Parameter identification for nonlinear aerodynamic systems

NASA Technical Reports Server (NTRS)

Pearson, Allan E.

1992-01-01

Continuing work on frequency analysis for transfer function identification is discussed. A new study was initiated into a 'weighted' least squares algorithm within the context of the Fourier modulating function approach. The first phase of applying these techniques to the F-18 flight data is nearing completion, and these results are summarized.

USING THE HASSE DIAGRAM TECHNIQUE TO PRIORITIZE POTENTIAL PBTS

EPA Science Inventory

The identification of chemicals with PBT (Persistence, Bioaccumulation,Toxicity) potential is of major interest to many organizations. In the present study about 2800 commercially important chemicals are included.

Initially Hasse Diagram Technique (HDT) has been applied to...

Reliable dual-redundant sensor failure detection and identification for the NASA F-8 DFBW aircraft

NASA Technical Reports Server (NTRS)

Deckert, J. C.; Desai, M. N.; Deyst, J. J., Jr.; Willsky, A. S.

1978-01-01

A technique was developed which provides reliable failure detection and identification (FDI) for a dual redundant subset of the flight control sensors onboard the NASA F-8 digital fly by wire (DFBW) aircraft. The technique was successfully applied to simulated sensor failures on the real time F-8 digital simulator and to sensor failures injected on telemetry data from a test flight of the F-8 DFBW aircraft. For failure identification the technique utilized the analytic redundancy which exists as functional and kinematic relationships among the various quantities being measured by the different control sensor types. The technique can be used not only in a dual redundant sensor system, but also in a more highly redundant system after FDI by conventional voting techniques reduced to two the number of unfailed sensors of a particular type. In addition the technique can be easily extended to the case in which only one sensor of a particular type is available.

Remote sensing techniques for the detection of soil erosion and the identification of soil conservation practices

NASA Technical Reports Server (NTRS)

Pelletier, R. E.; Griffin, R. H.

1985-01-01

The following paper is a summary of a number of techniques initiated under the AgRISTARS (Agriculture and Resources Inventory Surveys Through Aerospace Remote Sensing) project for the detection of soil degradation caused by water erosion and the identification of soil conservation practices for resource inventories. Discussed are methods to utilize a geographic information system to determine potential soil erosion through a USLE (Universal Soil Loss Equation) model; application of the Kauth-Thomas Transform to detect present erosional status; and the identification of conservation practices through visual interpretation and a variety of enhancement procedures applied to digital remotely sensed data.

Raman scattering spectroscopy for explosives identification

NASA Astrophysics Data System (ADS)

Nagli, L.; Gaft, M.

2007-04-01

Real time detection and identification of explosives at a standoff distance is a major issue in efforts to develop defense against so-called Improvised Explosive Devices (IED). It is recognized that the only technique, which is potentially capable to standoff detection of minimal amounts of explosives is laser-based spectroscopy. LDS technique belongs to trace detection, namely to its micro-particles variety. We applied gated Raman and time-resolved luminescence spectroscopy for detection of main explosive materials, both factory and homemade. Raman system was developed and tested by LDS for field remote detection and identification of minimal amounts of explosives on relevant surfaces at a distance of up to 30 meters.

Target identification for small bioactive molecules: finding the needle in the haystack.

PubMed

Ziegler, Slava; Pries, Verena; Hedberg, Christian; Waldmann, Herbert

2013-03-04

Identification and confirmation of bioactive small-molecule targets is a crucial, often decisive step both in academic and pharmaceutical research. Through the development and availability of several new experimental techniques, target identification is, in principle, feasible, and the number of successful examples steadily grows. However, a generic methodology that can successfully be applied in the majority of the cases has not yet been established. Herein we summarize current methods for target identification of small molecules, primarily for a chemistry audience but also the biological community, for example, the chemist or biologist attempting to identify the target of a given bioactive compound. We describe the most frequently employed experimental approaches for target identification and provide several representative examples illustrating the state-of-the-art. Among the techniques currently available, protein affinity isolation using suitable small-molecule probes (pulldown) and subsequent mass spectrometric analysis of the isolated proteins appears to be most powerful and most frequently applied. To provide guidance for rapid entry into the field and based on our own experience we propose a typical workflow for target identification, which centers on the application of chemical proteomics as the key step to generate hypotheses for potential target proteins. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Identification of quasi-steady compressor characteristics from transient data

NASA Technical Reports Server (NTRS)

Nunes, K. B.; Rock, S. M.

1984-01-01

The principal goal was to demonstrate that nonlinear compressor map parameters, which govern an in-stall response, can be identified from test data using parameter identification techniques. The tasks included developing and then applying an identification procedure to data generated by NASA LeRC on a hybrid computer. Two levels of model detail were employed. First was a lumped compressor rig model; second was a simplified turbofan model. The main outputs are the tools and procedures generated to accomplish the identification.

Simple and fast multiplex PCR method for detection of species origin in meat products.

PubMed

Izadpanah, Mehrnaz; Mohebali, Nazanin; Elyasi Gorji, Zahra; Farzaneh, Parvaneh; Vakhshiteh, Faezeh; Shahzadeh Fazeli, Seyed Abolhassan

2018-02-01

Identification of animal species is one of the major concerns in food regulatory control and quality assurance system. Different approaches have been used for species identification in animal origin of feedstuff. This study aimed to develop a multiplex PCR approach to detect the origin of meat and meat products. Specific primers were designed based on the conserved region of mitochondrial Cytochrome C Oxidase subunit I ( COX1 ) gene. This method could successfully distinguish the origin of the pig, camel, sheep, donkey, goat, cow, and chicken in one single reaction. Since PCR products derived from each species represent unique molecular weight, the amplified products could be identified by electrophoresis and analyzed based on their size. Due to the synchronized amplification of segments within a single PCR reaction, multiplex PCR is considered to be a simple, fast, and inexpensive technique that can be applied for identification of meat products in food industries. Nowadays, this technique has been considered as a practical method to identify the species origin, which could further applied for animal feedstuffs identification.

Description and detection of burst events in turbulent flows

NASA Astrophysics Data System (ADS)

Schmid, P. J.; García-Gutierrez, A.; Jiménez, J.

2018-04-01

A mathematical and computational framework is developed for the detection and identification of coherent structures in turbulent wall-bounded shear flows. In a first step, this data-based technique will use an embedding methodology to formulate the fluid motion as a phase-space trajectory, from which state-transition probabilities can be computed. Within this formalism, a second step then applies repeated clustering and graph-community techniques to determine a hierarchy of coherent structures ranked by their persistencies. This latter information will be used to detect highly transitory states that act as precursors to violent and intermittent events in turbulent fluid motion (e.g., bursts). Used as an analysis tool, this technique allows the objective identification of intermittent (but important) events in turbulent fluid motion; however, it also lays the foundation for advanced control strategies for their manipulation. The techniques are applied to low-dimensional model equations for turbulent transport, such as the self-sustaining process (SSP), for varying levels of complexity.

Evaluation of the veracity of one work by the artist Di Cavalcanti through non-destructive techniques: XRF, imaging and brush stroke analysis

NASA Astrophysics Data System (ADS)

Kajiya, E. A. M.; Campos, P. H. O. V.; Rizzutto, M. A.; Appoloni, C. R.; Lopes, F.

2014-02-01

This paper presents systematic studies and analysis that contributed to the identification of the forgery of a work by the artist Emiliano Augusto Cavalcanti de Albuquerque e Melo, known as Di Cavalcanti. The use of several areas of expertise such as brush stroke analysis ("pinacologia"), applied physics, and art history resulted in an accurate diagnosis for ascertaining the authenticity of the work entitled "Violeiro" (1950). For this work we used non-destructive methods such as techniques of infrared, ultraviolet, visible and tangential light imaging combined with chemical analysis of the pigments by portable X-Ray Fluorescence (XRF) and graphic gesture analysis. Each applied method of analysis produced specific information that made possible the identification of materials and techniques employed and we concluded that this work is not consistent with patterns characteristic of the artist Di Cavalcanti.

Novel Application of FTIR Spectroscopy for the Passive Standoff Detection of Radiological Materials

DTIC Science & Technology

2006-08-01

possibility of applying the long-wave passive standoff detection technique to the identification of radiological materials. This work is based on...infrared (FTIR) radiometry is a well-known technique for detecting and identifying chemical warfare agents. In addition to these potential threats...necessary tools and techniques available for detecting and identifying radioactive products. At present, the main detection techniques depend on methods

Cyclo-stationary linear parameter time-varying subspace realization method applied for identification of horizontal-axis wind turbines

NASA Astrophysics Data System (ADS)

Velazquez, Antonio; Swartz, R. Andrew

2013-04-01

Wind energy is becoming increasingly important worldwide as an alternative renewable energy source. Economical, maintenance and operation are critical issues for large slender dynamic structures, especially for remote offshore wind farms. Health monitoring systems are very promising instruments to assure reliability and good performance of the structure. These sensing and control technologies are typically informed by models based on mechanics or data-driven identification techniques in the time and/or frequency domain. Frequency response functions are popular but are difficult to realize autonomously for structures of higher order and having overlapping frequency content. Instead, time-domain techniques have shown powerful advantages from a practical point of view (e.g. embedded algorithms in wireless-sensor networks), being more suitable to differentiate closely-related modes. Customarily, time-varying effects are often neglected or dismissed to simplify the analysis, but such is not the case for wind loaded structures with spinning multibodies. A more complex scenario is constituted when dealing with both periodic mechanisms responsible for the vibration shaft of the rotor-blade system, and the wind tower substructure interaction. Transformations of the cyclic effects on the vibration data can be applied to isolate inertia quantities different from rotating-generated forces that are typically non-stationary in nature. After applying these transformations, structural identification can be carried out by stationary techniques via data-correlated Eigensystem realizations. In this paper an exploration of a periodic stationary or cyclo-stationary subspace identification technique is presented here by means of a modified Eigensystem Realization Algorithm (ERA) via Stochastic Subspace Identification (SSI) and Linear Parameter Time-Varying (LPTV) techniques. Structural response is assumed under stationary ambient excitation produced by a Gaussian (white) noise assembled in the operative range bandwidth of horizontal-axis wind turbines. ERA-OKID analysis is driven by correlation-function matrices from the stationary ambient response aiming to reduce noise effects. Singular value decomposition (SVD) and eigenvalue analysis are computed in a last stage to get frequencies and mode shapes. Proposed assumptions are carefully weighted to account for the uncertainty of the environment the wind turbines are subjected to. A numerical example is presented based on data acquisition carried out in a BWC XL.1 low power wind turbine device installed in University of California at Davis. Finally, comments and observations are provided on how this subspace realization technique can be extended for modal-parameter identification using exclusively ambient vibration data.

Rotorcraft Blade Mode Damping Identification from Random Responses Using a Recursive Maximum Likelihood Algorithm

NASA Technical Reports Server (NTRS)

Molusis, J. A.

1982-01-01

An on line technique is presented for the identification of rotor blade modal damping and frequency from rotorcraft random response test data. The identification technique is based upon a recursive maximum likelihood (RML) algorithm, which is demonstrated to have excellent convergence characteristics in the presence of random measurement noise and random excitation. The RML technique requires virtually no user interaction, provides accurate confidence bands on the parameter estimates, and can be used for continuous monitoring of modal damping during wind tunnel or flight testing. Results are presented from simulation random response data which quantify the identified parameter convergence behavior for various levels of random excitation. The data length required for acceptable parameter accuracy is shown to depend upon the amplitude of random response and the modal damping level. Random response amplitudes of 1.25 degrees to .05 degrees are investigated. The RML technique is applied to hingeless rotor test data. The inplane lag regressing mode is identified at different rotor speeds. The identification from the test data is compared with the simulation results and with other available estimates of frequency and damping.

Improving photoelectron counting and particle identification in scintillation detectors with Bayesian techniques

NASA Astrophysics Data System (ADS)

Akashi-Ronquest, M.; Amaudruz, P.-A.; Batygov, M.; Beltran, B.; Bodmer, M.; Boulay, M. G.; Broerman, B.; Buck, B.; Butcher, A.; Cai, B.; Caldwell, T.; Chen, M.; Chen, Y.; Cleveland, B.; Coakley, K.; Dering, K.; Duncan, F. A.; Formaggio, J. A.; Gagnon, R.; Gastler, D.; Giuliani, F.; Gold, M.; Golovko, V. V.; Gorel, P.; Graham, K.; Grace, E.; Guerrero, N.; Guiseppe, V.; Hallin, A. L.; Harvey, P.; Hearns, C.; Henning, R.; Hime, A.; Hofgartner, J.; Jaditz, S.; Jillings, C. J.; Kachulis, C.; Kearns, E.; Kelsey, J.; Klein, J. R.; Kuźniak, M.; LaTorre, A.; Lawson, I.; Li, O.; Lidgard, J. J.; Liimatainen, P.; Linden, S.; McFarlane, K.; McKinsey, D. N.; MacMullin, S.; Mastbaum, A.; Mathew, R.; McDonald, A. B.; Mei, D.-M.; Monroe, J.; Muir, A.; Nantais, C.; Nicolics, K.; Nikkel, J. A.; Noble, T.; O'Dwyer, E.; Olsen, K.; Orebi Gann, G. D.; Ouellet, C.; Palladino, K.; Pasuthip, P.; Perumpilly, G.; Pollmann, T.; Rau, P.; Retière, F.; Rielage, K.; Schnee, R.; Seibert, S.; Skensved, P.; Sonley, T.; Vázquez-Jáuregui, E.; Veloce, L.; Walding, J.; Wang, B.; Wang, J.; Ward, M.; Zhang, C.

2015-05-01

Many current and future dark matter and neutrino detectors are designed to measure scintillation light with a large array of photomultiplier tubes (PMTs). The energy resolution and particle identification capabilities of these detectors depend in part on the ability to accurately identify individual photoelectrons in PMT waveforms despite large variability in pulse amplitudes and pulse pileup. We describe a Bayesian technique that can identify the times of individual photoelectrons in a sampled PMT waveform without deconvolution, even when pileup is present. To demonstrate the technique, we apply it to the general problem of particle identification in single-phase liquid argon dark matter detectors. Using the output of the Bayesian photoelectron counting algorithm described in this paper, we construct several test statistics for rejection of backgrounds for dark matter searches in argon. Compared to simpler methods based on either observed charge or peak finding, the photoelectron counting technique improves both energy resolution and particle identification of low energy events in calibration data from the DEAP-1 detector and simulation of the larger MiniCLEAN dark matter detector.

Comments on Frequency Swept Rotating Input Perturbation Techniques and Identification of the Fluid Force Models in Rotor/bearing/seal Systems and Fluid Handling Machines

NASA Technical Reports Server (NTRS)

Muszynska, Agnes; Bently, Donald E.

1991-01-01

Perturbation techniques used for identification of rotating system dynamic characteristics are described. A comparison between two periodic frequency-swept perturbation methods applied in identification of fluid forces of rotating machines is presented. The description of the fluid force model identified by inputting circular periodic frequency-swept force is given. This model is based on the existence and strength of the circumferential flow, most often generated by the shaft rotation. The application of the fluid force model in rotor dynamic analysis is presented. It is shown that the rotor stability is an entire rotating system property. Some areas for further research are discussed.

Methods for Multiloop Identification of Visual and Neuromuscular Pilot Responses.

PubMed

Olivari, Mario; Nieuwenhuizen, Frank M; Venrooij, Joost; Bülthoff, Heinrich H; Pollini, Lorenzo

2015-12-01

In this paper, identification methods are proposed to estimate the neuromuscular and visual responses of a multiloop pilot model. A conventional and widely used technique for simultaneous identification of the neuromuscular and visual systems makes use of cross-spectral density estimates. This paper shows that this technique requires a specific noninterference hypothesis, often implicitly assumed, that may be difficult to meet during actual experimental designs. A mathematical justification of the necessity of the noninterference hypothesis is given. Furthermore, two methods are proposed that do not have the same limitations. The first method is based on autoregressive models with exogenous inputs, whereas the second one combines cross-spectral estimators with interpolation in the frequency domain. The two identification methods are validated by offline simulations and contrasted to the classic method. The results reveal that the classic method fails when the noninterference hypothesis is not fulfilled; on the contrary, the two proposed techniques give reliable estimates. Finally, the three identification methods are applied to experimental data from a closed-loop control task with pilots. The two proposed techniques give comparable estimates, different from those obtained by the classic method. The differences match those found with the simulations. Thus, the two identification methods provide a good alternative to the classic method and make it possible to simultaneously estimate human's neuromuscular and visual responses in cases where the classic method fails.

A Supplementary Clear-Sky Snow and Ice Recognition Technique for CERES Level 2 Products

NASA Technical Reports Server (NTRS)

Radkevich, Alexander; Khlopenkov, Konstantin; Rutan, David; Kato, Seiji

2013-01-01

Identification of clear-sky snow and ice is an important step in the production of cryosphere radiation budget products, which are used in the derivation of long-term data series for climate research. In this paper, a new method of clear-sky snow/ice identification for Moderate Resolution Imaging Spectroradiometer (MODIS) is presented. The algorithm's goal is to enhance the identification of snow and ice within the Clouds and the Earth's Radiant Energy System (CERES) data after application of the standard CERES scene identification scheme. The input of the algorithm uses spectral radiances from five MODIS bands and surface skin temperature available in the CERES Single Scanner Footprint (SSF) product. The algorithm produces a cryosphere rating from an aggregated test: a higher rating corresponds to a more certain identification of the clear-sky snow/ice-covered scene. Empirical analysis of regions of interest representing distinctive targets such as snow, ice, ice and water clouds, open waters, and snow-free land selected from a number of MODIS images shows that the cryosphere rating of snow/ice targets falls into 95% confidence intervals lying above the same confidence intervals of all other targets. This enables recognition of clear-sky cryosphere by using a single threshold applied to the rating, which makes this technique different from traditional branching techniques based on multiple thresholds. Limited tests show that the established threshold clearly separates the cryosphere rating values computed for the cryosphere from those computed for noncryosphere scenes, whereas individual tests applied consequently cannot reliably identify the cryosphere for complex scenes.

Commissioning Cornell OSTs for SRF cavity testing at Jlab

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

Eremeev, Grigory

2011-07-01

Understanding the current quench limitations in SRF cavities is a topic essential for any SRF accelerator that requires high fields. This understanding crucially depends on correct and precise quench identification. Second sound quench detection in superfluid liquid helium with oscillating superleak transducers is a technique recently applied at Cornell University as a fast and versatile method for quench identification in SRF cavities. Having adopted Cornell design, we report in this contribution on our experience with OST for quench identification in different cavities at JLab.

Crop identification technology assessment for remote sensing (CITARS). Volume 10: Interpretation of results

NASA Technical Reports Server (NTRS)

Bizzell, R. M.; Feiveson, A. H.; Hall, F. G.; Bauer, M. E.; Davis, B. J.; Malila, W. A.; Rice, D. P.

1975-01-01

The CITARS was an experiment designed to quantitatively evaluate crop identification performance for corn and soybeans in various environments using a well-defined set of automatic data processing (ADP) techniques. Each technique was applied to data acquired to recognize and estimate proportions of corn and soybeans. The CITARS documentation summarizes, interprets, and discusses the crop identification performances obtained using (1) different ADP procedures; (2) a linear versus a quadratic classifier; (3) prior probability information derived from historic data; (4) local versus nonlocal recognition training statistics and the associated use of preprocessing; (5) multitemporal data; (6) classification bias and mixed pixels in proportion estimation; and (7) data with differnt site characteristics, including crop, soil, atmospheric effects, and stages of crop maturity.

Microorganism Response to Stressed Terrestrial Environments: A Raman Spectroscopic Perspective of Extremophilic Life Strategies

NASA Astrophysics Data System (ADS)

Jorge-Villar, Susana E.; Edwards, Howell G. M.

2013-03-01

Raman spectroscopy is a valuable analytical technique for the identification of biomolecules and minerals in natural samples, which involves little or minimal sample manipulation. In this paper, we evaluate the advantages and disadvantages of this technique applied to the study of extremophiles. Furthermore, we provide a review of the results published, up to the present point in time, of the bio- and geo-strategies adopted by different types of extremophile colonies of microorganisms. We also show the characteristic Raman signatures for the identification of pigments and minerals, which appear in those complex samples.

Incomplete data based parameter identification of nonlinear and time-variant oscillators with fractional derivative elements

NASA Astrophysics Data System (ADS)

Kougioumtzoglou, Ioannis A.; dos Santos, Ketson R. M.; Comerford, Liam

2017-09-01

Various system identification techniques exist in the literature that can handle non-stationary measured time-histories, or cases of incomplete data, or address systems following a fractional calculus modeling. However, there are not many (if any) techniques that can address all three aforementioned challenges simultaneously in a consistent manner. In this paper, a novel multiple-input/single-output (MISO) system identification technique is developed for parameter identification of nonlinear and time-variant oscillators with fractional derivative terms subject to incomplete non-stationary data. The technique utilizes a representation of the nonlinear restoring forces as a set of parallel linear sub-systems. In this regard, the oscillator is transformed into an equivalent MISO system in the wavelet domain. Next, a recently developed L1-norm minimization procedure based on compressive sensing theory is applied for determining the wavelet coefficients of the available incomplete non-stationary input-output (excitation-response) data. Finally, these wavelet coefficients are utilized to determine appropriately defined time- and frequency-dependent wavelet based frequency response functions and related oscillator parameters. Several linear and nonlinear time-variant systems with fractional derivative elements are used as numerical examples to demonstrate the reliability of the technique even in cases of noise corrupted and incomplete data.

Evaluating the performance of distributed approaches for modal identification

NASA Astrophysics Data System (ADS)

Krishnan, Sriram S.; Sun, Zhuoxiong; Irfanoglu, Ayhan; Dyke, Shirley J.; Yan, Guirong

2011-04-01

In this paper two modal identification approaches appropriate for use in a distributed computing environment are applied to a full-scale, complex structure. The natural excitation technique (NExT) is used in conjunction with a condensed eigensystem realization algorithm (ERA), and the frequency domain decomposition with peak-picking (FDD-PP) are both applied to sensor data acquired from a 57.5-ft, 10 bay highway sign truss structure. Monte-Carlo simulations are performed on a numerical example to investigate the statistical properties and sensitivity to noise of the two distributed algorithms. Experimental results are provided and discussed.

Spectral identification of a 90Sr source in the presence of masking nuclides using Maximum-Likelihood deconvolution

NASA Astrophysics Data System (ADS)

Neuer, Marcus J.

2013-11-01

A technique for the spectral identification of strontium-90 is shown, utilising a Maximum-Likelihood deconvolution. Different deconvolution approaches are discussed and summarised. Based on the intensity distribution of the beta emission and Geant4 simulations, a combined response matrix is derived, tailored to the β- detection process in sodium iodide detectors. It includes scattering effects and attenuation by applying a base material decomposition extracted from Geant4 simulations with a CAD model for a realistic detector system. Inversion results of measurements show the agreement between deconvolution and reconstruction. A detailed investigation with additional masking sources like 40K, 226Ra and 131I shows that a contamination of strontium can be found in the presence of these nuisance sources. Identification algorithms for strontium are presented based on the derived technique. For the implementation of blind identification, an exemplary masking ratio is calculated.

A Procedure for Estimating a Criterion-Referenced Standard to Identify Educationally Deprived Children for Title I Services. Final Report.

ERIC Educational Resources Information Center

Ziomek, Robert L.; Wright, Benjamin D.

Techniques such as the norm-referenced and average score techniques, commonly used in the identification of educationally disadvantaged students, are critiqued. This study applied latent trait theory, specifically the Rasch Model, along with teacher judgments relative to the mastery of instructional/test decisions, to derive a standard setting…

Discrimination of Chinese Sauce liquor using FT-IR and two-dimensional correlation IR spectroscopy

NASA Astrophysics Data System (ADS)

Sun, Su-Qin; Li, Chang-Wen; Wei, Ji-Ping; Zhou, Qun; Noda, Isao

2006-11-01

We applied the three-step IR macro-fingerprint identification method to obtain the IR characteristic fingerprints of so-called Chinese Sauce liquor (Moutai liquor and Kinsly liquor) and a counterfeit Moutai. These fingerprints can be used for the identification and discrimination of similar liquor products. The comparison of their conventional IR spectra, as the first step of identification, shows that the primary difference in Sauce liquor is the intensity of characteristic peaks at 1592 and 1225 cm -1. The comparison of the second derivative IR spectra, as the second step of identification, shows that the characteristic absorption in 1400-1800 cm -1 is substantially different. The comparison of 2D-IR correlation spectra, as the third and final step of identification, can discriminate the liquors from another direction. Furthermore, the method was successfully applied to the discrimination of a counterfeit Moutai from the genuine Sauce liquor. The success of the three-step IR macro-fingerprint identification to provide a rapid and effective method for the identification of Chinese liquor suggests the potential extension of this technique to the identification and discrimination of other wine and spirits, as well.

Optical/digital identification/verification system based on digital watermarking technology

NASA Astrophysics Data System (ADS)

Herrigel, Alexander; Voloshynovskiy, Sviatoslav V.; Hrytskiv, Zenon D.

2000-06-01

This paper presents a new approach for the secure integrity verification of driver licenses, passports or other analogue identification documents. The system embeds (detects) the reference number of the identification document with the DCT watermark technology in (from) the owner photo of the identification document holder. During verification the reference number is extracted and compared with the reference number printed in the identification document. The approach combines optical and digital image processing techniques. The detection system must be able to scan an analogue driver license or passport, convert the image of this document into a digital representation and then apply the watermark verification algorithm to check the payload of the embedded watermark. If the payload of the watermark is identical with the printed visual reference number of the issuer, the verification was successful and the passport or driver license has not been modified. This approach constitutes a new class of application for the watermark technology, which was originally targeted for the copyright protection of digital multimedia data. The presented approach substantially increases the security of the analogue identification documents applied in many European countries.

Modeling and Model Identification of Autonomous Underwater Vehicles

DTIC Science & Technology

2015-06-01

setup, based on a quadrifilar pendulum , is developed to measure the moments of inertia of the vehicle. System identification techniques, based on...parametric models of the platforms: an individual channel excitation approach and a free decay pendulum test. The former is applied to THAUS, which can...excite the system in individual channels in four degrees of freedom. These results are verified in the free decay pendulum setup, which has the

Application Of The Wigner-Ville Distribution To The Identification Of Machine Noise

NASA Astrophysics Data System (ADS)

Boashash, Boualem; O'Shea, Peter

1988-02-01

The theory of signal detection using the Wigner-Ville Distribution (WVD) and the Cross Wagner-Ville Distribution (XWVD) is reviewed, and applied to the signaturing, detection, and identification of some specific machine sounds - the individual cylinder firings of a marine engine. For this task, a 4 step procedure has been devised. The Autocorrelation Function (ACF) is first employed for ascertaining the number of engine cylinders and the firing rate of the engine. Cross-correlation techniques are then used for detecting the occurrence of cylinder firing events. This is followed by the use WVD and XWVD based analyses to produce high resolution Time-Frequency signatures, and finally 2D correlations are employed for identification of the cylinders. The proposed methodology is applied to real data.

System Identification Applied to Dynamic CFD Simulation and Wind Tunnel Data

NASA Technical Reports Server (NTRS)

Murphy, Patrick C.; Klein, Vladislav; Frink, Neal T.; Vicroy, Dan D.

2011-01-01

Demanding aerodynamic modeling requirements for military and civilian aircraft have provided impetus for researchers to improve computational and experimental techniques. Model validation is a key component for these research endeavors so this study is an initial effort to extend conventional time history comparisons by comparing model parameter estimates and their standard errors using system identification methods. An aerodynamic model of an aircraft performing one-degree-of-freedom roll oscillatory motion about its body axes is developed. The model includes linear aerodynamics and deficiency function parameters characterizing an unsteady effect. For estimation of unknown parameters two techniques, harmonic analysis and two-step linear regression, were applied to roll-oscillatory wind tunnel data and to computational fluid dynamics (CFD) simulated data. The model used for this study is a highly swept wing unmanned aerial combat vehicle. Differences in response prediction, parameters estimates, and standard errors are compared and discussed

Applied Computational Electromagnetics Society Journal. Volume 7, Number 1, Summer 1992

DTIC Science & Technology

1992-01-01

previously-solved computational problem in electrical engineering, physics, or related fields of study. The technical activities promoted by this...in solution technique or in data input/output; identification of new applica- tions for electromagnetics modeling codes and techniques; integration of...papers will represent the computational electromagnetics aspects of research in electrical engineering, physics, or related disciplines. However, papers

Experimental parameter identification of a multi-scale musculoskeletal model controlled by electrical stimulation: application to patients with spinal cord injury.

PubMed

Benoussaad, Mourad; Poignet, Philippe; Hayashibe, Mitsuhiro; Azevedo-Coste, Christine; Fattal, Charles; Guiraud, David

2013-06-01

We investigated the parameter identification of a multi-scale physiological model of skeletal muscle, based on Huxley's formulation. We focused particularly on the knee joint controlled by quadriceps muscles under electrical stimulation (ES) in subjects with a complete spinal cord injury. A noninvasive and in vivo identification protocol was thus applied through surface stimulation in nine subjects and through neural stimulation in one ES-implanted subject. The identification protocol included initial identification steps, which are adaptations of existing identification techniques to estimate most of the parameters of our model. Then we applied an original and safer identification protocol in dynamic conditions, which required resolution of a nonlinear programming (NLP) problem to identify the serial element stiffness of quadriceps. Each identification step and cross validation of the estimated model in dynamic condition were evaluated through a quadratic error criterion. The results highlighted good accuracy, the efficiency of the identification protocol and the ability of the estimated model to predict the subject-specific behavior of the musculoskeletal system. From the comparison of parameter values between subjects, we discussed and explored the inter-subject variability of parameters in order to select parameters that have to be identified in each patient.

An automated method of quantifying ferrite microstructures using electron backscatter diffraction (EBSD) data.

PubMed

Shrestha, Sachin L; Breen, Andrew J; Trimby, Patrick; Proust, Gwénaëlle; Ringer, Simon P; Cairney, Julie M

2014-02-01

The identification and quantification of the different ferrite microconstituents in steels has long been a major challenge for metallurgists. Manual point counting from images obtained by optical and scanning electron microscopy (SEM) is commonly used for this purpose. While classification systems exist, the complexity of steel microstructures means that identifying and quantifying these phases is still a great challenge. Moreover, point counting is extremely tedious, time consuming, and subject to operator bias. This paper presents a new automated identification and quantification technique for the characterisation of complex ferrite microstructures by electron backscatter diffraction (EBSD). This technique takes advantage of the fact that different classes of ferrite exhibit preferential grain boundary misorientations, aspect ratios and mean misorientation, all of which can be detected using current EBSD software. These characteristics are set as criteria for identification and linked to grain size to determine the area fractions. The results of this method were evaluated by comparing the new automated technique with point counting results. The technique could easily be applied to a range of other steel microstructures. © 2013 Published by Elsevier B.V.

The application of a biometric identification technique for linking community and hospital data in rural Ghana

PubMed Central

Odei-Lartey, Eliezer Ofori; Boateng, Dennis; Danso, Samuel; Kwarteng, Anthony; Abokyi, Livesy; Amenga-Etego, Seeba; Gyaase, Stephaney; Asante, Kwaku Poku; Owusu-Agyei, Seth

2016-01-01

Background The reliability of counts for estimating population dynamics and disease burdens in communities depends on the availability of a common unique identifier for matching general population data with health facility data. Biometric data has been explored as a feasible common identifier between the health data and sociocultural data of resident members in rural communities within the Kintampo Health and Demographic Surveillance System located in the central part of Ghana. Objective Our goal was to assess the feasibility of using fingerprint identification to link community data and hospital data in a rural African setting. Design A combination of biometrics and other personal identification techniques were used to identify individual's resident within a surveillance population seeking care in two district hospitals. Visits from resident individuals were successfully recorded and categorized by the success of the techniques applied during identification. The successes of visits that involved identification by fingerprint were further examined by age. Results A total of 27,662 hospital visits were linked to resident individuals. Over 85% of those visits were successfully identified using at least one identification method. Over 65% were successfully identified and linked using their fingerprints. Supervisory support from the hospital administration was critical in integrating this identification system into its routine activities. No concerns were expressed by community members about the fingerprint registration and identification processes. Conclusions Fingerprint identification should be combined with other methods to be feasible in identifying community members in African rural settings. This can be enhanced in communities with some basic Demographic Surveillance System or census information. PMID:26993473

The application of a biometric identification technique for linking community and hospital data in rural Ghana.

PubMed

Odei-Lartey, Eliezer Ofori; Boateng, Dennis; Danso, Samuel; Kwarteng, Anthony; Abokyi, Livesy; Amenga-Etego, Seeba; Gyaase, Stephaney; Asante, Kwaku Poku; Owusu-Agyei, Seth

2016-01-01

The reliability of counts for estimating population dynamics and disease burdens in communities depends on the availability of a common unique identifier for matching general population data with health facility data. Biometric data has been explored as a feasible common identifier between the health data and sociocultural data of resident members in rural communities within the Kintampo Health and Demographic Surveillance System located in the central part of Ghana. Our goal was to assess the feasibility of using fingerprint identification to link community data and hospital data in a rural African setting. A combination of biometrics and other personal identification techniques were used to identify individual's resident within a surveillance population seeking care in two district hospitals. Visits from resident individuals were successfully recorded and categorized by the success of the techniques applied during identification. The successes of visits that involved identification by fingerprint were further examined by age. A total of 27,662 hospital visits were linked to resident individuals. Over 85% of those visits were successfully identified using at least one identification method. Over 65% were successfully identified and linked using their fingerprints. Supervisory support from the hospital administration was critical in integrating this identification system into its routine activities. No concerns were expressed by community members about the fingerprint registration and identification processes. Fingerprint identification should be combined with other methods to be feasible in identifying community members in African rural settings. This can be enhanced in communities with some basic Demographic Surveillance System or census information.

Gene Identification Algorithms Using Exploratory Statistical Analysis of Periodicity

NASA Astrophysics Data System (ADS)

Mukherjee, Shashi Bajaj; Sen, Pradip Kumar

2010-10-01

Studying periodic pattern is expected as a standard line of attack for recognizing DNA sequence in identification of gene and similar problems. But peculiarly very little significant work is done in this direction. This paper studies statistical properties of DNA sequences of complete genome using a new technique. A DNA sequence is converted to a numeric sequence using various types of mappings and standard Fourier technique is applied to study the periodicity. Distinct statistical behaviour of periodicity parameters is found in coding and non-coding sequences, which can be used to distinguish between these parts. Here DNA sequences of Drosophila melanogaster were analyzed with significant accuracy.

On-the-spot damage detection methodology for highway bridges.

DOT National Transportation Integrated Search

2010-07-01

Vibration-based damage identification (VBDI) techniques have been developed in part to address the problems associated with an aging civil infrastructure. To assess the potential of VBDI as it applies to highway bridges in Iowa, three applications of...

Vitamin K

USDA-ARS?s Scientific Manuscript database

A wide range of analytical techniques are available for the detection, quantitation, and evaluation of vitamin K in foods. The methods vary from simple to complex depending on extraction, separation, identification and detection of the analyte. Among the extraction methods applied for vitamin K anal...

Identification of magnetic anomalies based on ground magnetic data analysis using multifractal modeling: a case study in Qoja-Kandi, East Azerbaijan Province, Iran

NASA Astrophysics Data System (ADS)

Mansouri, E.; Feizi, F.; Karbalaei Ramezanali, A. A.

2015-07-01

Ground magnetic anomaly separation using reduction-to-the-pole (RTP) technique and the fractal concentration-area (C-A) method has been applied to the Qoja-Kandi prosepecting area in NW Iran. The geophysical survey that resulted in the ground magnetic data was conducted for magnetic elements exploration. Firstly, RTP technique was applied for recognizing underground magnetic anomalies. RTP anomalies was classified to different populations based on this method. For this reason, drilling points determination with RTP technique was complicated. Next, C-A method was applied on the RTP-Magnetic-Anomalies (RTP-MA) for demonstrating magnetic susceptibility concentration. This identification was appropriate for increasing the resolution of the drilling points determination and decreasing the drilling risk, due to the economic costs of underground prospecting. In this study, the results of C-A Modeling on the RTP-MA are compared with 8 borehole data. The results show there is good correlation between anomalies derived via C-A method and log report of boreholes. Two boreholes were drilled in magnetic susceptibility concentration, based on multifractal modeling data analyses, between 63 533.1 and 66 296 nT. Drilling results show appropriate magnetite thickness with the grades greater than 20 % Fe total. Also, anomalies associated with andesite units host iron mineralization.

Output-only cyclo-stationary linear-parameter time-varying stochastic subspace identification method for rotating machinery and spinning structures

NASA Astrophysics Data System (ADS)

Velazquez, Antonio; Swartz, R. Andrew

2015-02-01

Economical maintenance and operation are critical issues for rotating machinery and spinning structures containing blade elements, especially large slender dynamic beams (e.g., wind turbines). Structural health monitoring systems represent promising instruments to assure reliability and good performance from the dynamics of the mechanical systems. However, such devices have not been completely perfected for spinning structures. These sensing technologies are typically informed by both mechanistic models coupled with data-driven identification techniques in the time and/or frequency domain. Frequency response functions are popular but are difficult to realize autonomously for structures of higher order, especially when overlapping frequency content is present. Instead, time-domain techniques have shown to possess powerful advantages from a practical point of view (i.e. low-order computational effort suitable for real-time or embedded algorithms) and also are more suitable to differentiate closely-related modes. Customarily, time-varying effects are often neglected or dismissed to simplify this analysis, but such cannot be the case for sinusoidally loaded structures containing spinning multi-bodies. A more complex scenario is constituted when dealing with both periodic mechanisms responsible for the vibration shaft of the rotor-blade system and the interaction of the supporting substructure. Transformations of the cyclic effects on the vibrational data can be applied to isolate inertial quantities that are different from rotation-generated forces that are typically non-stationary in nature. After applying these transformations, structural identification can be carried out by stationary techniques via data-correlated eigensystem realizations. In this paper, an exploration of a periodic stationary or cyclo-stationary subspace identification technique is presented here for spinning multi-blade systems by means of a modified Eigensystem Realization Algorithm (ERA) via stochastic subspace identification (SSI) and linear parameter time-varying (LPTV) techniques. Structural response is assumed to be stationary ambient excitation produced by a Gaussian (white) noise within the operative range bandwidth of the machinery or structure in study. ERA-OKID analysis is driven by correlation-function matrices from the stationary ambient response aiming to reduce noise effects. Singular value decomposition (SVD) and eigenvalue analysis are computed in a last stage to identify frequencies and complex-valued mode shapes. Proposed assumptions are carefully weighted to account for the uncertainty of the environment. A numerical example is carried out based a spinning finite element (SFE) model, and verified using ANSYS® Ver. 12. Finally, comments and observations are provided on how this subspace realization technique can be extended to the problem of modal-parameter identification using only ambient vibration data.

