTER Science Team members data of their...

  19. Paul Broca and French Brains: Portraits from the Life of an Eminent Neuroscientist

    Science.gov (United States)

    LaPointe, Leonard L.

    2014-01-01

    Pierre Paul Broca is one of the most legendary neuroscientists of the last few centuries. His name graces a region of the brain, and his work is richly associated with human communication and its disorders. This article traces the contributions of this man and the historical context of his remarkable discoveries. After approval to visit and access…

  20. supp3.doc

    Indian Academy of Sciences (India)

    Sathiyanathan Felixa, Pratap Kollub, Bala P.C.Raghupathya,c,*, Soon Kwan Jeongd,* and Andrews Nirmala Grace a,d,*. a Centre for Nanotechnology Research, VIT University, Vellore - 632014, Tamil Nadu, India. b DST-INSPIRE Faculty, Department of Metallurgical Engineering and Materials Science, Indian Institute of ...

  1. Journal of Earth System Science | Indian Academy of Sciences

    Indian Academy of Sciences (India)

    This paper presents a GPU implementation of normalized cuts for road extraction problem using panchromatic satellite imagery. The roads have been extracted in three stages namely pre-processing, image segmentation and post-processing. Initially, the image is pre-processed to improve the tolerance by reducing the ...

  2. Longitudinal navigation log data on a large web domain

    NARCIS (Netherlands)

    Verberne, S.; Arends, B.; Kraaij, W.; Vries, A. de

    2016-01-01

    We have collected the access logs for our university's web domain over a time span of 4.5 years. We now release the pre-processed data of a 3-month period for research into user navigation behavior. We preprocessed the data so that only successful GET requests of web pages by non-bot users are kept.

  3. Chemical fingerprinting of petroleum biomakers using time warping and PCA

    DEFF Research Database (Denmark)

    Christensen, Jan H.; Tomasi, Giorgio; Hansen, Asger B.

    2005-01-01

    A new method for chemical fingerprinting of petroleum biomakers is described. The method consists of GC-MS analysis, preprocessing of GC-MS chromatograms, and principal component analysis (PCA) of selected regions. The preprocessing consists of baseline removal by derivatization, normalization...

  4. Zero-Knowledge Protocols and Multiparty Computation

    DEFF Research Database (Denmark)

    Pastro, Valerio

    majority, in which all players but one are controlled by the adversary. In Chapter 5 we present both the preprocessing and the online phase of [DKL+ 13], while in Chapter 2 we describe only the preprocessing phase of [DPSZ12] since the combination of this preprocessing phase with the online phase of [DKL...... on information-theoretic message authentication codes, requires only a linear amount of data from the preprocessing, and improves on the number of field multiplications needed to perform one secure multiplication (linear, instead of quadratic as in earlier work). The preprocessing phase in Chapter 5 comes...... in an actively secure flavour and in a covertly secure one, both of which compare favourably to previous work in terms of efficiency and provable security. Moreover, the covertly secure solution includes a key generation protocol that allows players to obtain a public key and shares of a corresponding secret key...

  5. Operational Implementation Design for the Earth System Prediction Capability (ESPC): A First-Look

    Science.gov (United States)

    2014-02-20

    developed column model containing 4 bulk soil layers described by their water and ice content and their temperature. The vegetation cover information...time-integration scheme to numerically integrate the governing equations of the physical processes of the soil- vegetation -snowpack medium. Noah has...GRACE-A ii. 5 COSMIC FM1-6 (FM3 has failed) iii. 2 GRAS iv. Terra and TanDEM SAR-X v. CORISS e. IR Sounding Radiances i. IASI ii. AIRS iii

  6. Low-cost digital image processing at the University of Oklahoma

    Science.gov (United States)

    Harrington, J. A., Jr.

    1981-01-01

    Computer assisted instruction in remote sensing at the University of Oklahoma involves two separate approaches and is dependent upon initial preprocessing of a LANDSAT computer compatible tape using software developed for an IBM 370/158 computer. In-house generated preprocessing algorithms permits students or researchers to select a subset of a LANDSAT scene for subsequent analysis using either general purpose statistical packages or color graphic image processing software developed for Apple II microcomputers. Procedures for preprocessing the data and image analysis using either of the two approaches for low-cost LANDSAT data processing are described.

  7. Comparative Study of Retinal Vessel Segmentation Based on Global Thresholding Techniques

    Directory of Open Access Journals (Sweden)

    Temitope Mapayi

    2015-01-01

    Full Text Available Due to noise from uneven contrast and illumination during acquisition process of retinal fundus images, the use of efficient preprocessing techniques is highly desirable to produce good retinal vessel segmentation results. This paper develops and compares the performance of different vessel segmentation techniques based on global thresholding using phase congruency and contrast limited adaptive histogram equalization (CLAHE for the preprocessing of the retinal images. The results obtained show that the combination of preprocessing technique, global thresholding, and postprocessing techniques must be carefully chosen to achieve a good segmentation performance.

  8. MODIS/Terra Calibrated Radiances 5-Min L1B Swath 500m V005

    Data.gov (United States)

    National Aeronautics and Space Administration — The 500 meter MODIS Level 1B data set contains calibrated and geolocated at-aperture radiances for 7 discrete bands located in the 0.45 to 2.20 micron region of the...

  9. MODIS/Terra Calibrated Radiances 5-Min L1B Swath 250m V005

    Data.gov (United States)

    National Aeronautics and Space Administration — The 250 meter MODIS Level 1B data set contains calibrated and geolocated at-aperture radiances for 2 discrete bands located in the 0.62 to 0.88 micron region of the...

  10. Sea surface height determination in the arctic ocean from Cryosat2 SAR data, the impact of using different empirical retrackers

    DEFF Research Database (Denmark)

    Jain, Maulik; Andersen, Ole Baltazar; Stenseng, Lars

    2012-01-01

    Cryosat2 Level 1B SAR data can be processed using different empirical retrackers to determine the sea surface height and its variations in the Arctic Ocean. Two improved retrackers based on the combination of OCOG (Offset Centre of Gravity), Threshold methods and Leading Edge Retrieval is used...

  11. MODIS/Aqua Calibrated Radiances 5-Min L1B Swath 250m - NRT

    Data.gov (United States)

    National Aeronautics and Space Administration — The 250 meter MODIS Level 1B Near Real Time (NRT) data set contains calibrated and geolocated at-aperture radiances for 2 discrete bands located in the 0.62 to 0.88...

  12. Study of land surface temperature and spectral emissivity using multi ...

    Indian Academy of Sciences (India)

    tral emissivities over a hard rock terrain using multi-sensor satellite data. The study area, of .... Georeferenced MODIS level 1B data (bands 31 and. 32) and Landsat ETM+ data .... the optical properties of the atmosphere. In the present study ...

  13. Download this PDF file

    African Journals Online (AJOL)

    The values of the bonding parameter (b) and angular overlap parameter (m) were found to be positive indicating covalent bonding [21]. Table 3. Electronic spectral data (cm) and related bonding parameters of lanthanide(III) isothiocyanato complexes of DABAAPS. 80 . Complexes Ln(NCS). Complex Energy levels (1-B).

  14. MODIS/Terra Calibrated Radiances 5-Min L1B Swath 1km Subsetted V005

    Data.gov (United States)

    National Aeronautics and Space Administration — This data type (MOD02SSH) is a subsample from the MODIS Level 1B 1-km data. Every fifth pixel is taken from the MOD021KM product and written out to MOD02SSH. The...