[Molecular techniques applied in species identification of Toxocara].

PubMed

Fogt, Renata

2006-01-01

Toxocarosis is still an important and actual problem in human medicine. It can manifest as visceral (VLM), ocular (OLM) or covert (CT) larva migrans syndroms. Complicated life cycle of Toxocara, lack of easy and practical methods of species differentiation of the adult nematode and embarrassing in recognition of the infection in definitive hosts create difficulties in fighting with the infection. Although studies on human toxocarosis have been continued for over 50 years there is no conclusive answer, which of species--T. canis or T. cati constitutes a greater risk of transmission of the nematode to man. Neither blood serological examinations nor microscopic observations of the morphological features of the nematode give the satisfied answer on the question. Since the 90-ths molecular methods were developed for species identification and became useful tools being widely applied in parasitological diagnosis. This paper cover the survey of methods of DNA analyses used for identification of Toxocara species. The review may be helpful for researchers focused on Toxocara and toxocarosis as well as on detection of new species. The following techniques are described: PCR (Polymerase Chain Reaction), RFLP (Restriction Fragment Length Polymorphism), RAPD (Random Amplified Polymorphic DNA) and SSCP (Single Strand Conformation Polymorphism).

Applications of aerospace technology to petroleum exploration. Volume 1: Efforts and results

NASA Technical Reports Server (NTRS)

Jaffe, L. D.

1976-01-01

The feasibility of applying aerospace techniques to help solve significant problems in petroleum exploration is studied. Through contacts with petroleum industry and petroleum service industry, important petroleum exploration problems were identified. For each problem, areas of aerospace technology that might aid in its solution were also identified where possible. Topics selected for investigation include: seismic reflection systems; down-hole acoustic techniques; identification of geological analogies; drilling methods; remote geological sensing; and sea floor imaging and mapping. Specific areas of aerospace technology are applied to 21 concepts formulated from the topics of concern.

Separomics applied to the proteomics and peptidomics of low-abundance proteins: Choice of methods and challenges - A review.

PubMed

Baracat-Pereira, Maria Cristina; de Oliveira Barbosa, Meire; Magalhães, Marcos Jorge; Carrijo, Lanna Clicia; Games, Patrícia Dias; Almeida, Hebréia Oliveira; Sena Netto, José Fabiano; Pereira, Matheus Rodrigues; de Barros, Everaldo Gonçalves

2012-06-01

The enrichment and isolation of proteins are considered limiting steps in proteomic studies. Identification of proteins whose expression is transient, those that are of low-abundance, and of natural peptides not described in databases, is still a great challenge. Plant extracts are in general complex, and contaminants interfere with the identification of proteins involved in important physiological processes, such as plant defense against pathogens. This review discusses the challenges and strategies of separomics applied to the identification of low-abundance proteins and peptides in plants, especially in plants challenged by pathogens. Separomics is described as a group of methodological strategies for the separation of protein molecules for proteomics. Several tools have been used to remove highly abundant proteins from samples and also non-protein contaminants. The use of chromatographic techniques, the partition of the proteome into subproteomes, and an effort to isolate proteins in their native form have allowed the isolation and identification of rare proteins involved in different processes.

Separomics applied to the proteomics and peptidomics of low-abundance proteins: Choice of methods and challenges – A review

PubMed Central

Baracat-Pereira, Maria Cristina; de Oliveira Barbosa, Meire; Magalhães, Marcos Jorge; Carrijo, Lanna Clicia; Games, Patrícia Dias; Almeida, Hebréia Oliveira; Sena Netto, José Fabiano; Pereira, Matheus Rodrigues; de Barros, Everaldo Gonçalves

2012-01-01

The enrichment and isolation of proteins are considered limiting steps in proteomic studies. Identification of proteins whose expression is transient, those that are of low-abundance, and of natural peptides not described in databases, is still a great challenge. Plant extracts are in general complex, and contaminants interfere with the identification of proteins involved in important physiological processes, such as plant defense against pathogens. This review discusses the challenges and strategies of separomics applied to the identification of low-abundance proteins and peptides in plants, especially in plants challenged by pathogens. Separomics is described as a group of methodological strategies for the separation of protein molecules for proteomics. Several tools have been used to remove highly abundant proteins from samples and also non-protein contaminants. The use of chromatographic techniques, the partition of the proteome into subproteomes, and an effort to isolate proteins in their native form have allowed the isolation and identification of rare proteins involved in different processes. PMID:22802713

A Parameter Identification Method for Helicopter Noise Source Identification and Physics-Based Semi-Empirical Modeling

NASA Technical Reports Server (NTRS)

Greenwood, Eric, II; Schmitz, Fredric H.

2010-01-01

A new physics-based parameter identification method for rotor harmonic noise sources is developed using an acoustic inverse simulation technique. This new method allows for the identification of individual rotor harmonic noise sources and allows them to be characterized in terms of their individual non-dimensional governing parameters. This new method is applied to both wind tunnel measurements and ground noise measurements of two-bladed rotors. The method is shown to match the parametric trends of main rotor Blade-Vortex Interaction (BVI) noise, allowing accurate estimates of BVI noise to be made for operating conditions based on a small number of measurements taken at different operating conditions.

Selectivity/Specificity Improvement Strategies in Surface-Enhanced Raman Spectroscopy Analysis

PubMed Central

Wang, Feng; Cao, Shiyu; Yan, Ruxia; Wang, Zewei; Wang, Dan; Yang, Haifeng

2017-01-01

Surface-enhanced Raman spectroscopy (SERS) is a powerful technique for the discrimination, identification, and potential quantification of certain compounds/organisms. However, its real application is challenging due to the multiple interference from the complicated detection matrix. Therefore, selective/specific detection is crucial for the real application of SERS technique. We summarize in this review five selective/specific detection techniques (chemical reaction, antibody, aptamer, molecularly imprinted polymers and microfluidics), which can be applied for the rapid and reliable selective/specific detection when coupled with SERS technique. PMID:29160798

Adaptive vibration control of structures under earthquakes

NASA Astrophysics Data System (ADS)

Lew, Jiann-Shiun; Juang, Jer-Nan; Loh, Chin-Hsiung

2017-04-01

techniques, for structural vibration suppression under earthquakes. Various control strategies have been developed to protect structures from natural hazards and improve the comfort of occupants in buildings. However, there has been little development of adaptive building control with the integration of real-time system identification and control design. Generalized predictive control, which combines the process of real-time system identification and the process of predictive control design, has received widespread acceptance and has been successfully applied to various test-beds. This paper presents a formulation of the predictive control scheme for adaptive vibration control of structures under earthquakes. Comprehensive simulations are performed to demonstrate and validate the proposed adaptive control technique for earthquake-induced vibration of a building.

The 32nd CDC: System identification using interval dynamic models

NASA Technical Reports Server (NTRS)

Keel, L. H.; Lew, J. S.; Bhattacharyya, S. P.

1992-01-01

Motivated by the recent explosive development of results in the area of parametric robust control, a new technique to identify a family of uncertain systems is identified. The new technique takes the frequency domain input and output data obtained from experimental test signals and produces an 'interval transfer function' that contains the complete frequency domain behavior with respect to the test signals. This interval transfer function is one of the key concepts in the parametric robust control approach and identification with such an interval model allows one to predict the worst case performance and stability margins using recent results on interval systems. The algorithm is illustrated by applying it to an 18 bay Mini-Mast truss structure.

Modal parameter identification using the log decrement method and band-pass filters

NASA Astrophysics Data System (ADS)

Liao, Yabin; Wells, Valana

2011-10-01

This paper presents a time-domain technique for identifying modal parameters of test specimens based on the log-decrement method. For lightly damped multidegree-of-freedom or continuous systems, the conventional method is usually restricted to identification of fundamental-mode parameters only. Implementation of band-pass filters makes it possible for the proposed technique to extract modal information of higher modes. The method has been applied to a polymethyl methacrylate (PMMA) beam for complex modulus identification in the frequency range 10-1100 Hz. Results compare well with those obtained using the Least Squares method, and with those previously published in literature. Then the accuracy of the proposed method has been further verified by experiments performed on a QuietSteel specimen with very low damping. The method is simple and fast. It can be used for a quick estimation of the modal parameters, or as a complementary approach for validation purposes.

Automatic limb identification and sleeping parameters assessment for pressure ulcer prevention.

PubMed

Baran Pouyan, Maziyar; Birjandtalab, Javad; Nourani, Mehrdad; Matthew Pompeo, M D

2016-08-01

Pressure ulcers (PUs) are common among vulnerable patients such as elderly, bedridden and diabetic. PUs are very painful for patients and costly for hospitals and nursing homes. Assessment of sleeping parameters on at-risk limbs is critical for ulcer prevention. An effective assessment depends on automatic identification and tracking of at-risk limbs. An accurate limb identification can be used to analyze the pressure distribution and assess risk for each limb. In this paper, we propose a graph-based clustering approach to extract the body limbs from the pressure data collected by a commercial pressure map system. A robust signature-based technique is employed to automatically label each limb. Finally, an assessment technique is applied to evaluate the experienced stress by each limb over time. The experimental results indicate high performance and more than 94% average accuracy of the proposed approach. Copyright © 2016 Elsevier Ltd. All rights reserved.

Experimental Mathematics and Mathematical Physics

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

Bailey, David H.; Borwein, Jonathan M.; Broadhurst, David

2009-06-26

One of the most effective techniques of experimental mathematics is to compute mathematical entities such as integrals, series or limits to high precision, then attempt to recognize the resulting numerical values. Recently these techniques have been applied with great success to problems in mathematical physics. Notable among these applications are the identification of some key multi-dimensional integrals that arise in Ising theory, quantum field theory and in magnetic spin theory.

Application of microscopy technique and high performance liquid chromatography for quality assessment of Polygonum multiflorum Thunb. (Heshouwu)

PubMed Central

Liang, Li; Zhao, Zhongzhen; Kang, Tingguo

2014-01-01

Background: The technique of microscopy has been applied for identification of Chinese materia medica (CMM) since decades. However, very few scientific publications report the combination of conventional microscopy and high performance liquid chromatography (HPLC) techniques for further application to quality assessment of CMM. Objective: The objective of this study is to analyze the quality of the dried root tuber of Polygonum multiflorum Thunb. (Heshouwu) and to establish the relationships between 2,3,5,4’-tetrahydroxystilbene-2-O-β-glucoside, combined anthraquinone (CAQ) and quantity of clusters of calcium oxalate. Materials and Methods: In this study, microscopy and HPLC techniques were applied to assess the quality of P. multiflorum Thunb., and SPSS software was used to establish the relationship between microscopic characteristics and chemical components. Results: The results showed close and direct correlations between the quantity of clusters of calcium oxalate in P. multiflorum Thunb. and the contents of 2,3,5,4’-tetrahydroxystilbene-2-O-β-glucoside and CAQ. From these results, it can be deduced that Polygoni Multiflori Radix with a higher quantity of clusters of calcium oxalate should be of better quality. Conclusion: The established method can be helpful for evaluating the quality of CMM based upon the identification and quantitation of chemical and ergastic substance of cells. PMID:25422540

Continuum of Medical Education in Obstetrics and Gynecology.

ERIC Educational Resources Information Center

Dohner, Charles W.; Hunter, Charles A., Jr.

1980-01-01

Over the past eight years the obstetric and gynecology specialty has applied a system model of instructional planning to the continuum of medical education. The systems model of needs identification, preassessment, instructional objectives, instructional materials, learning experiences; and evaluation techniques directly related to objectives was…

EXPERIMENTAL APPROACHES TO EVALUATING THE ROLE OF ENVIRONMENTAL FACTORS IN THE DEVELOPMENT OF CARDIOVASCULAR DISEASE

EPA Science Inventory

Epidemiologic studies have suggested factors in drinking water influence on the human cardiovascular system. A clear identification of the factors involved requires more invasive techniques and more strict experimental controls than can usually be applied in epidemiologic studies...

Semi-quantitative prediction of a multiple API solid dosage form with a combination of vibrational spectroscopy methods.

PubMed

Hertrampf, A; Sousa, R M; Menezes, J C; Herdling, T

2016-05-30

Quality control (QC) in the pharmaceutical industry is a key activity in ensuring medicines have the required quality, safety and efficacy for their intended use. QC departments at pharmaceutical companies are responsible for all release testing of final products but also all incoming raw materials. Near-infrared spectroscopy (NIRS) and Raman spectroscopy are important techniques for fast and accurate identification and qualification of pharmaceutical samples. Tablets containing two different active pharmaceutical ingredients (API) [bisoprolol, hydrochlorothiazide] in different commercially available dosages were analysed using Raman- and NIR Spectroscopy. The goal was to define multivariate models based on each vibrational spectroscopy to discriminate between different dosages (identity) and predict their dosage (semi-quantitative). Furthermore the combination of spectroscopic techniques was investigated. Therefore, two different multiblock techniques based on PLS have been applied: multiblock PLS (MB-PLS) and sequential-orthogonalised PLS (SO-PLS). NIRS showed better results compared to Raman spectroscopy for both identification and quantitation. The multiblock techniques investigated showed that each spectroscopy contains information not present or captured with the other spectroscopic technique, thus demonstrating that there is a potential benefit in their combined use for both identification and quantitation purposes. Copyright © 2016 Elsevier B.V. All rights reserved.

One drop chemical derivatization--DESI-MS analysis for metabolite structure identification.

PubMed

Lubin, Arnaud; Cabooter, Deirdre; Augustijns, Patrick; Cuyckens, Filip

2015-07-01

Structural elucidation of metabolites is an important part during the discovery and development process of new pharmaceutical drugs. Liquid Chromatography (LC) in combination with Mass Spectrometry (MS) is usually the technique of choice for structural identification but cannot always provide precise structural identification of the studied metabolite (e.g. site of hydroxylation and site of glucuronidation). In order to identify those metabolites, different approaches are used combined with MS data including nuclear magnetic resonance, hydrogen/deuterium exchange and chemical derivatization followed by LC-MS. Those techniques are often time-consuming and/or require extra sample pre-treatment. In this paper, a fast and easy to set up tool using desorption electrospray ionization-MS for metabolite identification is presented. In the developed method, analytes in solution are simply dried on a glass plate with printed Teflon spots and then a single drop of derivatization mixture is added. Once the spot is dried, the derivatized compound is analyzed. Six classic chemical derivatizations were adjusted to work as a one drop reaction and applied on a list of compounds with relevant functional groups. Subsequently, two successive reactions on a single spot of amoxicillin were tested and the methodology described was successfully applied on an in vitro incubated alprazolam metabolite. All reactions and analyses were performed within an hour and gave useful structural information by derivatizing functional groups, making the method a time-saving and efficient tool for metabolite identification if used in addition or in some cases as an alternative to common methods. Copyright © 2015 John Wiley & Sons, Ltd.

[Application of immunologic methods to the analysis of bio-leaching bacteria].

PubMed

Coto, O; Fernández, A I; León, T; Rodríguez, D

1994-09-01

Pure cultures of Thiobacillus ferrooxidans and mixed cultures of Thiobacillus ferrooxidans and Leptospirillum ferrooxidans isolated from the Matahambre mine (Cuba) were used to fit immunodiffusion and immunoelectron microscopy to the study of iron oxidizing bacteria. The possibilities, advantages and limits of those techniques have been studied from both the identification and the serological characterization points of view. Finally, the efficiency of these methods was tested by applying them to the identification of microorganisms from acidic waters from the mine.

[Computer simulation by passenger wound analysis of vehicle collision].

PubMed

Zou, Dong-Hua; Liu, Nning-Guo; Shen, Jie; Zhang, Xiao-Yun; Jin, Xian-Long; Chen, Yi-Jiu

2006-08-15

To reconstruct the course of vehicle collision, so that to provide the reference for forensic identification and disposal of traffic accidents. Through analyzing evidences left both on passengers and vehicles, technique of momentum impulse combined with multi-dynamics was applied to simulate the motion and injury of passengers as well as the track of vehicles. Model of computer stimulation perfectly reconstructed phases of the traffic collision, which coincide with details found by forensic investigation. Computer stimulation is helpful and feasible for forensic identification in traffic accidents.

Speckle noise reduction in quantitative optical metrology techniques by application of the discrete wavelet transformation

NASA Astrophysics Data System (ADS)

Furlong, Cosme; Pryputniewicz, Ryszard J.

2002-06-01

Effective suppression of speckle noise content in interferometric data images can help in improving accuracy and resolution of the results obtained with interferometric optical metrology techniques. In this paper, novel speckle noise reduction algorithms based on the discrete wavelet transformation are presented. The algorithms proceed by: (a) estimating the noise level contained in the interferograms of interest, (b) selecting wavelet families, (c) applying the wavelet transformation using the selected families, (d) wavelet thresholding, and (e) applying the inverse wavelet transformation, producing denoised interferograms. The algorithms are applied to the different stages of the processing procedures utilized for generation of quantitative speckle correlation interferometry data of fiber-optic based opto-electronic holography (FOBOEH) techniques, allowing identification of optimal processing conditions. It is shown that wavelet algorithms are effective for speckle noise reduction while preserving image features otherwise faded with other algorithms.

Line identification studies using traditional techniques and wavelength coincidence statistics

NASA Technical Reports Server (NTRS)

Cowley, Charles R.; Adelman, Saul J.

1990-01-01

Traditional line identification techniques result in the assignment of individual lines to an atomic or ionic species. These methods may be supplemented by wavelength coincidence statistics (WCS). The strength and weakness of these methods are discussed using spectra of a number of normal and peculiar B and A stars that have been studied independently by both methods. The present results support the overall findings of some earlier studies. WCS would be most useful in a first survey, before traditional methods have been applied. WCS can quickly make a global search for all species and in this way may enable identifications of an unexpected spectrum that could easily be omitted entirely from a traditional study. This is illustrated by O I. WCS is a subject to well known weakness of any statistical technique, for example, a predictable number of spurious results are to be expected. The danger of small number statistics are illustrated. WCS is at its best relative to traditional methods in finding a line-rich atomic species that is only weakly present in a complicated stellar spectrum.

Optimization of a chemical identification algorithm

NASA Astrophysics Data System (ADS)

Chyba, Thomas H.; Fisk, Brian; Gunning, Christin; Farley, Kevin; Polizzi, Amber; Baughman, David; Simpson, Steven; Slamani, Mohamed-Adel; Almassy, Robert; Da Re, Ryan; Li, Eunice; MacDonald, Steve; Slamani, Ahmed; Mitchell, Scott A.; Pendell-Jones, Jay; Reed, Timothy L.; Emge, Darren

2010-04-01

A procedure to evaluate and optimize the performance of a chemical identification algorithm is presented. The Joint Contaminated Surface Detector (JCSD) employs Raman spectroscopy to detect and identify surface chemical contamination. JCSD measurements of chemical warfare agents, simulants, toxic industrial chemicals, interferents and bare surface backgrounds were made in the laboratory and under realistic field conditions. A test data suite, developed from these measurements, is used to benchmark algorithm performance throughout the improvement process. In any one measurement, one of many possible targets can be present along with interferents and surfaces. The detection results are expressed as a 2-category classification problem so that Receiver Operating Characteristic (ROC) techniques can be applied. The limitations of applying this framework to chemical detection problems are discussed along with means to mitigate them. Algorithmic performance is optimized globally using robust Design of Experiments and Taguchi techniques. These methods require figures of merit to trade off between false alarms and detection probability. Several figures of merit, including the Matthews Correlation Coefficient and the Taguchi Signal-to-Noise Ratio are compared. Following the optimization of global parameters which govern the algorithm behavior across all target chemicals, ROC techniques are employed to optimize chemical-specific parameters to further improve performance.

COMMENT ON "PERCHLORATE IDENTIFICATION IN FERTILIZERS" AND THE SUBSEQUENT ADDITION/CORRECTION [LETTER TO EDITOR

EPA Science Inventory

Perchlorate contamination has been reported in several fertilizer materials and not just in mined Chile saltpeter, where it is a welo-known natural impurity. To survey fertilizers for perchlorate, two analytical techniques have been applied to 45 products that span agricultural, ...

An adaptive optimal control for smart structures based on the subspace tracking identification technique

NASA Astrophysics Data System (ADS)

Ripamonti, Francesco; Resta, Ferruccio; Borroni, Massimo; Cazzulani, Gabriele

2014-04-01

A new method for the real-time identification of mechanical system modal parameters is used in order to design different adaptive control logics aiming to reduce the vibrations in a carbon fiber plate smart structure. It is instrumented with three piezoelectric actuators, three accelerometers and three strain gauges. The real-time identification is based on a recursive subspace tracking algorithm whose outputs are elaborated by an ARMA model. A statistical approach is finally applied to choose the modal parameter correct values. These are given in input to model-based control logics such as a gain scheduling and an adaptive LQR control.

Social marketing: application to medical education.

PubMed

David, S P; Greer, D S

2001-01-16

Medical education is often a frustrating endeavor, particularly when it attempts to change practice behavior. Traditional lecture-based educational methods are limited in their ability to sustain concentration and interest and to promote learner adherence to best-practice guidelines. Marketing techniques have been very effective in changing consumer behavior and physician behavior. However, the techniques of social marketing-goal identification, audience segmentation, and market research-have not been harnessed and applied to medical education. Social marketing can be applied to medical education in the effort to go beyond inoculation of learners with information and actually change behaviors. The tremendous potential of social marketing for medical education should be pilot-tested and systematically evaluated.

Demonstration of a single-wavelength spectral-imaging-based Thai jasmine rice identification

NASA Astrophysics Data System (ADS)

Suwansukho, Kajpanya; Sumriddetchkajorn, Sarun; Buranasiri, Prathan

2011-07-01

A single-wavelength spectral-imaging-based Thai jasmine rice breed identification is demonstrated. Our nondestructive identification approach relies on a combination of fluorescent imaging and simple image processing techniques. Especially, we apply simple image thresholding, blob filtering, and image subtracting processes to either a 545 or a 575nm image in order to identify our desired Thai jasmine rice breed from others. Other key advantages include no waste product and fast identification time. In our demonstration, UVC light is used as our exciting light, a liquid crystal tunable optical filter is used as our wavelength seclector, and a digital camera with 640activepixels×480activepixels is used to capture the desired spectral image. Eight Thai rice breeds having similar size and shape are tested. Our experimental proof of concept shows that by suitably applying image thresholding, blob filtering, and image subtracting processes to the selected fluorescent image, the Thai jasmine rice breed can be identified with measured false acceptance rates of <22.9% and <25.7% for spectral images at 545 and 575nm wavelengths, respectively. A measured fast identification time is 25ms, showing high potential for real-time applications.

Parametric system identification of catamaran for improving controller design

NASA Astrophysics Data System (ADS)

Timpitak, Surasak; Prempraneerach, Pradya; Pengwang, Eakkachai

2018-01-01

This paper presents an estimation of simplified dynamic model for only surge- and yaw- motions of catamaran by using system identification (SI) techniques to determine associated unknown parameters. These methods will enhance the performance of designing processes for the motion control system of Unmanned Surface Vehicle (USV). The simulation results demonstrate an effective way to solve for damping forces and to determine added masses by applying least-square and AutoRegressive Exogenous (ARX) methods. Both methods are then evaluated according to estimated parametric errors from the vehicle’s dynamic model. The ARX method, which yields better estimated accuracy, can then be applied to identify unknown parameters as well as to help improving a controller design of a real unmanned catamaran.

A Support Vector Machine-Based Gender Identification Using Speech Signal

NASA Astrophysics Data System (ADS)

Lee, Kye-Hwan; Kang, Sang-Ick; Kim, Deok-Hwan; Chang, Joon-Hyuk

We propose an effective voice-based gender identification method using a support vector machine (SVM). The SVM is a binary classification algorithm that classifies two groups by finding the voluntary nonlinear boundary in a feature space and is known to yield high classification performance. In the present work, we compare the identification performance of the SVM with that of a Gaussian mixture model (GMM)-based method using the mel frequency cepstral coefficients (MFCC). A novel approach of incorporating a features fusion scheme based on a combination of the MFCC and the fundamental frequency is proposed with the aim of improving the performance of gender identification. Experimental results demonstrate that the gender identification performance using the SVM is significantly better than that of the GMM-based scheme. Moreover, the performance is substantially improved when the proposed features fusion technique is applied.

Improving Mobile Learning with Enhanced Shih's Model of Mobile Learning

ERIC Educational Resources Information Center

Moses, Oyelami Olufemi

2008-01-01

More recent motivational research focuses on the identification of effective techniques for enhancing instructional design and meeting the needs of diverse student populations (Wlodkowski R. J., 1981). Learning-motivation researchers are applying some of the same theories and concepts found to be effective in industry to the development of…

Standoff laser-based spectroscopy for explosives detection

NASA Astrophysics Data System (ADS)

Gaft, M.; Nagli, L.

2007-10-01

Real time detection and identification of explosives at a standoff distance is a major issue in efforts to develop defense against so-called Improvised Explosive Devices (IED). It is recognized that the only technique, which is potentially capable to standoff detection of minimal amounts of explosives is laser-based spectroscopy. LDS activity is based on a combination of laser-based spectroscopic methods with orthogonal capabilities. Our technique belongs to trace detection, namely to its micro-particles variety. It is based on commonly held belief that surface contamination was very difficult to avoid and could be exploited for standoff detection. We has applied optical techniques including gated Raman and time-resolved luminescence spectroscopy for detection of main explosive materials, both factory and homemade. We developed and tested a Raman system for the field remote detection and identification of minimal amounts of explosives on relevant surfaces at a distance of up to 30 meters.

Portable XRF and principal component analysis for bill characterization in forensic science.

PubMed

Appoloni, C R; Melquiades, F L

2014-02-01

Several modern techniques have been applied to prevent counterfeiting of money bills. The objective of this study was to demonstrate the potential of Portable X-ray Fluorescence (PXRF) technique and the multivariate analysis method of Principal Component Analysis (PCA) for classification of bills in order to use it in forensic science. Bills of Dollar, Euro and Real (Brazilian currency) were measured directly at different colored regions, without any previous preparation. Spectra interpretation allowed the identification of Ca, Ti, Fe, Cu, Sr, Y, Zr and Pb. PCA analysis separated the bills in three groups and subgroups among Brazilian currency. In conclusion, the samples were classified according to its origin identifying the elements responsible for differentiation and basic pigment composition. PXRF allied to multivariate discriminate methods is a promising technique for rapid and no destructive identification of false bills in forensic science. Copyright © 2013 Elsevier Ltd. All rights reserved.

Independent component analysis-based algorithm for automatic identification of Raman spectra applied to artistic pigments and pigment mixtures.

PubMed

González-Vidal, Juan José; Pérez-Pueyo, Rosanna; Soneira, María José; Ruiz-Moreno, Sergio

2015-03-01

A new method has been developed to automatically identify Raman spectra, whether they correspond to single- or multicomponent spectra. The method requires no user input or judgment. There are thus no parameters to be tweaked. Furthermore, it provides a reliability factor on the resulting identification, with the aim of becoming a useful support tool for the analyst in the decision-making process. The method relies on the multivariate techniques of principal component analysis (PCA) and independent component analysis (ICA), and on some metrics. It has been developed for the application of automated spectral analysis, where the analyzed spectrum is provided by a spectrometer that has no previous knowledge of the analyzed sample, meaning that the number of components in the sample is unknown. We describe the details of this method and demonstrate its efficiency by identifying both simulated spectra and real spectra. The method has been applied to artistic pigment identification. The reliable and consistent results that were obtained make the methodology a helpful tool suitable for the identification of pigments in artwork or in paint in general.

X-31 aerodynamic characteristics determined from flight data

NASA Technical Reports Server (NTRS)

Kokolios, Alex

1993-01-01

The lateral aerodynamic characteristics of the X-31 were determined at angles of attack ranging from 20 to 45 deg. Estimates of the lateral stability and control parameters were obtained by applying two parameter estimation techniques, linear regression, and the extended Kalman filter to flight test data. An attempt to apply maximum likelihood to extract parameters from the flight data was also made but failed for the reasons presented. An overview of the System Identification process is given. The overview includes a listing of the more important properties of all three estimation techniques that were applied to the data. A comparison is given of results obtained from flight test data and wind tunnel data for four important lateral parameters. Finally, future research to be conducted in this area is discussed.

Flight test evaluation of predicted light aircraft drag, performance, and stability

NASA Technical Reports Server (NTRS)

Smetana, F. O.; Fox, S. R.

1979-01-01

A technique was developed which permits simultaneous extraction of complete lift, drag, and thrust power curves from time histories of a single aircraft maneuver such as a pull up (from V max to V stall) and pushover (to V max for level flight). The technique, which is an extension of nonlinear equations of motion of the parameter identification methods of Iliff and Taylor and includes provisions for internal data compatibility improvement as well, was shown to be capable of correcting random errors in the most sensitive data channel and yielding highly accurate results. Flow charts, listings, sample inputs and outputs for the relevant routines are provided as appendices. This technique was applied to flight data taken on the ATLIT aircraft. Lack of adequate knowledge of the correct full throttle thrust horsepower true airspeed variation and considerable internal data inconsistency made it impossible to apply the trajectory matching features of the technique.

Effective techniques for the identification and accommodation of disturbances

NASA Technical Reports Server (NTRS)

Johnson, C. D.

1989-01-01

The successful control of dynamic systems such as space stations, or launch vehicles, requires a controller design methodology that acknowledges and addresses the disruptive effects caused by external and internal disturbances that inevitably act on such systems. These disturbances, technically defined as uncontrollable inputs, typically vary with time in an uncertain manner and usually cannot be directly measured in real time. A relatively new non-statistical technique for modeling, and (on-line) identification, of those complex uncertain disturbances that are not as erratic and capricious as random noise is described. This technique applies to multi-input cases and to many of the practical disturbances associated with the control of space stations, or launch vehicles. Then, a collection of smart controller design techniques that allow controlled dynamic systems, with possible multi-input controls, to accommodate (cope with) such disturbances with extraordinary effectiveness are associated. These new smart controllers are designed by non-statistical techniques and typically turn out to be unconventional forms of dynamic linear controllers (compensators) with constant coefficients. The simplicity and reliability of linear, constant coefficient controllers is well-known in the aerospace field.

Liquid chromatographic separation of terpenoid pigments in foods and food products.

PubMed

Cserháti, T; Forgács, E

2001-11-30

The newest achievements in the use of various liquid chromatographic techniques such as adsorption and reversed-phase thin-layer chromatography and HPLC employed for the separation and quantitative determination of terpenoid-based color substances in foods and food products are reviewed. The techniques applied for the analysis of individual pigments and pigments classes are surveyed and critically evaluated. Future trends in the separation and identification of pigments in foods and food products are delineated.

A simple iterative independent component analysis algorithm for vibration source signal identification of complex structures

NASA Astrophysics Data System (ADS)

Lee, Dong-Sup; Cho, Dae-Seung; Kim, Kookhyun; Jeon, Jae-Jin; Jung, Woo-Jin; Kang, Myeng-Hwan; Kim, Jae-Ho

2015-01-01

Independent Component Analysis (ICA), one of the blind source separation methods, can be applied for extracting unknown source signals only from received signals. This is accomplished by finding statistical independence of signal mixtures and has been successfully applied to myriad fields such as medical science, image processing, and numerous others. Nevertheless, there are inherent problems that have been reported when using this technique: instability and invalid ordering of separated signals, particularly when using a conventional ICA technique in vibratory source signal identification of complex structures. In this study, a simple iterative algorithm of the conventional ICA has been proposed to mitigate these problems. The proposed method to extract more stable source signals having valid order includes an iterative and reordering process of extracted mixing matrix to reconstruct finally converged source signals, referring to the magnitudes of correlation coefficients between the intermediately separated signals and the signals measured on or nearby sources. In order to review the problems of the conventional ICA technique and to validate the proposed method, numerical analyses have been carried out for a virtual response model and a 30 m class submarine model. Moreover, in order to investigate applicability of the proposed method to real problem of complex structure, an experiment has been carried out for a scaled submarine mockup. The results show that the proposed method could resolve the inherent problems of a conventional ICA technique.

Identification of Uranium Minerals in Natural U-Bearing Rocks Using Infrared Reflectance Spectroscopy.

PubMed

Beiswenger, Toya N; Gallagher, Neal B; Myers, Tanya L; Szecsody, James E; Tonkyn, Russell G; Su, Yin-Fong; Sweet, Lucas E; Lewallen, Tricia A; Johnson, Timothy J

2018-02-01

The identification of minerals, including uranium-bearing species, is often a labor-intensive process using X-ray diffraction (XRD), fluorescence, or other solid-phase or wet chemical techniques. While handheld XRD and fluorescence instruments can aid in field applications, handheld infrared (IR) reflectance spectrometers can now also be used in industrial or field environments, with rapid, nondestructive identification possible via analysis of the solid's reflectance spectrum providing information not found in other techniques. In this paper, we report the use of laboratory methods that measure the IR hemispherical reflectance of solids using an integrating sphere and have applied it to the identification of mineral mixtures (i.e., rocks), with widely varying percentages of uranium mineral content. We then apply classical least squares (CLS) and multivariate curve resolution (MCR) methods to better discriminate the minerals (along with two pure uranium chemicals U 3 O 8 and UO 2 ) against many common natural and anthropogenic background materials (e.g., silica sand, asphalt, calcite, K-feldspar) with good success. Ground truth as to mineral content was attained primarily by XRD. Identification is facile and specific, both for samples that are pure or are partially composed of uranium (e.g., boltwoodite, tyuyamunite, etc.) or non-uranium minerals. The characteristic IR bands generate unique (or class-specific) bands, typically arising from similar chemical moieties or functional groups in the minerals: uranyls, phosphates, silicates, etc. In some cases, the chemical groups that provide spectral discrimination in the longwave IR reflectance by generating upward-going (reststrahlen) bands can provide discrimination in the midwave and shortwave IR via downward-going absorption features, i.e., weaker overtone or combination bands arising from the same chemical moieties.

Component pattern analysis of chemicals using multispectral THz imaging system

NASA Astrophysics Data System (ADS)

Kawase, Kodo; Ogawa, Yuichi; Watanabe, Yuki

2004-04-01

We have developed a novel basic technology for terahertz (THz) imaging, which allows detection and identification of chemicals by introducing the component spatial pattern analysis. The spatial distributions of the chemicals were obtained from terahertz multispectral transillumination images, using absorption spectra previously measured with a widely tunable THz-wave parametric oscillator. Further we have applied this technique to the detection and identification of illicit drugs concealed in envelopes. The samples we used were methamphetamine and MDMA, two of the most widely consumed illegal drugs in Japan, and aspirin as a reference.

Identification of magnetic anomalies based on ground magnetic data analysis using multifractal modelling: a case study in Qoja-Kandi, East Azerbaijan Province, Iran

NASA Astrophysics Data System (ADS)

Mansouri, E.; Feizi, F.; Karbalaei Ramezanali, A. A.

2015-10-01

Ground magnetic anomaly separation using the reduction-to-the-pole (RTP) technique and the fractal concentration-area (C-A) method has been applied to the Qoja-Kandi prospecting area in northwestern Iran. The geophysical survey resulting in the ground magnetic data was conducted for magnetic element exploration. Firstly, the RTP technique was applied to recognize underground magnetic anomalies. RTP anomalies were classified into different populations based on the current method. For this reason, drilling point area determination by the RTP technique was complicated for magnetic anomalies, which are in the center and north of the studied area. Next, the C-A method was applied to the RTP magnetic anomalies (RTP-MA) to demonstrate magnetic susceptibility concentrations. This identification was appropriate for increasing the resolution of the drilling point area determination and decreasing the drilling risk issue, due to the economic costs of underground prospecting. In this study, the results of C-A modelling on the RTP-MA are compared with 8 borehole data. The results show that there is a good correlation between anomalies derived via the C-A method and the log report of boreholes. Two boreholes were drilled in magnetic susceptibility concentrations, based on multifractal modelling data analyses, between 63 533.1 and 66 296 nT. Drilling results showed appropriate magnetite thickness with grades greater than 20 % Fe. The total associated with anomalies containing andesite units hosts iron mineralization.

Wheeze sound analysis using computer-based techniques: a systematic review.

PubMed

Ghulam Nabi, Fizza; Sundaraj, Kenneth; Chee Kiang, Lam; Palaniappan, Rajkumar; Sundaraj, Sebastian

2017-10-31

Wheezes are high pitched continuous respiratory acoustic sounds which are produced as a result of airway obstruction. Computer-based analyses of wheeze signals have been extensively used for parametric analysis, spectral analysis, identification of airway obstruction, feature extraction and diseases or pathology classification. While this area is currently an active field of research, the available literature has not yet been reviewed. This systematic review identified articles describing wheeze analyses using computer-based techniques on the SCOPUS, IEEE Xplore, ACM, PubMed and Springer and Elsevier electronic databases. After a set of selection criteria was applied, 41 articles were selected for detailed analysis. The findings reveal that 1) computerized wheeze analysis can be used for the identification of disease severity level or pathology, 2) further research is required to achieve acceptable rates of identification on the degree of airway obstruction with normal breathing, 3) analysis using combinations of features and on subgroups of the respiratory cycle has provided a pathway to classify various diseases or pathology that stem from airway obstruction.

Joint OSNR monitoring and modulation format identification in digital coherent receivers using deep neural networks.