  15. Reducing the Cognitive Workload While Operating in Complex Sensory Environments

    National Research Council Canada - National Science Library

    Cooper, Leon

    2004-01-01

    .... However, there are some problems and ambiguities at the level of sensory processing, and preprocessing of the signal, that cannot be resolved without taking into account cognitive level expectations...

  16. Arabic Handwriting Recognition Using Neural Network Classifier

    African Journals Online (AJOL)

    pc

    2018-03-05

    Mar 5, 2018 ... an OCR using Neural Network classifier preceded by a set of preprocessing .... Artificial Neural Networks (ANNs), which we adopt in this research, consist of ... advantage and disadvantages of each technique. In [9],. Khemiri ...

  17. Research Article Special Issue

    African Journals Online (AJOL)

    2017-10-17

    Oct 17, 2017 ... These include verbal reasoning, working memory, non-reasoning ability ... each commonly associated with deep and light sleep. ... comprise of sample selection and EEG acquisition, signal pre-processing and filtering, power.

  18. Application of on-line analytical processing technique in accelerator

    International Nuclear Information System (INIS)

    Xie Dong; Li Weimin; He Duohui; Liu Gongfa; Xuan Ke

    2005-01-01

    A method of application of the on-line analytical processing technique in accelerator is described, which includes data pre-processing, the process of constructing of data warehouse and on-line analytical processing. (authors)

  19. Autonomous Non-Linear Classification of LPI Radar Signal Modulations

    National Research Council Canada - National Science Library

    Gulum, Taylan O

    2007-01-01

    ...) radar modulations is investigated. A software engineering architecture that allows a full investigation of various preprocessing algorithms and classification techniques is applied to a database of important LPI radar waveform...

  20. Research Article Special Issue

    African Journals Online (AJOL)

    pc

    2018-03-22

    Mar 22, 2018 ... transformation and preprocessing on machine learning algorithm. ... location in general only without investigating the best transformation and ... uses the distance measurements of a particular class for the prediction of class.

  1. Multiresolution wavelet-ANN model for significant wave height forecasting.

    Digital Repository Service at National Institute of Oceanography (India)

    Deka, P.C.; Mandal, S.; Prahlada, R.

    Hybrid wavelet artificial neural network (WLNN) has been applied in the present study to forecast significant wave heights (Hs). Here Discrete Wavelet Transformation is used to preprocess the time series data (Hs) prior to Artificial Neural Network...

  2. Applying machine learning to predict patient-specific current CD4 ...

    African Journals Online (AJOL)

    Apple apple

    This work shows the application of machine learning to predict current CD4 cell count of an HIV- .... Pre-processing ... remaining data elements of the PR and RT datasets. ... technique based on the structure of the human brain's neuron.

  3. Kalman Filter Predictor and Initialization Algorithm for PRI Tracking

    National Research Council Canada - National Science Library

    Hock, Melinda

    1998-01-01

    .... The algorithm uses a Kalman filter for prediction combined with a preprocessing routine to determine the period of the stagger sequence and to construct an uncorrupted data set for Kalman filter initialization...

  4. Embedded RF Photonic Crystals as Routing and Processing Devices in Naval Aperstructures

    National Research Council Canada - National Science Library

    Prather, Dennis W

    2008-01-01

    .... To address these issues, we utilize advanced artificial materials - photonic crystals (PhCs) and meta-material - to construct a sensing head with minaturized antennas as RF receivers and embedded signal channelization for pre-processing...

  5. Protoplast formation, regeneration and transformation from the taxol ...

    African Journals Online (AJOL)

    producing fungus Ozonium sp. BT2 were investigated, including the enzymolysis time and temperature, the osmotic pressure stabilizer, mycelial incubation time, the culture medium, the culture methods and preprocessing. The mycelia were ...

  6. Red's natural editor, a program designed to edit FORTRAN programs

    International Nuclear Information System (INIS)

    Cullen, D.E.

    1993-01-01

    An EDITOR code is documented which supplements the 1994 ENDF Pre-processing Code Package which is available from the IAEA Nuclear Data Section for the processing of ENDF formatted nuclear data libraries. (author)

  7. Quantum cascade laser infrared spectroscopy of single cancer cells

    KAUST Repository

    Patel, Imran

    2017-03-27

    Quantum cascade laser infrared spectroscopy is a next generation novel imaging technique allowing high resolution spectral imaging of cells. We show after spectral pre-processing, identification of different cancer cell populations within minutes.

  8. Quantum cascade laser infrared spectroscopy of single cancer cells

    KAUST Repository

    Patel, Imran; Rajamanickam, Vijayakumar Palanisamy; Bertoncini, Andrea; Pagliari, Francesca; Tirinato, Luca; Laptenok, Sergey P.; Liberale, Carlo

    2017-01-01

    Quantum cascade laser infrared spectroscopy is a next generation novel imaging technique allowing high resolution spectral imaging of cells. We show after spectral pre-processing, identification of different cancer cell populations within minutes.

  9. Publications | Page 278 | IDRC - International Development ...

    International Development Research Centre (IDRC) Digital Library (Canada)

    Multi-level participation for building adaptive capacity : formal ... to adaptive capacity helps formulate a theory of participation based on resilience thinking. ... kinds of ASCII text files for further analysis, with several pre-processing options.

  10. Parser Adaptation for Social Media by Integrating Normalization

    NARCIS (Netherlands)

    van der Goot, Rob; van Noord, Gerardus

    This work explores normalization for parser adaptation. Traditionally, normalization is used as separate pre-processing step. We show that integrating the normalization model into the parsing algorithm is beneficial. This way, multiple normalization candidates can be leveraged, which improves

  11. A classification model for non-alcoholic steatohepatitis (NASH) using confocal Raman micro-spectroscopy

    Science.gov (United States)

    Yan, Jie; Yu, Yang; Kang, Jeon Woong; Tam, Zhi Yang; Xu, Shuoyu; Fong, Eliza Li Shan; Singh, Surya Pratap; Song, Ziwei; Tucker Kellogg, Lisa; So, Peter; Yu, Hanry

    2017-07-01

    We combined Raman micro-spectroscopy and machine learning techniques to develop a classification model based on a well-established non-alcoholic steatohepatitis (NASH) mouse model, using spectrum pre-processing, biochemical component analysis (BCA) and logistic regression.

  12. Local dimensionality reduction and supervised learning within natural clusters for biomedical data analysis

    NARCIS (Netherlands)

    Pechenizkiy, M.; Tsymbal, A.; Puuronen, S.

    2006-01-01

    Inductive learning systems were successfully applied in a number of medical domains. Nevertheless, the effective use of these systems often requires data preprocessing before applying a learning algorithm. This is especially important for multidimensional heterogeneous data presented by a large

  13. A Simple Neural Network Contextual Classifier

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg; Tidemann, J.

    1997-01-01

    I. Kanellopoulos, G.G. Wilkinson, F. Roli and J. Austin (Eds.)Proceedings of European Union Environment and Climate Programme Concerted Action COMPARES (COnnectionist Methods in Pre-processing and Analysis of REmote Sensing data)....

  14. PCM- data processing - description of the program TAPEDUMP for the computer HP-2100 S

    International Nuclear Information System (INIS)

    Ziegler, G.

    1978-01-01

    The assembler program TADEDUMP has the task, to preprocess PCM-data for further processing with a large computer and to put them in an output routine on magnetic tape with a measurement specific header. In the preprocessing the data can be reduced by selection and averaging. In the case of certain reading errors the data are discarded, but the synchronization is reestablished. (orig.) [de

  15. Robust hybrid pitch detector for pathologic voice analysis

    OpenAIRE

    Boyanov, B.; Hadjitodorov, S.; Teston, B.; Doskov, D.

    1997-01-01

    International audience; A hybrid speech period (To) detector characterizided by parallel analyses of three speech signals in temporal spectral and cepstral domains and preprocessing for periodic/aperiodic (unvoiced) separation (PAS) is proposed. The preprocessing is realized by analysis in these three domains and PAS by multi layer Perceptron neural network.Two phonations of the wowel "a" of 40 speakers and 62 patients were analyzed. For the proposed detector errors were significantly minimized.

  16. Real-time trajectory analysis using stacked invariance methods

    OpenAIRE

    Kitts, B.

    1998-01-01

    Invariance methods are used widely in pattern recognition as a preprocessing stage before algorithms such as neural networks are applied to the problem. A pattern recognition system has to be able to recognise objects invariant to scale, translation, and rotation. Presumably the human eye implements some of these preprocessing transforms in making sense of incoming stimuli, for example, placing signals onto a log scale. This paper surveys many of the commonly used invariance methods, and asse...

  17. Front-end data processing the SLD data acquisition system

    International Nuclear Information System (INIS)

    Nielsen, B.S.

    1986-07-01

    The data acquisition system for the SLD detector will make extensive use of parallel at the front-end level. Fastbus acquisition modules are being built with powerful processing capabilities for calibration, data reduction and further pre-processing of the large amount of analog data handled by each module. This paper describes the read-out electronics chain and data pre-processing system adapted for most of the detector channels, exemplified by the central drift chamber waveform digitization and processing system

  18. A preprocessor for geotomographic imaging of irregular geometric scans

    International Nuclear Information System (INIS)

    Middleton, N.T.; Harman, M.T.

    1992-01-01

    Conventional tomographic image reconstruction algorithms that use algebraic methods are best suited to rectangular geometries. Although this is satisfactory for many rectangular cross-hole and in-seam geotomographic scans, difficulties arise in cases where the scanning geometry is nonrectangular. This paper describes a preprocessing algorithm that deals with nonrectangular geometries when merged with a conventional image reconstruction algorithm. The performance of the preprocessing algorithm is demonstrated with some simulation results

  19. Using self-organizing maps adaptive resonance theory (CARTMAP) for manufacturing feature recognition

    Science.gov (United States)

    Yu, Jason S.; Dagli, Cihan H.

    1993-10-01

    The invariant image preprocessing of moment invariants generates an invariant representation of object features which are insensitive to position, orientation, size, illusion, and contrast change. In this study ARTMAP is used for 3-D object recognition of manufacturing parts through these invariant characteristics. The analog of moment invariants created through the image preprocessing is interpreted by a binary code which is used to predict the manufacturing part through ARTMAP.

  20. A new method of machine vision reprocessing based on cellular neural networks

    International Nuclear Information System (INIS)

    Jianhua, W.; Liping, Z.; Fenfang, Z.; Guojian, H.

    1996-01-01

    This paper proposed a method of image preprocessing in machine vision based on Cellular Neural Network (CNN). CNN is introduced to design image smoothing, image recovering, image boundary detecting and other image preprocessing problems. The proposed methods are so simple that the speed of algorithms are increased greatly to suit the needs of real-time image processing. The experimental results show a satisfactory reply

  1. Convolutional neural networks for vibrational spectroscopic data analysis.

    Science.gov (United States)

    Acquarelli, Jacopo; van Laarhoven, Twan; Gerretzen, Jan; Tran, Thanh N; Buydens, Lutgarde M C; Marchiori, Elena

    2017-02-15

    In this work we show that convolutional neural networks (CNNs) can be efficiently used to classify vibrational spectroscopic data and identify important spectral regions. CNNs are the current state-of-the-art in image classification and speech recognition and can learn interpretable representations of the data. These characteristics make CNNs a good candidate for reducing the need for preprocessing and for highlighting important spectral regions, both of which are crucial steps in the analysis of vibrational spectroscopic data. Chemometric analysis of vibrational spectroscopic data often relies on preprocessing methods involving baseline correction, scatter correction and noise removal, which are applied to the spectra prior to model building. Preprocessing is a critical step because even in simple problems using 'reasonable' preprocessing methods may decrease the performance of the final model. We develop a new CNN based method and provide an accompanying publicly available software. It is based on a simple CNN architecture with a single convolutional layer (a so-called shallow CNN). Our method outperforms standard classification algorithms used in chemometrics (e.g. PLS) in terms of accuracy when applied to non-preprocessed test data (86% average accuracy compared to the 62% achieved by PLS), and it achieves better performance even on preprocessed test data (96% average accuracy compared to the 89% achieved by PLS). For interpretability purposes, our method includes a procedure for finding important spectral regions, thereby facilitating qualitative interpretation of results. Copyright © 2016 Elsevier B.V. All rights reserved.

  2. The Need for Intelligent Control of Space Power Systems

    Science.gov (United States)

    May, Ryan David; Soeder, James F.; Beach, Raymond F.; McNelis, Nancy B.

    2013-01-01

    As manned spacecraft venture farther from Earth, the need for reliable, autonomous control of vehicle subsystems becomes critical. This is particularly true for the electrical power system which is critical to every other system. Autonomy can not be achieved by simple scripting techniques due to the communication latency times and the difficulty associated with failures (or combinations of failures) that need to be handled in as graceful a manner as possible to ensure system availability. Therefore an intelligent control system must be developed that can respond to disturbances and failures in a robust manner and ensure that critical system loads are served and all system constraints are respected.

  3. The design, validation, and performance of Grace

    Directory of Open Access Journals (Sweden)

    Ru Zhu

    2016-05-01

    Full Text Available The design, validation and performance of Grace, a GPU-accelerated micromagnetic simulation software, are presented. The software adopts C+ + Accelerated Massive Parallelism (C+ + AMP so that it runs on GPUs from various hardware vendors including NVidia, AMD and Intel. At large simulation scales, up to two orders of magnitude of speedup factor is observed, compared to CPU-based micromagnetic simulation software OOMMF. The software can run on high-end professional GPUs as well as budget personal laptops, and is free to download.

  4. Study of a polarized proton source for a cyclotron using a high frequency transition (1961); Etude d'une source de protons polarises utilisant une transition haute frequence pour un cyclotron (1961)

    Energy Technology Data Exchange (ETDEWEB)

    Thirion, J; Beurtey, R; Papineau, A [Commissariat a l' Energie Atomique, Saclay (France). Centre d' Etudes Nucleaires

    1961-07-01

    The authors have developed an experimental unit yielding a jet of hydrogen or deuterium atoms in which the protons and deutons are polarized. By use of the 'adiabatic passage' method a proton polarisation approaching 100 per cent is assured. (authors) [French] Les auteurs ont mis au point un ensemble experimental permettant d'obtenir un jet d'atomes d'hydrogene ou de deuterium, dans lequel les protons et les deutons sont polarises. Grace a la methode du 'passage adiabatique' une polarisation de protons voisine de 100 pour cent est obtenue. (auteurs)

  5. Improving performances of suboptimal greedy iterative biclustering heuristics via localization.

    Science.gov (United States)