PubMed

Khan, Faisal Nadeem; Zhong, Kangping; Zhou, Xian; Al-Arashi, Waled Hussein; Yu, Changyuan; Lu, Chao; Lau, Alan Pak Tao

2017-07-24

We experimentally demonstrate the use of deep neural networks (DNNs) in combination with signals' amplitude histograms (AHs) for simultaneous optical signal-to-noise ratio (OSNR) monitoring and modulation format identification (MFI) in digital coherent receivers. The proposed technique automatically extracts OSNR and modulation format dependent features of AHs, obtained after constant modulus algorithm (CMA) equalization, and exploits them for the joint estimation of these parameters. Experimental results for 112 Gbps polarization-multiplexed (PM) quadrature phase-shift keying (QPSK), 112 Gbps PM 16 quadrature amplitude modulation (16-QAM), and 240 Gbps PM 64-QAM signals demonstrate OSNR monitoring with mean estimation errors of 1.2 dB, 0.4 dB, and 1 dB, respectively. Similarly, the results for MFI show 100% identification accuracy for all three modulation formats. The proposed technique applies deep machine learning algorithms inside standard digital coherent receiver and does not require any additional hardware. Therefore, it is attractive for cost-effective multi-parameter estimation in next-generation elastic optical networks (EONs).

Identification of optimal feedback control rules from micro-quadrotor and insect flight trajectories.

PubMed

Faruque, Imraan A; Muijres, Florian T; Macfarlane, Kenneth M; Kehlenbeck, Andrew; Humbert, J Sean

2018-06-01

This paper presents "optimal identification," a framework for using experimental data to identify the optimality conditions associated with the feedback control law implemented in the measurements. The technique compares closed loop trajectory measurements against a reduced order model of the open loop dynamics, and uses linear matrix inequalities to solve an inverse optimal control problem as a convex optimization that estimates the controller optimality conditions. In this study, the optimal identification technique is applied to two examples, that of a millimeter-scale micro-quadrotor with an engineered controller on board, and the example of a population of freely flying Drosophila hydei maneuvering about forward flight. The micro-quadrotor results show that the performance indices used to design an optimal flight control law for a micro-quadrotor may be recovered from the closed loop simulated flight trajectories, and the Drosophila results indicate that the combined effect of the insect longitudinal flight control sensing and feedback acts principally to regulate pitch rate.

Free-decay time-domain modal identification for large space structures

NASA Technical Reports Server (NTRS)

Kim, Hyoung M.; Vanhorn, David A.; Doiron, Harold H.

1992-01-01

Concept definition studies for the Modal Identification Experiment (MIE), a proposed space flight experiment for the Space Station Freedom (SSF), have demonstrated advantages and compatibility of free-decay time-domain modal identification techniques with the on-orbit operational constraints of large space structures. Since practical experience with modal identification using actual free-decay responses of large space structures is very limited, several numerical and test data reduction studies were conducted. Major issues and solutions were addressed, including closely-spaced modes, wide frequency range of interest, data acquisition errors, sampling delay, excitation limitations, nonlinearities, and unknown disturbances during free-decay data acquisition. The data processing strategies developed in these studies were applied to numerical simulations of the MIE, test data from a deployable truss, and launch vehicle flight data. Results of these studies indicate free-decay time-domain modal identification methods can provide accurate modal parameters necessary to characterize the structural dynamics of large space structures.

Use of system identification techniques for improving airframe finite element models using test data

NASA Technical Reports Server (NTRS)

Hanagud, Sathya V.; Zhou, Weiyu; Craig, James I.; Weston, Neil J.

1991-01-01

A method for using system identification techniques to improve airframe finite element models was developed and demonstrated. The method uses linear sensitivity matrices to relate changes in selected physical parameters to changes in total system matrices. The values for these physical parameters were determined using constrained optimization with singular value decomposition. The method was confirmed using both simple and complex finite element models for which pseudo-experimental data was synthesized directly from the finite element model. The method was then applied to a real airframe model which incorporated all the complexities and details of a large finite element model and for which extensive test data was available. The method was shown to work, and the differences between the identified model and the measured results were considered satisfactory.

Laser-Induced Breakdown Spectroscopy: A Review of Applied Explosive Detection

DTIC Science & Technology

2013-09-01

Based Techniques ..........................................................................................7 2.5 Ion Mobility and Mass Spectrometry...proximal trace detection. We show that the algorithms for material identification could be improved by including the critical signatures (e.g., C2...IMS), desorption electrospray ionization (DESI), laser electrospray mass spectrometry (LEMS), emerging efforts like antibody/antigen-based efforts

Identification of particle-laden flow features from wavelet decomposition

NASA Astrophysics Data System (ADS)

Jackson, A.; Turnbull, B.

2017-12-01

A wavelet decomposition based technique is applied to air pressure data obtained from laboratory-scale powder snow avalanches. This technique is shown to be a powerful tool for identifying both repeatable and chaotic features at any frequency within the signal. Additionally, this technique is demonstrated to be a robust method for the removal of noise from the signal as well as being capable of removing other contaminants from the signal. Whilst powder snow avalanches are the focus of the experiments analysed here, the features identified can provide insight to other particle-laden gravity currents and the technique described is applicable to a wide variety of experimental signals.

Pattern-recognition techniques applied to performance monitoring of the DSS 13 34-meter antenna control assembly

NASA Technical Reports Server (NTRS)

Mellstrom, J. A.; Smyth, P.

1991-01-01

The results of applying pattern recognition techniques to diagnose fault conditions in the pointing system of one of the Deep Space network's large antennas, the DSS 13 34-meter structure, are discussed. A previous article described an experiment whereby a neural network technique was used to identify fault classes by using data obtained from a simulation model of the Deep Space Network (DSN) 70-meter antenna system. Described here is the extension of these classification techniques to the analysis of real data from the field. The general architecture and philosophy of an autonomous monitoring paradigm is described and classification results are discussed and analyzed in this context. Key features of this approach include a probabilistic time-varying context model, the effective integration of signal processing and system identification techniques with pattern recognition algorithms, and the ability to calibrate the system given limited amounts of training data. Reported here are recognition accuracies in the 97 to 98 percent range for the particular fault classes included in the experiments.

Advances in parameter estimation techniques applied to flexible structures

NASA Technical Reports Server (NTRS)

Maben, Egbert; Zimmerman, David C.

1994-01-01

In this work, various parameter estimation techniques are investigated in the context of structural system identification utilizing distributed parameter models and 'measured' time-domain data. Distributed parameter models are formulated using the PDEMOD software developed by Taylor. Enhancements made to PDEMOD for this work include the following: (1) a Wittrick-Williams based root solving algorithm; (2) a time simulation capability; and (3) various parameter estimation algorithms. The parameter estimations schemes will be contrasted using the NASA Mini-Mast as the focus structure.

New Flutter Analysis Technique for Time-Domain Computational Aeroelasticity

NASA Technical Reports Server (NTRS)

Pak, Chan-Gi; Lung, Shun-Fat

2017-01-01

A new time-domain approach for computing flutter speed is presented. Based on the time-history result of aeroelastic simulation, the unknown unsteady aerodynamics model is estimated using a system identification technique. The full aeroelastic model is generated via coupling the estimated unsteady aerodynamic model with the known linear structure model. The critical dynamic pressure is computed and used in the subsequent simulation until the convergence of the critical dynamic pressure is achieved. The proposed method is applied to a benchmark cantilevered rectangular wing.

High resolution melting analysis (HRM) as a new tool for the identification of species belonging to the Lactobacillus casei group and comparison with species-specific PCRs and multiplex PCR.

PubMed

Iacumin, Lucilla; Ginaldi, Federica; Manzano, Marisa; Anastasi, Veronica; Reale, Anna; Zotta, Teresa; Rossi, Franca; Coppola, Raffaele; Comi, Giuseppe

2015-04-01

The correct identification and characterisation of bacteria is essential for several reasons: the classification of lactic acid bacteria (LAB) has changed significantly over the years, and it is important to distinguish and define them correctly, according to the current nomenclature, avoiding problems in the interpretation of literature, as well as mislabelling when probiotic are used in food products. In this study, species-specific PCR and HRM (high-resolution melting) analysis were developed to identify strains belonging to the Lactobacillus casei group and to classify them into L. casei, Lactobacillus paracasei and Lactobacillus rhamnosus. HRM analysis confirmed to be a potent, simple, fast and economic tool for microbial identification. In particular, 201 strains, collected from International collections and attributed to the L. casei group, were examined using these techniques and the results were compared with consolidated molecular methods, already published. Seven of the tested strains don't belong to the L. casei group. Among the remaining 194 strains, 6 showed inconsistent results, leaving identification undetermined. All the applied techniques were congruent for the identification of the vast majority of the tested strains (188). Notably, for 46 of the strains, the identification differed from the previous attribution. Copyright © 2014 Elsevier Ltd. All rights reserved.

Frequency domain system identification of helicopter rotor dynamics incorporating models with time periodic coefficients

NASA Astrophysics Data System (ADS)

Hwang, Sunghwan

1997-08-01

One of the most prominent features of helicopter rotor dynamics in forward flight is the periodic coefficients in the equations of motion introduced by the rotor rotation. The frequency response characteristics of such a linear time periodic system exhibits sideband behavior, which is not the case for linear time invariant systems. Therefore, a frequency domain identification methodology for linear systems with time periodic coefficients was developed, because the linear time invariant theory cannot account for sideband behavior. The modulated complex Fourier series was introduced to eliminate the smearing effect of Fourier series expansions of exponentially modulated periodic signals. A system identification theory was then developed using modulated complex Fourier series expansion. Correlation and spectral density functions were derived using the modulated complex Fourier series expansion for linear time periodic systems. Expressions of the identified harmonic transfer function were then formulated using the spectral density functions both with and without additive noise processes at input and/or output. A procedure was developed to identify parameters of a model to match the frequency response characteristics between measured and estimated harmonic transfer functions by minimizing an objective function defined in terms of the trace of the squared frequency response error matrix. Feasibility was demonstrated by the identification of the harmonic transfer function and parameters for helicopter rigid blade flapping dynamics in forward flight. This technique is envisioned to satisfy the needs of system identification in the rotating frame, especially in the context of individual blade control. The technique was applied to the coupled flap-lag-inflow dynamics of a rigid blade excited by an active pitch link. The linear time periodic technique results were compared with the linear time invariant technique results. Also, the effect of noise processes and initial parameter guess on the identification procedure were investigated. To study the effect of elastic modes, a rigid blade with a trailing edge flap excited by a smart actuator was selected and system parameters were successfully identified, but with some expense of computational storage and time. Conclusively, the linear time periodic technique substantially improved the identified parameter accuracy compared to the linear time invariant technique. Also, the linear time periodic technique was robust to noises and initial guess of parameters. However, an elastic mode of higher frequency relative to the system pumping frequency tends to increase the computer storage requirement and computing time.

Identification of piecewise affine systems based on fuzzy PCA-guided robust clustering technique

NASA Astrophysics Data System (ADS)

Khanmirza, Esmaeel; Nazarahari, Milad; Mousavi, Alireza

2016-12-01

Hybrid systems are a class of dynamical systems whose behaviors are based on the interaction between discrete and continuous dynamical behaviors. Since a general method for the analysis of hybrid systems is not available, some researchers have focused on specific types of hybrid systems. Piecewise affine (PWA) systems are one of the subsets of hybrid systems. The identification of PWA systems includes the estimation of the parameters of affine subsystems and the coefficients of the hyperplanes defining the partition of the state-input domain. In this paper, we have proposed a PWA identification approach based on a modified clustering technique. By using a fuzzy PCA-guided robust k-means clustering algorithm along with neighborhood outlier detection, the two main drawbacks of the well-known clustering algorithms, i.e., the poor initialization and the presence of outliers, are eliminated. Furthermore, this modified clustering technique enables us to determine the number of subsystems without any prior knowledge about system. In addition, applying the structure of the state-input domain, that is, considering the time sequence of input-output pairs, provides a more efficient clustering algorithm, which is the other novelty of this work. Finally, the proposed algorithm has been evaluated by parameter identification of an IGV servo actuator. Simulation together with experiment analysis has proved the effectiveness of the proposed method.

Hyphenated GC-FTIR and GC-MS techniques applied in the analysis of bioactive compounds

NASA Astrophysics Data System (ADS)

Gosav, Steluta; Paduraru, Nicoleta; Praisler, Mirela

2014-08-01

The drugs of abuse, which affect human nature and cause numerous crimes, have become a serious problem throughout the world. There are hundreds of amphetamine analogues on the black market. They consist of various alterations of the basic amphetamine molecular structure, which are yet not yet included in the lists of forbidden compounds although they retain or slightly modify the hallucinogenic effects of their parent compound. It is their important variety that makes their identification quite a challenge. A number of analytical procedures for the identification of amphetamines and their analogues have recently been reported. We are presenting the profile of the main hallucinogenic amphetamines obtained with the hyphenated techniques that are recommended for the identification of illicit amphetamines, i. e. gas chromatography combined with mass spectrometry (GC-MS) and gas chromatography coupled with Fourier transform infrared spectrometry (GC-FTIR). The infrared spectra of the analyzed hallucinogenic amphetamines present some absorption bands (1490 cm-1, 1440 cm-1, 1245 cm-1, 1050 cm-1 and 940 cm-1) that are very stable as position and shape, while their intensity depends of the side-chain substitution. The specific ionic fragment of the studied hallucinogenic compounds is the 3,4-methylenedioxybenzyl cation (m/e = 135) which has a small relative abundance (lesser than 20%). The complementarity of the above mentioned techniques for the identification of hallucinogenic compounds is discussed.

Mapping sites of aspirin-induced acetylations in live cells by quantitative acid-cleavable activity-based protein profiling (QA-ABPP)

PubMed Central

Wang, Jigang; Zhang, Chong-Jing; Zhang, Jianbin; He, Yingke; Lee, Yew Mun; Chen, Songbi; Lim, Teck Kwang; Ng, Shukie; Shen, Han-Ming; Lin, Qingsong

2015-01-01

Target-identification and understanding of mechanism-of-action (MOA) are challenging for development of small-molecule probes and their application in biology and drug discovery. For example, although aspirin has been widely used for more than 100 years, its molecular targets have not been fully characterized. To cope with this challenge, we developed a novel technique called quantitative acid-cleavable activity-based protein profiling (QA-ABPP) with combination of the following two parts: (i) activity-based protein profiling (ABPP) and iTRAQ™ quantitative proteomics for identification of target proteins and (ii) acid-cleavable linker-based ABPP for identification of peptides with specific binding sites. It is known that reaction of aspirin with its target proteins leads to acetylation. We thus applied the above technique using aspirin-based probes in human cancer HCT116 cells. We identified 1110 target proteins and 2775 peptides with exact acetylation sites. By correlating these two sets of data, 523 proteins were identified as targets of aspirin. We used various biological assays to validate the effects of aspirin on inhibition of protein synthesis and induction of autophagy which were elicited from the pathway analysis of Aspirin target profile. This technique is widely applicable for target identification in the field of drug discovery and biology, especially for the covalent drugs. PMID:25600173

The application of artificial intelligence for the identification of the maceral groups and mineral components of coal

NASA Astrophysics Data System (ADS)

Mlynarczuk, Mariusz; Skiba, Marta

2017-06-01

The correct and consistent identification of the petrographic properties of coal is an important issue for researchers in the fields of mining and geology. As part of the study described in this paper, investigations concerning the application of artificial intelligence methods for the identification of the aforementioned characteristics were carried out. The methods in question were used to identify the maceral groups of coal, i.e. vitrinite, inertinite, and liptinite. Additionally, an attempt was made to identify some non-organic minerals. The analyses were performed using pattern recognition techniques (NN, kNN), as well as artificial neural network techniques (a multilayer perceptron - MLP). The classification process was carried out using microscopy images of polished sections of coals. A multidimensional feature space was defined, which made it possible to classify the discussed structures automatically, based on the methods of pattern recognition and algorithms of the artificial neural networks. Also, from the study we assessed the impact of the parameters for which the applied methods proved effective upon the final outcome of the classification procedure. The result of the analyses was a high percentage (over 97%) of correct classifications of maceral groups and mineral components. The paper discusses also an attempt to analyze particular macerals of the inertinite group. It was demonstrated that using artificial neural networks to this end makes it possible to classify the macerals properly in over 91% of cases. Thus, it was proved that artificial intelligence methods can be successfully applied for the identification of selected petrographic features of coal.

Identification of pesticide varieties by detecting characteristics of Chlorella pyrenoidosa using Visible/Near infrared hyperspectral imaging and Raman microspectroscopy technology.

PubMed

Shao, Yongni; Li, Yuan; Jiang, Linjun; Pan, Jian; He, Yong; Dou, Xiaoming

2016-11-01

The main goal of this research is to examine the feasibility of applying Visible/Near-infrared hyperspectral imaging (Vis/NIR-HSI) and Raman microspectroscopy technology for non-destructive identification of pesticide varieties (glyphosate and butachlor). Both mentioned technologies were explored to investigate how internal elements or characteristics of Chlorella pyrenoidosa change when pesticides are applied, and in the meantime, to identify varieties of the pesticides during this procedure. Successive projections algorithm (SPA) was introduced to our study to identify seven most effective wavelengths. With those wavelengths suggested by SPA, a model of the linear discriminant analysis (LDA) was established to classify the pesticide varieties, and the correct classification rate of the SPA-LDA model reached as high as 100%. For the Raman technique, a few partial least squares discriminant analysis models were established with different preprocessing methods from which we also identified one processing approach that achieved the most optimal result. The sensitive wavelengths (SWs) which are related to algae's pigment were chosen, and a model of LDA was established with the correct identification reached a high level of 90.0%. The results showed that both Vis/NIR-HSI and Raman microspectroscopy techniques are capable to identify pesticide varieties in an indirect but effective way, and SPA is an effective wavelength extracting method. The SWs corresponding to microalgae pigments, which were influenced by pesticides, could also help to characterize different pesticide varieties and benefit the variety identification. Copyright © 2016 Elsevier Ltd. All rights reserved.

[Evaluation of mass spectrometry: MALDI-TOF MS for fast and reliable yeast identification].

PubMed

Relloso, María S; Nievas, Jimena; Fares Taie, Santiago; Farquharson, Victoria; Mujica, María T; Romano, Vanesa; Zarate, Mariela S; Smayevsky, Jorgelina

2015-01-01

The matrix-assisted laser desorption/ionization time-of-flight mass spectrometry technique known as MALDI-TOF MS is a tool used for the identification of clinical pathogens by generating a protein spectrum that is unique for a given species. In this study we assessed the identification of clinical yeast isolates by MALDI-TOF MS in a university hospital from Argentina and compared two procedures for protein extraction: a rapid method and a procedure based on the manufacturer's recommendations. A short protein extraction procedure was applied in 100 isolates and the rate of correct identification at genus and species level was 98.0%. In addition, we analyzed 201 isolates, previously identified by conventional methods, using the methodology recommended by the manufacturer and there was 95.38% coincidence in the identification at species level. MALDI TOF MS showed to be a fast, simple and reliable tool for yeast identification. Copyright © 2014 Asociación Argentina de Microbiología. Publicado por Elsevier España, S.L.U. All rights reserved.

Mining MaNGA for Merging Galaxies: A New Imaging and Kinematic Technique from Hydrodynamical Simulations

NASA Astrophysics Data System (ADS)

Nevin, Becky; Comerford, Julia M.; Blecha, Laura

2018-06-01

Merging galaxies play a key role in galaxy evolution, and progress in our understanding of galaxy evolution is slowed by the difficulty of making accurate galaxy merger identifications. Mergers are typically identified using imaging alone, which has its limitations and biases. With the growing popularity of integral field spectroscopy (IFS), it is now possible to use kinematic signatures to improve galaxy merger identifications. I use GADGET-3 hydrodynamical simulations of merging galaxies with the radiative transfer code SUNRISE, the later of which enables me to apply the same analysis to simulations and observations. From the simulated galaxies, I have developed the first merging galaxy classification scheme that is based on kinematics and imaging. Utilizing a Linear Discriminant Analysis tool, I have determined which kinematic and imaging predictors are most useful for identifying mergers of various merger parameters (such as orientation, mass ratio, gas fraction, and merger stage). I will discuss the strengths and limitations of the classification technique and then my initial results for applying the classification to the >10,000 observed galaxies in the MaNGA (Mapping Nearby Galaxies at Apache Point) IFS survey. Through accurate identification of merging galaxies in the MaNGA survey, I will advance our understanding of supermassive black hole growth in galaxy mergers and other open questions related to galaxy evolution.

Simultaneous Intrinsic and Extrinsic Parameter Identification of a Hand-Mounted Laser-Vision Sensor

PubMed Central

Lee, Jong Kwang; Kim, Kiho; Lee, Yongseok; Jeong, Taikyeong

2011-01-01

In this paper, we propose a simultaneous intrinsic and extrinsic parameter identification of a hand-mounted laser-vision sensor (HMLVS). A laser-vision sensor (LVS), consisting of a camera and a laser stripe projector, is used as a sensor component of the robotic measurement system, and it measures the range data with respect to the robot base frame using the robot forward kinematics and the optical triangulation principle. For the optimal estimation of the model parameters, we applied two optimization techniques: a nonlinear least square optimizer and a particle swarm optimizer. Best-fit parameters, including both the intrinsic and extrinsic parameters of the HMLVS, are simultaneously obtained based on the least-squares criterion. From the simulation and experimental results, it is shown that the parameter identification problem considered was characterized by a highly multimodal landscape; thus, the global optimization technique such as a particle swarm optimization can be a promising tool to identify the model parameters for a HMLVS, while the nonlinear least square optimizer often failed to find an optimal solution even when the initial candidate solutions were selected close to the true optimum. The proposed optimization method does not require good initial guesses of the system parameters to converge at a very stable solution and it could be applied to a kinematically dissimilar robot system without loss of generality. PMID:22164104

High Resolution Ultrasonic Method for 3D Fingerprint Recognizable Characteristics in Biometrics Identification

NASA Astrophysics Data System (ADS)

Maev, R. Gr.; Bakulin, E. Yu.; Maeva, A.; Severin, F.

Biometrics is a rapidly evolving scientific and applied discipline that studies possible ways of personal identification by means of unique biological characteristics. Such identification is important in various situations requiring restricted access to certain areas, information and personal data and for cases of medical emergencies. A number of automated biometric techniques have been developed, including fingerprint, hand shape, eye and facial recognition, thermographic imaging, etc. All these techniques differ in the recognizable parameters, usability, accuracy and cost. Among these, fingerprint recognition stands alone since a very large database of fingerprints has already been acquired. Also, fingerprints are key evidence left at a crime scene and can be used to indentify suspects. Therefore, of all automated biometric techniques, especially in the field of law enforcement, fingerprint identification seems to be the most promising. We introduce a newer development of the ultrasonic fingerprint imaging. The proposed method obtains a scan only once and then varies the C-scan gate position and width to visualize acoustic reflections from any appropriate depth inside the skin. Also, B-scans and A-scans can be recreated from any position using such data array, which gives the control over the visualization options. By setting the C-scan gate deeper inside the skin, distribution of the sweat pores (which are located along the ridges) can be easily visualized. This distribution should be unique for each individual so this provides a means of personal identification, which is not affected by any changes (accidental or intentional) of the fingers' surface conditions. This paper discusses different setups, acoustic parameters of the system, signal and image processing options and possible ways of 3-dimentional visualization that could be used as a recognizable characteristic in biometric identification.

Identification and characterization of earthquake clusters: a comparative analysis for selected sequences in Italy

NASA Astrophysics Data System (ADS)

Peresan, Antonella; Gentili, Stefania

2017-04-01

Identification and statistical characterization of seismic clusters may provide useful insights about the features of seismic energy release and their relation to physical properties of the crust within a given region. Moreover, a number of studies based on spatio-temporal analysis of main-shocks occurrence require preliminary declustering of the earthquake catalogs. Since various methods, relying on different physical/statistical assumptions, may lead to diverse classifications of earthquakes into main events and related events, we aim to investigate the classification differences among different declustering techniques. Accordingly, a formal selection and comparative analysis of earthquake clusters is carried out for the most relevant earthquakes in North-Eastern Italy, as reported in the local OGS-CRS bulletins, compiled at the National Institute of Oceanography and Experimental Geophysics since 1977. The comparison is then extended to selected earthquake sequences associated with a different seismotectonic setting, namely to events that occurred in the region struck by the recent Central Italy destructive earthquakes, making use of INGV data. Various techniques, ranging from classical space-time windows methods to ad hoc manual identification of aftershocks, are applied for detection of earthquake clusters. In particular, a statistical method based on nearest-neighbor distances of events in space-time-energy domain, is considered. Results from clusters identification by the nearest-neighbor method turn out quite robust with respect to the time span of the input catalogue, as well as to minimum magnitude cutoff. The identified clusters for the largest events reported in North-Eastern Italy since 1977 are well consistent with those reported in earlier studies, which were aimed at detailed manual aftershocks identification. The study shows that the data-driven approach, based on the nearest-neighbor distances, can be satisfactorily applied to decompose the seismic catalog into background seismicity and individual sequences of earthquake clusters, also in areas characterized by moderate seismic activity, where the standard declustering techniques may turn out rather gross approximations. With these results acquired, the main statistical features of seismic clusters are explored, including complex interdependence of related events, with the aim to characterize the space-time patterns of earthquakes occurrence in North-Eastern Italy and capture their basic differences with Central Italy sequences.

An intelligent signal processing and pattern recognition technique for defect identification using an active sensor network

NASA Astrophysics Data System (ADS)

Su, Zhongqing; Ye, Lin

2004-08-01

The practical utilization of elastic waves, e.g. Rayleigh-Lamb waves, in high-performance structural health monitoring techniques is somewhat impeded due to the complicated wave dispersion phenomena, the existence of multiple wave modes, the high susceptibility to diverse interferences, the bulky sampled data and the difficulty in signal interpretation. An intelligent signal processing and pattern recognition (ISPPR) approach using the wavelet transform and artificial neural network algorithms was developed; this was actualized in a signal processing package (SPP). The ISPPR technique comprehensively functions as signal filtration, data compression, characteristic extraction, information mapping and pattern recognition, capable of extracting essential yet concise features from acquired raw wave signals and further assisting in structural health evaluation. For validation, the SPP was applied to the prediction of crack growth in an alloy structural beam and construction of a damage parameter database for defect identification in CF/EP composite structures. It was clearly apparent that the elastic wave propagation-based damage assessment could be dramatically streamlined by introduction of the ISPPR technique.

Evaluation of the Technical Adequacy of Three Methods for Identifying Specific Learning Disabilities Based on Cognitive Discrepancies

ERIC Educational Resources Information Center

Stuebing, Karla K.; Fletcher, Jack M.; Branum-Martin, Lee; Francis, David J.

2012-01-01

This study used simulation techniques to evaluate the technical adequacy of three methods for the identification of specific learning disabilities via patterns of strengths and weaknesses in cognitive processing. Latent and observed data were generated and the decision-making process of each method was applied to assess concordance in…

Signal-Noise Identification of Magnetotelluric Signals Using Fractal-Entropy and Clustering Algorithm for Targeted De-Noising

NASA Astrophysics Data System (ADS)

Li, Jin; Zhang, Xian; Gong, Jinzhe; Tang, Jingtian; Ren, Zhengyong; Li, Guang; Deng, Yanli; Cai, Jin

A new technique is proposed for signal-noise identification and targeted de-noising of Magnetotelluric (MT) signals. This method is based on fractal-entropy and clustering algorithm, which automatically identifies signal sections corrupted by common interference (square, triangle and pulse waves), enabling targeted de-noising and preventing the loss of useful information in filtering. To implement the technique, four characteristic parameters — fractal box dimension (FBD), higuchi fractal dimension (HFD), fuzzy entropy (FuEn) and approximate entropy (ApEn) — are extracted from MT time-series. The fuzzy c-means (FCM) clustering technique is used to analyze the characteristic parameters and automatically distinguish signals with strong interference from the rest. The wavelet threshold (WT) de-noising method is used only to suppress the identified strong interference in selected signal sections. The technique is validated through signal samples with known interference, before being applied to a set of field measured MT/Audio Magnetotelluric (AMT) data. Compared with the conventional de-noising strategy that blindly applies the filter to the overall dataset, the proposed method can automatically identify and purposefully suppress the intermittent interference in the MT/AMT signal. The resulted apparent resistivity-phase curve is more continuous and smooth, and the slow-change trend in the low-frequency range is more precisely reserved. Moreover, the characteristic of the target-filtered MT/AMT signal is close to the essential characteristic of the natural field, and the result more accurately reflects the inherent electrical structure information of the measured site.

3D matching techniques using OCT fingerprint point clouds

NASA Astrophysics Data System (ADS)

Gutierrez da Costa, Henrique S.; Silva, Luciano; Bellon, Olga R. P.; Bowden, Audrey K.; Czovny, Raphael K.

2017-02-01

Optical Coherence Tomography (OCT) makes viable acquisition of 3D fingerprints from both dermis and epidermis skin layers and their interfaces, exposing features that can be explored to improve biometric identification such as the curvatures and distinctive 3D regions. Scanned images from eleven volunteers allowed the construction of the first OCT 3D fingerprint database, to our knowledge, containing epidermal and dermal fingerprints. 3D dermal fingerprints can be used to overcome cases of Failure to Enroll (FTE) due to poor ridge image quality and skin alterations, cases that affect 2D matching performance. We evaluate three matching techniques, including the well-established Iterative Closest Points algorithm (ICP), Surface Interpenetration Measure (SIM) and the well-known KH Curvature Maps, all assessed using a 3D OCT fingerprint database, the first one for this purpose. Two of these techniques are based on registration techniques and one on curvatures. These were evaluated, compared and the fusion of matching scores assessed. We applied a sequence of steps to extract regions of interest named (ROI) minutiae clouds, representing small regions around distinctive minutia, usually located at ridges/valleys endings or bifurcations. The obtained ROI is acquired from the epidermis and dermis-epidermis interface by OCT imaging. A comparative analysis of identification accuracy was explored using different scenarios and the obtained results shows improvements for biometric identification. A comparison against 2D fingerprint matching algorithms is also presented to assess the improvements.

Identification of Low Order Equivalent System Models From Flight Test Data

NASA Technical Reports Server (NTRS)

Morelli, Eugene A.

2000-01-01

Identification of low order equivalent system dynamic models from flight test data was studied. Inputs were pilot control deflections, and outputs were aircraft responses, so the models characterized the total aircraft response including bare airframe and flight control system. Theoretical investigations were conducted and related to results found in the literature. Low order equivalent system modeling techniques using output error and equation error parameter estimation in the frequency domain were developed and validated on simulation data. It was found that some common difficulties encountered in identifying closed loop low order equivalent system models from flight test data could be overcome using the developed techniques. Implications for data requirements and experiment design were discussed. The developed methods were demonstrated using realistic simulation cases, then applied to closed loop flight test data from the NASA F-18 High Alpha Research Vehicle.

Time series modeling of human operator dynamics in manual control tasks

NASA Technical Reports Server (NTRS)

Biezad, D. J.; Schmidt, D. K.

1984-01-01

A time-series technique is presented for identifying the dynamic characteristics of the human operator in manual control tasks from relatively short records of experimental data. Control of system excitation signals used in the identification is not required. The approach is a multi-channel identification technique for modeling multi-input/multi-output situations. The method presented includes statistical tests for validity, is designed for digital computation, and yields estimates for the frequency responses of the human operator. A comprehensive relative power analysis may also be performed for validated models. This method is applied to several sets of experimental data; the results are discussed and shown to compare favorably with previous research findings. New results are also presented for a multi-input task that has not been previously modeled to demonstrate the strengths of the method.

Use of system identification techniques for improving airframe finite element models using test data

NASA Technical Reports Server (NTRS)

Hanagud, Sathya V.; Zhou, Weiyu; Craig, James I.; Weston, Neil J.

1993-01-01

A method for using system identification techniques to improve airframe finite element models using test data was developed and demonstrated. The method uses linear sensitivity matrices to relate changes in selected physical parameters to changes in the total system matrices. The values for these physical parameters were determined using constrained optimization with singular value decomposition. The method was confirmed using both simple and complex finite element models for which pseudo-experimental data was synthesized directly from the finite element model. The method was then applied to a real airframe model which incorporated all of the complexities and details of a large finite element model and for which extensive test data was available. The method was shown to work, and the differences between the identified model and the measured results were considered satisfactory.

Time Series Modeling of Human Operator Dynamics in Manual Control Tasks

NASA Technical Reports Server (NTRS)

Biezad, D. J.; Schmidt, D. K.

1984-01-01

A time-series technique is presented for identifying the dynamic characteristics of the human operator in manual control tasks from relatively short records of experimental data. Control of system excitation signals used in the identification is not required. The approach is a multi-channel identification technique for modeling multi-input/multi-output situations. The method presented includes statistical tests for validity, is designed for digital computation, and yields estimates for the frequency response of the human operator. A comprehensive relative power analysis may also be performed for validated models. This method is applied to several sets of experimental data; the results are discussed and shown to compare favorably with previous research findings. New results are also presented for a multi-input task that was previously modeled to demonstrate the strengths of the method.

Determination of the ruminant origin of bone particles using fluorescence in situ hybridization (FISH)

PubMed Central

Lecrenier, M. C.; Ledoux, Q.; Berben, G.; Fumière, O.; Saegerman, C.; Baeten, V.; Veys, P.

2014-01-01

Molecular biology techniques such as PCR constitute powerful tools for the determination of the taxonomic origin of bones. DNA degradation and contamination by exogenous DNA, however, jeopardise bone identification. Despite the vast array of techniques used to decontaminate bone fragments, the isolation and determination of bone DNA content are still problematic. Within the framework of the eradication of transmissible spongiform encephalopathies (including BSE, commonly known as “mad cow disease”), a fluorescence in situ hybridization (FISH) protocol was developed. Results from the described study showed that this method can be applied directly to bones without a demineralisation step and that it allows the identification of bovine and ruminant bones even after severe processing. The results also showed that the method is independent of exogenous contamination and that it is therefore entirely appropriate for this application. PMID:25034259

Determination of the ruminant origin of bone particles using fluorescence in situ hybridization (FISH).

PubMed

Lecrenier, M C; Ledoux, Q; Berben, G; Fumière, O; Saegerman, C; Baeten, V; Veys, P

2014-07-17

Molecular biology techniques such as PCR constitute powerful tools for the determination of the taxonomic origin of bones. DNA degradation and contamination by exogenous DNA, however, jeopardise bone identification. Despite the vast array of techniques used to decontaminate bone fragments, the isolation and determination of bone DNA content are still problematic. Within the framework of the eradication of transmissible spongiform encephalopathies (including BSE, commonly known as "mad cow disease"), a fluorescence in situ hybridization (FISH) protocol was developed. Results from the described study showed that this method can be applied directly to bones without a demineralisation step and that it allows the identification of bovine and ruminant bones even after severe processing. The results also showed that the method is independent of exogenous contamination and that it is therefore entirely appropriate for this application.

Pore network quantification of sandstones under experimental CO2 injection using image analysis

NASA Astrophysics Data System (ADS)

Berrezueta, Edgar; González-Menéndez, Luís; Ordóñez-Casado, Berta; Olaya, Peter

2015-04-01

Automated-image identification and quantification of minerals, pores and textures together with petrographic analysis can be applied to improve pore system characterization in sedimentary rocks. Our case study is focused on the application of these techniques to study the evolution of rock pore network subjected to super critical CO2-injection. We have proposed a Digital Image Analysis (DIA) protocol that guarantees measurement reproducibility and reliability. This can be summarized in the following stages: (i) detailed description of mineralogy and texture (before and after CO2-injection) by optical and scanning electron microscopy (SEM) techniques using thin sections; (ii) adjustment and calibration of DIA tools; (iii) data acquisition protocol based on image capture with different polarization conditions (synchronized movement of polarizers); (iv) study and quantification by DIA that allow (a) identification and isolation of pixels that belong to the same category: minerals vs. pores in each sample and (b) measurement of changes in pore network, after the samples have been exposed to new conditions (in our case: SC-CO2-injection). Finally, interpretation of the petrography and the measured data by an automated approach were done. In our applied study, the DIA results highlight the changes observed by SEM and microscopic techniques, which consisted in a porosity increase when CO2 treatment occurs. Other additional changes were minor: variations in the roughness and roundness of pore edges, and pore aspect ratio, shown in the bigger pore population. Additionally, statistic tests of pore parameters measured were applied to verify that the differences observed between samples before and after CO2-injection were significant.

Modal parameter identification based on combining transmissibility functions and blind source separation techniques

NASA Astrophysics Data System (ADS)

Araújo, Iván Gómez; Sánchez, Jesús Antonio García; Andersen, Palle

2018-05-01

Transmissibility-based operational modal analysis is a recent and alternative approach used to identify the modal parameters of structures under operational conditions. This approach is advantageous compared with traditional operational modal analysis because it does not make any assumptions about the excitation spectrum (i.e., white noise with a flat spectrum). However, common methodologies do not include a procedure to extract closely spaced modes with low signal-to-noise ratios. This issue is relevant when considering that engineering structures generally have closely spaced modes and that their measured responses present high levels of noise. Therefore, to overcome these problems, a new combined method for modal parameter identification is proposed in this work. The proposed method combines blind source separation (BSS) techniques and transmissibility-based methods. Here, BSS techniques were used to recover source signals, and transmissibility-based methods were applied to estimate modal information from the recovered source signals. To achieve this combination, a new method to define a transmissibility function was proposed. The suggested transmissibility function is based on the relationship between the power spectral density (PSD) of mixed signals and the PSD of signals from a single source. The numerical responses of a truss structure with high levels of added noise and very closely spaced modes were processed using the proposed combined method to evaluate its ability to identify modal parameters in these conditions. Colored and white noise excitations were used for the numerical example. The proposed combined method was also used to evaluate the modal parameters of an experimental test on a structure containing closely spaced modes. The results showed that the proposed combined method is capable of identifying very closely spaced modes in the presence of noise and, thus, may be potentially applied to improve the identification of damping ratios.

Detection of regulated herbs and plants in plant food supplements and traditional medicines using infrared spectroscopy.