    Erten, Cesim; Sözdinler, Melih

    2010-10-15

    Biclustering gene expression data is the problem of extracting submatrices of genes and conditions exhibiting significant correlation across both the rows and the columns of a data matrix of expression values. Even the simplest versions of the problem are computationally hard. Most of the proposed solutions therefore employ greedy iterative heuristics that locally optimize a suitably assigned scoring function. We provide a fast and simple pre-processing algorithm called localization that reorders the rows and columns of the input data matrix in such a way as to group correlated entries in small local neighborhoods within the matrix. The proposed localization algorithm takes its roots from effective use of graph-theoretical methods applied to problems exhibiting a similar structure to that of biclustering. In order to evaluate the effectivenesss of the localization pre-processing algorithm, we focus on three representative greedy iterative heuristic methods. We show how the localization pre-processing can be incorporated into each representative algorithm to improve biclustering performance. Furthermore, we propose a simple biclustering algorithm, Random Extraction After Localization (REAL) that randomly extracts submatrices from the localization pre-processed data matrix, eliminates those with low similarity scores, and provides the rest as correlated structures representing biclusters. We compare the proposed localization pre-processing with another pre-processing alternative, non-negative matrix factorization. We show that our fast and simple localization procedure provides similar or even better results than the computationally heavy matrix factorization pre-processing with regards to H-value tests. We next demonstrate that the performances of the three representative greedy iterative heuristic methods improve with localization pre-processing when biological correlations in the form of functional enrichment and PPI verification constitute the main performance

  6. Uncertainties in Life Cycle Greenhouse Gas Emissions from Advanced Biomass Feedstock Logistics Supply Chains in Kansas

    Directory of Open Access Journals (Sweden)

    Long Nguyen

    2014-11-01

    Full Text Available To meet Energy Independence and Security Act (EISA cellulosic biofuel mandates, the United States will require an annual domestic supply of about 242 million Mg of biomass by 2022. To improve the feedstock logistics of lignocellulosic biofuels in order to access available biomass resources from areas with varying yields, commodity systems have been proposed and designed to deliver quality-controlled biomass feedstocks at preprocessing “depots”. Preprocessing depots densify and stabilize the biomass prior to long-distance transport and delivery to centralized biorefineries. The logistics of biomass commodity supply chains could introduce spatially variable environmental impacts into the biofuel life cycle due to needing to harvest, move, and preprocess biomass from multiple distances that have variable spatial density. This study examines the uncertainty in greenhouse gas (GHG emissions of corn stover logistics within a bio-ethanol supply chain in the state of Kansas, where sustainable biomass supply varies spatially. Two scenarios were evaluated each having a different number of depots of varying capacity and location within Kansas relative to a central commodity-receiving biorefinery to test GHG emissions uncertainty. The first scenario sited four preprocessing depots evenly across the state of Kansas but within the vicinity of counties having high biomass supply density. The second scenario located five depots based on the shortest depot-to-biorefinery rail distance and biomass availability. The logistics supply chain consists of corn stover harvest, collection and storage, feedstock transport from field to biomass preprocessing depot, preprocessing depot operations, and commodity transport from the biomass preprocessing depot to the biorefinery. Monte Carlo simulation was used to estimate the spatial uncertainty in the feedstock logistics gate-to-gate sequence. Within the logistics supply chain GHG emissions are most sensitive to the

  7. Multi-objective optimization for an automated and simultaneous phase and baseline correction of NMR spectral data

    Science.gov (United States)

    Sawall, Mathias; von Harbou, Erik; Moog, Annekathrin; Behrens, Richard; Schröder, Henning; Simoneau, Joël; Steimers, Ellen; Neymeyr, Klaus

    2018-04-01

    Spectral data preprocessing is an integral and sometimes inevitable part of chemometric analyses. For Nuclear Magnetic Resonance (NMR) spectra a possible first preprocessing step is a phase correction which is applied to the Fourier transformed free induction decay (FID) signal. This preprocessing step can be followed by a separate baseline correction step. Especially if series of high-resolution spectra are considered, then automated and computationally fast preprocessing routines are desirable. A new method is suggested that applies the phase and the baseline corrections simultaneously in an automated form without manual input, which distinguishes this work from other approaches. The underlying multi-objective optimization or Pareto optimization provides improved results compared to consecutively applied correction steps. The optimization process uses an objective function which applies strong penalty constraints and weaker regularization conditions. The new method includes an approach for the detection of zero baseline regions. The baseline correction uses a modified Whittaker smoother. The functionality of the new method is demonstrated for experimental NMR spectra. The results are verified against gravimetric data. The method is compared to alternative preprocessing tools. Additionally, the simultaneous correction method is compared to a consecutive application of the two correction steps.

  8. Analyses and quantitative determination of the strontium radioisotopes 89 and 90 in milk powder; Recherche et dosage des isotopes radioactifs 89 et 90 du strontium dans le lait en poudre

    Energy Technology Data Exchange (ETDEWEB)

    Jeanmaire, L; Michon, G [Commissariat a l' Energie Atomique, Saclay (France).Centre d' Etudes Nucleaires

    1959-07-01

    The authors describe a procedure for the determination of the strontium radioisotopes 89 and 90. The concentration of strontium is made possible by the insolubility of its nitrate salt in strong nitric acid which allows the removal of greatest part of calcium. The purification is performed on a cation exchange column. The amount of radioisotope 90 is determined by means of its daughter product yttrium 90 necessary calibrations and computations are treated in special paragraphs. With regard to the reproducibility of the measurements, the fluctuations are less than 20 per cent. This seems satisfaction for such a technique which have great sensibility while being long and necessitative great carefulness. (author) [French] Les auteurs decrivent une technique de dosage des isotopes 89 et 90 du strontium. La concentration du strontium est assuree grace a l'insolubilite de son nitrate dans l'acide nitrique concentre, ce qui permet d'eliminer la plus grande partie du Ca. La purification se fait sur une colonne echangeuse de cations. L'isotope 90 est dose grace a son descendant l'yttrium 90. Les etalonnages et calculs necessaires font l'objet de paragraphes detailles. En ce qui concerne la reproductibilite des mesures, les fluctuations sont inferieures a 20 pour cent, ce qui semble satisfaisant devant la grande sensibilite de la methode qui reste cependant longue et delicate. (auteur)

  9. First results from the GPS atmosphere sounding experiment TOR aboard the TerraSAR-X satellite

    Directory of Open Access Journals (Sweden)

    G. Beyerle

    2011-07-01

    Full Text Available GPS radio occultation events observed between 24 July and 17 November 2008 by the IGOR occultation receiver aboard the TerraSAR-X satellite are processed and analyzed. The comparison of 15 327 refractivity profiles with collocated ECMWF data yield a mean bias between zero and −0.30 % at altitudes between 5 and 30 km. Standard deviations decrease from about 1.4 % at 5 km to about 0.6 % at 10 km altitude, however, increase significantly in the upper stratosphere. At low latitudes mean biases and standard deviations are larger, in particular in the lower troposphere. The results are consistent with 15 159 refractivity observations collected during the same time period by the BlackJack receiver aboard GRACE-A and processed by GFZ's operational processing system. The main difference between the two occultation instruments is the implementation of open-loop signal tracking in the IGOR (TerraSAR-X receiver which improves the tropospheric penetration depth in terms of ray height by about 2 km compared to the conventional closed-loop data acquired by BlackJack (GRACE-A.

  10. Automatic Semantic Orientation of Adjectives for Indonesian Language Using PMI-IR and Clustering

    Science.gov (United States)

    Riyanti, Dewi; Arif Bijaksana, M.; Adiwijaya

    2018-03-01

    We present our work in the area of sentiment analysis for Indonesian language. We focus on bulding automatic semantic orientation using available resources in Indonesian. In this research we used Indonesian corpus that contains 9 million words from kompas.txt and tempo.txt that manually tagged and annotated with of part-of-speech tagset. And then we construct a dataset by taking all the adjectives from the corpus, removing the adjective with no orientation. The set contained 923 adjective words. This systems will include several steps such as text pre-processing and clustering. The text pre-processing aims to increase the accuracy. And finally clustering method will classify each word to related sentiment which is positive or negative. With improvements to the text preprocessing, can be achieved 72% of accuracy.

  11. AN IMPLEMENTATION OF EIS-SVM CLASSIFIER USING RESEARCH ARTICLES FOR TEXT CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    B Ramesh

    2016-04-01

    Full Text Available Automatic text classification is a prominent research topic in text mining. The text pre-processing is a major role in text classifier. The efficiency of pre-processing techniques is increasing the performance of text classifier. In this paper, we are implementing ECAS stemmer, Efficient Instance Selection and Pre-computed Kernel Support Vector Machine for text classification using recent research articles. We are using better pre-processing techniques such as ECAS stemmer to find root word, Efficient Instance Selection for dimensionality reduction of text data and Pre-computed Kernel Support Vector Machine for classification of selected instances. In this experiments were performed on 750 research articles with three classes such as engineering article, medical articles and educational articles. The EIS-SVM classifier provides better performance in real-time research articles classification.

  12. Phase-aware echocardiogram stabilization using keyframes.

    Science.gov (United States)

    Wu, Hui; Huynh, Toan T; Souvenir, Richard

    2017-01-01

    This paper presents an echocardiogram stabilization method designed to compensate for unwanted auxilliary motion. Echocardiograms contain both deformable cardiac motion and approximately rigid motion due to a number of factors. The goal of this work is to stabilize the video, while preserving the informative deformable cardiac motion. Our approach incorporates synchronized side information, extracted from electrocardiography (ECG), which provides a proxy for cardiac phase. To avoid the computational expense of pairwise alignment, we propose an efficient strategy for keyframe selection, formulated as a submodular optimization problem. We evaluate our approach quantitatively on synthetic data and demonstrate its benefit as a preprocessing step for two common echocardiogram applications: denoising and left ventricle segmentation. In both cases, preprocessing with our method improved the performance compared to no preprocessing or other alignment approaches. Copyright © 2016 Elsevier B.V. All rights reserved.

  13. Cloud screening Coastal Zone Color Scanner images using channel 5

    Science.gov (United States)

    Eckstein, B. A.; Simpson, J. J.

    1991-01-01

    Clouds are removed from Coastal Zone Color Scanner (CZCS) data using channel 5. Instrumentation problems require pre-processing of channel 5 before an intelligent cloud-screening algorithm can be used. For example, at intervals of about 16 lines, the sensor records anomalously low radiances. Moreover, the calibration equation yields negative radiances when the sensor records zero counts, and pixels corrupted by electronic overshoot must also be excluded. The remaining pixels may then be used in conjunction with the procedure of Simpson and Humphrey to determine the CZCS cloud mask. These results plus in situ observations of phytoplankton pigment concentration show that pre-processing and proper cloud-screening of CZCS data are necessary for accurate satellite-derived pigment concentrations. This is especially true in the coastal margins, where pigment content is high and image distortion associated with electronic overshoot is also present. The pre-processing algorithm is critical to obtaining accurate global estimates of pigment from spacecraft data.

  14. Illumination-invariant face recognition with a contrast sensitive silicon retina

    Energy Technology Data Exchange (ETDEWEB)

    Buhmann, J.M. [Rheinische Friedrich-Wilhelms-Univ., Bonn (Germany). Inst. fuer Informatik II; Lades, M. [Bochum Univ. (Germany). Inst. fuer Neuroinformatik; Eeckman, F. [Lawrence Livermore National Lab., CA (United States)

    1993-11-29

    Changes in lighting conditions strongly effect the performance and reliability of computer vision systems. We report face recognition results under drastically changing lighting conditions for a computer vision system which concurrently uses a contrast sensitive silicon retina and a conventional, gain controlled CCD camera. For both input devices the face recognition system employs an elastic matching algorithm with wavelet based features to classify unknown faces. To assess the effect of analog on-chip preprocessing by the silicon retina the CCD images have been digitally preprocessed with a bandpass filter to adjust the power spectrum. The silicon retina with its ability to adjust sensitivity increases the recognition rate up to 50 percent. These comparative experiments demonstrate that preprocessing with an analog VLSI silicon retina generates image data enriched with object-constant features.

  15. WekaPyScript: Classification, Regression, and Filter Schemes for WEKA Implemented in Python

    Directory of Open Access Journals (Sweden)

    Christopher Beckham

    2016-08-01

    Full Text Available WekaPyScript is a package for the machine learning software WEKA that allows learning algorithms and preprocessing methods for classification and regression to be written in Python, as opposed to WEKA’s implementation language, Java. This opens up WEKA to its machine learning and scientific computing ecosystem. Furthermore, due to Python’s minimalist syntax, learning algorithms and preprocessing methods can be prototyped easily and utilised from within WEKA. WekaPyScript works by running a local Python server using the host’s installation of Python; as a result, any libraries installed in the host installation can be leveraged when writing a script for WekaPyScript. Three example scripts (two learning algorithms and one preprocessing method are presented.

  16. Nonterrestrial material processing and manufacturing of large space systems

    Science.gov (United States)

    Von Tiesenhausen, G.

    1979-01-01

    Nonterrestrial processing of materials and manufacturing of large space system components from preprocessed lunar materials at a manufacturing site in space is described. Lunar materials mined and preprocessed at the lunar resource complex will be flown to the space manufacturing facility (SMF), where together with supplementary terrestrial materials, they will be final processed and fabricated into space communication systems, solar cell blankets, radio frequency generators, and electrical equipment. Satellite Power System (SPS) material requirements and lunar material availability and utilization are detailed, and the SMF processing, refining, fabricating facilities, material flow and manpower requirements are described.

  17. Using a digital signal processor as a data stream controller for digital subtraction angiography

    International Nuclear Information System (INIS)

    Meng, J.D.; Katz, J.E.

    1991-10-01

    High speed, flexibility, and good arithmetic abilities make digital signal processors (DSP) a good choice as input/output controllers for real time applications. The DSP can be made to pre-process data in real time to reduce data volume, to open early windows on what is being acquired and to implement local servo loops. We present an example of a DSP as an input/output controller for a digital subtraction angiographic imaging system. The DSP pre-processes the raw data, reducing data volume by a factor of two, and is potentially capable of producing real-time subtracted images for immediate display

  18. Performance Improvement of Power Analysis Attacks on AES with Encryption-Related Signals

    Science.gov (United States)

    Lee, You-Seok; Lee, Young-Jun; Han, Dong-Guk; Kim, Ho-Won; Kim, Hyoung-Nam

    A power analysis attack is a well-known side-channel attack but the efficiency of the attack is frequently degraded by the existence of power components, irrelative to the encryption included in signals used for the attack. To enhance the performance of the power analysis attack, we propose a preprocessing method based on extracting encryption-related parts from the measured power signals. Experimental results show that the attacks with the preprocessed signals detect correct keys with much fewer signals, compared to the conventional power analysis attacks.

  19. Computing with high-resolution upwind schemes for hyperbolic equations

    International Nuclear Information System (INIS)

    Chakravarthy, S.R.; Osher, S.; California Univ., Los Angeles)

    1985-01-01

    Computational aspects of modern high-resolution upwind finite-difference schemes for hyperbolic systems of conservation laws are examined. An operational unification is demonstrated for constructing a wide class of flux-difference-split and flux-split schemes based on the design principles underlying total variation diminishing (TVD) schemes. Consideration is also given to TVD scheme design by preprocessing, the extension of preprocessing and postprocessing approaches to general control volumes, the removal of expansion shocks and glitches, relaxation methods for implicit TVD schemes, and a new family of high-accuracy TVD schemes. 21 references

  20. High Classification Rates for Continuous Cow Activity Recognition using Low-cost GPS Positioning Sensors and Standard Machine Learning Techniques

    DEFF Research Database (Denmark)

    Godsk, Torben; Kjærgaard, Mikkel Baun

    2011-01-01

    activities. By preprocessing the raw cow position data, we obtain high classification rates using standard machine learning techniques to recognize cow activities. Our objectives were to (i) determine to what degree it is possible to robustly recognize cow activities from GPS positioning data, using low...... and their activities manually logged to serve as ground truth. For our dataset we managed to obtain an average classification success rate of 86.2% of the four activities: eating/seeking (90.0%), walking (100%), lying (76.5%), and standing (75.8%) by optimizing both the preprocessing of the raw GPS data...