PubMed

Deconinck, E; Djiogo, C A Sokeng; Bothy, J L; Courselle, P

2017-08-05

The identification of a specific toxic or regulated plant in herbal preparations or plant food supplements is a real challenge, since they are often powdered, mixed with other herbal or synthetic powders and compressed into tablets or capsules. The classical identification approaches based on micro- and macroscopy are therefore not possible anymore. In this paper infrared spectroscopy, combined with attenuated total reflectance was evaluated for the screening of plant based preparations for nine specific plants (five regulated and four common plants for herbal supplements). IR and NIR spectra were recorded for a series of self-made triturations of the targeted plants. After pretreatment of the spectral data chemometric classification techniques were applied to both data sets (IR and NIR) separately and the combination of both. The results show that the screening of herbal preparations or plant food supplements for specific plants, using infrared spectroscopy, is feasible. The best model was obtained with the Mid-IR data, using SIMCA as modelling technique. During validation of the model, using an external test set, 21 of 25 were correctly classified and six of the nine targeted plants showed no misclassifications for the selected test set. For the other three a success rate of 50% was obtained. Mid-IR combined with SIMCA can therefore be applied as a first step in the screening of unknown samples, before applying more sophisticated fingerprint approaches or identification tests described in several national and international pharmacopoeia. As a proof of concept five real suspicious samples were successfully screened for the targeted regulated plants. Copyright © 2017 Elsevier B.V. All rights reserved.

Identification of Chinese Herbal Medicines with Electronic Nose Technology: Applications and Challenges

PubMed Central

Zhou, Huaying; Luo, Dehan; GholamHosseini, Hamid; Li, Zhong; He, Jiafeng

2017-01-01

This paper provides a review of the most recent works in machine olfaction as applied to the identification of Chinese Herbal Medicines (CHMs). Due to the wide variety of CHMs, the complexity of growing sources and the diverse specifications of herb components, the quality control of CHMs is a challenging issue. Much research has demonstrated that an electronic nose (E-nose) as an advanced machine olfaction system, can overcome this challenge through identification of the complex odors of CHMs. E-nose technology, with better usability, high sensitivity, real-time detection and non-destructive features has shown better performance in comparison with other analytical techniques such as gas chromatography-mass spectrometry (GC-MS). Although there has been immense development of E-nose techniques in other applications, there are limited reports on the application of E-noses for the quality control of CHMs. The aim of current study is to review practical implementation and advantages of E-noses for robust and effective odor identification of CHMs. It covers the use of E-nose technology to study the effects of growing regions, identification methods, production procedures and storage time on CHMs. Moreover, the challenges and applications of E-nose for CHM identification are investigated. Based on the advancement in E-nose technology, odor may become a new quantitative index for quality control of CHMs and drug discovery. It was also found that more research could be done in the area of odor standardization and odor reproduction for remote sensing. PMID:28486407

Identification of Chinese Herbal Medicines with Electronic Nose Technology: Applications and Challenges.

PubMed

Zhou, Huaying; Luo, Dehan; GholamHosseini, Hamid; Li, Zhong; He, Jiafeng

2017-05-09

This paper provides a review of the most recent works in machine olfaction as applied to the identification of Chinese Herbal Medicines (CHMs). Due to the wide variety of CHMs, the complexity of growing sources and the diverse specifications of herb components, the quality control of CHMs is a challenging issue. Much research has demonstrated that an electronic nose (E-nose) as an advanced machine olfaction system, can overcome this challenge through identification of the complex odors of CHMs. E-nose technology, with better usability, high sensitivity, real-time detection and non-destructive features has shown better performance in comparison with other analytical techniques such as gas chromatography-mass spectrometry (GC-MS). Although there has been immense development of E-nose techniques in other applications, there are limited reports on the application of E-noses for the quality control of CHMs. The aim of current study is to review practical implementation and advantages of E-noses for robust and effective odor identification of CHMs. It covers the use of E-nose technology to study the effects of growing regions, identification methods, production procedures and storage time on CHMs. Moreover, the challenges and applications of E-nose for CHM identification are investigated. Based on the advancement in E-nose technology, odor may become a new quantitative index for quality control of CHMs and drug discovery. It was also found that more research could be done in the area of odor standardization and odor reproduction for remote sensing.

[A peak recognition algorithm designed for chromatographic peaks of transformer oil].

PubMed

Ou, Linjun; Cao, Jian

2014-09-01

In the field of the chromatographic peak identification of the transformer oil, the traditional first-order derivative requires slope threshold to achieve peak identification. In terms of its shortcomings of low automation and easy distortion, the first-order derivative method was improved by applying the moving average iterative method and the normalized analysis techniques to identify the peaks. Accurate identification of the chromatographic peaks was realized through using multiple iterations of the moving average of signal curves and square wave curves to determine the optimal value of the normalized peak identification parameters, combined with the absolute peak retention times and peak window. The experimental results show that this algorithm can accurately identify the peaks and is not sensitive to the noise, the chromatographic peak width or the peak shape changes. It has strong adaptability to meet the on-site requirements of online monitoring devices of dissolved gases in transformer oil.

A Technique for Measuring Rotocraft Dynamic Stability in the 40 by 80 Foot Wind Tunnel

NASA Technical Reports Server (NTRS)

Gupta, N. K.; Bohn, J. G.

1977-01-01

An on-line technique is described for the measurement of tilt rotor aircraft dynamic stability in the Ames 40- by 80-Foot Wind Tunnel. The technique is based on advanced system identification methodology and uses the instrumental variables approach. It is particulary applicable to real time estimation problems with limited amounts of noise-contaminated data. Several simulations are used to evaluate the algorithm. Estimated natural frequencies and damping ratios are compared with simulation values. The algorithm is also applied to wind tunnel data in an off-line mode. The results are used to develop preliminary guidelines for effective use of the algorithm.

Direct identification of microorganisms from positive blood cultures using the lysis-filtration technique and matrix assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS): a multicentre study.

PubMed

Farina, Claudio; Arena, Fabio; Casprini, Patrizia; Cichero, Paola; Clementi, Massimo; Cosentino, Marina; Degl'Innocenti, Roberto; Giani, Tommaso; Luzzaro, Francesco; Mattei, Romano; Mauri, Carola; Nardone, Maria; Rossolini, Gian Maria; Serna Ortega, Paula Andrea; Vailati, Francesca

2015-04-01

Microbial identification from blood cultures is essential to institute optimal antibiotic therapy and improve survival possibilities. Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) has been successfully applied to identify bacteria and yeasts from positive blood cultures broths. The aim of this multicentre study was to evaluate the reliability of the lysis-filtration technique associated with MALDI-TOF MS to directly identify microorganisms from 765 positive blood cultures collected in six Italian hospitals. Overall, 675/765 (78.1%) blood isolates were correctly identified at the species level, with significant differences between Gram-negative and Gram-positive bacteria (92.6%, and 69.8%, respectively). Some difficulties arise in identifying Streptococcus pneumoniae, Staphylococcus aureus, yeasts and anaerobes. The lysis-filtration protocol is a suitable procedure in terms of performance in identifying microorganisms, but it is quite expensive and technically time-consuming since the time of filtration is not regular for all the samples. The application of the MALDI-TOF MS technique to the direct microbial identification from positive blood cultures is a very promising approach, even if more experience must be gained to minimize errors and costs.

An investigation of hydrogenized amorphous Si structures with Doppler broadening positron annihilation techniques

NASA Astrophysics Data System (ADS)

Petkov, M. P.; Marek, T.; Asoka-Kumar, P.; Lynn, K. G.; Crandall, R. S.; Mahan, A. H.

1998-07-01

In this letter, we examine the feasibility of applying positron annihilation spectroscopy to the study of hydrogenized amorphous silicon (a-Si:H)-based structures produced by chemical vapor deposition techniques. The positron probe, sensitive to open volume formations, is used to characterize neutral and negatively charged silicon dangling bonds, typical for undoped and n-doped a-Si:H, respectively. Using depth profiling along the growth direction a difference was observed in the electronic environment of these defects, which enables their identification in a p-i-n device.

Comparison of μ-ATR-FTIR spectroscopy and py-GCMS as identification tools for microplastic particles and fibers isolated from river sediments.

PubMed

Käppler, Andrea; Fischer, Marten; Scholz-Böttcher, Barbara M; Oberbeckmann, Sonja; Labrenz, Matthias; Fischer, Dieter; Eichhorn, Klaus-Jochen; Voit, Brigitte

2018-06-16

In recent years, many studies on the analysis of microplastics (MP) in environmental samples have been published. These studies are hardly comparable due to different sampling, sample preparation, as well as identification and quantification techniques. Here, MP identification is one of the crucial pitfalls. Visual identification approaches using morphological criteria alone often lead to significant errors, being especially true for MP fibers. Reliable, chemical structure-based identification methods are indispensable. In this context, the frequently used vibrational spectroscopic techniques but also thermoanalytical methods are established. However, no critical comparison of these fundamentally different approaches has ever been carried out with regard to analyzing MP in environmental samples. In this blind study, we investigated 27 single MP particles and fibers of unknown material isolated from river sediments. Successively micro-attenuated total reflection Fourier transform infrared spectroscopy (μ-ATR-FTIR) and pyrolysis gas chromatography-mass spectrometry (py-GCMS) in combination with thermochemolysis were applied. Both methods differentiated between plastic vs. non-plastic in the same way in 26 cases, with 19 particles and fibers (22 after re-evaluation) identified as the same polymer type. To illustrate the different approaches and emphasize the complementarity of their information content, we exemplarily provide a detailed comparison of four particles and three fibers and a critical discussion of advantages and disadvantages of both methods.

A Galerkin method for the estimation of parameters in hybrid systems governing the vibration of flexible beams with tip bodies

NASA Technical Reports Server (NTRS)

Banks, H. T.; Rosen, I. G.

1985-01-01

An approximation scheme is developed for the identification of hybrid systems describing the transverse vibrations of flexible beams with attached tip bodies. In particular, problems involving the estimation of functional parameters are considered. The identification problem is formulated as a least squares fit to data subject to the coupled system of partial and ordinary differential equations describing the transverse displacement of the beam and the motion of the tip bodies respectively. A cubic spline-based Galerkin method applied to the state equations in weak form and the discretization of the admissible parameter space yield a sequence of approximating finite dimensional identification problems. It is shown that each of the approximating problems admits a solution and that from the resulting sequence of optimal solutions a convergent subsequence can be extracted, the limit of which is a solution to the original identification problem. The approximating identification problems can be solved using standard techniques and readily available software.

Automated colour identification in melanocytic lesions.

PubMed

Sabbaghi, S; Aldeen, M; Garnavi, R; Varigos, G; Doliantis, C; Nicolopoulos, J

2015-08-01

Colour information plays an important role in classifying skin lesion. However, colour identification by dermatologists can be very subjective, leading to cases of misdiagnosis. Therefore, a computer-assisted system for quantitative colour identification is highly desirable for dermatologists to use. Although numerous colour detection systems have been developed, few studies have focused on imitating the human visual perception of colours in melanoma application. In this paper we propose a new methodology based on QuadTree decomposition technique for automatic colour identification in dermoscopy images. Our approach mimics the human perception of lesion colours. The proposed method is trained on a set of 47 images from NIH dataset and applied to a test set of 190 skin lesions obtained from PH2 dataset. The results of our proposed method are compared with a recently reported colour identification method using the same dataset. The effectiveness of our method in detecting colours in dermoscopy images is vindicated by obtaining approximately 93% accuracy when the CIELab1 colour space is used.

On-site identification of meat species in processed foods by a rapid real-time polymerase chain reaction system.

PubMed

Furutani, Shunsuke; Hagihara, Yoshihisa; Nagai, Hidenori

2017-09-01

Correct labeling of foods is critical for consumers who wish to avoid a specific meat species for religious or cultural reasons. Therefore, gene-based point-of-care food analysis by real-time Polymerase Chain Reaction (PCR) is expected to contribute to the quality control in the food industry. In this study, we perform rapid identification of meat species by our portable rapid real-time PCR system, following a very simple DNA extraction method. Applying these techniques, we correctly identified beef, pork, chicken, rabbit, horse, and mutton in processed foods in 20min. Our system was sensitive enough to detect the interfusion of about 0.1% chicken egg-derived DNA in a processed food sample. Our rapid real-time PCR system is expected to contribute to the quality control in food industries because it can be applied for the identification of meat species, and future applications can expand its functionality to the detection of genetically modified organisms or mutations. Copyright © 2017 Elsevier Ltd. All rights reserved.

(GTG)5 MSP-PCR fingerprinting as a technique for discrimination of wine associated yeasts?

PubMed

Ramírez-Castrillón, Mauricio; Mendes, Sandra Denise Camargo; Inostroza-Ponta, Mario; Valente, Patricia

2014-01-01

In microbiology, identification of all isolates by sequencing is still unfeasible in small research laboratories. Therefore, many yeast diversity studies follow a screening procedure consisting of clustering the yeast isolates using MSP-PCR fingerprinting, followed by identification of one or a few selected representatives of each cluster by sequencing. Although this procedure has been widely applied in the literature, it has not been properly validated. We evaluated a standardized protocol using MSP-PCR fingerprinting with the primers (GTG)5 and M13 for the discrimination of wine associated yeasts in South Brazil. Two datasets were used: yeasts isolated from bottled wines and vineyard environments. We compared the discriminatory power of both primers in a subset of 16 strains, choosing the primer (GTG)5 for further evaluation. Afterwards, we applied this technique to 245 strains, and compared the results with the identification obtained by partial sequencing of the LSU rRNA gene, considered as the gold standard. An array matrix was constructed for each dataset and used as input for clustering with two methods (hierarchical dendrograms and QAPGrid layout). For both yeast datasets, unrelated species were clustered in the same group. The sensitivity score of (GTG)5 MSP-PCR fingerprinting was high, but specificity was low. As a conclusion, the yeast diversity inferred in several previous studies may have been underestimated and some isolates were probably misidentified due to the compliance to this screening procedure.

(GTG)5 MSP-PCR Fingerprinting as a Technique for Discrimination of Wine Associated Yeasts?

PubMed Central

Inostroza-Ponta, Mario; Valente, Patricia

2014-01-01

In microbiology, identification of all isolates by sequencing is still unfeasible in small research laboratories. Therefore, many yeast diversity studies follow a screening procedure consisting of clustering the yeast isolates using MSP-PCR fingerprinting, followed by identification of one or a few selected representatives of each cluster by sequencing. Although this procedure has been widely applied in the literature, it has not been properly validated. We evaluated a standardized protocol using MSP-PCR fingerprinting with the primers (GTG)5 and M13 for the discrimination of wine associated yeasts in South Brazil. Two datasets were used: yeasts isolated from bottled wines and vineyard environments. We compared the discriminatory power of both primers in a subset of 16 strains, choosing the primer (GTG)5 for further evaluation. Afterwards, we applied this technique to 245 strains, and compared the results with the identification obtained by partial sequencing of the LSU rRNA gene, considered as the gold standard. An array matrix was constructed for each dataset and used as input for clustering with two methods (hierarchical dendrograms and QAPGrid layout). For both yeast datasets, unrelated species were clustered in the same group. The sensitivity score of (GTG)5 MSP-PCR fingerprinting was high, but specificity was low. As a conclusion, the yeast diversity inferred in several previous studies may have been underestimated and some isolates were probably misidentified due to the compliance to this screening procedure. PMID:25171185

Plant Species Identification by Bi-channel Deep Convolutional Networks

NASA Astrophysics Data System (ADS)

He, Guiqing; Xia, Zhaoqiang; Zhang, Qiqi; Zhang, Haixi; Fan, Jianping

2018-04-01

Plant species identification achieves much attention recently as it has potential application in the environmental protection and human life. Although deep learning techniques can be directly applied for plant species identification, it still needs to be designed for this specific task to obtain the state-of-art performance. In this paper, a bi-channel deep learning framework is developed for identifying plant species. In the framework, two different sub-networks are fine-tuned over their pretrained models respectively. And then a stacking layer is used to fuse the output of two different sub-networks. We construct a plant dataset of Orchidaceae family for algorithm evaluation. Our experimental results have demonstrated that our bi-channel deep network can achieve very competitive performance on accuracy rates compared to the existing deep learning algorithm.

Continuous-time system identification of a smoking cessation intervention

NASA Astrophysics Data System (ADS)

Timms, Kevin P.; Rivera, Daniel E.; Collins, Linda M.; Piper, Megan E.

2014-07-01

Cigarette smoking is a major global public health issue and the leading cause of preventable death in the United States. Toward a goal of designing better smoking cessation treatments, system identification techniques are applied to intervention data to describe smoking cessation as a process of behaviour change. System identification problems that draw from two modelling paradigms in quantitative psychology (statistical mediation and self-regulation) are considered, consisting of a series of continuous-time estimation problems. A continuous-time dynamic modelling approach is employed to describe the response of craving and smoking rates during a quit attempt, as captured in data from a smoking cessation clinical trial. The use of continuous-time models provide benefits of parsimony, ease of interpretation, and the opportunity to work with uneven or missing data.

Raman Spectroscopy of Optically Trapped Single Biological Micro-Particles

PubMed Central

Redding, Brandon; Schwab, Mark J.; Pan, Yong-le

2015-01-01

The combination of optical trapping with Raman spectroscopy provides a powerful method for the study, characterization, and identification of biological micro-particles. In essence, optical trapping helps to overcome the limitation imposed by the relative inefficiency of the Raman scattering process. This allows Raman spectroscopy to be applied to individual biological particles in air and in liquid, providing the potential for particle identification with high specificity, longitudinal studies of changes in particle composition, and characterization of the heterogeneity of individual particles in a population. In this review, we introduce the techniques used to integrate Raman spectroscopy with optical trapping in order to study individual biological particles in liquid and air. We then provide an overview of some of the most promising applications of this technique, highlighting the unique types of measurements enabled by the combination of Raman spectroscopy with optical trapping. Finally, we present a brief discussion of future research directions in the field. PMID:26247952

Molecular identification of Malassezia species isolated from dermatitis affections.

PubMed

Affes, M; Ben Salah, S; Makni, F; Sellami, H; Ayadi, A

2009-05-01

The lipophilic yeast of the genus Malassezia are opportunistic microorganisms of the skin microflora but they can be agents of various dermatomycoses. The aim of this study was to perform molecular identification of the commonly isolated Malassezia species from various dermatomycoses in our region. Thirty strains of Malassezia were isolated from different dermatologic affections: pityriasis versicolor (17), dandruff (5), seborrheic dermatitis (4), onyxis (2), folliculitis (1) and blepharitis (1). These species were identified by their morphological features and biochemical characterisation. The molecular identification was achieved by amplification of the internal transcribed spacer region by simple PCR. PCR technique was used for molecular characterisation of four Malassezia species: Malassezia globosa (270 bp), Malassezia furfur (230 bp), Malassezia sympodialis (190 bp) and Malassezia restricta (320 bp). We have detected the association between M. furfur and M. sympodialis in 16% and confirmed presumptive identification in 70% of the cases. The phenotypic identification based on microscopic and physiological method is difficult and time consuming. The application of a simple PCR method provides a sensitive and rapid identification system for Malassezia species, which may be applied in epidemiological surveys and routine practice.

Phospholipid Fatty Acid Analysis: Past, Present and Future

NASA Astrophysics Data System (ADS)

Findlay, R. H.

2008-12-01

With their 1980 publication, Bobbie and White initiated the use of phospholipid fatty acids for the study of microbial communities. This method, integrated with a previously published biomass assay based on the colorimetric detection of orthophosphate liberated from phospholipids, provided the first quantitative method for determining microbial community structure. The method is based on a quantitative extraction of lipids from the sample matrix, isolation of the phospholipids, conversion of the phospholipid fatty acids to their corresponding fatty acid methyl esters (known by the acronym FAME) and the separation, identification and quantification of the FAME by gas chromatography. Early laboratory and field samples focused on correlating individual fatty acids to particular groups of microorganisms. Subsequent improvements to the methodology include reduced solvent volumes for extractions, improved sensitivity in the detection of orthophosphate and the use of solid phase extraction technology. Improvements in the field of gas chromatography also increased accessibility of the technique and it has been widely applied to water, sediment, soil and aerosol samples. Whole cell fatty acid analysis, a related but not equal technique, is currently used for phenotypic characterization in bacterial species descriptions and is the basis for a commercial, rapid bacterial identification system. In the early 1990ês application of multivariate statistical analysis, first cluster analysis and then principal component analysis, further improved the usefulness of the technique and allowed the development of a functional group approach to interpretation of phospholipid fatty acid profiles. Statistical techniques currently applied to the analysis of phospholipid fatty acid profiles include constrained ordinations and neutral networks. Using redundancy analysis, a form of constrained ordination, we have recently shown that both cation concentration and dissolved organic matter (DOM) quality are determinates of microbial community structure in forested headwater streams. One of the most exciting recent developments in phospholipid fatty acid analysis is the application of compound specific stable isotope analysis. We are currently applying this technique to stream sediments to help determine which microorganisms are involved in the initial processing of DOM and the technique promises to be a useful tool for assigning ecological function to microbial populations.

An experimental approach to identify dynamical models of transcriptional regulation in living cells

NASA Astrophysics Data System (ADS)

Fiore, G.; Menolascina, F.; di Bernardo, M.; di Bernardo, D.

2013-06-01

We describe an innovative experimental approach, and a proof of principle investigation, for the application of System Identification techniques to derive quantitative dynamical models of transcriptional regulation in living cells. Specifically, we constructed an experimental platform for System Identification based on a microfluidic device, a time-lapse microscope, and a set of automated syringes all controlled by a computer. The platform allows delivering a time-varying concentration of any molecule of interest to the cells trapped in the microfluidics device (input) and real-time monitoring of a fluorescent reporter protein (output) at a high sampling rate. We tested this platform on the GAL1 promoter in the yeast Saccharomyces cerevisiae driving expression of a green fluorescent protein (Gfp) fused to the GAL1 gene. We demonstrated that the System Identification platform enables accurate measurements of the input (sugars concentrations in the medium) and output (Gfp fluorescence intensity) signals, thus making it possible to apply System Identification techniques to obtain a quantitative dynamical model of the promoter. We explored and compared linear and nonlinear model structures in order to select the most appropriate to derive a quantitative model of the promoter dynamics. Our platform can be used to quickly obtain quantitative models of eukaryotic promoters, currently a complex and time-consuming process.

A collaborative approach to lean laboratory workstation design reduces wasted technologist travel.

PubMed

Yerian, Lisa M; Seestadt, Joseph A; Gomez, Erron R; Marchant, Kandice K

2012-08-01

Lean methodologies have been applied in many industries to reduce waste. We applied Lean techniques to redesign laboratory workstations with the aim of reducing the number of times employees must leave their workstations to complete their tasks. At baseline in 68 workflows (aggregates or sequence of process steps) studied, 251 (38%) of 664 tasks required workers to walk away from their workstations. After analysis and redesign, only 59 (9%) of the 664 tasks required technologists to leave their workstations to complete these tasks. On average, 3.4 travel events were removed for each workstation. Time studies in a single laboratory section demonstrated that workers spend 8 to 70 seconds in travel each time they step away from the workstation. The redesigned workstations will allow employees to spend less time travelling around the laboratory. Additional benefits include employee training in waste identification, improved overall laboratory layout, and identification of other process improvement opportunities in our laboratory.

Using Blocked Fractional Factorial Designs to Construct Discrete Choice Experiments for Health Care Studies

PubMed Central

Jaynes, Jessica; Wong, Weng Kee; Xu, Hongquan

2016-01-01

Discrete choice experiments (DCEs) are increasingly used for studying and quantifying subjects preferences in a wide variety of health care applications. They provide a rich source of data to assess real-life decision making processes, which involve trade-offs between desirable characteristics pertaining to health and health care, and identification of key attributes affecting health care. The choice of the design for a DCE is critical because it determines which attributes’ effects and their interactions are identifiable. We apply blocked fractional factorial designs to construct DCEs and address some identification issues by utilizing the known structure of blocked fractional factorial designs. Our design techniques can be applied to several situations including DCEs where attributes have different number of levels. We demonstrate our design methodology using two health care studies to evaluate (1) asthma patients’ preferences for symptom-based outcome measures, and (2) patient preference for breast screening services. PMID:26823156

Profiling refined hydrocarbon fuels using polar components

USGS Publications Warehouse

Rostad, C.E.; Hostettler, F.D.

2007-01-01

Identification of a fuel released into the environment can be difficult due to biodegradation or weathering. Negative electrospray ionization/mass spectrometry was used to screen for unique polar components in a wide variety of commercial hydrocarbon products and mixtures. These fuels produced unique and relatively simple spectra. When applied to hydrocarbon samples from a large, long-term fuel spill in a relatively cool climate in which the alkane, isoprenoid, and alkylcyclohexane portions had begun to biodegrade or weather, the polar components in these samples had changed little over time. This technique provided rapid fuel identification on hydrocarbons released into the environment, without sample preparation, fractionation, or chromatography. Copyright ?? Taylor & Francis Group, LLC.

Behavioral biometrics for verification and recognition of malicious software agents

NASA Astrophysics Data System (ADS)

Yampolskiy, Roman V.; Govindaraju, Venu

2008-04-01

Homeland security requires technologies capable of positive and reliable identification of humans for law enforcement, government, and commercial applications. As artificially intelligent agents improve in their abilities and become a part of our everyday life, the possibility of using such programs for undermining homeland security increases. Virtual assistants, shopping bots, and game playing programs are used daily by millions of people. We propose applying statistical behavior modeling techniques developed by us for recognition of humans to the identification and verification of intelligent and potentially malicious software agents. Our experimental results demonstrate feasibility of such methods for both artificial agent verification and even for recognition purposes.

Three-dimensional gauge theories and gravitational instantons from string theory

NASA Astrophysics Data System (ADS)

Cherkis, Sergey Alexander

Various realizations of gauge theories in string theory allow an identification of their spaces of vacua with gravitational instantons. Also, they provide a correspondence of vacua of gauge theories with nonabelian monopole configurations and solutions of a system of integrable equations called Nahm equations. These identifications make it possible to apply powerful techniques of differential and algebraic geometry to solve the gauge theories in question. In other words, it becomes possible to find the exact metrics on their moduli spaces of vacua with all quantum corrections included. As another outcome we obtain for the first time the description of a series of all Dk-type gravitational instantons.

Modal Parameter Identification of a Flexible Arm System

NASA Technical Reports Server (NTRS)

Barrington, Jason; Lew, Jiann-Shiun; Korbieh, Edward; Wade, Montanez; Tantaris, Richard

1998-01-01

In this paper an experiment is designed for the modal parameter identification of a flexible arm system. This experiment uses a function generator to provide input signal and an oscilloscope to save input and output response data. For each vibrational mode, many sets of sine-wave inputs with frequencies close to the natural frequency of the arm system are used to excite the vibration of this mode. Then a least-squares technique is used to analyze the experimental input/output data to obtain the identified parameters for this mode. The identified results are compared with the analytical model obtained by applying finite element analysis.

Identifying 1st instar larvae for three forensically important blowfly species using "fingerprint" cuticular hydrocarbon analysis.

PubMed

Moore, Hannah E; Adam, Craig D; Drijfhout, Falko P

2014-07-01

Calliphoridae are known to be the most forensically important insects when it comes to establishing the minimum post mortem interval (PMImin) in criminal investigations. The first step in calculating the PMImin is to identify the larvae present to species level. Accurate identification which is conventionally carried out by morphological analysis is crucial because different insects have different life stage timings. Rapid identification in the immature larvae stages would drastically cut time in criminal investigations as it would eliminate the need to rear larvae to adult flies to determine the species. Cuticular hydrocarbon analysis on 1st instar larvae has been applied to three forensically important blowflies; Lucilia sericata, Calliphora vicina and Calliphora vomitoria, using gas chromatography-mass spectrometry (GC-MS) and principal component analysis (PCA). The results show that each species holds a distinct "fingerprint" hydrocarbon profile, allowing for accurate identification to be established in 1-day old larvae, when it can be challenging to apply morphological criteria. Consequently, this GC-MS based technique could accelerate and strengthen the identification process, not only for forensically important species, but also for other entomological samples which are hard to identify using morphological features. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Quantitative Index and Abnormal Alarm Strategy Using Sensor-Dependent Vibration Data for Blade Crack Identification in Centrifugal Booster Fans

PubMed Central

Chen, Jinglong; Sun, Hailiang; Wang, Shuai; He, Zhengjia

2016-01-01

Centrifugal booster fans are important equipment used to recover blast furnace gas (BFG) for generating electricity, but blade crack faults (BCFs) in centrifugal booster fans can lead to unscheduled breakdowns and potentially serious accidents, so in this work quantitative fault identification and an abnormal alarm strategy based on acquired historical sensor-dependent vibration data is proposed for implementing condition-based maintenance for this type of equipment. Firstly, three group dependent sensors are installed to acquire running condition data. Then a discrete spectrum interpolation method and short time Fourier transform (STFT) are applied to preliminarily identify the running data in the sensor-dependent vibration data. As a result a quantitative identification and abnormal alarm strategy based on compound indexes including the largest Lyapunov exponent and relative energy ratio at the second harmonic frequency component is proposed. Then for validation the proposed blade crack quantitative identification and abnormality alarm strategy is applied to analyze acquired experimental data for centrifugal booster fans and it has successfully identified incipient blade crack faults. In addition, the related mathematical modelling work is also introduced to investigate the effects of mistuning and cracks on the vibration features of centrifugal impellers and to explore effective techniques for crack detection. PMID:27171083

Robust Library Building for Autonomous Classification of Downhole Geophysical Logs Using Gaussian Processes

NASA Astrophysics Data System (ADS)

Silversides, Katherine L.; Melkumyan, Arman

2017-03-01

Machine learning techniques such as Gaussian Processes can be used to identify stratigraphically important features in geophysical logs. The marker shales in the banded iron formation hosted iron ore deposits of the Hamersley Ranges, Western Australia, form distinctive signatures in the natural gamma logs. The identification of these marker shales is important for stratigraphic identification of unit boundaries for the geological modelling of the deposit. Machine learning techniques each have different unique properties that will impact the results. For Gaussian Processes (GPs), the output values are inclined towards the mean value, particularly when there is not sufficient information in the library. The impact that these inclinations have on the classification can vary depending on the parameter values selected by the user. Therefore, when applying machine learning techniques, care must be taken to fit the technique to the problem correctly. This study focuses on optimising the settings and choices for training a GPs system to identify a specific marker shale. We show that the final results converge even when different, but equally valid starting libraries are used for the training. To analyse the impact on feature identification, GP models were trained so that the output was inclined towards a positive, neutral or negative output. For this type of classification, the best results were when the pull was towards a negative output. We also show that the GP output can be adjusted by using a standard deviation coefficient that changes the balance between certainty and accuracy in the results.

Rapid analysis of controlled substances using desorption electrospray ionization mass spectrometry.

PubMed

Rodriguez-Cruz, Sandra E

2006-01-01

The recently developed technique of desorption electrospray ionization (DESI) has been applied to the rapid analysis of controlled substances. Experiments have been performed using a commercial ThermoFinnigan LCQ Advantage MAX ion-trap mass spectrometer with limited modifications. Results from the ambient sampling of licit and illicit tablets demonstrate the ability of the DESI technique to detect the main active ingredient(s) or controlled substance(s), even in the presence of other higher-concentration components. Full-scan mass spectrometry data provide preliminary identification by molecular weight determination, while rapid analysis using the tandem mass spectrometry (MS/MS) mode provides fragmentation data which, when compared to the laboratory-generated ESI-MS/MS spectral library, provide structural information and final identification of the active ingredient(s). The consecutive analysis of tablets containing different active components indicates there is no cross-contamination or interference from tablet to tablet, demonstrating the reliability of the DESI technique for rapid sampling (one tablet/min or better). Active ingredients have been detected for tablets in which the active component represents less than 1% of the total tablet weight, demonstrating the sensitivity of the technique. The real-time sampling of cannabis plant material is also presented.

Identification of transformer fault based on dissolved gas analysis using hybrid support vector machine-modified evolutionary particle swarm optimisation

PubMed Central

2018-01-01

Early detection of power transformer fault is important because it can reduce the maintenance cost of the transformer and it can ensure continuous electricity supply in power systems. Dissolved Gas Analysis (DGA) technique is commonly used to identify oil-filled power transformer fault type but utilisation of artificial intelligence method with optimisation methods has shown convincing results. In this work, a hybrid support vector machine (SVM) with modified evolutionary particle swarm optimisation (EPSO) algorithm was proposed to determine the transformer fault type. The superiority of the modified PSO technique with SVM was evaluated by comparing the results with the actual fault diagnosis, unoptimised SVM and previous reported works. Data reduction was also applied using stepwise regression prior to the training process of SVM to reduce the training time. It was found that the proposed hybrid SVM-Modified EPSO (MEPSO)-Time Varying Acceleration Coefficient (TVAC) technique results in the highest correct identification percentage of faults in a power transformer compared to other PSO algorithms. Thus, the proposed technique can be one of the potential solutions to identify the transformer fault type based on DGA data on site. PMID:29370230

Identification of transformer fault based on dissolved gas analysis using hybrid support vector machine-modified evolutionary particle swarm optimisation.

PubMed

Illias, Hazlee Azil; Zhao Liang, Wee

2018-01-01

Early detection of power transformer fault is important because it can reduce the maintenance cost of the transformer and it can ensure continuous electricity supply in power systems. Dissolved Gas Analysis (DGA) technique is commonly used to identify oil-filled power transformer fault type but utilisation of artificial intelligence method with optimisation methods has shown convincing results. In this work, a hybrid support vector machine (SVM) with modified evolutionary particle swarm optimisation (EPSO) algorithm was proposed to determine the transformer fault type. The superiority of the modified PSO technique with SVM was evaluated by comparing the results with the actual fault diagnosis, unoptimised SVM and previous reported works. Data reduction was also applied using stepwise regression prior to the training process of SVM to reduce the training time. It was found that the proposed hybrid SVM-Modified EPSO (MEPSO)-Time Varying Acceleration Coefficient (TVAC) technique results in the highest correct identification percentage of faults in a power transformer compared to other PSO algorithms. Thus, the proposed technique can be one of the potential solutions to identify the transformer fault type based on DGA data on site.

Identification of human operator performance models utilizing time series analysis

NASA Technical Reports Server (NTRS)

Holden, F. M.; Shinners, S. M.

1973-01-01

The results of an effort performed by Sperry Systems Management Division for AMRL in applying time series analysis as a tool for modeling the human operator are presented. This technique is utilized for determining the variation of the human transfer function under various levels of stress. The human operator's model is determined based on actual input and output data from a tracking experiment.

Plan View Pattern Control for Steel Plates through Constrained Locally Weighted Regression

NASA Astrophysics Data System (ADS)

Shigemori, Hiroyasu; Nambu, Koji; Nagao, Ryo; Araki, Tadashi; Mizushima, Narihito; Kano, Manabu; Hasebe, Shinji

A technique for performing parameter identification in a locally weighted regression model using foresight information on the physical properties of the object of interest as constraints was proposed. This method was applied to plan view pattern control of steel plates, and a reduction of shape nonconformity (crop) at the plate head end was confirmed by computer simulation based on real operation data.

Fingerprinting and quantification of GMOs in the agro-food sector.

PubMed

Taverniers, I; Van Bockstaele, E; De Loose, M

2003-01-01

Most strategies for analyzing GMOs in plants and derived food and feed products, are based on the polymerase chain reaction (PCR) technique. In conventional PCR methods, a 'known' sequence between two specific primers is amplified. To the contrary, with the 'anchor PCR' technique, unknown sequences adjacent to a known sequence, can be amplified. Because T-DNA/plant border sequences are being amplified, anchor PCR is the perfect tool for unique identification of transgenes, including non-authorized GMOs. In this work, anchor PCR was applied to characterize the 'transgene locus' and to clarify the complete molecular structure of at least six different commercial transgenic plants. Based on sequences of T-DNA/plant border junctions, obtained by anchor PCR, event specific primers were developed. The junction fragments, together with endogeneous reference gene targets, were cloned in plasmids. The latter were then used as event specific calibrators in real-time PCR, a new technique for the accurate relative quantification of GMOs. We demonstrate here the importance of anchor PCR for identification and the usefulness of plasmid DNA calibrators in quantification strategies for GMOs, throughout the agro-food sector.

Comparative study of electromechanical impedance and Lamb wave techniques for fatigue crack detection and monitoring in metallic structures

NASA Astrophysics Data System (ADS)

Lim, Say Ian; Liu, Yu; Soh, Chee Kiong

2012-04-01

Fatigue cracks often initiate at the weld toes of welded steel connections. Usually, these cracks cannot be identified by the naked eyes. Existing identification methods like dye-penetration test and alternating current potential drop (ACPD) may be useful for detecting fatigue cracks at the weld toes. To apply these non-destructive evaluation (NDE) techniques, the potential sites have to be accessible during inspection. Therefore, there is a need to explore other detection and monitoring techniques for fatigue cracks especially when their locations are inaccessible or cost of access is uneconomical. Electro-mechanical Impedance (EMI) and Lamb wave techniques are two fast growing techniques in the Structural Health Monitoring (SHM) community. These techniques use piezoelectric ceramics (PZT) for actuation and sensing. Since the monitoring site is only needed to be accessed once for the instrumentation of the transducers, remote monitoring is made possible. The permanent locations of these transducers also translate to having consistent measurement for monitoring. The main focus of this study is to conduct a comparative investigation on the effectiveness and efficiency of the EMI technique and the Lamb wave technique for successful fatigue crack identification and monitoring of welded steel connections using piezoelectric transducers. A laboratory-sized non-load carrying fillet weld specimen is used in this study. The specimen is subjected to cyclic tensile load and data for both techniques are acquired at stipulated intervals. It can be concluded that the EMI technique is sensitive to the crack initiation phase while the Lamb wave technique correlates well with the crack propagation phase.

Convolutional neural networks applied to neutrino events in a liquid argon time projection chamber

NASA Astrophysics Data System (ADS)

Acciarri, R.; Adams, C.; An, R.; Asaadi, J.; Auger, M.; Bagby, L.; Baller, B.; Barr, G.; Bass, M.; Bay, F.; Bishai, M.; Blake, A.; Bolton, T.; Bugel, L.; Camilleri, L.; Caratelli, D.; Carls, B.; Castillo Fernandez, R.; Cavanna, F.; Chen, H.; Church, E.; Cianci, D.; Collin, G. H.; Conrad, J. M.; Convery, M.; Crespo-Anadón, J. I.; Del Tutto, M.; Devitt, D.; Dytman, S.; Eberly, B.; Ereditato, A.; Escudero Sanchez, L.; Esquivel, J.; Fleming, B. T.; Foreman, W.; Furmanski, A. P.; Garvey, G. T.; Genty, V.; Goeldi, D.; Gollapinni, S.; Graf, N.; Gramellini, E.; Greenlee, H.; Grosso, R.; Guenette, R.; Hackenburg, A.; Hamilton, P.; Hen, O.; Hewes, J.; Hill, C.; Ho, J.; Horton-Smith, G.; James, C.; de Vries, J. Jan; Jen, C.-M.; Jiang, L.; Johnson, R. A.; Jones, B. J. P.; Joshi, J.; Jostlein, H.; Kaleko, D.; Karagiorgi, G.; Ketchum, W.; Kirby, B.; Kirby, M.; Kobilarcik, T.; Kreslo, I.; Laube, A.; Li, Y.; Lister, A.; Littlejohn, B. R.; Lockwitz, S.; Lorca, D.; Louis, W. C.; Luethi, M.; Lundberg, B.; Luo, X.; Marchionni, A.; Mariani, C.; Marshall, J.; Martinez Caicedo, D. A.; Meddage, V.; Miceli, T.; Mills, G. B.; Moon, J.; Mooney, M.; Moore, C. D.; Mousseau, J.; Murrells, R.; Naples, D.; Nienaber, P.; Nowak, J.; Palamara, O.; Paolone, V.; Papavassiliou, V.; Pate, S. F.; Pavlovic, Z.; Porzio, D.; Pulliam, G.; Qian, X.; Raaf, J. L.; Rafique, A.; Rochester, L.; von Rohr, C. Rudolf; Russell, B.; Schmitz, D. W.; Schukraft, A.; Seligman, W.; Shaevitz, M. H.; Sinclair, J.; Snider, E. L.; Soderberg, M.; Söldner-Rembold, S.; Soleti, S. R.; Spentzouris, P.; Spitz, J.; St. John, J.; Strauss, T.; Szelc, A. M.; Tagg, N.; Terao, K.; Thomson, M.; Toups, M.; Tsai, Y.-T.; Tufanli, S.; Usher, T.; Van de Water, R. G.; Viren, B.; Weber, M.; Weston, J.; Wickremasinghe, D. A.; Wolbers, S.; Wongjirad, T.; Woodruff, K.; Yang, T.; Zeller, G. P.; Zennamo, J.; Zhang, C.

2017-03-01

We present several studies of convolutional neural networks applied to data coming from the MicroBooNE detector, a liquid argon time projection chamber (LArTPC). The algorithms studied include the classification of single particle images, the localization of single particle and neutrino interactions in an image, and the detection of a simulated neutrino event overlaid with cosmic ray backgrounds taken from real detector data. These studies demonstrate the potential of convolutional neural networks for particle identification or event detection on simulated neutrino interactions. We also address technical issues that arise when applying this technique to data from a large LArTPC at or near ground level.

Identification and robust control of an experimental servo motor.

PubMed

Adam, E J; Guestrin, E D

2002-04-01

In this work, the design of a robust controller for an experimental laboratory-scale position control system based on a dc motor drive as well as the corresponding identification and robust stability analysis are presented. In order to carry out the robust design procedure, first, a classic closed-loop identification technique is applied and then, the parametrization by internal model control is used. The model uncertainty is evaluated under both parametric and global representation. For the latter case, an interesting discussion about the conservativeness of this description is presented by means of a comparison between the uncertainty disk and the critical perturbation radius approaches. Finally, conclusions about the performance of the experimental system with the robust controller are discussed using comparative graphics of the controlled variable and the Nyquist stability margin as a robustness measurement.

Differential PIXE for investigating the layer structure of paintings

NASA Astrophysics Data System (ADS)

Mandò, P. A.; Fedi, M. E.; Grassi, N.; Migliori, A.

2005-09-01

This paper reports an example of how the differential PIXE technique can be successfully applied to the investigation of wood or canvas paintings. The work analysed is a famous wood painting by Leonardo da Vinci, the "Madonna dei fusi" (ex-Reford version, 1501), chosen for a pilot study in a wide international project aimed at analysing Leonardo's works of art by means of non-destructive techniques. While illustrating the results obtained concerning the identification of pigments and the discrimination of the stratigraphy of layers, the merits and limits of differential PIXE in general are pointed out.

Comparison of data mining techniques applied to fetal heart rate parameters for the early identification of IUGR fetuses.

PubMed

Magenes, G; Bellazzi, R; Malovini, A; Signorini, M G

2016-08-01

The onset of fetal pathologies can be screened during pregnancy by means of Fetal Heart Rate (FHR) monitoring and analysis. Noticeable advances in understanding FHR variations were obtained in the last twenty years, thanks to the introduction of quantitative indices extracted from the FHR signal. This study searches for discriminating Normal and Intra Uterine Growth Restricted (IUGR) fetuses by applying data mining techniques to FHR parameters, obtained from recordings in a population of 122 fetuses (61 healthy and 61 IUGRs), through standard CTG non-stress test. We computed N=12 indices (N=4 related to time domain FHR analysis, N=4 to frequency domain and N=4 to non-linear analysis) and normalized them with respect to the gestational week. We compared, through a 10-fold crossvalidation procedure, 15 data mining techniques in order to select the more reliable approach for identifying IUGR fetuses. The results of this comparison highlight that two techniques (Random Forest and Logistic Regression) show the best classification accuracy and that both outperform the best single parameter in terms of mean AUROC on the test sets.

Collecting data on potentially harmful events: a method for monitoring incidents in general practice.

PubMed

Britt, H; Miller, G C; Steven, I D; Howarth, G C; Nicholson, P A; Bhasale, A L; Norton, K J

1997-04-01

The prediction and subsequent prevention of errors, which are an integral element of human behaviour, require an understanding of their cause. The incident monitoring technique was developed in the study of aviation errors in the Second World War and has been applied more recently in the field of anaesthetics. This pilot study represents one of the first attempts to apply the incident monitoring technique in the general practice environment. A total of 297 GPs across Australia anonymously reported details of unintended events which harmed or could have harmed the patient. Reports were contemporaneously recorded on prepared forms which allowed a free text description of the incident, and structured responses for contributing and mitigating factors, immediate and long-term out-comes, additional costs etc. The first 500 reports were analysed using both of qualitative and quantitative methods and a brief overview of results is presented. The methodological issues arising in the application of this technique to such a large, widely spread profession, in which episodes of care are not necessarily confined to a single consultation, are discussed. This study demonstrated that the incident monitoring technique can be successfully applied in general practice and that the resulting information can facilitate the identification of common factors contributing to such events and allow the development of preventive interventions.

Color enhancement of landsat agricultural imagery: JPL LACIE image processing support task

NASA Technical Reports Server (NTRS)

Madura, D. P.; Soha, J. M.; Green, W. B.; Wherry, D. B.; Lewis, S. D.

1978-01-01

Color enhancement techniques were applied to LACIE LANDSAT segments to determine if such enhancement can assist analysis in crop identification. The procedure involved increasing the color range by removing correlation between components. First, a principal component transformation was performed, followed by contrast enhancement to equalize component variances, followed by an inverse transformation to restore familiar color relationships. Filtering was applied to lower order components to reduce color speckle in the enhanced products. Use of single acquisition and multiple acquisition statistics to control the enhancement were compared, and the effects of normalization investigated. Evaluation is left to LACIE personnel.

Dereplication of Natural Products Using GC-TOF Mass Spectrometry: Improved Metabolite Identification by Spectral Deconvolution Ratio Analysis.

PubMed

Carnevale Neto, Fausto; Pilon, Alan C; Selegato, Denise M; Freire, Rafael T; Gu, Haiwei; Raftery, Daniel; Lopes, Norberto P; Castro-Gamboa, Ian

2016-01-01

Dereplication based on hyphenated techniques has been extensively applied in plant metabolomics, thereby avoiding re-isolation of known natural products. However, due to the complex nature of biological samples and their large concentration range, dereplication requires the use of chemometric tools to comprehensively extract information from the acquired data. In this work we developed a reliable GC-MS-based method for the identification of non-targeted plant metabolites by combining the Ratio Analysis of Mass Spectrometry deconvolution tool (RAMSY) with Automated Mass Spectral Deconvolution and Identification System software (AMDIS). Plants species from Solanaceae, Chrysobalanaceae and Euphorbiaceae were selected as model systems due to their molecular diversity, ethnopharmacological potential, and economical value. The samples were analyzed by GC-MS after methoximation and silylation reactions. Dereplication was initiated with the use of a factorial design of experiments to determine the best AMDIS configuration for each sample, considering linear retention indices and mass spectral data. A heuristic factor (CDF, compound detection factor) was developed and applied to the AMDIS results in order to decrease the false-positive rates. Despite the enhancement in deconvolution and peak identification, the empirical AMDIS method was not able to fully deconvolute all GC-peaks, leading to low MF values and/or missing metabolites. RAMSY was applied as a complementary deconvolution method to AMDIS to peaks exhibiting substantial overlap, resulting in recovery of low-intensity co-eluted ions. The results from this combination of optimized AMDIS with RAMSY attested to the ability of this approach as an improved dereplication method for complex biological samples such as plant extracts.

Dereplication of Natural Products Using GC-TOF Mass Spectrometry: Improved Metabolite Identification by Spectral Deconvolution Ratio Analysis

PubMed Central

Carnevale Neto, Fausto; Pilon, Alan C.; Selegato, Denise M.; Freire, Rafael T.; Gu, Haiwei; Raftery, Daniel; Lopes, Norberto P.; Castro-Gamboa, Ian

2016-01-01

Dereplication based on hyphenated techniques has been extensively applied in plant metabolomics, thereby avoiding re-isolation of known natural products. However, due to the complex nature of biological samples and their large concentration range, dereplication requires the use of chemometric tools to comprehensively extract information from the acquired data. In this work we developed a reliable GC-MS-based method for the identification of non-targeted plant metabolites by combining the Ratio Analysis of Mass Spectrometry deconvolution tool (RAMSY) with Automated Mass Spectral Deconvolution and Identification System software (AMDIS). Plants species from Solanaceae, Chrysobalanaceae and Euphorbiaceae were selected as model systems due to their molecular diversity, ethnopharmacological potential, and economical value. The samples were analyzed by GC-MS after methoximation and silylation reactions. Dereplication was initiated with the use of a factorial design of experiments to determine the best AMDIS configuration for each sample, considering linear retention indices and mass spectral data. A heuristic factor (CDF, compound detection factor) was developed and applied to the AMDIS results in order to decrease the false-positive rates. Despite the enhancement in deconvolution and peak identification, the empirical AMDIS method was not able to fully deconvolute all GC-peaks, leading to low MF values and/or missing metabolites. RAMSY was applied as a complementary deconvolution method to AMDIS to peaks exhibiting substantial overlap, resulting in recovery of low-intensity co-eluted ions. The results from this combination of optimized AMDIS with RAMSY attested to the ability of this approach as an improved dereplication method for complex biological samples such as plant extracts. PMID:27747213

Decoupling Identification for Serial Two-Link Two-Inertia System

NASA Astrophysics Data System (ADS)

Oaki, Junji; Adachi, Shuichi

The purpose of our study is to develop a precise model by applying the technique of system identification for the model-based control of a nonlinear robot arm, under taking joint-elasticity into consideration. We previously proposed a systematic identification method, called “decoupling identification,” for a “SCARA-type” planar two-link robot arm with elastic joints caused by the Harmonic-drive® reduction gears. The proposed method serves as an extension of the conventional rigid-joint-model-based identification. The robot arm is treated as a serial two-link two-inertia system with nonlinearity. The decoupling identification method using link-accelerometer signals enables the serial two-link two-inertia system to be divided into two linear one-link two-inertia systems. The MATLAB®'s commands for state-space model estimation are utilized in the proposed method. Physical parameters such as motor inertias, link inertias, joint-friction coefficients, and joint-spring coefficients are estimated through the identified one-link two-inertia systems using a gray-box approach. This paper describes accuracy evaluations using the two-link arm for the decoupling identification method under introducing closed-loop-controlled elements and varying amplitude-setup of identification-input. Experimental results show that the identification method also works with closed-loop-controlled elements. Therefore, the identification method is applicable to a “PUMA-type” vertical robot arm under gravity.

Monitoring fatigue damage in carbon fiber composites using an acoustic impact technique

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

Haque, A.; Raju, P.K.

1998-06-01

The acoustic impact technique (AIT) of nondestructive testing (NDT) has been used to identify the damage that results from the compressive and tension-compression cycle loading around a circular notch of quasiisotropic carbon-fiber composites. This method involves applying a low velocity impact to the test specimen and evaluating the resulting localized acoustic response. Results indicate that AIT can be applied for identification of both compressive and fatigue damage in composite laminates. The gross area of compressive and fatigue damage is detected through an increase in the pulse width, and a decrease in the amplitude, of the force-time signal. The response obtainedmore » in AIT is sensitive to the frequency of the impactor and the amplitude of the impact force and requires careful monitoring of these values to achieve repeatability of results.« less

An iris recognition algorithm based on DCT and GLCM

NASA Astrophysics Data System (ADS)

Feng, G.; Wu, Ye-qing

2008-04-01

With the enlargement of mankind's activity range, the significance for person's status identity is becoming more and more important. So many different techniques for person's status identity were proposed for this practical usage. Conventional person's status identity methods like password and identification card are not always reliable. A wide variety of biometrics has been developed for this challenge. Among those biologic characteristics, iris pattern gains increasing attention for its stability, reliability, uniqueness, noninvasiveness and difficult to counterfeit. The distinct merits of the iris lead to its high reliability for personal identification. So the iris identification technique had become hot research point in the past several years. This paper presents an efficient algorithm for iris recognition using gray-level co-occurrence matrix(GLCM) and Discrete Cosine transform(DCT). To obtain more representative iris features, features from space and DCT transformation domain are extracted. Both GLCM and DCT are applied on the iris image to form the feature sequence in this paper. The combination of GLCM and DCT makes the iris feature more distinct. Upon GLCM and DCT the eigenvector of iris extracted, which reflects features of spatial transformation and frequency transformation. Experimental results show that the algorithm is effective and feasible with iris recognition.

Damage detection and quantification in a structural model under seismic excitation using time-frequency analysis

NASA Astrophysics Data System (ADS)

Chan, Chun-Kai; Loh, Chin-Hsiung; Wu, Tzu-Hsiu

2015-04-01

In civil engineering, health monitoring and damage detection are typically carry out by using a large amount of sensors. Typically, most methods require global measurements to extract the properties of the structure. However, some sensors, like LVDT, cannot be used due to in situ limitation so that the global deformation remains unknown. An experiment is used to demonstrate the proposed algorithms: a one-story 2-bay reinforce concrete frame under weak and strong seismic excitation. In this paper signal processing techniques and nonlinear identification are used and applied to the response measurements of seismic response of reinforced concrete structures subject to different level of earthquake excitations. Both modal-based and signal-based system identification and feature extraction techniques are used to study the nonlinear inelastic response of RC frame using both input and output response data or output only measurement. From the signal-based damage identification method, which include the enhancement of time-frequency analysis of acceleration responses and the estimation of permanent deformation using directly from acceleration response data. Finally, local deformation measurement from dense optical tractor is also use to quantify the damage of the RC frame structure.

Using a tracer technique to identify the extent of non-ideal flows in the continuous mixing of non-Newtonian fluids

NASA Astrophysics Data System (ADS)

Patel, D.; Ein-Mozaffari, F.; Mehrvar, M.

2013-05-01

The identification of non-ideal flows in a continuous-flow mixing of non-Newtonian fluids is a challenging task for various chemical industries: plastic manufacturing, water and wastewater treatment, and pulp and paper manufacturing. Non-ideal flows such as channelling, recirculation, and dead zones significantly affect the performance of continuous-flow mixing systems. Therefore, the main objective of this paper was to develop an identification protocol to measure non-ideal flows in the continuous-flow mixing system. The extent of non-ideal flows was quantified using a dynamic model that incorporated channelling, recirculation, and dead volume in the mixing vessel. To estimate the dynamic model parameters, the system was excited using a frequency-modulated random binary input by injecting the saline solution (as a tracer) into the fresh feed stream prior to being pumped into the mixing vessel. The injection of the tracer was controlled by a computer-controlled on-off solenoid valve. Using the trace technique, the extent of channelling and the effective mixed volume were successfully determined and used as mixing quality criteria. Such identification procedures can be applied at various areas of chemical engineering in order to improve the mixing quality.

Towards the identification of Idiopathic Parkinson’s Disease from the speech. New articulatory kinetic biomarkers

PubMed Central

Shattuck-Hufnagel, S.; Choi, J. Y.; Moro-Velázquez, L.; Gómez-García, J. A.

2017-01-01

Although a large amount of acoustic indicators have already been proposed in the literature to evaluate the hypokinetic dysarthria of people with Parkinson’s Disease, the goal of this work is to identify and interpret new reliable and complementary articulatory biomarkers that could be applied to predict/evaluate Parkinson’s Disease from a diadochokinetic test, contributing to the possibility of a further multidimensional analysis of the speech of parkinsonian patients. The new biomarkers proposed are based on the kinetic behaviour of the envelope trace, which is directly linked with the articulatory dysfunctions introduced by the disease since the early stages. The interest of these new articulatory indicators stands on their easiness of identification and interpretation, and their potential to be translated into computer based automatic methods to screen the disease from the speech. Throughout this paper, the accuracy provided by these acoustic kinetic biomarkers is compared with the one obtained with a baseline system based on speaker identification techniques. Results show accuracies around 85% that are in line with those obtained with the complex state of the art speaker recognition techniques, but with an easier physical interpretation, which open the possibility to be transferred to a clinical setting. PMID:29240814

The effects of AVIRIS atmospheric calibration methodology on identification and quantitative mapping of surface mineralogy, Drum Mountains, Utah

NASA Technical Reports Server (NTRS)

Kruse, Fred A.; Dwyer, John L.

1993-01-01

The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) measures reflected light in 224 contiguous spectra bands in the 0.4 to 2.45 micron region of the electromagnetic spectrum. Numerous studies have used these data for mineralogic identification and mapping based on the presence of diagnostic spectral features. Quantitative mapping requires conversion of the AVIRIS data to physical units (usually reflectance) so that analysis results can be compared and validated with field and laboratory measurements. This study evaluated two different AVIRIS calibration techniques to ground reflectance: an empirically-based method and an atmospheric model based method to determine their effects on quantitative scientific analyses. Expert system analysis and linear spectral unmixing were applied to both calibrated data sets to determine the effect of the calibration on the mineral identification and quantitative mapping results. Comparison of the image-map results and image reflectance spectra indicate that the model-based calibrated data can be used with automated mapping techniques to produce accurate maps showing the spatial distribution and abundance of surface mineralogy. This has positive implications for future operational mapping using AVIRIS or similar imaging spectrometer data sets without requiring a priori knowledge.

Applying face identification to detecting hijacking of airplane

NASA Astrophysics Data System (ADS)

Luo, Xuanwen; Cheng, Qiang

2004-09-01

That terrorists hijacked the airplanes and crashed the World Trade Center is disaster to civilization. To avoid the happening of hijack is critical to homeland security. To report the hijacking in time, limit the terrorist to operate the plane if happened and land the plane to the nearest airport could be an efficient way to avoid the misery. Image processing technique in human face recognition or identification could be used for this task. Before the plane take off, the face images of pilots are input into a face identification system installed in the airplane. The camera in front of pilot seat keeps taking the pilot face image during the flight and comparing it with pre-input pilot face images. If a different face is detected, a warning signal is sent to ground automatically. At the same time, the automatic cruise system is started or the plane is controlled by the ground. The terrorists will have no control over the plane. The plane will be landed to a nearest or appropriate airport under the control of the ground or cruise system. This technique could also be used in automobile industry as an image key to avoid car stealth.

Parametric output-only identification of time-varying structures using a kernel recursive extended least squares TARMA approach

NASA Astrophysics Data System (ADS)

Ma, Zhi-Sai; Liu, Li; Zhou, Si-Da; Yu, Lei; Naets, Frank; Heylen, Ward; Desmet, Wim

2018-01-01

The problem of parametric output-only identification of time-varying structures in a recursive manner is considered. A kernelized time-dependent autoregressive moving average (TARMA) model is proposed by expanding the time-varying model parameters onto the basis set of kernel functions in a reproducing kernel Hilbert space. An exponentially weighted kernel recursive extended least squares TARMA identification scheme is proposed, and a sliding-window technique is subsequently applied to fix the computational complexity for each consecutive update, allowing the method to operate online in time-varying environments. The proposed sliding-window exponentially weighted kernel recursive extended least squares TARMA method is employed for the identification of a laboratory time-varying structure consisting of a simply supported beam and a moving mass sliding on it. The proposed method is comparatively assessed against an existing recursive pseudo-linear regression TARMA method via Monte Carlo experiments and shown to be capable of accurately tracking the time-varying dynamics. Furthermore, the comparisons demonstrate the superior achievable accuracy, lower computational complexity and enhanced online identification capability of the proposed kernel recursive extended least squares TARMA approach.

Moment Method and Pixel-by-Pixel Method: Complementary Mode Identification I. Testing FG Vir-like pulsation modes

NASA Astrophysics Data System (ADS)

Zima, W.; Kolenberg, K.; Briquet, M.; Breger, M.

2004-06-01

We have carried out a Hare-and-Hound test to determine the reliability of the Moment Method (Briquet & Aerts 2003) and the Pixel-by-Pixel Method (Mantegazza 2000) for the identification of pulsation modes in Delta Scuti stars. For this purpose we calculated synthetic line profiles, exhibiting six pulsation modes of low degree and with input parameters initially unknown to us. The aim was to test and increase the quality of the mode identification by applying both methods independently and by using a combined technique. Our results show that, whereas the azimuthal order m and its sign can be fixed by both methods, the degree l is not determined unambiguously. Both identification methods show a better reliability if multiple modes are fitted simultaneously. In particular, the inclination angle is better determined. We have to emphasize that the outcome of this test is only meaningful for stars having pulsational velocities below 0.2 vsini. This is the first part of a series of articles, in which we will test these spectroscopic identification methods.

Methods and Apparatus for Reducing Multipath Signal Error Using Deconvolution

NASA Technical Reports Server (NTRS)

Kumar, Rajendra (Inventor); Lau, Kenneth H. (Inventor)

1999-01-01

A deconvolution approach to adaptive signal processing has been applied to the elimination of signal multipath errors as embodied in one preferred embodiment in a global positioning system receiver. The method and receiver of the present invention estimates then compensates for multipath effects in a comprehensive manner. Application of deconvolution, along with other adaptive identification and estimation techniques, results in completely novel GPS (Global Positioning System) receiver architecture.

Force Enhancement Packages for Countering Nuclear Threats in the 2022-2027 Time Frame

DTIC Science & Technology

2015-09-01

characterization methods . • Apply proper radioisotope identification techniques. c. A one-week CNT operations exercise at Fort Belvoir, Virginia. Team members...on experiments to seek better methods , holding active teaching until later. The team expects that better methods would involve collection using...conduct more effective wide-area searches than those commonly employed by civil law enforcement agencies. The IDA team suggests that better methods

How (not) to protect genomic data privacy in a distributed network: using trail re-identification to evaluate and design anonymity protection systems.

PubMed

Malin, Bradley; Sweeney, Latanya

2004-06-01

The increasing integration of patient-specific genomic data into clinical practice and research raises serious privacy concerns. Various systems have been proposed that protect privacy by removing or encrypting explicitly identifying information, such as name or social security number, into pseudonyms. Though these systems claim to protect identity from being disclosed, they lack formal proofs. In this paper, we study the erosion of privacy when genomic data, either pseudonymous or data believed to be anonymous, are released into a distributed healthcare environment. Several algorithms are introduced, collectively called RE-Identification of Data In Trails (REIDIT), which link genomic data to named individuals in publicly available records by leveraging unique features in patient-location visit patterns. Algorithmic proofs of re-identification are developed and we demonstrate, with experiments on real-world data, that susceptibility to re-identification is neither trivial nor the result of bizarre isolated occurrences. We propose that such techniques can be applied as system tests of privacy protection capabilities.

Real-time radionuclide identification in γ-emitter mixtures based on spiking neural network.

PubMed

Bobin, C; Bichler, O; Lourenço, V; Thiam, C; Thévenin, M

2016-03-01

Portal radiation monitors dedicated to the prevention of illegal traffic of nuclear materials at international borders need to deliver as fast as possible a radionuclide identification of a potential radiological threat. Spectrometry techniques applied to identify the radionuclides contributing to γ-emitter mixtures are usually performed using off-line spectrum analysis. As an alternative to these usual methods, a real-time processing based on an artificial neural network and Bayes' rule is proposed for fast radionuclide identification. The validation of this real-time approach was carried out using γ-emitter spectra ((241)Am, (133)Ba, (207)Bi, (60)Co, (137)Cs) obtained with a high-efficiency well-type NaI(Tl). The first tests showed that the proposed algorithm enables a fast identification of each γ-emitting radionuclide using the information given by the whole spectrum. Based on an iterative process, the on-line analysis only needs low-statistics spectra without energy calibration to identify the nature of a radiological threat. Copyright © 2015 Elsevier Ltd. All rights reserved.

LC-MS screening techniques for wastewater analysis and analytical data handling strategies: Sartans and their transformation products as an example.

PubMed

Letzel, Thomas; Bayer, Anne; Schulz, Wolfgang; Heermann, Alexandra; Lucke, Thomas; Greco, Giorgia; Grosse, Sylvia; Schüssler, Walter; Sengl, Manfred; Letzel, Marion

2015-10-01

A large number of anthropogenic trace contaminants such as pharmaceuticals, their human metabolites and further transformation products (TPs) enter wastewater treatment plants on a daily basis. A mixture of known, expected, and unknown molecules are discharged into the receiving aquatic environment because only partial elimination occurs for many of these chemicals during physical, biological and chemical treatment processes. In this study, an array of LC-MS methods from three collaborating laboratories was applied to detect and identify anthropogenic trace contaminants and their TPs in different waters. Starting with theoretical predictions of TPs, an efficient workflow using the combination of target, suspected-target and non-target strategies for the identification of these TPs in the environment was developed. These techniques and strategies were applied to study anti-hypertensive drugs from the sartan group (i.e., candesartan, eprosartan, irbesartan, olmesartan, and valsartan). Degradation experiments were performed in lab-scale wastewater treatment plants, and a screening workflow including an inter-laboratory approach was used for the identification of transformation products in the effluent samples. Subsequently, newly identified compounds were successfully analyzed in effluents of real wastewater treatment plants and river waters. Copyright © 2015 Elsevier Ltd. All rights reserved.

Application of Raman spectroscopy for direct analysis of Carlina acanthifolia subsp. utzka root essential oil.

PubMed

Strzemski, Maciej; Wójciak-Kosior, Magdalena; Sowa, Ireneusz; Agacka-Mołdoch, Monika; Drączkowski, Piotr; Matosiuk, Dariusz; Kurach, Łukasz; Kocjan, Ryszard; Dresler, Sławomir

2017-11-01

Carlina genus plants e.g. Carlina acanthifolia subsp. utzka have been still used in folk medicine of many European countries and its biological activity is mostly associated with root essential oils. In the present paper, Raman spectroscopy (RS) was applied for the first time for evaluation of essential oil distribution in root of C. acnthifolia subsp. utzka and identification of root structures containing the essential oil. Furthermore, RS technique was applied to assess chemical stability of oil during drying of plant material or distillation process. Gas chromatography-mass spectrometry was used for qualitative and quantitative analysis of the essential oil. The identity of compounds was confirmed using Raman, ATR-IR and NMR spectroscopy. Carlina oxide was found to be the main component of the oil (98.96% ± 0.15). The spectroscopic study showed the high stability of essential oil and Raman distribution analysis indicated that the oil reservoirs were localized mostly in the structures of outer layer of the root while the inner part showed nearly no signal assigned to the oil. Raman spectroscopy technique enabled rapid, non-destructive direct analysis of plant material with minimal sample preparation and allowed straightforward, unambiguous identification of the essential oil in the sample. Copyright © 2017. Published by Elsevier B.V.

A facial reconstruction and identification technique for seriously devastating head wounds.

PubMed

Joukal, Marek; Frišhons, Jan

2015-07-01

Many authors have focused on facial identification techniques, and facial reconstructions for cases when skulls have been found are especially well known. However, a standardized facial identification technique for an unknown body with seriously devastating head injuries has not yet been developed. A reconstruction and identification technique was used in 7 cases of accidents involving trains striking pedestrians. This identification technique is based on the removal of skull bone fragments, subsequent fixation of soft tissue onto a universal commercial polystyrene head model, precise suture of dermatomuscular flaps, and definitive adjustment using cosmetic treatments. After reconstruction, identifying marks such as scars, eyebrows, facial lines, facial hair and partly hairstyle become evident. It is then possible to present a modified picture of the reconstructed face to relatives. After comparing the results with photos of the person before death, this technique has proven to be very useful for identifying unknown bodies when other identification techniques are not available. This technique is useful for its being rather quick and especially for its results. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Direct Identification of Dilute Surface Spins on Al2 O3 : Origin of Flux Noise in Quantum Circuits

NASA Astrophysics Data System (ADS)

de Graaf, S. E.; Adamyan, A. A.; Lindström, T.; Erts, D.; Kubatkin, S. E.; Tzalenchuk, A. Ya.; Danilov, A. V.

2017-02-01

An on-chip electron spin resonance technique is applied to reveal the nature and origin of surface spins on Al2 O3 . We measure a spin density of 2.2 ×1 017 spins/m2 , attributed to physisorbed atomic hydrogen and S =1 /2 electron spin states on the surface. This is direct evidence for the nature of spins responsible for flux noise in quantum circuits, which has been an issue of interest for several decades. Our findings open up a new approach to the identification and controlled reduction of paramagnetic sources of noise and decoherence in superconducting quantum devices.

Intergration of system identification and robust controller designs for flexible structures in space

NASA Technical Reports Server (NTRS)

Juang, Jer-Nan; Lew, Jiann-Shiun

1990-01-01

An approach is developed using experimental data to identify a reduced-order model and its model error for a robust controller design. There are three steps involved in the approach. First, an approximately balanced model is identified using the Eigensystem Realization Algorithm, which is an identification algorithm. Second, the model error is calculated and described in frequency domain in terms of the H(infinity) norm. Third, a pole placement technique in combination with a H(infinity) control method is applied to design a controller for the considered system. A set experimental data from an existing setup, namely the Mini-Mast system, is used to illustrate and verify the approach.

Identification of superficial defects in reconstructed 3D objects using phase-shifting fringe projection

NASA Astrophysics Data System (ADS)

Madrigal, Carlos A.; Restrepo, Alejandro; Branch, John W.

2016-09-01

3D reconstruction of small objects is used in applications of surface analysis, forensic analysis and tissue reconstruction in medicine. In this paper, we propose a strategy for the 3D reconstruction of small objects and the identification of some superficial defects. We applied a technique of projection of structured light patterns, specifically sinusoidal fringes and an algorithm of phase unwrapping. A CMOS camera was used to capture images and a DLP digital light projector for synchronous projection of the sinusoidal pattern onto the objects. We implemented a technique based on a 2D flat pattern as calibration process, so the intrinsic and extrinsic parameters of the camera and the DLP were defined. Experimental tests were performed in samples of artificial teeth, coal particles, welding defects and surfaces tested with Vickers indentation. Areas less than 5cm were studied. The objects were reconstructed in 3D with densities of about one million points per sample. In addition, the steps of 3D description, identification of primitive, training and classification were implemented to recognize defects, such as: holes, cracks, roughness textures and bumps. We found that pattern recognition strategies are useful, when quality supervision of surfaces has enough quantities of points to evaluate the defective region, because the identification of defects in small objects is a demanding activity of the visual inspection.

Characterization and identification of microorganisms by FT-IR microspectrometry

NASA Astrophysics Data System (ADS)

Ngo-Thi, N. A.; Kirschner, C.; Naumann, D.

2003-12-01

We report on a novel FT-IR approach for microbial characterization/identification based on a light microscope coupled to an infrared spectrometer which offers the possibility to acquire IR-spectra of microcolonies containing only few hundred cells. Microcolony samples suitable for FT-IR microspectroscopic measurements were obtained by a replica technique with a stamping device that transfers spatially accurate cells of microcolonies growing on solid culture plates to a special, IR-transparent or reflecting stamping plate. High quality spectra could be recorded either by applying the transmission/absorbance or the reflectance/absorbance mode of the infrared microscope. Signal to noise ratios higher than 1000 were obtained for microcolonies as small as 40 μm in diameter. Reproducibility levels were established that allowed species and strain identification. The differentiation and classification capacity of the FT-IR microscopic technique was tested for different selected microorganisms. Cluster and factor analysis methods were used to evaluate the complex spectral data. Excellent discrimination between bacteria and yeasts, and at the same time Gram-negative and Gram-positive bacterial strains was obtained. Twenty-two selected strains of different species within the genus Staphylococcus were repetitively measured and could be grouped into correct species cluster. Moreover, the results indicated that the method allows also identifications at the subspecies level. Additionally, the new approach allowed spectral mapping analysis of single colonies which provided spatially resolved characterization of growth heterogeneity within complex microbial populations such as colonies.

Identification of exhumed remains of fire tragedy victims using conventional methods and autosomal/Y-chromosomal short tandem repeat DNA profiling.

PubMed

Calacal, Gayvelline C; Delfin, Frederick C; Tan, Michelle Music M; Roewer, Lutz; Magtanong, Danilo L; Lara, Myra C; Fortun, Raquel dR; De Ungria, Maria Corazon A

2005-09-01

In a fire tragedy in Manila in December 1998, one of the worst tragic incidents which resulted in the reported death of 23 children, identity could not be established initially resulting in the burial of still unidentified bodies. Underscoring the importance of identifying each of the human remains, the bodies were exhumed 3 months after the tragedy. We describe here our work, which was the first national case handled by local laboratories wherein conventional and molecular-based techniques were successfully applied in forensic identification. The study reports analysis of DNA obtained from skeletal remains exposed to conditions of burning, burial, and exhumation. DNA typing methods using autosomal and Y-chromosomal short tandem repeat (Y-STR) markers reinforced postmortem examinations using conventional identification techniques. The strategy resulted in the identification of 18 out of the 21 human remains analyzed, overcoming challenges encountered due to the absence of established procedures for the recovery of mass disaster remains. There was incomplete antemortem information to match the postmortem data obtained from the remains of 3 female child victims. Two victims were readily identified due to the availability of antemortem tissues. In the absence of this biologic material, parentage testing was performed using reference blood samples collected from parents and relatives. Data on patrilineal lineage based on common Y-STR haplotypes augmented autosomal DNA typing, particularly in deficiency cases.

Multisource information fusion applied to ship identification for the recognized maritime picture

NASA Astrophysics Data System (ADS)

Simard, Marc-Alain; Lefebvre, Eric; Helleur, Christopher

2000-04-01

The Recognized Maritime Picture (RMP) is defined as a composite picture of activity over a maritime area of interest. In simplistic terms, building an RAMP comes down to finding if an object of interest, a ship in our case, is there or not, determining what it is, determining what it is doing and determining if some type of follow-on action is required. The Canadian Department of National Defence currently has access to or may, in the near future, have access to a number of civilians, military and allied information or sensor systems to accomplish these purposes. These systems include automatic self-reporting positional systems, air patrol surveillance systems, high frequency surface radars, electronic intelligence systems, radar space systems and high frequency direction finding sensors. The ability to make full use of these systems is limited by the existing capability to fuse data from all sources in a timely, accurate and complete manner. This paper presents an information fusion systems under development that correlates and fuses these information and sensor data sources. This fusion system, named Adaptive Fuzzy Logic Correlator, correlates the information in batch but fuses and constructs ship tracks sequentially. It applies standard Kalman filter techniques and fuzzy logic correlation techniques. We propose a set of recommendations that should improve the ship identification process. Particularly it is proposed to utilize as many non-redundant sources of information as possible that address specific vessel attributes. Another important recommendation states that the information fusion and data association techniques should be capable of dealing with incomplete and imprecise information. Some fuzzy logic techniques capable of tolerating imprecise and dissimilar data are proposed.

Inverse analysis of aerodynamic loads from strain information using structural models and neural networks

NASA Astrophysics Data System (ADS)

Wada, Daichi; Sugimoto, Yohei

2017-04-01

Aerodynamic loads on aircraft wings are one of the key parameters to be monitored for reliable and effective aircraft operations and management. Flight data of the aerodynamic loads would be used onboard to control the aircraft and accumulated data would be used for the condition-based maintenance and the feedback for the fatigue and critical load modeling. The effective sensing techniques such as fiber optic distributed sensing have been developed and demonstrated promising capability of monitoring structural responses, i.e., strains on the surface of the aircraft wings. By using the developed techniques, load identification methods for structural health monitoring are expected to be established. The typical inverse analysis for load identification using strains calculates the loads in a discrete form of concentrated forces, however, the distributed form of the loads is essential for the accurate and reliable estimation of the critical stress at structural parts. In this study, we demonstrate an inverse analysis to identify the distributed loads from measured strain information. The introduced inverse analysis technique calculates aerodynamic loads not in a discrete but in a distributed manner based on a finite element model. In order to verify the technique through numerical simulations, we apply static aerodynamic loads on a flat panel model, and conduct the inverse identification of the load distributions. We take two approaches to build the inverse system between loads and strains. The first one uses structural models and the second one uses neural networks. We compare the performance of the two approaches, and discuss the effect of the amount of the strain sensing information.

Intelligent identification of remnant ridge edges in region west of Yongxing Island, South China Sea

NASA Astrophysics Data System (ADS)

Wang, Weiwei; Guo, Jing; Cai, Guanqiang; Wang, Dawei

2018-02-01

Edge detection enables identification of geomorphologic unit boundaries and thus assists with geomorphical mapping. In this paper, an intelligent edge identification method is proposed and image processing techniques are applied to multi-beam bathymetry data. To accomplish this, a color image is generated by the bathymetry, and a weighted method is used to convert the color image to a gray image. As the quality of the image has a significant influence on edge detection, different filter methods are applied to the gray image for de-noising. The peak signal-to-noise ratio and mean square error are calculated to evaluate which filter method is most appropriate for depth image filtering and the edge is subsequently detected using an image binarization method. Traditional image binarization methods cannot manage the complicated uneven seafloor, and therefore a binarization method is proposed that is based on the difference between image pixel values; the appropriate threshold for image binarization is estimated according to the probability distribution of pixel value differences between two adjacent pixels in horizontal and vertical directions, respectively. Finally, an eight-neighborhood frame is adopted to thin the binary image, connect the intermittent edge, and implement contour extraction. Experimental results show that the method described here can recognize the main boundaries of geomorphologic units. In addition, the proposed automatic edge identification method avoids use of subjective judgment, and reduces time and labor costs.