  1. Evaluation of small area crop estimation techniques using LANDSAT- and ground-derived data. [South Dakota

    Science.gov (United States)

    Amis, M. L.; Martin, M. V.; Mcguire, W. G.; Shen, S. S. (Principal Investigator)

    1982-01-01

    Studies completed in fiscal year 1981 in support of the clustering/classification and preprocessing activities of the Domestic Crops and Land Cover project. The theme throughout the study was the improvement of subanalysis district (usually county level) crop hectarage estimates, as reflected in the following three objectives: (1) to evaluate the current U.S. Department of Agriculture Statistical Reporting Service regression approach to crop area estimation as applied to the problem of obtaining subanalysis district estimates; (2) to develop and test alternative approaches to subanalysis district estimation; and (3) to develop and test preprocessing techniques for use in improving subanalysis district estimates.

  2. Neural processing of auditory signals and modular neural control for sound tropism of walking machines

    DEFF Research Database (Denmark)

    Manoonpong, Poramate; Pasemann, Frank; Fischer, Joern

    2005-01-01

    and a neural preprocessing system together with a modular neural controller are used to generate a sound tropism of a four-legged walking machine. The neural preprocessing network is acting as a low-pass filter and it is followed by a network which discerns between signals coming from the left or the right....... The parameters of these networks are optimized by an evolutionary algorithm. In addition, a simple modular neural controller then generates the desired different walking patterns such that the machine walks straight, then turns towards a switched-on sound source, and then stops near to it....

  3. Highway three-dimensional modeling based on Vehicle-borne laser data

    International Nuclear Information System (INIS)

    Weili, Sun; Ruofei, Zhong; Jiangxia, Wei; Fanyang, Zeng

    2014-01-01

    The of Vehicle-borne LiDAR (Light Detection And Ranging) scanning technology is an efficiently practical approach on the acquisition and application of 3D information and its geographic elements of highway(including road surface, rails, attached facilities, slopes, ditches, etc.). The acquired information is significant on many aspects such as road maintenance, reconstruction, survey, landscape design, visualized modelling and highway hazard supervision and prevention. The initial laser data cannot be directly used to construct highway 3D model, operations of pre-processing are necessary. This paper presented a set of procedure about pre-processing laser data and constructing TIN (Triangle Irregular Net) model of highway

  4. Processing method of images obtained during the TESIS/CORONAS-PHOTON experiment

    Science.gov (United States)

    Kuzin, S. V.; Shestov, S. V.; Bogachev, S. A.; Pertsov, A. A.; Ulyanov, A. S.; Reva, A. A.

    2011-04-01

    In January 2009, the CORONAS-PHOTON spacecraft was successfully launched. It includes a set of telescopes and spectroheliometers—TESIS—designed to image the solar corona in soft X-ray and EUV spectral ranges. Due to features of the reading system, to obtain physical information from these images, it is necessary to preprocess them, i.e., to remove the background, correct the white field, level, and clean. The paper discusses the algorithms and software developed and used for the preprocessing of images.

  5. Improving Feature Representation Based on a Neural Network for Author Profiling in Social Media Texts.

    Science.gov (United States)

    Gómez-Adorno, Helena; Markov, Ilia; Sidorov, Grigori; Posadas-Durán, Juan-Pablo; Sanchez-Perez, Miguel A; Chanona-Hernandez, Liliana

    2016-01-01

    We introduce a lexical resource for preprocessing social media data. We show that a neural network-based feature representation is enhanced by using this resource. We conducted experiments on the PAN 2015 and PAN 2016 author profiling corpora and obtained better results when performing the data preprocessing using the developed lexical resource. The resource includes dictionaries of slang words, contractions, abbreviations, and emoticons commonly used in social media. Each of the dictionaries was built for the English, Spanish, Dutch, and Italian languages. The resource is freely available.

  6. zipHMMlib:

    DEFF Research Database (Denmark)

    Sand, Andreas; Kristiansen, Martin; Pedersen, Christian Nørgaard Storm

    2013-01-01

    the computations in the forward algorithm which can be reused. This analysis can be saved between uses of the library and is independent of concrete hidden Markov models so one preprocessing can be used to run a number of different models. Using this library, we achieve up to 78 times shorter wall-clock time...... have built a software library for efficiently computing the likelihood of a hidden Markov model. The library exploits commonly occurring substrings in the input to reuse computations in the forward algorithm. In a pre-processing step our library identifies common substrings and builds a structure over...

  7. Flexible Method for the Automated Offline-Detection of Artifacts in Multi-Channel Electroencephalogram Recordings

    DEFF Research Database (Denmark)

    Waser, Markus; Garn, Heinrich; Benke, Thomas

    2017-01-01

    . However, these preprocessing steps do not allow for complete artifact correction. We propose a method for the automated offline-detection of remaining artifacts after preprocessing in multi-channel EEG recordings. In contrast to existing methods it requires neither adaptive parameters varying between...... recordings nor a topography template. It is suited for short EEG segments and is flexible with regard to target applications. The algorithm was developed and tested on 60 clinical EEG samples of 20 seconds each that were recorded both in resting state and during cognitive activation to gain a realistic...

  8. Application of up-sampling and resolution scaling to Fresnel reconstruction of digital holograms.

    Science.gov (United States)

    Williams, Logan A; Nehmetallah, Georges; Aylo, Rola; Banerjee, Partha P

    2015-02-20

    Fresnel transform implementation methods using numerical preprocessing techniques are investigated in this paper. First, it is shown that up-sampling dramatically reduces the minimum reconstruction distance requirements and allows maximal signal recovery by eliminating aliasing artifacts which typically occur at distances much less than the Rayleigh range of the object. Second, zero-padding is employed to arbitrarily scale numerical resolution for the purpose of resolution matching multiple holograms, where each hologram is recorded using dissimilar geometric or illumination parameters. Such preprocessing yields numerical resolution scaling at any distance. Both techniques are extensively illustrated using experimental results.

  9. Semi-Homomorphic Encryption and Multiparty Computation

    DEFF Research Database (Denmark)

    Bendlin, Rikke; Damgård, Ivan Bjerre; Orlandi, Claudio

    2011-01-01

    allow us to construct an efficient multiparty computation protocol for arithmetic circuits, UC-secure against a dishonest majority. The protocol consists of a preprocessing phase and an online phase. Neither the inputs nor the function to be computed have to be known during preprocessing. Moreover......, the online phase is extremely efficient as it requires no cryptographic operations: the parties only need to exchange additive shares and verify information theoretic MACs. Our contribution is therefore twofold: from a theoretical point of view, we can base multiparty computation on a variety of different...

  10. Deterministic indexing for packed strings

    DEFF Research Database (Denmark)

    Bille, Philip; Gørtz, Inge Li; Skjoldjensen, Frederik Rye

    2017-01-01

    Given a string S of length n, the classic string indexing problem is to preprocess S into a compact data structure that supports efficient subsequent pattern queries. In the deterministic variant the goal is to solve the string indexing problem without any randomization (at preprocessing time...... or query time). In the packed variant the strings are stored with several character in a single word, giving us the opportunity to read multiple characters simultaneously. Our main result is a new string index in the deterministic and packed setting. Given a packed string S of length n over an alphabet σ...