Applications of liquid-based separation in conjunction with mass spectrometry to the analysis of forensic evidence.

PubMed

Moini, Mehdi

2018-05-01

In the past few years, there has been a significant effort by the forensic science community to develop new scientific techniques for the analysis of forensic evidence. Forensic chemists have been spearheaded to develop information-rich confirmatory technologies and techniques and apply them to a broad array of forensic challenges. The purpose of these confirmatory techniques is to provide alternatives to presumptive techniques that rely on data such as color changes, pattern matching, or retention time alone, which are prone to more false positives. To this end, the application of separation techniques in conjunction with mass spectrometry has played an important role in the analysis of forensic evidence. Moreover, in the past few years the role of liquid separation techniques, such as liquid chromatography and capillary electrophoresis in conjunction with mass spectrometry, has gained significant tractions and have been applied to a wide range of chemicals, from small molecules such as drugs and explosives, to large molecules such as proteins. For example, proteomics and peptidomics have been used for identification of humans, organs, and bodily fluids. A wide range of HPLC techniques including reversed phase, hydrophilic interaction, mixed-mode, supercritical fluid, multidimensional chromatography, and nanoLC, as well as several modes of capillary electrophoresis mass spectrometry, including capillary zone electrophoresis, partial filling, full filling, and micellar electrokenetic chromatography have been applied to the analysis drugs, explosives, and questioned documents. In this article, we review recent (2015-2017) applications of liquid separation in conjunction with mass spectrometry to the analysis of forensic evidence. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

IDENTIFICATION OF MEMBERS IN THE CENTRAL AND OUTER REGIONS OF GALAXY CLUSTERS

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

Serra, Ana Laura; Diaferio, Antonaldo, E-mail: serra@ph.unito.it

2013-05-10

The caustic technique measures the mass of galaxy clusters in both their virial and infall regions and, as a byproduct, yields the list of cluster galaxy members. Here we use 100 galaxy clusters with mass M{sub 200} {>=} 10{sup 14} h {sup -1} M{sub Sun} extracted from a cosmological N-body simulation of a {Lambda}CDM universe to test the ability of the caustic technique to identify the cluster galaxy members. We identify the true three-dimensional members as the gravitationally bound galaxies. The caustic technique uses the caustic location in the redshift diagram to separate the cluster members from the interlopers. Wemore » apply the technique to mock catalogs containing 1000 galaxies in the field of view of 12 h {sup -1} Mpc on a side at the cluster location. On average, this sample size roughly corresponds to 180 real galaxy members within 3r{sub 200}, similar to recent redshift surveys of cluster regions. The caustic technique yields a completeness, the fraction of identified true members, f{sub c} = 0.95 {+-} 0.03, within 3r{sub 200}. The contamination, the fraction of interlopers in the observed catalog of members, increases from f{sub i}=0.020{sup +0.046}{sub -0.015} at r{sub 200} to f{sub i}=0.08{sup +0.11}{sub -0.05} at 3r{sub 200}. No other technique for the identification of the members of a galaxy cluster provides such large completeness and small contamination at these large radii. The caustic technique assumes spherical symmetry and the asphericity of the cluster is responsible for most of the spread of the completeness and the contamination. By applying the technique to an approximately spherical system obtained by stacking the individual clusters, the spreads decrease by at least a factor of two. We finally estimate the cluster mass within 3r{sub 200} after removing the interlopers: for individual clusters, the mass estimated with the virial theorem is unbiased and within 30% of the actual mass; this spread decreases to less than 10% for the spherically symmetric stacked cluster.« less

Remote photoacoustic detection of liquid contamination of a surface.

PubMed

Perrett, Brian; Harris, Michael; Pearson, Guy N; Willetts, David V; Pitter, Mark C

2003-08-20

A method for the remote detection and identification of liquid chemicals at ranges of tens of meters is presented. The technique uses pulsed indirect photoacoustic spectroscopy in the 10-microm wavelength region. Enhanced sensitivity is brought about by three main system developments: (1) increased laser-pulse energy (150 microJ/pulse), leading to increased strength of the generated photoacoustic signal; (2) increased microphone sensitivity and improved directionality by the use of a 60-cm-diameter parabolic dish; and (3) signal processing that allows improved discrimination of the signal from noise levels through prior knowledge of the pulse shape and pulse-repetition frequency. The practical aspects of applying the technique in a field environment are briefly examined, and possible applications of this technique are discussed.

Modelling and identification for control of gas bearings

NASA Astrophysics Data System (ADS)

Theisen, Lukas R. S.; Niemann, Hans H.; Santos, Ilmar F.; Galeazzi, Roberto; Blanke, Mogens

2016-03-01

Gas bearings are popular for their high speed capabilities, low friction and clean operation, but suffer from poor damping, which poses challenges for safe operation in presence of disturbances. Feedback control can achieve enhanced damping but requires low complexity models of the dominant dynamics over its entire operating range. Models from first principles are complex and sensitive to parameter uncertainty. This paper presents an experimental technique for "in situ" identification of a low complexity model of a rotor-bearing-actuator system and demonstrates identification over relevant ranges of rotational speed and gas injection pressure. This is obtained using parameter-varying linear models that are found to capture the dominant dynamics. The approach is shown to be easily applied and to suit subsequent control design. Based on the identified models, decentralised proportional control is designed and shown to obtain the required damping in theory and in a laboratory test rig.

Private content identification based on soft fingerprinting

NASA Astrophysics Data System (ADS)

Voloshynovskiy, Sviatoslav; Holotyak, Taras; Koval, Oleksiy; Beekhof, Fokko; Farhadzadeh, Farzad

2011-02-01

In many problems such as biometrics, multimedia search, retrieval, recommendation systems requiring privacypreserving similarity computations and identification, some binary features are stored in the public domain or outsourced to third parties that might raise certain privacy concerns about the original data. To avoid this privacy leak, privacy protection is used. In most cases, privacy protection is uniformly applied to all binary features resulting in data degradation and corresponding loss of performance. To avoid this undesirable effect we propose a new privacy amplification technique that is based on data hiding principles and benefits from side information about bit reliability a.k.a. soft fingerprinting. In this paper, we investigate the identification-rate vs privacy-leak trade-off. The analysis is performed for the case of a perfect match between side information shared between the encoder and decoder as well as for the case of partial side information.

Aircraft applications of fault detection and isolation techniques

NASA Astrophysics Data System (ADS)

Marcos Esteban, Andres

In this thesis the problems of fault detection & isolation and fault tolerant systems are studied from the perspective of LTI frequency-domain, model-based techniques. Emphasis is placed on the applicability of these LTI techniques to nonlinear models, especially to aerospace systems. Two applications of Hinfinity LTI fault diagnosis are given using an open-loop (no controller) design approach: one for the longitudinal motion of a Boeing 747-100/200 aircraft, the other for a turbofan jet engine. An algorithm formalizing a robust identification approach based on model validation ideas is also given and applied to the previous jet engine. A general linear fractional transformation formulation is given in terms of the Youla and Dual Youla parameterizations for the integrated (control and diagnosis filter) approach. This formulation provides better insight into the trade-off between the control and the diagnosis objectives. It also provides the basic groundwork towards the development of nested schemes for the integrated approach. These nested structures allow iterative improvements on the control/filter Youla parameters based on successive identification of the system uncertainty (as given by the Dual Youla parameter). The thesis concludes with an application of Hinfinity LTI techniques to the integrated design for the longitudinal motion of the previous Boeing 747-100/200 model.

Acetic acid bacteria from biofilm of strawberry vinegar visualized by microscopy and detected by complementing culture-dependent and culture-independent techniques.

PubMed

Valera, Maria José; Torija, Maria Jesús; Mas, Albert; Mateo, Estibaliz

2015-04-01

Acetic acid bacteria (AAB) usually develop biofilm on the air-liquid interface of the vinegar elaborated by traditional method. This is the first study in which the AAB microbiota present in a biofilm of vinegar obtained by traditional method was detected by pyrosequencing. Direct genomic DNA extraction from biofilm was set up to obtain suitable quality of DNA to apply in culture-independent molecular techniques. The set of primers and TaqMan--MGB probe designed in this study to enumerate the total AAB population by Real Time--PCR detected between 8 × 10(5) and 1.2 × 10(6) cells/g in the biofilm. Pyrosequencing approach reached up to 10 AAB genera identification. The combination of culture-dependent and culture-independent molecular techniques provided a broader view of AAB microbiota from the strawberry biofilm, which was dominated by Ameyamaea, Gluconacetobacter, and Komagataeibacter genera. Culture-dependent techniques allowed isolating only one genotype, which was assigned into the Ameyamaea genus and which required more analysis for a correct species identification. Furthermore, biofilm visualization by laser confocal microscope and scanning electronic microscope showed different dispositions and cell morphologies in the strawberry vinegar biofilm compared with a grape vinegar biofilm. Copyright © 2014 Elsevier Ltd. All rights reserved.

Near-infrared imaging spectroscopy for counterfeit drug detection

NASA Astrophysics Data System (ADS)

Arnold, Thomas; De Biasio, Martin; Leitner, Raimund

2011-06-01

Pharmaceutical counterfeiting is a significant issue in the healthcare community as well as for the pharmaceutical industry worldwide. The use of counterfeit medicines can result in treatment failure or even death. A rapid screening technique such as near infrared (NIR) spectroscopy could aid in the search for and identification of counterfeit drugs. This work presents a comparison of two laboratory NIR imaging systems and the chemometric analysis of the acquired spectroscopic image data. The first imaging system utilizes a NIR liquid crystal tuneable filter and is designed for the investigation of stationary objects. The second imaging system utilizes a NIR imaging spectrograph and is designed for the fast analysis of moving objects on a conveyor belt. Several drugs in form of tablets and capsules were analyzed. Spectral unmixing techniques were applied to the mixed reflectance spectra to identify constituent parts of the investigated drugs. The results show that NIR spectroscopic imaging can be used for contact-less detection and identification of a variety of counterfeit drugs.

Deployment of a Smart Structural Health Monitoring System for Long-Span Arch Bridges: A Review and a Case Study

PubMed Central

Chen, Zengshun; Zhou, Xiao; Wang, Xu; Dong, Lili; Qian, Yuanhao

2017-01-01

Structural health monitoring (SHM) technology for surveillance and evaluation of existing and newly built long-span bridges has been widely developed, and the significance of the technique has been recognized by many administrative authorities. The paper reviews the recent progress of the SHM technology that has been applied to long-span bridges. The deployment of a SHM system is introduced. Subsequently, the data analysis and condition assessment including techniques on modal identification, methods on signal processing, and damage identification were reviewed and summarized. A case study about a SHM system of a long-span arch bridge (the Jiubao bridge in China) was systematically incorporated in each part to advance our understanding of deployment and investigation of a SHM system for long-span arch bridges. The applications of SHM systems of long-span arch bridge were also introduced. From the illustrations, the challenges and future trends for development a SHM system were concluded. PMID:28925943

A novel universal real-time PCR system using the attached universal duplex probes for quantitative analysis of nucleic acids.

PubMed

Yang, Litao; Liang, Wanqi; Jiang, Lingxi; Li, Wenquan; Cao, Wei; Wilson, Zoe A; Zhang, Dabing

2008-06-04

Real-time PCR techniques are being widely used for nucleic acids analysis, but one limitation of current frequently employed real-time PCR is the high cost of the labeled probe for each target molecule. We describe a real-time PCR technique employing attached universal duplex probes (AUDP), which has the advantage of generating fluorescence by probe hydrolysis and strand displacement over current real-time PCR methods. AUDP involves one set of universal duplex probes in which the 5' end of the fluorescent probe (FP) and a complementary quenching probe (QP) lie in close proximity so that fluorescence can be quenched. The PCR primer pair with attached universal template (UT) and the FP are identical to the UT sequence. We have shown that the AUDP technique can be used for detecting multiple target DNA sequences in both simplex and duplex real-time PCR assays for gene expression analysis, genotype identification, and genetically modified organism (GMO) quantification with comparable sensitivity, reproducibility, and repeatability with other real-time PCR methods. The results from GMO quantification, gene expression analysis, genotype identification, and GMO quantification using AUDP real-time PCR assays indicate that the AUDP real-time PCR technique has been successfully applied in nucleic acids analysis, and the developed AUDP real-time PCR technique will offer an alternative way for nucleic acid analysis with high efficiency, reliability, and flexibility at low cost.

Convolutional neural networks applied to neutrino events in a liquid argon time projection chamber

DOE PAGES

Acciarri, R.; Adams, C.; An, R.; ...

2017-03-14

Here, we present several studies of convolutional neural networks applied to data coming from the MicroBooNE detector, a liquid argon time projection chamber (LArTPC). The algorithms studied include the classification of single particle images, the localization of single particle and neutrino interactions in an image, and the detection of a simulated neutrino event overlaid with cosmic ray backgrounds taken from real detector data. These studies demonstrate the potential of convolutional neural networks for particle identification or event detection on simulated neutrino interactions. Lastly, we also address technical issues that arise when applying this technique to data from a large LArTPCmore » at or near ground level.« less

Application of gray level mapping in computed tomographic colonography: a pilot study to compare with traditional surface rendering method for identification and differentiation of endoluminal lesions

PubMed Central

Chen, Lih-Shyang; Hsu, Ta-Wen; Chang, Shu-Han; Lin, Chih-Wen; Chen, Yu-Ruei; Hsieh, Chin-Chiang; Han, Shu-Chen; Chang, Ku-Yaw; Hou, Chun-Ju

2017-01-01

Objective: In traditional surface rendering (SR) computed tomographic endoscopy, only the shape of endoluminal lesion is depicted without gray-level information unless the volume rendering technique is used. However, volume rendering technique is relatively slow and complex in terms of computation time and parameter setting. We use computed tomographic colonography (CTC) images as examples and report a new visualization technique by three-dimensional gray level mapping (GM) to better identify and differentiate endoluminal lesions. Methods: There are 33 various endoluminal cases from 30 patients evaluated in this clinical study. These cases were segmented using gray-level threshold. The marching cube algorithm was used to detect isosurfaces in volumetric data sets. GM is applied using the surface gray level of CTC. Radiologists conducted the clinical evaluation of the SR and GM images. The Wilcoxon signed-rank test was used for data analysis. Results: Clinical evaluation confirms GM is significantly superior to SR in terms of gray-level pattern and spatial shape presentation of endoluminal cases (p < 0.01) and improves the confidence of identification and clinical classification of endoluminal lesions significantly (p < 0.01). The specificity and diagnostic accuracy of GM is significantly better than those of SR in diagnostic performance evaluation (p < 0.01). Conclusion: GM can reduce confusion in three-dimensional CTC and well correlate CTC with sectional images by the location as well as gray-level value. Hence, GM increases identification and differentiation of endoluminal lesions, and facilitates diagnostic process. Advances in knowledge: GM significantly improves the traditional SR method by providing reliable gray-level information for the surface points and is helpful in identification and differentiation of endoluminal lesions according to their shape and density. PMID:27925483

ClusterTAD: an unsupervised machine learning approach to detecting topologically associated domains of chromosomes from Hi-C data.

PubMed

Oluwadare, Oluwatosin; Cheng, Jianlin

2017-11-14

With the development of chromosomal conformation capturing techniques, particularly, the Hi-C technique, the study of the spatial conformation of a genome is becoming an important topic in bioinformatics and computational biology. The Hi-C technique can generate genome-wide chromosomal interaction (contact) data, which can be used to investigate the higher-level organization of chromosomes, such as Topologically Associated Domains (TAD), i.e., locally packed chromosome regions bounded together by intra chromosomal contacts. The identification of the TADs for a genome is useful for studying gene regulation, genomic interaction, and genome function. Here, we formulate the TAD identification problem as an unsupervised machine learning (clustering) problem, and develop a new TAD identification method called ClusterTAD. We introduce a novel method to represent chromosomal contacts as features to be used by the clustering algorithm. Our results show that ClusterTAD can accurately predict the TADs on a simulated Hi-C data. Our method is also largely complementary and consistent with existing methods on the real Hi-C datasets of two mouse cells. The validation with the chromatin immunoprecipitation (ChIP) sequencing (ChIP-Seq) data shows that the domain boundaries identified by ClusterTAD have a high enrichment of CTCF binding sites, promoter-related marks, and enhancer-related histone modifications. As ClusterTAD is based on a proven clustering approach, it opens a new avenue to apply a large array of clustering methods developed in the machine learning field to the TAD identification problem. The source code, the results, and the TADs generated for the simulated and real Hi-C datasets are available here: https://github.com/BDM-Lab/ClusterTAD .

Modal identification of structures by a novel approach based on FDD-wavelet method

NASA Astrophysics Data System (ADS)

Tarinejad, Reza; Damadipour, Majid

2014-02-01

An important application of system identification in structural dynamics is the determination of natural frequencies, mode shapes and damping ratios during operation which can then be used for calibrating numerical models. In this paper, the combination of two advanced methods of Operational Modal Analysis (OMA) called Frequency Domain Decomposition (FDD) and Continuous Wavelet Transform (CWT) based on novel cyclic averaging of correlation functions (CACF) technique are used for identification of dynamic properties. By using this technique, the autocorrelation of averaged correlation functions is used instead of original signals. Integration of FDD and CWT methods is used to overcome their deficiency and take advantage of the unique capabilities of these methods. The FDD method is able to accurately estimate the natural frequencies and mode shapes of structures in the frequency domain. On the other hand, the CWT method is in the time-frequency domain for decomposition of a signal at different frequencies and determines the damping coefficients. In this paper, a new formulation applied to the wavelet transform of the averaged correlation function of an ambient response is proposed. This application causes to accurate estimation of damping ratios from weak (noise) or strong (earthquake) vibrations and long or short duration record. For this purpose, the modified Morlet wavelet having two free parameters is used. The optimum values of these two parameters are obtained by employing a technique which minimizes the entropy of the wavelet coefficients matrix. The capabilities of the novel FDD-Wavelet method in the system identification of various dynamic systems with regular or irregular distribution of mass and stiffness are illustrated. This combined approach is superior to classic methods and yields results that agree well with the exact solutions of the numerical models.

Force Enhancement Packages for Countering Nuclear Threats in the 2022-2027 Time Frame: Final Report

DTIC Science & Technology

2015-09-01

survey, and area characterization methods . • Apply proper radioisotope identification techniques. A-10 c. A one-week CNT operations exercise at Fort...focus on experiments to seek better iv methods , holding active teaching until later. The team expects that better methods would involve collection... methods likely will involve collection by multiple ISR sensors and on-the-ground investigators, with only limited use of radiation detectors. The

Identification of Noise Sources and Design of Noise Reduction Measures for a Pneumatic Nail Gun

PubMed Central

Jayakumar, Vignesh; Zechmann, Edward

2015-01-01

An experimental-analytical procedure was implemented to reduce the operating noise level of a nail gun, a commonly found power tool in a construction site. The procedure is comprised of preliminary measurements, identification and ranking of major noise sources and application of noise controls. Preliminary measurements show that the impact noise transmitted through the structure and the exhaust related noise were found to be the first and second major contributors. Applying a noise absorbing foam on the outside of the nail gun body was found to be an effective noise reduction technique. One and two-volume small mufflers were designed and applied to the exhaust side of the nail gun which reduced not only the exhaust noise but also the impact noise. It was shown that the overall noise level could be reduced by as much as 3.5 dB, suggesting that significant noise reduction is possible in construction power tools without any significant increase of the cost. PMID:26366038

Optimization of Energy Resolution in the Digital Hadron Calorimeter using Longitudinal Weights

NASA Astrophysics Data System (ADS)

Smith, J. R.; Bilki, B.; Francis, K.; Repond, J.; Schlereth, J.; Xia, L.

2013-04-01

Physics at a future lepton collider requires unprecedented jet energy and dijet mass resolutions. Particle Flow Algorithms (PFAs) have been proposed to achieve these. PFAs measure particles in a jet individually with the detector subsystem providing the best resolution. For this to work a calorimeter system with very high granularity is required. A prototype Digital Hadron Calorimeter (the DHCAL) based on the Resistive Plate Chamber (RPC) technology with a record count of readout channels has been developed, constructed, and exposed to particle beams. In this context, we report on a technique to improve the single hadron energy resolution by applying a set of calibration weights to the individual layers of the calorimeter. This weighting procedure was applied to approximately 1 million events in the energy range up to 60 GeV and shows an improvement in the pion energy resolution. Simulated data is used to verify particle identification techniques and to compare with the data.

Hazard identification by methods of animal-based toxicology.

PubMed

Barlow, S M; Greig, J B; Bridges, J W; Carere, A; Carpy, A J M; Galli, C L; Kleiner, J; Knudsen, I; Koëter, H B W M; Levy, L S; Madsen, C; Mayer, S; Narbonne, J-F; Pfannkuch, F; Prodanchuk, M G; Smith, M R; Steinberg, P

2002-01-01

This paper is one of several prepared under the project "Food Safety In Europe: Risk Assessment of Chemicals in Food and Diet" (FOSIE), a European Commission Concerted Action Programme, organised by the International Life Sciences Institute, Europe (ILSI). The aim of the FOSIE project is to review the current state of the science of risk assessment of chemicals in food and diet, by consideration of the four stages of risk assessment, that is, hazard identification, hazard characterisation, exposure assessment and risk characterisation. The contribution of animal-based methods in toxicology to hazard identification of chemicals in food and diet is discussed. The importance of first applying existing technical and chemical knowledge to the design of safety testing programs for food chemicals is emphasised. There is consideration of the presently available and commonly used toxicity testing approaches and methodologies, including acute and repeated dose toxicity, reproductive and developmental toxicity, neurotoxicity, genotoxicity, carcinogenicity, immunotoxicity and food allergy. They are considered from the perspective of whether they are appropriate for assessing food chemicals and whether they are adequate to detect currently known or anticipated hazards from food. Gaps in knowledge and future research needs are identified; research on these could lead to improvements in the methods of hazard identification for food chemicals. The potential impact of some emerging techniques and toxicological issues on hazard identification for food chemicals, such as new measurement techniques, the use of transgenic animals, assessment of hormone balance and the possibilities for conducting studies in which common human diseases have been modelled, is also considered.

NASA standard: Trend analysis techniques

NASA Technical Reports Server (NTRS)

1990-01-01

Descriptive and analytical techniques for NASA trend analysis applications are presented in this standard. Trend analysis is applicable in all organizational elements of NASA connected with, or supporting, developmental/operational programs. This document should be consulted for any data analysis activity requiring the identification or interpretation of trends. Trend analysis is neither a precise term nor a circumscribed methodology: it generally connotes quantitative analysis of time-series data. For NASA activities, the appropriate and applicable techniques include descriptive and graphical statistics, and the fitting or modeling of data by linear, quadratic, and exponential models. Usually, but not always, the data is time-series in nature. Concepts such as autocorrelation and techniques such as Box-Jenkins time-series analysis would only rarely apply and are not included in this document. The basic ideas needed for qualitative and quantitative assessment of trends along with relevant examples are presented.

Automated identification of Monogeneans using digital image processing and K-nearest neighbour approaches.

PubMed

Yousef Kalafi, Elham; Tan, Wooi Boon; Town, Christopher; Dhillon, Sarinder Kaur

2016-12-22

Monogeneans are flatworms (Platyhelminthes) that are primarily found on gills and skin of fishes. Monogenean parasites have attachment appendages at their haptoral regions that help them to move about the body surface and feed on skin and gill debris. Haptoral attachment organs consist of sclerotized hard parts such as hooks, anchors and marginal hooks. Monogenean species are differentiated based on their haptoral bars, anchors, marginal hooks, reproductive parts' (male and female copulatory organs) morphological characters and soft anatomical parts. The complex structure of these diagnostic organs and also their overlapping in microscopic digital images are impediments for developing fully automated identification system for monogeneans (LNCS 7666:256-263, 2012), (ISDA; 457-462, 2011), (J Zoolog Syst Evol Res 52(2): 95-99. 2013;). In this study images of hard parts of the haptoral organs such as bars and anchors are used to develop a fully automated identification technique for monogenean species identification by implementing image processing techniques and machine learning methods. Images of four monogenean species namely Sinodiplectanotrema malayanus, Trianchoratus pahangensis, Metahaliotrema mizellei and Metahaliotrema sp. (undescribed) were used to develop an automated technique for identification. K-nearest neighbour (KNN) was applied to classify the monogenean specimens based on the extracted features. 50% of the dataset was used for training and the other 50% was used as testing for system evaluation. Our approach demonstrated overall classification accuracy of 90%. In this study Leave One Out (LOO) cross validation is used for validation of our system and the accuracy is 91.25%. The methods presented in this study facilitate fast and accurate fully automated classification of monogeneans at the species level. In future studies more classes will be included in the model, the time to capture the monogenean images will be reduced and improvements in extraction and selection of features will be implemented.

Synchrotron X-Ray Diffraction Analysis of Meteorites in Thin Section: Preliminary Results

NASA Technical Reports Server (NTRS)

Treiman, A. H.; Lanzirotti, A.; Xirouchakis, D.

2004-01-01

X-ray diffraction is the pre-eminent technique for mineral identification and structure determination, but is difficult to apply to grains in thin section, the standard meteorite preparation. Bright focused X-ray beams from synchrotrons have been used extensively in mineralogy and have been applied to extraterrestrial particles. The intensity and small spot size achievable in synchrotron X-ray beams makes them useful for study of materials in thin sections. Here, we describe Synchrotron X-ray Diffraction (SXRD) in thin section as done at the National Synchrotron Light Source, and cite examples of its value for studies of meteorites in thin section.

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

Acciarri, R.; Adams, C.; An, R.

Here, we present several studies of convolutional neural networks applied to data coming from the MicroBooNE detector, a liquid argon time projection chamber (LArTPC). The algorithms studied include the classification of single particle images, the localization of single particle and neutrino interactions in an image, and the detection of a simulated neutrino event overlaid with cosmic ray backgrounds taken from real detector data. These studies demonstrate the potential of convolutional neural networks for particle identification or event detection on simulated neutrino interactions. Lastly, we also address technical issues that arise when applying this technique to data from a large LArTPCmore » at or near ground level.« less

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

Acciarri, R.; Adams, C.; An, R.

We present several studies of convolutional neural networks applied to data coming from the MicroBooNE detector, a liquid argon time projection chamber (LArTPC). The algorithms studied include the classification of single particle images, the localization of single particle and neutrino interactions in an image, and the detection of a simulated neutrino event overlaid with cosmic ray backgrounds taken from real detector data. These studies demonstrate the potential of convolutional neural networks for particle identification or event detection on simulated neutrino interactions. We also address technical issues that arise when applying this technique to data from a large LArTPC at ormore » near ground level.« less

Identification of Species in Tripterygium (Celastraceae) Based on DNA Barcoding.

PubMed

Zhang, Xiaomei; Li, Na; Yao, Yuanyuan; Liang, Xuming; Qu, Xianyou; Liu, Xiang; Zhu, Yingjie; Yang, Dajian; Sun, Wei

2016-11-01

Species of genus Tripterygium (Celastraceae) have attracted much attention owing to their excellent effect on treating autoimmune and inflammatory diseases. However, due to high market demand causing overexploitation, natural populations of genus Tripterygium have rapidly declined. Tripterygium medicinal materials are mainly collected from the wild, making the quality of medicinal materials unstable. Additionally, identification of herbal materials from Tripterygium species and their adulterants is difficult based on morphological characters. Therefore, an accurate, convenient, and stability method is urgently needed. In this wok, we developed a DNA barcoding technique to distinguish T. wilfordii HOOK. f., T. hypoglaucum (LÉVL.) HUTCH, and T. regelii SPRAGUE et TAKEDA and their adulterants based on four uniform and standard DNA regions (internal transcribed spacer 2 (ITS2), matK, rbcL, and psbA-trnH). DNA was extracted from 26 locations of fresh leaves. Phylogenetic tree was constructed with Neighbor-Joining (NJ) method, while barcoding gap was analyzed to assess identification efficiency. Compared with the other DNA barcodes applied individually or in combination, ITS2+psbA-trnH was demonstrated as the optimal barcode. T. hypoglaucum and T. wilfordii can be considered as conspecific, while T. regelii was recognized as a separate species. Furthermore, identification of commercial Tripterygium samples was conducted using BLAST against GenBank and Species Identification System for Traditional Chinese Medicine. Our results indicated that DNA barcoding is a convenient, effective, and stability method to identify and distinguish Tripterygium and its adulterants, and could be applied as the quality control for Tripterygium medicinal preparations and monitoring of the medicinal herb trade in markets.

Highly efficient classification and identification of human pathogenic bacteria by MALDI-TOF MS.

PubMed

Hsieh, Sen-Yung; Tseng, Chiao-Li; Lee, Yun-Shien; Kuo, An-Jing; Sun, Chien-Feng; Lin, Yen-Hsiu; Chen, Jen-Kun

2008-02-01

Accurate and rapid identification of pathogenic microorganisms is of critical importance in disease treatment and public health. Conventional work flows are time-consuming, and procedures are multifaceted. MS can be an alternative but is limited by low efficiency for amino acid sequencing as well as low reproducibility for spectrum fingerprinting. We systematically analyzed the feasibility of applying MS for rapid and accurate bacterial identification. Directly applying bacterial colonies without further protein extraction to MALDI-TOF MS analysis revealed rich peak contents and high reproducibility. The MS spectra derived from 57 isolates comprising six human pathogenic bacterial species were analyzed using both unsupervised hierarchical clustering and supervised model construction via the Genetic Algorithm. Hierarchical clustering analysis categorized the spectra into six groups precisely corresponding to the six bacterial species. Precise classification was also maintained in an independently prepared set of bacteria even when the numbers of m/z values were reduced to six. In parallel, classification models were constructed via Genetic Algorithm analysis. A model containing 18 m/z values accurately classified independently prepared bacteria and identified those species originally not used for model construction. Moreover bacteria fewer than 10(4) cells and different species in bacterial mixtures were identified using the classification model approach. In conclusion, the application of MALDI-TOF MS in combination with a suitable model construction provides a highly accurate method for bacterial classification and identification. The approach can identify bacteria with low abundance even in mixed flora, suggesting that a rapid and accurate bacterial identification using MS techniques even before culture can be attained in the near future.

The Identification and Tracking of Uterine Contractions Using Template Based Cross-Correlation.

PubMed

McDonald, Sarah C; Brooker, Graham; Phipps, Hala; Hyett, Jon

2017-09-01

The purpose of this paper is to outline a novel method of using template based cross-correlation to identify and track uterine contractions during labour. A purpose built six-channel Electromyography (EMG) device was used to collect data from consenting women during labour and birth. A range of templates were constructed for the purpose of identifying and tracking uterine activity when cross-correlated with the EMG signal. Peak finding techniques were applied on the cross-correlated result to simplify and automate the identification and tracking of contractions. The EMG data showed a unique pattern when a woman was contracting with key features of the contraction signal remaining consistent and identifiable across subjects. Contraction profiles across subjects were automatically identified using template based cross-correlation. Synthetic templates from a rectangular function with a duration of between 5 and 10 s performed best at identifying and tracking uterine activity across subjects. The successful application of this technique provides opportunity for both simple and accurate real-time analysis of contraction data while enabling investigations into the application of techniques such as machine learning which could enable automated learning from contraction data as part of real-time monitoring and post analysis.

Wavelet Analyses of F/A-18 Aeroelastic and Aeroservoelastic Flight Test Data

NASA Technical Reports Server (NTRS)

Brenner, Martin J.

1997-01-01

Time-frequency signal representations combined with subspace identification methods were used to analyze aeroelastic flight data from the F/A-18 Systems Research Aircraft (SRA) and aeroservoelastic data from the F/A-18 High Alpha Research Vehicle (HARV). The F/A-18 SRA data were produced from a wingtip excitation system that generated linear frequency chirps and logarithmic sweeps. HARV data were acquired from digital Schroeder-phased and sinc pulse excitation signals to actuator commands. Nondilated continuous Morlet wavelets implemented as a filter bank were chosen for the time-frequency analysis to eliminate phase distortion as it occurs with sliding window discrete Fourier transform techniques. Wavelet coefficients were filtered to reduce effects of noise and nonlinear distortions identically in all inputs and outputs. Cleaned reconstructed time domain signals were used to compute improved transfer functions. Time and frequency domain subspace identification methods were applied to enhanced reconstructed time domain data and improved transfer functions, respectively. Time domain subspace performed poorly, even with the enhanced data, compared with frequency domain techniques. A frequency domain subspace method is shown to produce better results with the data processed using the Morlet time-frequency technique.

Virus detection and quantification using electrical parameters

NASA Astrophysics Data System (ADS)

Ahmad, Mahmoud Al; Mustafa, Farah; Ali, Lizna M.; Rizvi, Tahir A.

2014-10-01

Here we identify and quantitate two similar viruses, human and feline immunodeficiency viruses (HIV and FIV), suspended in a liquid medium without labeling, using a semiconductor technique. The virus count was estimated by calculating the impurities inside a defined volume by observing the change in electrical parameters. Empirically, the virus count was similar to the absolute value of the ratio of the change of the virus suspension dopant concentration relative to the mock dopant over the change in virus suspension Debye volume relative to mock Debye volume. The virus type was identified by constructing a concentration-mobility relationship which is unique for each kind of virus, allowing for a fast (within minutes) and label-free virus quantification and identification. For validation, the HIV and FIV virus preparations were further quantified by a biochemical technique and the results obtained by both approaches corroborated well. We further demonstrate that the electrical technique could be applied to accurately measure and characterize silica nanoparticles that resemble the virus particles in size. Based on these results, we anticipate our present approach to be a starting point towards establishing the foundation for label-free electrical-based identification and quantification of an unlimited number of viruses and other nano-sized particles.

Motor Oil Classification using Color Histograms and Pattern Recognition Techniques.

PubMed

Ahmadi, Shiva; Mani-Varnosfaderani, Ahmad; Habibi, Biuck

2018-04-20

Motor oil classification is important for quality control and the identification of oil adulteration. In thiswork, we propose a simple, rapid, inexpensive and nondestructive approach based on image analysis and pattern recognition techniques for the classification of nine different types of motor oils according to their corresponding color histograms. For this, we applied color histogram in different color spaces such as red green blue (RGB), grayscale, and hue saturation intensity (HSI) in order to extract features that can help with the classification procedure. These color histograms and their combinations were used as input for model development and then were statistically evaluated by using linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), and support vector machine (SVM) techniques. Here, two common solutions for solving a multiclass classification problem were applied: (1) transformation to binary classification problem using a one-against-all (OAA) approach and (2) extension from binary classifiers to a single globally optimized multilabel classification model. In the OAA strategy, LDA, QDA, and SVM reached up to 97% in terms of accuracy, sensitivity, and specificity for both the training and test sets. In extension from binary case, despite good performances by the SVM classification model, QDA and LDA provided better results up to 92% for RGB-grayscale-HSI color histograms and up to 93% for the HSI color map, respectively. In order to reduce the numbers of independent variables for modeling, a principle component analysis algorithm was used. Our results suggest that the proposed method is promising for the identification and classification of different types of motor oils.

Application of the angle measure technique as image texture analysis method for the identification of uranium ore concentrate samples: New perspective in nuclear forensics.

PubMed

Fongaro, Lorenzo; Ho, Doris Mer Lin; Kvaal, Knut; Mayer, Klaus; Rondinella, Vincenzo V

2016-05-15

The identification of interdicted nuclear or radioactive materials requires the application of dedicated techniques. In this work, a new approach for characterizing powder of uranium ore concentrates (UOCs) is presented. It is based on image texture analysis and multivariate data modelling. 26 different UOCs samples were evaluated applying the Angle Measure Technique (AMT) algorithm to extract textural features on samples images acquired at 250× and 1000× magnification by Scanning Electron Microscope (SEM). At both magnifications, this method proved effective to classify the different types of UOC powder based on the surface characteristics that depend on particle size, homogeneity, and graininess and are related to the composition and processes used in the production facilities. Using the outcome data from the application of the AMT algorithm, the total explained variance was higher than 90% with Principal Component Analysis (PCA), while partial least square discriminant analysis (PLS-DA) applied only on the 14 black colour UOCs powder samples, allowed their classification only on the basis of their surface texture features (sensitivity>0.6; specificity>0.6). This preliminary study shows that this method was able to distinguish samples with similar composition, but obtained from different facilities. The mean angle spectral data obtained by the image texture analysis using the AMT algorithm can be considered as a specific fingerprint or signature of UOCs and could be used for nuclear forensic investigation. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Automated Solid Phase Extraction (SPE) LC/NMR Applied to the Structural Analysis of Extractable Compounds from a Pharmaceutical Packaging Material of Construction.

PubMed

Norwood, Daniel L; Mullis, James O; Davis, Mark; Pennino, Scott; Egert, Thomas; Gonnella, Nina C

2013-01-01

The structural analysis (i.e., identification) of organic chemical entities leached into drug product formulations has traditionally been accomplished with techniques involving the combination of chromatography with mass spectrometry. These include gas chromatography/mass spectrometry (GC/MS) for volatile and semi-volatile compounds, and various forms of liquid chromatography/mass spectrometry (LC/MS or HPLC/MS) for semi-volatile and relatively non-volatile compounds. GC/MS and LC/MS techniques are complementary for structural analysis of leachables and potentially leachable organic compounds produced via laboratory extraction of pharmaceutical container closure/delivery system components and corresponding materials of construction. Both hyphenated analytical techniques possess the separating capability, compound specific detection attributes, and sensitivity required to effectively analyze complex mixtures of trace level organic compounds. However, hyphenated techniques based on mass spectrometry are limited by the inability to determine complete bond connectivity, the inability to distinguish between many types of structural isomers, and the inability to unambiguously determine aromatic substitution patterns. Nuclear magnetic resonance spectroscopy (NMR) does not have these limitations; hence it can serve as a complement to mass spectrometry. However, NMR technology is inherently insensitive and its ability to interface with chromatography has been historically challenging. This article describes the application of NMR coupled with liquid chromatography and automated solid phase extraction (SPE-LC/NMR) to the structural analysis of extractable organic compounds from a pharmaceutical packaging material of construction. The SPE-LC/NMR technology combined with micro-cryoprobe technology afforded the sensitivity and sample mass required for full structure elucidation. Optimization of the SPE-LC/NMR analytical method was achieved using a series of model compounds representing the chemical diversity of extractables. This study demonstrates the complementary nature of SPE-LC/NMR with LC/MS for this particular pharmaceutical application. The identification of impurities leached into drugs from the components and materials associated with pharmaceutical containers, packaging components, and materials has historically been done using laboratory techniques based on the combination of chromatography with mass spectrometry. Such analytical techniques are widely recognized as having the selectivity and sensitivity required to separate the complex mixtures of impurities often encountered in such identification studies, including both the identification of leachable impurities as well as potential leachable impurities produced by laboratory extraction of packaging components and materials. However, while mass spectrometry-based analytical techniques have limitations for this application, newer analytical techniques based on the combination of chromatography with nuclear magnetic resonance spectroscopy provide an added dimension of structural definition. This article describes the development, optimization, and application of an analytical technique based on the combination of chromatography and nuclear magnetic resonance spectroscopy to the identification of potential leachable impurities from a pharmaceutical packaging material. The complementary nature of the analytical techniques for this particular pharmaceutical application is demonstrated.

Machine learning and next-generation asteroid surveys

NASA Astrophysics Data System (ADS)

Nugent, Carrie R.; Dailey, John; Cutri, Roc M.; Masci, Frank J.; Mainzer, Amy K.

2017-10-01

Next-generation surveys such as NEOCam (Mainzer et al., 2016) will sift through tens of millions of point source detections daily to detect and discover asteroids. This requires new, more efficient techniques to distinguish between solar system objects, background stars and galaxies, and artifacts such as cosmic rays, scattered light and diffraction spikes.Supervised machine learning is a set of algorithms that allows computers to classify data on a training set, and then apply that classification to make predictions on new datasets. It has been employed by a broad range of fields, including computer vision, medical diagnoses, economics, and natural language processing. It has also been applied to astronomical datasets, including transient identification in the Palomar Transient Factory pipeline (Masci et al., 2016), and in the Pan-STARRS1 difference imaging (D. E. Wright et al., 2015).As part of the NEOCam extended phase A work we apply machine learning techniques to the problem of asteroid detection. Asteroid detection is an ideal application of supervised learning, as there is a wealth of metrics associated with each extracted source, and suitable training sets are easily created. Using the vetted NEOWISE dataset (E. L. Wright et al., 2010, Mainzer et al., 2011) as a proof-of-concept of this technique, we applied the python package sklearn. We report on reliability, feature set selection, and the suitability of various algorithms.

An insight into the isolation, enumeration, and molecular detection of Listeria monocytogenes in food

PubMed Central

Law, Jodi Woan-Fei; Ab Mutalib, Nurul-Syakima; Chan, Kok-Gan; Lee, Learn-Han

2015-01-01

Listeria monocytogenes, a foodborne pathogen that can cause listeriosis through the consumption of food contaminated with this pathogen. The ability of L. monocytogenes to survive in extreme conditions and cause food contaminations have become a major concern. Hence, routine microbiological food testing is necessary to prevent food contamination and outbreaks of foodborne illness. This review provides insight into the methods for cultural detection, enumeration, and molecular identification of L. monocytogenes in various food samples. There are a number of enrichment and plating media that can be used for the isolation of L. monocytogenes from food samples. Enrichment media such as buffered Listeria enrichment broth, Fraser broth, and University of Vermont Medium (UVM) Listeria enrichment broth are recommended by regulatory agencies such as Food and Drug Administration-bacteriological and analytical method (FDA-BAM), US Department of Agriculture-Food and Safety (USDA-FSIS), and International Organization for Standardization (ISO). Many plating media are available for the isolation of L. monocytogenes, for instance, polymyxin acriflavin lithium-chloride ceftazidime aesculin mannitol, Oxford, and other chromogenic media. Besides, reference methods like FDA-BAM, ISO 11290 method, and USDA-FSIS method are usually applied for the cultural detection or enumeration of L. monocytogenes. most probable number technique is applied for the enumeration of L. monocytogenes in the case of low level contamination. Molecular methods including polymerase chain reaction, multiplex polymerase chain reaction, real-time/quantitative polymerase chain reaction, nucleic acid sequence-based amplification, loop-mediated isothermal amplification, DNA microarray, and next generation sequencing technology for the detection and identification of L. monocytogenes are discussed in this review. Overall, molecular methods are rapid, sensitive, specific, time- and labor-saving. In future, there are chances for the development of new techniques for the detection and identification of foodborne with improved features. PMID:26579116

Identification of substances migrating from plastic baby bottles using a combination of low-resolution and high-resolution mass spectrometric analysers coupled to gas and liquid chromatography.

PubMed

Onghena, Matthias; Van Hoeck, Els; Van Loco, Joris; Ibáñez, María; Cherta, Laura; Portolés, Tania; Pitarch, Elena; Hernandéz, Félix; Lemière, Filip; Covaci, Adrian

2015-11-01

This work presents a strategy for elucidation of unknown migrants from plastic food contact materials (baby bottles) using a combination of analytical techniques in an untargeted approach. First, gas chromatography (GC) coupled to mass spectrometry (MS) in electron ionisation mode was used to identify migrants through spectral library matching. When no acceptable match was obtained, a second analysis by GC-(electron ionisation) high resolution mass spectrometry time of flight (TOF) was applied to obtain accurate mass fragmentation spectra and isotopic patterns. Databases were then searched to find a possible elemental composition for the unknown compounds. Finally, a GC hybrid quadrupole-TOF-MS with an atmospheric pressure chemical ionisation source was used to obtain the molecular ion or the protonated molecule. Accurate mass data also provided additional information on the fragmentation behaviour as two acquisition functions with different collision energies were available (MS(E) approach). In the low-energy function, limited fragmentation took place, whereas for the high-energy function, fragmentation was enhanced. For less volatile unknowns, ultra-high pressure liquid chromatography-quadrupole-TOF-MS was additionally applied. Using a home-made database containing common migrating compounds and plastic additives, tentative identification was made for several positive findings based on accurate mass of the (de)protonated molecule, product ion fragments and characteristic isotopic ions. Six illustrative examples are shown to demonstrate the modus operandi and the difficulties encountered during identification. The combination of these techniques was proven to be a powerful tool for the elucidation of unknown migrating compounds from plastic baby bottles. Copyright © 2015 John Wiley & Sons, Ltd.

DNA Barcoding of the Endangered Aquilaria (Thymelaeaceae) and Its Application in Species Authentication of Agarwood Products Traded in the Market

PubMed Central

Lee, Shiou Yih; Ng, Wei Lun; Mahat, Mohd Noor; Nazre, Mohd; Mohamed, Rozi

2016-01-01

The identification of Aquilaria species from their resinous non-wood product, the agarwood, is challenging as conventional techniques alone are unable to ascertain the species origin. Aquilaria is a highly protected species due to the excessive exploitation of its precious agarwood. Here, we applied the DNA barcoding technique to generate barcode sequences for Aquilaria species and later applied the barcodes to identify the source species of agarwood found in the market. We developed a reference DNA barcode library using eight candidate barcode loci (matK, rbcL, rpoB, rpoC1, psbA-trnH, trnL-trnF, ITS, and ITS2) amplified from 24 leaf accessions of seven Aquilaria species obtained from living trees. Our results indicated that all single barcodes can be easily amplified and sequenced with the selected primers. The combination of trnL-trnF+ITS and trnL-trnF+ITS2 yielded the greatest species resolution using the least number of loci combination, while matK+trnL-trnF+ITS showed potential in detecting the geographical origins of Aquilaria species. We propose trnL-trnF+ITS2 as the best candidate barcode for Aquilaria as ITS2 has a shorter sequence length compared to ITS, which eases PCR amplification especially when using degraded DNA samples such as those extracted from processed agarwood products. A blind test conducted on eight agarwood samples in different forms using the proposed barcode combination proved successful in their identification up to the species level. Such potential of DNA barcoding in identifying the source species of agarwood will contribute to the international timber trade control, by providing an effective method for species identification and product authentication. PMID:27128309

An insight into the isolation, enumeration, and molecular detection of Listeria monocytogenes in food.

PubMed

Law, Jodi Woan-Fei; Ab Mutalib, Nurul-Syakima; Chan, Kok-Gan; Lee, Learn-Han

2015-01-01

Listeria monocytogenes, a foodborne pathogen that can cause listeriosis through the consumption of food contaminated with this pathogen. The ability of L. monocytogenes to survive in extreme conditions and cause food contaminations have become a major concern. Hence, routine microbiological food testing is necessary to prevent food contamination and outbreaks of foodborne illness. This review provides insight into the methods for cultural detection, enumeration, and molecular identification of L. monocytogenes in various food samples. There are a number of enrichment and plating media that can be used for the isolation of L. monocytogenes from food samples. Enrichment media such as buffered Listeria enrichment broth, Fraser broth, and University of Vermont Medium (UVM) Listeria enrichment broth are recommended by regulatory agencies such as Food and Drug Administration-bacteriological and analytical method (FDA-BAM), US Department of Agriculture-Food and Safety (USDA-FSIS), and International Organization for Standardization (ISO). Many plating media are available for the isolation of L. monocytogenes, for instance, polymyxin acriflavin lithium-chloride ceftazidime aesculin mannitol, Oxford, and other chromogenic media. Besides, reference methods like FDA-BAM, ISO 11290 method, and USDA-FSIS method are usually applied for the cultural detection or enumeration of L. monocytogenes. most probable number technique is applied for the enumeration of L. monocytogenes in the case of low level contamination. Molecular methods including polymerase chain reaction, multiplex polymerase chain reaction, real-time/quantitative polymerase chain reaction, nucleic acid sequence-based amplification, loop-mediated isothermal amplification, DNA microarray, and next generation sequencing technology for the detection and identification of L. monocytogenes are discussed in this review. Overall, molecular methods are rapid, sensitive, specific, time- and labor-saving. In future, there are chances for the development of new techniques for the detection and identification of foodborne with improved features.

The Accuracy of Parameter Estimation in System Identification of Noisy Aircraft Load Measurement. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Kong, Jeffrey

1994-01-01

This thesis focuses on the subject of the accuracy of parameter estimation and system identification techniques. Motivated by a complicated load measurement from NASA Dryden Flight Research Center, advanced system identification techniques are needed. The objective of this problem is to accurately predict the load experienced by the aircraft wing structure during flight determined from a set of calibrated load and gage response relationship. We can then model the problem as a black box input-output system identification from which the system parameter has to be estimated. Traditional LS (Least Square) techniques and the issues of noisy data and model accuracy are addressed. A statistical bound reflecting the change in residual is derived in order to understand the effects of the perturbations on the data. Due to the intrinsic nature of the LS problem, LS solution faces the dilemma of the trade off between model accuracy and noise sensitivity. A method of conflicting performance indices is presented, thus allowing us to improve the noise sensitivity while at the same time configuring the degredation of the model accuracy. SVD techniques for data reduction are studied and the equivalence of the Correspondence Analysis (CA) and Total Least Squares Criteria are proved. We also looked at nonlinear LS problems with NASA F-111 data set as an example. Conventional methods are neither easily applicable nor suitable for the specific load problem since the exact model of the system is unknown. Neural Network (NN) does not require prior information on the model of the system. This robustness motivated us to apply the NN techniques on our load problem. Simulation results for the NN methods used in both the single load and the 'warning signal' problems are both useful and encouraging. The performance of the NN (for single load estimate) is better than the LS approach, whereas no conventional approach was tried for the 'warning signals' problems. The NN design methodology is also presented. The use of SVD, CA and Collinearity Index methods are used to reduce the number of neurons in a layer.

Linear control of oscillator and amplifier flows*

NASA Astrophysics Data System (ADS)

Schmid, Peter J.; Sipp, Denis

2016-08-01

Linear control applied to fluid systems near an equilibrium point has important applications for many flows of industrial or fundamental interest. In this article we give an exposition of tools and approaches for the design of control strategies for globally stable or unstable flows. For unstable oscillator flows a feedback configuration and a model-based approach is proposed, while for stable noise-amplifier flows a feedforward setup and an approach based on system identification is advocated. Model reduction and robustness issues are addressed for the oscillator case; statistical learning techniques are emphasized for the amplifier case. Effective suppression of global and convective instabilities could be demonstrated for either case, even though the system-identification approach results in a superior robustness to off-design conditions.

Autonomous Modal Identification of the Space Shuttle Tail Rudder

NASA Technical Reports Server (NTRS)

Pappa, Richard S.; James, George H., III; Zimmerman, David C.

1997-01-01

Autonomous modal identification automates the calculation of natural vibration frequencies, damping, and mode shapes of a structure from experimental data. This technology complements damage detection techniques that use continuous or periodic monitoring of vibration characteristics. The approach shown in the paper incorporates the Eigensystem Realization Algorithm (ERA) as a data analysis engine and an autonomous supervisor to condense multiple estimates of modal parameters using ERA's Consistent-Mode Indicator and correlation of mode shapes. The procedure was applied to free-decay responses of a Space Shuttle tail rudder and successfully identified the seven modes of the structure below 250 Hz. The final modal parameters are a condensed set of results for 87 individual ERA cases requiring approximately five minutes of CPU time on a DEC Alpha computer.

Use of consumer insight in the new product development process in the meat sector.

PubMed

Grunert, Klaus G; Verbeke, Wim; Kügler, Jens O; Saeed, Faiza; Scholderer, Joachim

2011-11-01

Successful new product development requires input from the market throughout the product development process, from identification of opportunities via screening of ideas, development of concepts, development of physical prototypes and to launch. Drawing on work done in the EU FP6 projects PROSAFEBEEF and Q-PORKCHAINS and a Danish project, all dealing with new product development in the meat sector, it is shown how the use of consumer insight techniques can a) support the identification of market opportunities, b) make sure that technologies applied are acceptable to consumers, c) aid the selection and optimisation of new product concepts and related communication, and d) be used to test product prototypes before final launch. Copyright © 2011 Elsevier Ltd. All rights reserved.

A Wavelet Analysis Approach for Categorizing Air Traffic Behavior

NASA Technical Reports Server (NTRS)

Drew, Michael; Sheth, Kapil

2015-01-01

In this paper two frequency domain techniques are applied to air traffic analysis. The Continuous Wavelet Transform (CWT), like the Fourier Transform, is shown to identify changes in historical traffic patterns caused by Traffic Management Initiatives (TMIs) and weather with the added benefit of detecting when in time those changes take place. Next, with the expectation that it could detect anomalies in the network and indicate the extent to which they affect traffic flows, the Spectral Graph Wavelet Transform (SGWT) is applied to a center based graph model of air traffic. When applied to simulations based on historical flight plans, it identified the traffic flows between centers that have the greatest impact on either neighboring flows, or flows between centers many centers away. Like the CWT, however, it can be difficult to interpret SGWT results and relate them to simulations where major TMIs are implemented, and more research may be warranted in this area. These frequency analysis techniques can detect off-nominal air traffic behavior, but due to the nature of air traffic time series data, so far they prove difficult to apply in a way that provides significant insight or specific identification of traffic patterns.

Identification of solid state fermentation degree with FT-NIR spectroscopy: Comparison of wavelength variable selection methods of CARS and SCARS.

PubMed

Jiang, Hui; Zhang, Hang; Chen, Quansheng; Mei, Congli; Liu, Guohai

2015-01-01

The use of wavelength variable selection before partial least squares discriminant analysis (PLS-DA) for qualitative identification of solid state fermentation degree by FT-NIR spectroscopy technique was investigated in this study. Two wavelength variable selection methods including competitive adaptive reweighted sampling (CARS) and stability competitive adaptive reweighted sampling (SCARS) were employed to select the important wavelengths. PLS-DA was applied to calibrate identified model using selected wavelength variables by CARS and SCARS for identification of solid state fermentation degree. Experimental results showed that the number of selected wavelength variables by CARS and SCARS were 58 and 47, respectively, from the 1557 original wavelength variables. Compared with the results of full-spectrum PLS-DA, the two wavelength variable selection methods both could enhance the performance of identified models. Meanwhile, compared with CARS-PLS-DA model, the SCARS-PLS-DA model achieved better results with the identification rate of 91.43% in the validation process. The overall results sufficiently demonstrate the PLS-DA model constructed using selected wavelength variables by a proper wavelength variable method can be more accurate identification of solid state fermentation degree. Copyright © 2015 Elsevier B.V. All rights reserved.

Identification of solid state fermentation degree with FT-NIR spectroscopy: Comparison of wavelength variable selection methods of CARS and SCARS

NASA Astrophysics Data System (ADS)

Jiang, Hui; Zhang, Hang; Chen, Quansheng; Mei, Congli; Liu, Guohai

2015-10-01

The use of wavelength variable selection before partial least squares discriminant analysis (PLS-DA) for qualitative identification of solid state fermentation degree by FT-NIR spectroscopy technique was investigated in this study. Two wavelength variable selection methods including competitive adaptive reweighted sampling (CARS) and stability competitive adaptive reweighted sampling (SCARS) were employed to select the important wavelengths. PLS-DA was applied to calibrate identified model using selected wavelength variables by CARS and SCARS for identification of solid state fermentation degree. Experimental results showed that the number of selected wavelength variables by CARS and SCARS were 58 and 47, respectively, from the 1557 original wavelength variables. Compared with the results of full-spectrum PLS-DA, the two wavelength variable selection methods both could enhance the performance of identified models. Meanwhile, compared with CARS-PLS-DA model, the SCARS-PLS-DA model achieved better results with the identification rate of 91.43% in the validation process. The overall results sufficiently demonstrate the PLS-DA model constructed using selected wavelength variables by a proper wavelength variable method can be more accurate identification of solid state fermentation degree.

Intelligent Systems Approach for Automated Identification of Individual Control Behavior of a Human Operator

NASA Technical Reports Server (NTRS)

Zaychik, Kirill B.; Cardullo, Frank M.

2012-01-01

Results have been obtained using conventional techniques to model the generic human operator?s control behavior, however little research has been done to identify an individual based on control behavior. The hypothesis investigated is that different operators exhibit different control behavior when performing a given control task. Two enhancements to existing human operator models, which allow personalization of the modeled control behavior, are presented. One enhancement accounts for the testing control signals, which are introduced by an operator for more accurate control of the system and/or to adjust the control strategy. This uses the Artificial Neural Network which can be fine-tuned to model the testing control. Another enhancement takes the form of an equiripple filter which conditions the control system power spectrum. A novel automated parameter identification technique was developed to facilitate the identification process of the parameters of the selected models. This utilizes a Genetic Algorithm based optimization engine called the Bit-Climbing Algorithm. Enhancements were validated using experimental data obtained from three different sources: the Manual Control Laboratory software experiments, Unmanned Aerial Vehicle simulation, and NASA Langley Research Center Visual Motion Simulator studies. This manuscript also addresses applying human operator models to evaluate the effectiveness of motion feedback when simulating actual pilot control behavior in a flight simulator.

Identification and differentiation of Campylobacter species by high-resolution melting curve analysis.

PubMed

Hoseinpour, Fatemeh; Foroughi, Azadeh; Nomanpour, Bizhan; Nasab, Rezvan Sobhani

2017-07-01

Campylobacter jejuni and Campylobacter coli are the important food-born zoonotic pathogen, also are leading causes of human food borne illnesses worldwide. cadF gene is expressed in all C. jejuni and C. coli strains and mediates cell binding to the cell matrix protein, Fibronectin. High-resolution melting (HRM) analysis is emerging as an efficient and robust method for discriminating DNA sequence variants. The goal of this study was to apply HRM analysis to identification of C. jejuni and C. coli. A total of 100 samples were obtained from chicken in Kermanshah, Iran. HRM analysis based on cadF gene and Eva Green was developed to the identification of Campylobacter to the species level. Fifty-five of 100 samples were positive as campylobacter (7 C. jejuni, 29 C. coli, 16 mixes and 3 unknown). Minor variations were observed in melting point temperatures of C. coli or C. jejuni isolates and this variation can be used to the differentiation between C. coli or C. jejuni isolates. The results of this study indicated that HRM curve analysis can be a suitable technique and rapid technique for distinguishing between C. jejuni and C. coli isolates. Copyright © 2017 Elsevier Ltd. All rights reserved.

Causal gene identification using combinatorial V-structure search.

PubMed

Cai, Ruichu; Zhang, Zhenjie; Hao, Zhifeng

2013-07-01

With the advances of biomedical techniques in the last decade, the costs of human genomic sequencing and genomic activity monitoring are coming down rapidly. To support the huge genome-based business in the near future, researchers are eager to find killer applications based on human genome information. Causal gene identification is one of the most promising applications, which may help the potential patients to estimate the risk of certain genetic diseases and locate the target gene for further genetic therapy. Unfortunately, existing pattern recognition techniques, such as Bayesian networks, cannot be directly applied to find the accurate causal relationship between genes and diseases. This is mainly due to the insufficient number of samples and the extremely high dimensionality of the gene space. In this paper, we present the first practical solution to causal gene identification, utilizing a new combinatorial formulation over V-Structures commonly used in conventional Bayesian networks, by exploring the combinations of significant V-Structures. We prove the NP-hardness of the combinatorial search problem under a general settings on the significance measure on the V-Structures, and present a greedy algorithm to find sub-optimal results. Extensive experiments show that our proposal is both scalable and effective, particularly with interesting findings on the causal genes over real human genome data. Copyright © 2013 Elsevier Ltd. All rights reserved.

Blind source computer device identification from recorded VoIP calls for forensic investigation.

PubMed

Jahanirad, Mehdi; Anuar, Nor Badrul; Wahab, Ainuddin Wahid Abdul

2017-03-01

The VoIP services provide fertile ground for criminal activity, thus identifying the transmitting computer devices from recorded VoIP call may help the forensic investigator to reveal useful information. It also proves the authenticity of the call recording submitted to the court as evidence. This paper extended the previous study on the use of recorded VoIP call for blind source computer device identification. Although initial results were promising but theoretical reasoning for this is yet to be found. The study suggested computing entropy of mel-frequency cepstrum coefficients (entropy-MFCC) from near-silent segments as an intrinsic feature set that captures the device response function due to the tolerances in the electronic components of individual computer devices. By applying the supervised learning techniques of naïve Bayesian, linear logistic regression, neural networks and support vector machines to the entropy-MFCC features, state-of-the-art identification accuracy of near 99.9% has been achieved on different sets of computer devices for both call recording and microphone recording scenarios. Furthermore, unsupervised learning techniques, including simple k-means, expectation-maximization and density-based spatial clustering of applications with noise (DBSCAN) provided promising results for call recording dataset by assigning the majority of instances to their correct clusters. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

A strategy for identification and structural characterization of compounds from Gardenia jasminoides by integrating macroporous resin column chromatography and liquid chromatography-tandem mass spectrometry combined with ion-mobility spectrometry.

PubMed

Wang, Lu; Liu, Shu; Zhang, Xueju; Xing, Junpeng; Liu, Zhiqiang; Song, Fengrui

2016-06-24

In this paper, an analysis strategy integrating macroporous resin (AB-8) column chromatography and high performance liquid chromatography-electrospray ionization-tandem mass spectrometry (HPLC-ESI-MS/MS) combined with ion mobility spectrometry (IMS) was proposed and applied for identification and structural characterization of compounds from the fruits of Gardenia jasminoides. The extracts of G. jasminoides were separated by AB-8 resin column chromatography combined with reversed phase liquid chromatography (C18 column) and detected by electrospray ionization tandem mass spectrometry. Additionally, ion mobility spectrometry (IMS) was employed as a supplementary separation technique to discover previously undetected isomers from the fruits of G. jasminoides. A total of 71 compounds, including iridoids, flavonoids, triterpenes, monoterpenoids, carotenoids and phenolic acids were identified by the characteristic high resolution mass spectrometry and the ESI-MS/MS fragmentations. In conclusion, the IMS-MS technique achieved the separation of isomers in crocin-3 and crocin-4 according to their acquired mobility drift times differing from classical analysis by mass spectrometry. The proposed strategy can be used as a highly sensitive and efficient procedure for identification and separation isomeric components in extracts of herbal medicines. Copyright © 2016 Elsevier B.V. All rights reserved.

A possible glycosidic benzophenone with full substitution on B-ring from Psidium guajava leaves.

PubMed

Venditti, Alessandro; Ukwueze, Stanley E

2017-04-01

Bidimensional NMR analysis may be a useful tool to resolve the structure of chemical compounds also in mixture. This letter would demonstrate how these techniques could be applied e.g. to the reported case on identification of benzophenone glycoside from Psidium guajava. A tentative structure for the secondary component, not yet described, was possibly proposed on the basis of observation and critic review of available 1D and 2D NMR spectra.

Single-shot detection of bacterial endospores via coherent Raman spectroscopy.

PubMed

Pestov, Dmitry; Wang, Xi; Ariunbold, Gombojav O; Murawski, Robert K; Sautenkov, Vladimir A; Dogariu, Arthur; Sokolov, Alexei V; Scully, Marlan O

2008-01-15

Recent advances in coherent Raman spectroscopy hold exciting promise for many potential applications. For example, a technique, mitigating the nonresonant four-wave-mixing noise while maximizing the Raman-resonant signal, has been developed and applied to the problem of real-time detection of bacterial endospores. After a brief review of the technique essentials, we show how extensions of our earlier experimental work [Pestov D, et al. (2007) Science 316:265-268] yield single-shot identification of a small sample of Bacillus subtilis endospores (approximately 10(4) spores). The results convey the utility of the technique and its potential for "on-the-fly" detection of biohazards, such as Bacillus anthracis. The application of optimized coherent anti-Stokes Raman scattering scheme to problems requiring chemical specificity and short signal acquisition times is demonstrated.

Ship Speed Retrieval From Single Channel TerraSAR-X Data

NASA Astrophysics Data System (ADS)

Soccorsi, Matteo; Lehner, Susanne

2010-04-01

A method to estimate the speed of a moving ship is presented. The technique, introduced in Kirscht (1998), is extended to marine application and validated on TerraSAR-X High-Resolution (HR) data. The generation of a sequence of single-look SAR images from a single- channel image corresponds to an image time series with reduced resolution. This allows applying change detection techniques on the time series to evaluate the velocity components in range and azimuth of the ship. The evaluation of the displacement vector of a moving target in consecutive images of the sequence allows the estimation of the azimuth velocity component. The range velocity component is estimated by evaluating the variation of the signal amplitude during the sequence. In order to apply the technique on TerraSAR-X Spot Light (SL) data a further processing step is needed. The phase has to be corrected as presented in Eineder et al. (2009) due to the SL acquisition mode; otherwise the image sequence cannot be generated. The analysis, when possible validated by the Automatic Identification System (AIS), was performed in the framework of the ESA project MARISS.

High-Resolution Laser-Induced Breakdown Spectroscopy used in Homeland Security and Forensic Applications

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

Martin, Madhavi Z; Wullschleger, Stan D; Vass, Arpad Alexander

The technique of laser-induced breakdown spectroscopy (LIBS) to detect elements for a variety of homeland security applications such as nuclear materials identification and inventory,and forensic applications has been demonstrated. For nuclear materials applications, we detected and profiled metals in coatings that were used to encapsulate nuclear fuel. Multivariate analysis has been successfully employed in the quantification of elements present in treated wood and engineered wood composites. These examples demonstrate that LIBS-based techniques are inherently well suited for diverse environmental applications related to homeland security. Three key advantages are evident: (1) small samples (mg) are sufficient; (2) samples can be analyzedmore » by LIBS very rapidly, and (3) biological materials such as human and animal bones and wood can be analyzed with minimal sample preparation. For forensic applications they have used LIBS to determine differences in animal and human bones. They have also applied this technique in the determination of counterfeit and non-counterfeit currency. They recently applied LIBS in helping to solve a murder case.« less

A Pragmatic Smoothing Method for Improving the Quality of the Results in Atomic Spectroscopy

NASA Astrophysics Data System (ADS)

Bennun, Leonardo

2017-07-01

A new smoothing method for the improvement on the identification and quantification of spectral functions based on the previous knowledge of the signals that are expected to be quantified, is presented. These signals are used as weighted coefficients in the smoothing algorithm. This smoothing method was conceived to be applied in atomic and nuclear spectroscopies preferably to these techniques where net counts are proportional to acquisition time, such as particle induced X-ray emission (PIXE) and other X-ray fluorescence spectroscopic methods, etc. This algorithm, when properly applied, does not distort the form nor the intensity of the signal, so it is well suited for all kind of spectroscopic techniques. This method is extremely effective at reducing high-frequency noise in the signal much more efficient than a single rectangular smooth of the same width. As all of smoothing techniques, the proposed method improves the precision of the results, but in this case we found also a systematic improvement on the accuracy of the results. We still have to evaluate the improvement on the quality of the results when this method is applied over real experimental results. We expect better characterization of the net area quantification of the peaks, and smaller Detection and Quantification Limits. We have applied this method to signals that obey Poisson statistics, but with the same ideas and criteria, it could be applied to time series. In a general case, when this algorithm is applied over experimental results, also it would be required that the sought characteristic functions, required for this weighted smoothing method, should be obtained from a system with strong stability. If the sought signals are not perfectly clean, this method should be carefully applied

A data-independent acquisition workflow for qualitative screening of new psychoactive substances in biological samples.

PubMed

Kinyua, Juliet; Negreira, Noelia; Ibáñez, María; Bijlsma, Lubertus; Hernández, Félix; Covaci, Adrian; van Nuijs, Alexander L N

2015-11-01

Identification of new psychoactive substances (NPS) is challenging. Developing targeted methods for their analysis can be difficult and costly due to their impermanence on the drug scene. Accurate-mass mass spectrometry (AMMS) using a quadrupole time-of-flight (QTOF) analyzer can be useful for wide-scope screening since it provides sensitive, full-spectrum MS data. Our article presents a qualitative screening workflow based on data-independent acquisition mode (all-ions MS/MS) on liquid chromatography (LC) coupled to QTOFMS for the detection and identification of NPS in biological matrices. The workflow combines and structures fundamentals of target and suspect screening data processing techniques in a structured algorithm. This allows the detection and tentative identification of NPS and their metabolites. We have applied the workflow to two actual case studies involving drug intoxications where we detected and confirmed the parent compounds ketamine, 25B-NBOMe, 25C-NBOMe, and several predicted phase I and II metabolites not previously reported in urine and serum samples. The screening workflow demonstrates the added value for the detection and identification of NPS in biological matrices.

A photometric mode identification method, including an improved non-adiabatic treatment of the atmosphere

NASA Astrophysics Data System (ADS)

Dupret, M.-A.; De Ridder, J.; De Cat, P.; Aerts, C.; Scuflaire, R.; Noels, A.; Thoul, A.

2003-02-01

We present an improved version of the method of photometric mode identification of Heynderickx et al. (\\cite{hey}). Our new version is based on the inclusion of precise non-adiabatic eigenfunctions determined in the outer stellar atmosphere according to the formalism recently proposed by Dupret et al. (\\cite{dup}). Our improved photometric mode identification technique is therefore no longer dependent on ad hoc parameters for the non-adiabatic effects. It contains the complete physical conditions of the outer atmosphere of the star, provided that rotation does not play a key role. We apply our method to the two slowly pulsating B stars HD 74560 and HD 138764 and to the beta Cephei star EN (16) Lac. Besides identifying the degree l of the pulsating stars, our method is also a tool for improving the knowledge of stellar interiors and atmospheres, by imposing constraints on parameters such as the metallicity and the mixing-length parameter alpha (a procedure we label non-adiabatic asteroseismology). The non-adiabatic eigenfunctions needed for the mode identification are available upon request from the authors.

Markov-random-field-based super-resolution mapping for identification of urban trees in VHR images

NASA Astrophysics Data System (ADS)

Ardila, Juan P.; Tolpekin, Valentyn A.; Bijker, Wietske; Stein, Alfred

2011-11-01

Identification of tree crowns from remote sensing requires detailed spectral information and submeter spatial resolution imagery. Traditional pixel-based classification techniques do not fully exploit the spatial and spectral characteristics of remote sensing datasets. We propose a contextual and probabilistic method for detection of tree crowns in urban areas using a Markov random field based super resolution mapping (SRM) approach in very high resolution images. Our method defines an objective energy function in terms of the conditional probabilities of panchromatic and multispectral images and it locally optimizes the labeling of tree crown pixels. Energy and model parameter values are estimated from multiple implementations of SRM in tuning areas and the method is applied in QuickBird images to produce a 0.6 m tree crown map in a city of The Netherlands. The SRM output shows an identification rate of 66% and commission and omission errors in small trees and shrub areas. The method outperforms tree crown identification results obtained with maximum likelihood, support vector machines and SRM at nominal resolution (2.4 m) approaches.

System Identification and POD Method Applied to Unsteady Aerodynamics

NASA Technical Reports Server (NTRS)

Tang, Deman; Kholodar, Denis; Juang, Jer-Nan; Dowell, Earl H.

2001-01-01

The representation of unsteady aerodynamic flow fields in terms of global aerodynamic modes has proven to be a useful method for reducing the size of the aerodynamic model over those representations that use local variables at discrete grid points in the flow field. Eigenmodes and Proper Orthogonal Decomposition (POD) modes have been used for this purpose with good effect. This suggests that system identification models may also be used to represent the aerodynamic flow field. Implicit in the use of a systems identification technique is the notion that a relative small state space model can be useful in describing a dynamical system. The POD model is first used to show that indeed a reduced order model can be obtained from a much larger numerical aerodynamical model (the vortex lattice method is used for illustrative purposes) and the results from the POD and the system identification methods are then compared. For the example considered, the two methods are shown to give comparable results in terms of accuracy and reduced model size. The advantages and limitations of each approach are briefly discussed. Both appear promising and complementary in their characteristics.

Simultaneous separation and identification of limonoids from citrus using liquid chromatography-collision-induced dissociation mass spectra.

PubMed

Jayaprakasha, Guddadarangavvanahally K; Dandekar, Deepak V; Tichy, Shane E; Patil, Bhimanagouda S

2011-01-01

Limonoids are considered as potential cancer chemopreventive agents and are widely distributed in the Citrus genus as aglycones and glucosides. In the present study, reversed-phase HPLC coupled with CID mass spectra was developed for the simultaneous separation and identification of aglycones and glucosides of limonoids from citrus. Five aglycones such as limonin, deacetyl nomilin, ichangin, isolimonoic acid and nomilin were identified by positive ion CID MS/MS, whereas five glucosides, viz. limonin glucoside, isoobacunoic acid glucoside, obacunone glucoside, deacetyl nomilinic acid glucoside and nomilinic acid glucoside were analyzed by negative ion CID mass spectra. The developed method was successfully applied to complex citrus samples for the separation and identification of aglycones and glucosides. Citrus seeds were extracted with methanol and partially purified and analyzed by LC-CID mass spectra. The separation was achieved by C-18 column; eight limonoids were identified by comparing the retention times and mass spectral fragmentation. To the best of our knowledge, this is the first report on the identification of citrus limonoids using CID technique. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Rigid body mode identification of the PAH-2 helicopter using the eigensystem realization algorithm

NASA Technical Reports Server (NTRS)

Schenk, Axel; Pappa, Richard S.

1992-01-01

The rigid body modes of the PAH-2 'Tiger' helicopter were identified using the Eigensystem Realization Algorithm (ERA). This work complements ground vibration tests performed using DLR's traditional phase resonance technique and the ISSPA (Identification of Structural System Parameters) method. Rigid body modal parameters are important for ground resonance prediction. Time-domain data for ERA were obtained by inverse Fourier transformation of frequency response functions measured with stepped-sine excitation. Mode purity (based on the Phase Resonance Criterion) was generally equal to or greater than corresponding results obtained in the ground vibration tests. All identified natural frequencies and mode shapes correlate well with corresponding ground vibration test results. The modal identification approach discussed in this report has become increasingly attractive in recent years due to the steadily declining cost and increased performance of scientific computers. As illustrated in this application, modern time-domain methods can be successfully applied to data acquired using DLR's existing test equipment. Some suggestions are made for future applications of time domain modal identification in this manner.

[Advances of studies on new technology and method for identifying traditional Chinese medicinal materials].

PubMed

Chen, Shilin; Guo, Baolin; Zhang, Guijun; Yan, Zhuyun; Luo, Guangming; Sun, Suqin; Wu, Hezhen; Huang, Linfang; Pang, Xiaohui; Chen, Jianbo

2012-04-01

In this review, the authors summarized the new technologies and methods for identifying traditional Chinese medicinal materials, including molecular identification, chemical identification, morphological identification, microscopic identification and identification based on biological effects. The authors introduced the principle, characteristics, application and prospect on each new technology or method and compared their advantages and disadvantages. In general, new methods make the result more objective and accurate. DNA barcoding technique and spectroscopy identification have their owner obvious strongpoint in universality and digitalization. In the near future, the two techniques are promising to be the main trend for identifying traditional Chinese medicinal materials. The identification techniques based on microscopy, liquid chromatography, PCR, biological effects and DNA chip will be indispensable supplements. However, the bionic identification technology is just placed in the developing stage at present.

Identification of microRNAs with regulatory potential using a matched microRNA-mRNA time-course data.

PubMed

Jayaswal, Vivek; Lutherborrow, Mark; Ma, David D F; Hwa Yang, Yee

2009-05-01

Over the past decade, a class of small RNA molecules called microRNAs (miRNAs) has been shown to regulate gene expression at the post-transcription stage. While early work focused on the identification of miRNAs using a combination of experimental and computational techniques, subsequent studies have focused on identification of miRNA-target mRNA pairs as each miRNA can have hundreds of mRNA targets. The experimental validation of some miRNAs as oncogenic has provided further motivation for research in this area. In this article we propose an odds-ratio (OR) statistic for identification of regulatory miRNAs. It is based on integrative analysis of matched miRNA and mRNA time-course microarray data. The OR-statistic was used for (i) identification of miRNAs with regulatory potential, (ii) identification of miRNA-target mRNA pairs and (iii) identification of time lags between changes in miRNA expression and those of its target mRNAs. We applied the OR-statistic to a cancer data set and identified a small set of miRNAs that were negatively correlated to mRNAs. A literature survey revealed that some of the miRNAs that were predicted to be regulatory, were indeed oncogenic or tumor suppressors. Finally, some of the predicted miRNA targets have been shown to be experimentally valid.