  11. New baseline correction algorithm for text-line recognition with bidirectional recurrent neural networks

    Science.gov (United States)

    Morillot, Olivier; Likforman-Sulem, Laurence; Grosicki, Emmanuèle

    2013-04-01

    Many preprocessing techniques have been proposed for isolated word recognition. However, recently, recognition systems have dealt with text blocks and their compound text lines. In this paper, we propose a new preprocessing approach to efficiently correct baseline skew and fluctuations. Our approach is based on a sliding window within which the vertical position of the baseline is estimated. Segmentation of text lines into subparts is, thus, avoided. Experiments conducted on a large publicly available database (Rimes), with a BLSTM (bidirectional long short-term memory) recurrent neural network recognition system, show that our baseline correction approach highly improves performance.

  12. Summary Report: Multigrid for Systems of Elliptic PDEs

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Barry [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2016-11-17

    We are interested in determining if multigrid can be effectively applied to the system. The conclusion that I seem to be drawn to is that it is impossible to develop a blackbox multigrid solver for these general systems. Analysis of the system of PDEs must be conducted first to determine pre-processing procedures on the continuous problem before applying a multigrid method. Determining this pre-processing is currently not incorporated in black-box multigrid strategies. Nevertheless, we characterize some system features that will make the system more amenable to multigrid approaches, techniques that may lead to more amenable systems, and multigrid procedures that are generally more appropriate for these systems.

  13. RAWS II: A MULTIPLE REGRESSION ANALYSIS PROGRAM,

    Science.gov (United States)

    This memorandum gives instructions for the use and operation of a revised version of RAWS, a multiple regression analysis program. The program...of preprocessed data, the directed retention of variable, listing of the matrix of the normal equations and its inverse, and the bypassing of the regression analysis to provide the input variable statistics only. (Author)

  14. Combining Illumination Normalization Methods for Better Face Recognition

    NARCIS (Netherlands)

    Boom, B.J.; Tao, Q.; Spreeuwers, Lieuwe Jan; Veldhuis, Raymond N.J.

    2009-01-01

    Face Recognition under uncontrolled illumination conditions is partly an unsolved problem. There are two categories of illumination normalization methods. The first category performs a local preprocessing, where they correct a pixel value based on a local neighborhood in the images. The second

  15. Multivariate Analysis of Industrial Scale Fermentation Data

    DEFF Research Database (Denmark)

    Mears, Lisa; Nørregård, Rasmus; Stocks, Stuart M.

    2015-01-01

    Multivariate analysis allows process understanding to be gained from the vast and complex datasets recorded from fermentation processes, however the application of such techniques to this field can be limited by the data pre-processing requirements and data handling. In this work many iterations...

  16. Wood to energy: using southern interface fuels for bioenergy

    Science.gov (United States)

    C. Staudhammer; L.A. Hermansen; D. Carter; Ed Macie

    2011-01-01

    This publications aims to increase awareness of potential uses for woody biomass in the southern wildland-urban interface (WUI) and to disseminate knowledge about putting bioenergy production systems in place, while addressing issues unique to WUI areas. Chapter topics include woody biomass sources in the wildland-urban interface; harvesting, preprocessing and delivery...

  17. BJUT at TREC 2015 Microblog Track: Real-Time Filtering Using Non-negative Matrix Factorization

    Science.gov (United States)

    2015-11-20

    query accurate ambiguity intergration Tweets Vector Preprocessing W-d matrix Feature vector Similarity ranking Recommended twittres Get...recommendation tech- nique based on product category attributes[J]. Expert Systems with Applications, 2009, 36(9): 11480-11488. [5] Sobecki J, Babiak E,Sanina M

  18. New Ideas on Labeling Schemes

    DEFF Research Database (Denmark)

    Rotbart, Noy Galil

    With ever increasing size of graphs, many distributed graph systems emerged to store, preprocess and analyze them. While such systems ease up congestion on servers, they incur certain penalties compared to centralized data structure. First, the total storage required to store a graph in a distrib...

  19. The effect of image enhancement on the statistical analysis of functional neuroimages : Wavelet-based denoising and Gaussian smoothing

    NARCIS (Netherlands)

    Wink, AM; Roerdink, JBTM; Sonka, M; Fitzpatrick, JM

    2003-01-01

    The quality of statistical analyses of functional neuroimages is studied after applying various preprocessing methods. We present wavelet-based denoising as an alternative to Gaussian smoothing, the standard denoising method in statistical parametric mapping (SPM). The wavelet-based denoising

  20. Marker-controlled watershed segmentation of nuclei in H&E stained breast cancer biopsy images

    NARCIS (Netherlands)

    Veta, M.; Huisman, A.; Viergever, M.A.; Diest, van P.J.; Pluim, J.P.W.

    2011-01-01

    In this paper we present an unsupervised automatic method for segmentation of nuclei in H&E stained breast cancer biopsy images. Colour deconvolution and morphological operations are used to preprocess the images in order to remove irrelevant structures. Candidate nuclei locations, obtained with the

  1. Improving mine recognition through processing and Dempster-Shafer fusion of ground-penetrating radar data

    NARCIS (Netherlands)

    Milisavljević, N.; Bloch, I.; Broek, S.P. van den; Acheroy, M.

    2003-01-01

    A methodfor modeling andcombination of measures extractedfrom a ground-penetrating radar (GPR) in terms of belief functions within the Dempster-Shafer framework is presentedandillustratedon a real GPR data set. A starting point in the analysis is a preprocessed C-scan of a sand-lane containing some

  2. Implementation and testing of WELD and automatic spectral rule-based classifications for Landsat ETM+ in South Africa

    CSIR Research Space (South Africa)

    Wessels, Konrad J

    2013-04-01

    Full Text Available The Web-enabled Landsat Data (WELD) system was successfully installed in South Africa (SA) and used for pre-processing large amounts of Landsat ETM+ data to composited seasonal mosaics. In pursuit of automated land cover mapping, the overall...

  3. Quality effect of freeze-chilling in cod and rainbow trout

    DEFF Research Database (Denmark)

    Jensen, Louise Helene Søgaard; Nielsen, Jette; Jørgensen, Bo

    ‘Meal elements’ is the name of a concept in which elements of a meal, e.g. portions of pre-fried meat, sauces, fish or pre-processed vegetables are prepared industrially. The meal elements are distributed to professional satellite kitchens for instance in hospitals and canteens, where the kitchen...

  4. Beatrice Hill Virus Represents a Novel Species in the Genus Tibrovirus (Mononegavirales: Rhabdoviridae)

    Science.gov (United States)

    2017-01-26

    Bioinformatics in Action 17:10-12. 2 15. Schmieder R, Edwards R. 2011. Quality control and preprocessing of metagenomic 3 datasets. Bioinformatics...2Commonwealth Scientific and Industrial Research Organisation (CSIRO), Health 7 and Biosecurity, Australian Animal Health Laboratory , Geelong, Victoria...Frederick), Division of Clinical Research (DCR), National Institute of Allergy and Infectious 15 Diseases (NIAID), National Institutes of Health

  5. An approach for extracting the vein and heart boundaries from raw NM images

    International Nuclear Information System (INIS)

    Mitrovski, Cvetko D.; Kostov, Mitko B.

    2003-01-01

    In this paper we present our approach on prE.processing chest region dynamical NM images which enables anatomical data extraction of the vena cava and the heart. The aim of the method is developing sophisticated diagnostic software that could automatically offer the optimal positions and the shapes of the regions of interest needed for the heart studies. (Author)

  6. Safe reduction rules for weighted treewidth

    NARCIS (Netherlands)

    Eijkhof, F. van den; Bodlaender, H.L.; Koster, A.M.C.A.

    2002-01-01

    Several sets of reductions rules are known for preprocessing a graph when computing its treewidth. In this paper, we give reduction rules for a weighted variant of treewidth, motivated by the analysis of algorithms for probabilistic networks. We present two general reduction rules that are safe for

  7. Incremental Learning of Medical Data for Multi-Step Patient Health Classification

    DEFF Research Database (Denmark)

    Kranen, Philipp; Müller, Emmanuel; Assent, Ira

    2010-01-01

    of textile sensors, body sensors and preprocessing techniques as well as the integration and merging of sensor data in electronic health record systems. Emergency detection on multiple levels will show the benefits of multi-step classification and further enhance the scalability of emergency detection...

  8. Non-uniform crosstalk reduction for dynamic scenes

    NARCIS (Netherlands)

    Smit, F.A.; Liere, van R.; Fröhlich, B.

    2007-01-01

    Stereo displays suffer from crosstalk, an effect that reduces or even inhibits the viewer's ability to correctly perceive depth. Previous work on software crosstalk reduction focussed on the preprocessing of static scenes which are viewed from a fixed viewpoint. However, in virtual environments

  9. Impact of eye detection error on face recognition performance

    NARCIS (Netherlands)

    Dutta, A.; Günther, Manuel; El Shafey, Laurent; Veldhuis, Raymond N.J.; Spreeuwers, Lieuwe Jan

    2015-01-01

    The locations of the eyes are the most commonly used features to perform face normalisation (i.e. alignment of facial features), which is an essential preprocessing stage of many face recognition systems. In this study, the authors study the sensitivity of open source implementations of five face

  10. Hybrid Adaptive/Nonadaptive Delayed Signal Cancellation-Based Phase-Locked Loop

    DEFF Research Database (Denmark)

    Golestan, Saeed; Guerrero, Josep M.; Quintero, Juan Carlos Vasquez

    2017-01-01

    cancellation (DSC) operator is highly popular probably because it can be easily tailored for different grid scenarios. The DSC operator(s) can be used either as an in-loop filter in the PLL structure or as a preprocessing filter before the PLL input. The latter case is often preferred mainly because it results...

  11. An intelligent trust-based access control model for affective ...

    African Journals Online (AJOL)

    In this study, a fuzzy expert system Trust-Based Access Control (TBAC) model for improving the Quality of crowdsourcing using emotional affective computing is presented. This model takes into consideration a pre-processing module consisting of three inputs such as crowd-workers category, trust metric and emotional ...

  12. Display graphical information optimization methods in a client-server information system

    Directory of Open Access Journals (Sweden)

    Юрий Викторович Мазуревич

    2015-07-01

    Full Text Available This paper presents an approach to reduce load time and volume of data necessary to display web page due to server side preprocessing. Measurement of this approach’s effectivity has been conducted. There were discovered conditions in which this approach will be the most effective, its disadvantages and presented ways to reduce them

  13. Image and Sensor Data Processing for Target Acquisition and Recognition.

    Science.gov (United States)

    1980-11-01

    speculations, and an exciting theme with which I can finish, that once we can invent our way into the connectivity problem and have reached the levels...to operate 10’ times faster! The future is unimaginably exciting . " - -. . .. .. .. . ti ii. I ~i . . . ... . . .. ... I . . ... . .. . .. . . . . . I...parallel operations often used for picture preprocessing and feature extraction. Those parallel operations are spatial imagefiltering , template

  14. Analysis of single nucleotide polymorphisms in case-control studies.

    Science.gov (United States)

    Li, Yonghong; Shiffman, Dov; Oberbauer, Rainer

    2011-01-01

    Single nucleotide polymorphisms (SNPs) are the most common type of genetic variants in the human genome. SNPs are known to modify susceptibility to complex diseases. We describe and discuss methods used to identify SNPs associated with disease in case-control studies. An outline on study population selection, sample collection and genotyping platforms is presented, complemented by SNP selection, data preprocessing and analysis.

  15. Evaluation of colour in white and yellow trifoliate yam flours in ...

    African Journals Online (AJOL)

    Colour is one of the important sensory properties that determine the acceptability of food products. Therefore, this work determines the colour in white and yellow trifoliate yam flours in relation to harvesting periods and pre-processing methods. Freshly harvested trifoliate yam tubers were prepared into flour using four ...

  16. Efficient Searching with Linear Constraints

    DEFF Research Database (Denmark)

    Agarwal, Pankaj K.; Arge, Lars Allan; Erickson, Jeff

    2000-01-01

    We show how to preprocess a set S of points in d into an external memory data structure that efficiently supports linear-constraint queries. Each query is in the form of a linear constraint xd a0+∑d−1i=1 aixi; the data structure must report all the points of S that satisfy the constraint. This pr...

  17. Masking as an effective quality control method for next-generation sequencing data analysis.

    Science.gov (United States)

    Yun, Sajung; Yun, Sijung

    2014-12-13

    Next generation sequencing produces base calls with low quality scores that can affect the accuracy of identifying simple nucleotide variation calls, including single nucleotide polymorphisms and small insertions and deletions. Here we compare the effectiveness of two data preprocessing methods, masking and trimming, and the accuracy of simple nucleotide variation calls on whole-genome sequence data from Caenorhabditis elegans. Masking substitutes low quality base calls with 'N's (undetermined bases), whereas trimming removes low quality bases that results in a shorter read lengths. We demonstrate that masking is more effective than trimming in reducing the false-positive rate in single nucleotide polymorphism (SNP) calling. However, both of the preprocessing methods did not affect the false-negative rate in SNP calling with statistical significance compared to the data analysis without preprocessing. False-positive rate and false-negative rate for small insertions and deletions did not show differences between masking and trimming. We recommend masking over trimming as a more effective preprocessing method for next generation sequencing data analysis since masking reduces the false-positive rate in SNP calling without sacrificing the false-negative rate although trimming is more commonly used currently in the field. The perl script for masking is available at http://code.google.com/p/subn/. The sequencing data used in the study were deposited in the Sequence Read Archive (SRX450968 and SRX451773).

  18. Fast Computation of Output-Sensitive Maxima in a Word RAM

    DEFF Research Database (Denmark)

    Afshani, Peyman

    2014-01-01

    In the concurrent range reporting (CRR) problem, the input is L disjoint sets S1..., SL of points in Rd with a total of N points. The goal is to preprocess the sets into a structure such that, given a query range r and an arbitrary set Q ⊆ {1,..., L}, we can efficiently report all the points in S...

  19. Microcomputer-based system for 24-hour recording of oesophageal motility and pH profile with automated analysis

    NARCIS (Netherlands)

    Breedijk, M.; Smout, A. J.; van der Zouw, C.; Verwey, H.; Akkermans, L. M.

    1989-01-01

    A system developed for long-term simultaneous recording of oesophageal motility and pH in the ambulant patient is described. The system consists of a microprocessor based data-acquisition and preprocessing device, a personal computer for postprocessing, report generation and data storage, a

  20. Sass essentials

    CERN Document Server

    Libby, Alex

    2015-01-01

    This book is primarily aimed at web designers who have a good understanding of CSS, jQuery, and HTML, but who are new to using CSS preprocessing. Some prior knowledge is assumed of WordPress, CSS grids, and Bootstrap, although these skills can be picked up reasonably quickly.