The role of chemometrics in single and sequential extraction assays: a review. Part II. Cluster analysis, multiple linear regression, mixture resolution, experimental design and other techniques.

PubMed

Giacomino, Agnese; Abollino, Ornella; Malandrino, Mery; Mentasti, Edoardo

2011-03-04

Single and sequential extraction procedures are used for studying element mobility and availability in solid matrices, like soils, sediments, sludge, and airborne particulate matter. In the first part of this review we reported an overview on these procedures and described the applications of chemometric uni- and bivariate techniques and of multivariate pattern recognition techniques based on variable reduction to the experimental results obtained. The second part of the review deals with the use of chemometrics not only for the visualization and interpretation of data, but also for the investigation of the effects of experimental conditions on the response, the optimization of their values and the calculation of element fractionation. We will describe the principles of the multivariate chemometric techniques considered, the aims for which they were applied and the key findings obtained. The following topics will be critically addressed: pattern recognition by cluster analysis (CA), linear discriminant analysis (LDA) and other less common techniques; modelling by multiple linear regression (MLR); investigation of spatial distribution of variables by geostatistics; calculation of fractionation patterns by a mixture resolution method (Chemometric Identification of Substrates and Element Distributions, CISED); optimization and characterization of extraction procedures by experimental design; other multivariate techniques less commonly applied. Copyright © 2010 Elsevier B.V. All rights reserved.

NASA standard: Trend analysis techniques

NASA Technical Reports Server (NTRS)

1988-01-01

This Standard presents descriptive and analytical techniques for NASA trend analysis applications. Trend analysis is applicable in all organizational elements of NASA connected with, or supporting, developmental/operational programs. Use of this Standard is not mandatory; however, it should be consulted for any data analysis activity requiring the identification or interpretation of trends. Trend Analysis is neither a precise term nor a circumscribed methodology, but rather connotes, generally, quantitative analysis of time-series data. For NASA activities, the appropriate and applicable techniques include descriptive and graphical statistics, and the fitting or modeling of data by linear, quadratic, and exponential models. Usually, but not always, the data is time-series in nature. Concepts such as autocorrelation and techniques such as Box-Jenkins time-series analysis would only rarely apply and are not included in this Standard. The document presents the basic ideas needed for qualitative and quantitative assessment of trends, together with relevant examples. A list of references provides additional sources of information.

Apps to promote physical activity among adults: a review and content analysis.

PubMed

Middelweerd, Anouk; Mollee, Julia S; van der Wal, C Natalie; Brug, Johannes; Te Velde, Saskia J

2014-07-25

In May 2013, the iTunes and Google Play stores contained 23,490 and 17,756 smartphone applications (apps) categorized as Health and Fitness, respectively. The quality of these apps, in terms of applying established health behavior change techniques, remains unclear. The study sample was identified through systematic searches in iTunes and Google Play. Search terms were based on Boolean logic and included AND combinations for physical activity, healthy lifestyle, exercise, fitness, coach, assistant, motivation, and support. Sixty-four apps were downloaded, reviewed, and rated based on the taxonomy of behavior change techniques used in the interventions. Mean and ranges were calculated for the number of observed behavior change techniques. Using nonparametric tests, we compared the number of techniques observed in free and paid apps and in iTunes and Google Play. On average, the reviewed apps included 5 behavior change techniques (range 2-8). Techniques such as self-monitoring, providing feedback on performance, and goal-setting were used most frequently, whereas some techniques such as motivational interviewing, stress management, relapse prevention, self-talk, role models, and prompted barrier identification were not. No differences in the number of behavior change techniques between free and paid apps, or between the app stores were found. The present study demonstrated that apps promoting physical activity applied an average of 5 out of 23 possible behavior change techniques. This number was not different for paid and free apps or between app stores. The most frequently used behavior change techniques in apps were similar to those most frequently used in other types of physical activity promotion interventions.

Standoff detection: classification of biological aerosols using laser induced fluorescence (LIF) technique

NASA Astrophysics Data System (ADS)

Hausmann, Anita; Duschek, Frank; Fischbach, Thomas; Pargmann, Carsten; Aleksejev, Valeri; Poryvkina, Larisa; Sobolev, Innokenti; Babichenko, Sergey; Handke, Jürgen

2014-05-01

The challenges of detecting hazardous biological materials are manifold: Such material has to be discriminated from other substances in various natural surroundings. The detection sensitivity should be extremely high. As living material may reproduce itself, already one single bacterium may represent a high risk. Of course, identification should be quite fast with a low false alarm rate. Up to now, there is no single technique to solve this problem. Point sensors may collect material and identify it, but the problems of fast identification and especially of appropriate positioning of local collectors are sophisticated. On the other hand, laser based standoff detection may instantaneously provide the information of some accidental spillage of material by detecting the generated thin cloud. LIF technique may classify but hardly identify the substance. A solution can be the use of LIF technique in a first step to collect primary data and - if necessary- followed by utilizing these data for an optimized positioning of point sensors. We perform studies on an open air laser test range at distances between 20 and 135 m applying LIF technique to detect and classify aerosols. In order to employ LIF capability, we use a laser source emitting two wavelengths alternatively, 280 and 355 nm, respectively. Moreover, the time dependence of fluorescence spectra is recorded by a gated intensified CCD camera. Signal processing is performed by dedicated software for spectral pattern recognition. The direct comparison of all results leads to a basic classification of the various compounds.

Olive oil sensory defects classification with data fusion of instrumental techniques and multivariate analysis (PLS-DA).

PubMed

Borràs, Eva; Ferré, Joan; Boqué, Ricard; Mestres, Montserrat; Aceña, Laura; Calvo, Angels; Busto, Olga

2016-07-15

Three instrumental techniques, headspace-mass spectrometry (HS-MS), mid-infrared spectroscopy (MIR) and UV-visible spectrophotometry (UV-vis), have been combined to classify virgin olive oil samples based on the presence or absence of sensory defects. The reference sensory values were provided by an official taste panel. Different data fusion strategies were studied to improve the discrimination capability compared to using each instrumental technique individually. A general model was applied to discriminate high-quality non-defective olive oils (extra-virgin) and the lowest-quality olive oils considered non-edible (lampante). A specific identification of key off-flavours, such as musty, winey, fusty and rancid, was also studied. The data fusion of the three techniques improved the classification results in most of the cases. Low-level data fusion was the best strategy to discriminate musty, winey and fusty defects, using HS-MS, MIR and UV-vis, and the rancid defect using only HS-MS and MIR. The mid-level data fusion approach using partial least squares-discriminant analysis (PLS-DA) scores was found to be the best strategy for defective vs non-defective and edible vs non-edible oil discrimination. However, the data fusion did not sufficiently improve the results obtained by a single technique (HS-MS) to classify non-defective classes. These results indicate that instrumental data fusion can be useful for the identification of sensory defects in virgin olive oils. Copyright © 2016 Elsevier Ltd. All rights reserved.

A novel universal real-time PCR system using the attached universal duplex probes for quantitative analysis of nucleic acids

PubMed Central

Yang, Litao; Liang, Wanqi; Jiang, Lingxi; Li, Wenquan; Cao, Wei; Wilson, Zoe A; Zhang, Dabing

2008-01-01

Background Real-time PCR techniques are being widely used for nucleic acids analysis, but one limitation of current frequently employed real-time PCR is the high cost of the labeled probe for each target molecule. Results We describe a real-time PCR technique employing attached universal duplex probes (AUDP), which has the advantage of generating fluorescence by probe hydrolysis and strand displacement over current real-time PCR methods. AUDP involves one set of universal duplex probes in which the 5' end of the fluorescent probe (FP) and a complementary quenching probe (QP) lie in close proximity so that fluorescence can be quenched. The PCR primer pair with attached universal template (UT) and the FP are identical to the UT sequence. We have shown that the AUDP technique can be used for detecting multiple target DNA sequences in both simplex and duplex real-time PCR assays for gene expression analysis, genotype identification, and genetically modified organism (GMO) quantification with comparable sensitivity, reproducibility, and repeatability with other real-time PCR methods. Conclusion The results from GMO quantification, gene expression analysis, genotype identification, and GMO quantification using AUDP real-time PCR assays indicate that the AUDP real-time PCR technique has been successfully applied in nucleic acids analysis, and the developed AUDP real-time PCR technique will offer an alternative way for nucleic acid analysis with high efficiency, reliability, and flexibility at low cost. PMID:18522756

Tumor or abnormality identification from magnetic resonance images using statistical region fusion based segmentation.

PubMed

Subudhi, Badri Narayan; Thangaraj, Veerakumar; Sankaralingam, Esakkirajan; Ghosh, Ashish

2016-11-01

In this article, a statistical fusion based segmentation technique is proposed to identify different abnormality in magnetic resonance images (MRI). The proposed scheme follows seed selection, region growing-merging and fusion of multiple image segments. In this process initially, an image is divided into a number of blocks and for each block we compute the phase component of the Fourier transform. The phase component of each block reflects the gray level variation among the block but contains a large correlation among them. Hence a singular value decomposition (SVD) technique is adhered to generate a singular value of each block. Then a thresholding procedure is applied on these singular values to identify edgy and smooth regions and some seed points are selected for segmentation. By considering each seed point we perform a binary segmentation of the complete MRI and hence with all seed points we get an equal number of binary images. A parcel based statistical fusion process is used to fuse all the binary images into multiple segments. Effectiveness of the proposed scheme is tested on identifying different abnormalities: prostatic carcinoma detection, tuberculous granulomas identification and intracranial neoplasm or brain tumor detection. The proposed technique is established by comparing its results against seven state-of-the-art techniques with six performance evaluation measures. Copyright © 2016 Elsevier Inc. All rights reserved.

Use of simulated experiments for material characterization of brittle materials subjected to high strain rate dynamic tension

PubMed Central

Saletti, Dominique

2017-01-01

Rapid progress in ultra-high-speed imaging has allowed material properties to be studied at high strain rates by applying full-field measurements and inverse identification methods. Nevertheless, the sensitivity of these techniques still requires a better understanding, since various extrinsic factors present during an actual experiment make it difficult to separate different sources of errors that can significantly affect the quality of the identified results. This study presents a methodology using simulated experiments to investigate the accuracy of the so-called spalling technique (used to study tensile properties of concrete subjected to high strain rates) by numerically simulating the entire identification process. The experimental technique uses the virtual fields method and the grid method. The methodology consists of reproducing the recording process of an ultra-high-speed camera by generating sequences of synthetically deformed images of a sample surface, which are then analysed using the standard tools. The investigation of the uncertainty of the identified parameters, such as Young's modulus along with the stress–strain constitutive response, is addressed by introducing the most significant user-dependent parameters (i.e. acquisition speed, camera dynamic range, grid sampling, blurring), proving that the used technique can be an effective tool for error investigation. This article is part of the themed issue ‘Experimental testing and modelling of brittle materials at high strain rates’. PMID:27956505

Dynamic Parameter Identification of Subject-Specific Body Segment Parameters Using Robotics Formalism: Case Study Head Complex.

PubMed

Díaz-Rodríguez, Miguel; Valera, Angel; Page, Alvaro; Besa, Antonio; Mata, Vicente

2016-05-01

Accurate knowledge of body segment inertia parameters (BSIP) improves the assessment of dynamic analysis based on biomechanical models, which is of paramount importance in fields such as sport activities or impact crash test. Early approaches for BSIP identification rely on the experiments conducted on cadavers or through imaging techniques conducted on living subjects. Recent approaches for BSIP identification rely on inverse dynamic modeling. However, most of the approaches are focused on the entire body, and verification of BSIP for dynamic analysis for distal segment or chain of segments, which has proven to be of significant importance in impact test studies, is rarely established. Previous studies have suggested that BSIP should be obtained by using subject-specific identification techniques. To this end, our paper develops a novel approach for estimating subject-specific BSIP based on static and dynamics identification models (SIM, DIM). We test the validity of SIM and DIM by comparing the results using parameters obtained from a regression model proposed by De Leva (1996, "Adjustments to Zatsiorsky-Seluyanov's Segment Inertia Parameters," J. Biomech., 29(9), pp. 1223-1230). Both SIM and DIM are developed considering robotics formalism. First, the static model allows the mass and center of gravity (COG) to be estimated. Second, the results from the static model are included in the dynamics equation allowing us to estimate the moment of inertia (MOI). As a case study, we applied the approach to evaluate the dynamics modeling of the head complex. Findings provide some insight into the validity not only of the proposed method but also of the application proposed by De Leva (1996, "Adjustments to Zatsiorsky-Seluyanov's Segment Inertia Parameters," J. Biomech., 29(9), pp. 1223-1230) for dynamic modeling of body segments.

On the prompt identification of traces of explosives

NASA Astrophysics Data System (ADS)

Trobajo, M. T.; López-Cabeceira, M. M.; Carriegos, M. V.; Díez-Machío, H.

2014-12-01

Some recent results in the use of Raman spectroscopy for recognition of explosives are reviewed. Experimental study using spectra data base has been developed. In order to simulate a more real situation, both blank substances and explosives substances have been considered in this research. Statistic classification techniques have been performed. Estimations of prediction errors were obtained by cross-validation methods. These results can be applied in airport security systems in order to prevent terror acts (by the detection of explosive/flammable substances).

Changing vacancy balance in ZnO by tuning synthesis between zinc/oxygen lean conditions

NASA Astrophysics Data System (ADS)

Venkatachalapathy, Vishnukanthan; Galeckas, Augustinas; Zubiaga, Asier; Tuomisto, Filip; Kuznetsov, Andrej Yu.

2010-08-01

The nature of intrinsic defects in ZnO films grown by metal organic vapor phase epitaxy was studied by positron annihilation and photoluminescence spectroscopy techniques. The supply of Zn and O during the film synthesis was varied by applying different growth temperatures (325-485 °C), affecting decomposition of the metal organic precursors. The microscopic identification of vacancy complexes was derived from a systematic variation in the defect balance in accordance with Zn/O supply trends.

Positron lifetime beam for defect studies in thin epitaxial semiconductor structures

NASA Astrophysics Data System (ADS)

Laakso, A.; Saarinen, K.; Hautojärvi, P.

2001-12-01

Positron annihilation spectroscopies are methods for direct identification of vacancy-type defects by measuring positron lifetime and Doppler broadening of annihilation radiation and providing information about open volume, concentration and atoms surrounding the defect. Both these techniques are easily applied to bulk samples. Only the Doppler broadening spectroscopy can be employed in thin epitaxial samples by utilizing low-energy positron beams. Here we describe the positron lifetime beam which will provide us with a method to measure lifetime in thin semiconductor layers.

Diagnostic Molecular Microbiology: A 2018 Snapshot.

PubMed

Fairfax, Marilynn Ransom; Bluth, Martin H; Salimnia, Hossein

2018-06-01

Molecular biological techniques have evolved expeditiously and in turn have been applied to the detection of infectious disease. Maturation of these technologies and their coupling with related technological advancement in fluorescence, electronics, digitization, nanodynamics, and sensors among others have afforded clinical medicine additional tools toward expedient identification of infectious organisms at concentrations and sensitivities previously unattainable. These advancements have been adapted in select settings toward addressing clinical demands for more timely and effective patient management. Copyright © 2018 Elsevier Inc. All rights reserved.

UV gated Raman spectroscopy for standoff detection of explosives

NASA Astrophysics Data System (ADS)

Gaft, M.; Nagli, L.

2008-07-01

Real-time detection and identification of explosives at a standoff distance is a major issue in efforts to develop defense against so-called improvised explosive devices (IED). It is recognized that the only method, which is potentially capable to standoff detection of minimal amounts of explosives is laser-based spectroscopy. LDS technique belongs to trace detection, namely to its micro-particles variety. It is based on commonly held belief that surface contamination was very difficult to avoid and could be exploited for standoff detection. We have applied gated Raman spectroscopy for detection of main explosive materials, both factory and homemade. We developed and tested a Raman system for the field remote detection and identification of minimal amounts of explosives on relevant surfaces at a distance of up to 30 m.

VizieR Online Data Catalog: SDSS DR7 white dwarf catalog (Kleinman+, 2013)

NASA Astrophysics Data System (ADS)

Kleinman, S. J.; Kepler, S. O.; Koester, D.; Pelisoli, I.; Pecanha, V.; Nitta, A.; Costa, J. E. S.; Krzesinski, J.; Dufour, P.; Lachapelle, F.-R.; Bergeron, P.; Yip, C.-W.; Harris, H. C.; Eisenstein, D. J.; Althaus, L.; Corsico, A.

2013-01-01

Here, we report on the white dwarf catalog built from the SDSS DR7 (Cat. II/294). We have applied automated techniques supplemented by complete, consistent human identifications of each candidate white dwarf spectrum. We make use of the latest SDSS reductions and white dwarf model atmosphere improvements in our spectral fits, providing logg and Teff determinations for each identified clean DA and DB where we use the word "clean" to identify spectra that show only features of non-magnetic, nonmixed, DA or DB stars. Our catalog includes all white dwarf stars from the earlier Kleinman et al. (2004, Cat. J/ApJ/607/426) and Eisenstein et al. (2006, Cat. J/ApJS/167/40) catalogs, although occasionally with different identifications. (1 data file).

⁶Li-loaded directionally sensitive anti-neutrino detector for possible geo-neutrinographic imaging applications.

PubMed

Tanaka, H K M; Watanabe, H

2014-04-24

Despite the latent and unique benefits of imaging uranium and thorium's distribution in the earth's interior, previously proposed experimental techniques used to identify the incoming geo-neutrino's direction are not applicable to practical imaging due to the high miss-identification in a neutrino's track reconstruction. After performing experimental studies and Monte-Carlo simulations, we confirmed that a significant improvement is possible in neutrino tracking identification with a (6)Li-loaded neutrino detector. For possible imaging applications, we also explore the feasibility of producing geo-neutrinographic images of gigantic magmatic reservoirs and deep structure in the mantle. We anticipate and plan to apply these newly designed detectors to radiographic imaging of the Earth's interior, monitoring of nuclear reactors, and tracking astrophysical sources of neutrinos.

6Li-loaded directionally sensitive anti-neutrino detector for possible geo-neutrinographic imaging applications

PubMed Central

Tanaka, H. K. M.; Watanabe, H.

2014-01-01

Despite the latent and unique benefits of imaging uranium and thorium's distribution in the earth's interior, previously proposed experimental techniques used to identify the incoming geo-neutrino's direction are not applicable to practical imaging due to the high miss-identification in a neutrino's track reconstruction. After performing experimental studies and Monte-Carlo simulations, we confirmed that a significant improvement is possible in neutrino tracking identification with a 6Li-loaded neutrino detector. For possible imaging applications, we also explore the feasibility of producing geo-neutrinographic images of gigantic magmatic reservoirs and deep structure in the mantle. We anticipate and plan to apply these newly designed detectors to radiographic imaging of the Earth's interior, monitoring of nuclear reactors, and tracking astrophysical sources of neutrinos. PMID:24759616

A Statistical Methodology for Detecting and Monitoring Change in Forest Ecosystems Using Remotely Sensed Imagery

NASA Astrophysics Data System (ADS)

Mills, R. T.; Kumar, J.; Hoffman, F. M.; Hargrove, W. W.; Spruce, J.

2011-12-01

Variations in vegetation phenology, the annual temporal pattern of leaf growth and senescence, can be a strong indicator of ecological change or disturbance. However, phenology is also strongly influenced by seasonal, interannual, and long-term trends in climate, making identification of changes in forest ecosystems a challenge. Forest ecosystems are vulnerable to extreme weather events, insect and disease attacks, wildfire, harvesting, and other land use change. Normalized difference vegetation index (NDVI), a remotely sensed measure of greenness, provides a proxy for phenology. NDVI for the conterminous United States (CONUS) derived from the Moderate Resolution Spectroradiometer (MODIS) at 250 m resolution was used in this study to develop phenological signatures of ecological regimes called phenoregions. By applying a quantitative data mining technique to the NDVI measurements for every eight days over the entire MODIS record, annual maps of phenoregions were developed. This geospatiotemporal cluster analysis technique employs high performance computing resources, enabling analysis of such very large data sets. This technique produces a prescribed number of prototypical phenological states to which every location belongs in any year. Analysis of the shifts among phenological states yields information about responses to interannual climate variability and, more importantly, changes in ecosystem health due to disturbances. Moreover, a large change in the phenological states occupied by a single location over time indicates a significant disturbance or ecological shift. This methodology has been applied for identification of various forest disturbance events, including wildfire, tree mortality due to Mountain Pine Beetle, and other insect infestation and diseases, as well as extreme events like storms and hurricanes in the U.S. Presented will be results from analysis of phenological state dynamics, along with disturbance and validation data.

Extending birthday paradox theory to estimate the number of tags in RFID systems.

PubMed

Shakiba, Masoud; Singh, Mandeep Jit; Sundararajan, Elankovan; Zavvari, Azam; Islam, Mohammad Tariqul

2014-01-01

The main objective of Radio Frequency Identification systems is to provide fast identification for tagged objects. However, there is always a chance of collision, when tags transmit their data to the reader simultaneously. Collision is a time-consuming event that reduces the performance of RFID systems. Consequently, several anti-collision algorithms have been proposed in the literature. Dynamic Framed Slotted ALOHA (DFSA) is one of the most popular of these algorithms. DFSA dynamically modifies the frame size based on the number of tags. Since the real number of tags is unknown, it needs to be estimated. Therefore, an accurate tag estimation method has an important role in increasing the efficiency and overall performance of the tag identification process. In this paper, we propose a novel estimation technique for DFSA anti-collision algorithms that applies birthday paradox theory to estimate the number of tags accurately. The analytical discussion and simulation results prove that the proposed method increases the accuracy of tag estimation and, consequently, outperforms previous schemes.

Towards writing the encyclopaedia of life: an introduction to DNA barcoding

PubMed Central

Savolainen, Vincent; Cowan, Robyn S; Vogler, Alfried P; Roderick, George K; Lane, Richard

2005-01-01

An international consortium of major natural history museums, herbaria and other organizations has launched an ambitious project, the ‘Barcode of Life Initiative’, to promote a process enabling the rapid and inexpensive identification of the estimated 10 million species on Earth. DNA barcoding is a diagnostic technique in which short DNA sequence(s) can be used for species identification. The first international scientific conference on Barcoding of Life was held at the Natural History Museum in London in February 2005, and here we review the scientific challenges discussed during this conference and in previous publications. Although still controversial, the scientific benefits of DNA barcoding include: (i) enabling species identification, including any life stage or fragment, (ii) facilitating species discoveries based on cluster analyses of gene sequences (e.g. cox1=CO1, in animals), (iii) promoting development of handheld DNA sequencing technology that can be applied in the field for biodiversity inventories and (iv) providing insight into the diversity of life. PMID:16214739

Modal Identification in an Automotive Multi-Component System Using HS 3D-DIC

PubMed Central

López-Alba, Elías; Felipe-Sesé, Luis; Díaz, Francisco A.

2018-01-01

The modal characterization of automotive lighting systems becomes difficult using sensors due to the light weight of the elements which compose the component as well as the intricate access to allocate them. In experimental modal analysis, high speed 3D digital image correlation (HS 3D-DIC) is attracting the attention since it provides full-field contactless measurements of 3D displacements as main advantage over other techniques. Different methodologies have been published that perform modal identification, i.e., natural frequencies, damping ratios, and mode shapes using the full-field information. In this work, experimental modal analysis has been performed in a multi-component automotive lighting system using HS 3D-DIC. Base motion excitation was applied to simulate operating conditions. A recently validated methodology has been employed for modal identification using transmissibility functions, i.e., the transfer functions from base motion tests. Results make it possible to identify local and global behavior of the different elements of injected polymeric and metallic materials. PMID:29401725

Identification tibia and fibula bone fracture location using scanline algorithm

NASA Astrophysics Data System (ADS)

Muchtar, M. A.; Simanjuntak, S. E.; Rahmat, R. F.; Mawengkang, H.; Zarlis, M.; Sitompul, O. S.; Winanto, I. D.; Andayani, U.; Syahputra, M. F.; Siregar, I.; Nasution, T. H.

2018-03-01

Fracture is a condition that there is a damage in the continuity of the bone, usually caused by stress, trauma or weak bones. The tibia and fibula are two separated-long bones in the lower leg, closely linked at the knee and ankle. Tibia/fibula fracture often happen when there is too much force applied to the bone that it can withstand. One of the way to identify the location of tibia/fibula fracture is to read X-ray image manually. Visual examination requires more time and allows for errors in identification due to the noise in image. In addition, reading X-ray needs highlighting background to make the objects in X-ray image appear more clearly. Therefore, a method is required to help radiologist to identify the location of tibia/fibula fracture. We propose some image-processing techniques for processing cruris image and Scan line algorithm for the identification of fracture location. The result shows that our proposed method is able to identify it and reach up to 87.5% of accuracy.

Extending Birthday Paradox Theory to Estimate the Number of Tags in RFID Systems

PubMed Central

Shakiba, Masoud; Singh, Mandeep Jit; Sundararajan, Elankovan; Zavvari, Azam; Islam, Mohammad Tariqul

2014-01-01

The main objective of Radio Frequency Identification systems is to provide fast identification for tagged objects. However, there is always a chance of collision, when tags transmit their data to the reader simultaneously. Collision is a time-consuming event that reduces the performance of RFID systems. Consequently, several anti-collision algorithms have been proposed in the literature. Dynamic Framed Slotted ALOHA (DFSA) is one of the most popular of these algorithms. DFSA dynamically modifies the frame size based on the number of tags. Since the real number of tags is unknown, it needs to be estimated. Therefore, an accurate tag estimation method has an important role in increasing the efficiency and overall performance of the tag identification process. In this paper, we propose a novel estimation technique for DFSA anti-collision algorithms that applies birthday paradox theory to estimate the number of tags accurately. The analytical discussion and simulation results prove that the proposed method increases the accuracy of tag estimation and, consequently, outperforms previous schemes. PMID:24752285

Identification of downy mildew resistance gene candidates by positional cloning in maize (Zea mays subsp. mays; Poaceae)1

PubMed Central

Kim, Jae Yoon; Moon, Jun-Cheol; Kim, Hyo Chul; Shin, Seungho; Song, Kitae; Kim, Kyung-Hee; Lee, Byung-Moo

2017-01-01

Premise of the study: Positional cloning in combination with phenotyping is a general approach to identify disease-resistance gene candidates in plants; however, it requires several time-consuming steps including population or fine mapping. Therefore, in the present study, we suggest a new combined strategy to improve the identification of disease-resistance gene candidates. Methods and Results: Downy mildew (DM)–resistant maize was selected from five cultivars using a spreader row technique. Positional cloning and bioinformatics tools were used to identify the DM-resistance quantitative trait locus marker (bnlg1702) and 47 protein-coding gene annotations. Eventually, five DM-resistance gene candidates, including bZIP34, Bak1, and Ppr, were identified by quantitative reverse-transcription PCR (RT-PCR) without fine mapping of the bnlg1702 locus. Conclusions: The combined protocol with the spreader row technique, quantitative trait locus positional cloning, and quantitative RT-PCR was effective for identifying DM-resistance candidate genes. This cloning approach may be applied to other whole-genome-sequenced crops or resistance to other diseases. PMID:28224059

Accurate Quantitation and Analysis of Nitrofuran Metabolites, Chloramphenicol, and Florfenicol in Seafood by Ultrahigh-Performance Liquid Chromatography-Tandem Mass Spectrometry: Method Validation and Regulatory Samples.

PubMed

Aldeek, Fadi; Hsieh, Kevin C; Ugochukwu, Obiadada N; Gerard, Ghislain; Hammack, Walter

2018-05-23

We developed and validated a method for the extraction, identification, and quantitation of four nitrofuran metabolites, 3-amino-2-oxazolidinone (AOZ), 3-amino-5-morpholinomethyl-2-oxazolidinone (AMOZ), semicarbazide (SC), and 1-aminohydantoin (AHD), as well as chloramphenicol and florfenicol in a variety of seafood commodities. Samples were extracted by liquid-liquid extraction techniques, analyzed by ultrahigh-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS), and quantitated using commercially sourced, derivatized nitrofuran metabolites, with their isotopically labeled internal standards in-solvent. We obtained recoveries of 90-100% at various fortification levels. The limit of detection (LOD) was set at 0.25 ng/g for AMOZ and AOZ, 1 ng/g for AHD and SC, and 0.1 ng/g for the phenicols. Various extraction methods, standard stability, derivatization efficiency, and improvements to conventional quantitation techniques were also investigated. We successfully applied this method to the identification and quantitation of nitrofuran metabolites and phenicols in 102 imported seafood products. Our results revealed that four of the samples contained residues from banned veterinary drugs.

Terahertz spectroscopic investigation of human gastric normal and tumor tissues

NASA Astrophysics Data System (ADS)

Hou, Dibo; Li, Xian; Cai, Jinhui; Ma, Yehao; Kang, Xusheng; Huang, Pingjie; Zhang, Guangxin

2014-09-01

Human dehydrated normal and cancerous gastric tissues were measured using transmission time-domain terahertz spectroscopy. Based on the obtained terahertz absorption spectra, the contrasts between the two kinds of tissue were investigated and techniques for automatic identification of cancerous tissue were studied. Distinctive differences were demonstrated in both the shape and amplitude of the absorption spectra between normal and tumor tissue. Additionally, some spectral features in the range of 0.2~0.5 THz and 1~1.5 THz were revealed for all cancerous gastric tissues. To systematically achieve the identification of gastric cancer, principal component analysis combined with t-test was used to extract valuable information indicating the best distinction between the two types. Two clustering approaches, K-means and support vector machine (SVM), were then performed to classify the processed terahertz data into normal and cancerous groups. SVM presented a satisfactory result with less false classification cases. The results of this study implicate the potential of the terahertz technique to detect gastric cancer. The applied data analysis methodology provides a suggestion for automatic discrimination of terahertz spectra in other applications.

Spatiotemporal topology and temporal sequence identification with an adaptive time-delay neural network

NASA Astrophysics Data System (ADS)

Lin, Daw-Tung; Ligomenides, Panos A.; Dayhoff, Judith E.

1993-08-01

Inspired from the time delays that occur in neurobiological signal transmission, we describe an adaptive time delay neural network (ATNN) which is a powerful dynamic learning technique for spatiotemporal pattern transformation and temporal sequence identification. The dynamic properties of this network are formulated through the adaptation of time-delays and synapse weights, which are adjusted on-line based on gradient descent rules according to the evolution of observed inputs and outputs. We have applied the ATNN to examples that possess spatiotemporal complexity, with temporal sequences that are completed by the network. The ATNN is able to be applied to pattern completion. Simulation results show that the ATNN learns the topology of a circular and figure eight trajectories within 500 on-line training iterations, and reproduces the trajectory dynamically with very high accuracy. The ATNN was also trained to model the Fourier series expansion of the sum of different odd harmonics. The resulting network provides more flexibility and efficiency than the TDNN and allows the network to seek optimal values for time-delays as well as optimal synapse weights.

Identification of unusual events in multi-channel bridge monitoring data

NASA Astrophysics Data System (ADS)

Omenzetter, Piotr; Brownjohn, James Mark William; Moyo, Pilate

2004-03-01

Continuously operating instrumented structural health monitoring (SHM) systems are becoming a practical alternative to replace visual inspection for assessment of condition and soundness of civil infrastructure such as bridges. However, converting large amounts of data from an SHM system into usable information is a great challenge to which special signal processing techniques must be applied. This study is devoted to identification of abrupt, anomalous and potentially onerous events in the time histories of static, hourly sampled strains recorded by a multi-sensor SHM system installed in a major bridge structure and operating continuously for a long time. Such events may result, among other causes, from sudden settlement of foundation, ground movement, excessive traffic load or failure of post-tensioning cables. A method of outlier detection in multivariate data has been applied to the problem of finding and localising sudden events in the strain data. For sharp discrimination of abrupt strain changes from slowly varying ones wavelet transform has been used. The proposed method has been successfully tested using known events recorded during construction of the bridge, and later effectively used for detection of anomalous post-construction events.

Ultrabroadband phased-array radio frequency (RF) receivers based on optical techniques

NASA Astrophysics Data System (ADS)

Overmiller, Brock M.; Schuetz, Christopher A.; Schneider, Garrett; Murakowski, Janusz; Prather, Dennis W.

2014-03-01

Military operations require the ability to locate and identify electronic emissions in the battlefield environment. However, recent developments in radio detection and ranging (RADAR) and communications technology are making it harder to effectively identify such emissions. Phased array systems aid in discriminating emitters in the scene by virtue of their relatively high-gain beam steering and nulling capabilities. For the purpose of locating emitters, we present an approach realize a broadband receiver based on optical processing techniques applied to the response of detectors in conformal antenna arrays. This approach utilizes photonic techniques that enable us to capture, route, and process the incoming signals. Optical modulators convert the incoming signals up to and exceeding 110 GHz with appreciable conversion efficiency and route these signals via fiber optics to a central processing location. This central processor consists of a closed loop phase control system which compensates for phase fluctuations induced on the fibers due to thermal or acoustic vibrations as well as an optical heterodyne approach for signal conversion down to baseband. Our optical heterodyne approach uses injection-locked paired optical sources to perform heterodyne downconversion/frequency identification of the detected emission. Preliminary geolocation and frequency identification testing of electronic emissions has been performed demonstrating the capabilities of our RF receiver.

Comparing the landcapes of common retroviral insertion sites across tumor models

NASA Astrophysics Data System (ADS)

Weishaupt, Holger; Čančer, Matko; Engström, Cristopher; Silvestrov, Sergei; Swartling, Fredrik J.

2017-01-01

Retroviral tagging represents an important technique, which allows researchers to screen for candidate cancer genes. The technique is based on the integration of retroviral sequences into the genome of a host organism, which might then lead to the artificial inhibition or expression of proximal genetic elements. The identification of potential cancer genes in this framework involves the detection of genomic regions (common insertion sites; CIS) which contain a number of such viral integration sites that is greater than expected by chance. During the last two decades, a number of different methods have been discussed for the identification of such loci and the respective techniques have been applied to a variety of different retroviruses and/or tumor models. We have previously established a retrovirus driven brain tumor model and reported the CISs which were found based on a Monte Carlo statistics derived detection paradigm. In this study, we consider a recently proposed alternative graph theory based method for identifying CISs and compare the resulting CIS landscape in our brain tumor dataset to those obtained when using the Monte Carlo approach. Finally, we also employ the graph-based method to compare the CIS landscape in our brain tumor model with those of other published retroviral tumor models.

Principal component analysis of normalized full spectrum mass spectrometry data in multiMS-toolbox: An effective tool to identify important factors for classification of different metabolic patterns and bacterial strains.

PubMed

Cejnar, Pavel; Kuckova, Stepanka; Prochazka, Ales; Karamonova, Ludmila; Svobodova, Barbora

2018-06-15

Explorative statistical analysis of mass spectrometry data is still a time-consuming step. We analyzed critical factors for application of principal component analysis (PCA) in mass spectrometry and focused on two whole spectrum based normalization techniques and their application in the analysis of registered peak data and, in comparison, in full spectrum data analysis. We used this technique to identify different metabolic patterns in the bacterial culture of Cronobacter sakazakii, an important foodborne pathogen. Two software utilities, the ms-alone, a python-based utility for mass spectrometry data preprocessing and peak extraction, and the multiMS-toolbox, an R software tool for advanced peak registration and detailed explorative statistical analysis, were implemented. The bacterial culture of Cronobacter sakazakii was cultivated on Enterobacter sakazakii Isolation Agar, Blood Agar Base and Tryptone Soya Agar for 24 h and 48 h and applied by the smear method on an Autoflex speed MALDI-TOF mass spectrometer. For three tested cultivation media only two different metabolic patterns of Cronobacter sakazakii were identified using PCA applied on data normalized by two different normalization techniques. Results from matched peak data and subsequent detailed full spectrum analysis identified only two different metabolic patterns - a cultivation on Enterobacter sakazakii Isolation Agar showed significant differences to the cultivation on the other two tested media. The metabolic patterns for all tested cultivation media also proved the dependence on cultivation time. Both whole spectrum based normalization techniques together with the full spectrum PCA allow identification of important discriminative factors in experiments with several variable condition factors avoiding any problems with improper identification of peaks or emphasis on bellow threshold peak data. The amounts of processed data remain still manageable. Both implemented software utilities are available free of charge from http://uprt.vscht.cz/ms. Copyright © 2018 John Wiley & Sons, Ltd.

Use of PCR-restriction fragment length polymorphism analysis for identification of yeast species isolated from bovine intramammary infection.

PubMed

Fadda, M E; Pisano, M B; Scaccabarozzi, L; Mossa, V; Deplano, M; Moroni, P; Liciardi, M; Cosentino, S

2013-01-01

This study reports a rapid PCR-based technique using a one-enzyme RFLP for discrimination of yeasts isolated from bovine clinical and subclinical mastitis milk samples. We analyzed a total of 1,486 milk samples collected over 1 yr in south Sardinia and northern Italy, and 142 yeast strains were preliminarily grouped based on their cultural morphology and physiological characteristics. Assimilation tests were conducted using the identification kit API ID 32C and APILAB Plus software (bioMérieux, Marcy l'Etoile, France). For PCR-RFLP analysis, the 18S-ITS1-5.8S ribosomal(r)DNA region was amplified and then digested with HaeIII, and dendrogram analysis of RFLP fragments was carried out. Furthermore, within each of the groups identified by the API or PCR-RFLP methods, the identification of isolates was confirmed by sequencing of the D1/D2 region using an ABI Prism 310 automatic sequencer (Applied Biosystems, Foster City, CA). The combined phenotypic and molecular approach enabled the identification of 17 yeast species belonging to the genera Candida (47.9%), Cryptococcus (21.1%), Trichosporon (19.7%), Geotrichum (7.1%), and Rhodotorula (4.2%). All Candida species were correctly identified by the API test and their identification confirmed by sequencing. All strains identified with the API system as Geotrichum candidum, Cryptococcus uniguttulatus, and Rhodotorula glutinis also produced characteristic restriction patterns and were confirmed as Galactomyces geotrichum (a teleomorph of G. candidum), Filobasidium uniguttulatum (teleomorph of Crypt. uniguttulatus), and R. glutinis, respectively, by D1/D2 rDNA sequencing. With regard to the genus Trichosporon, preliminary identification by API was problematic, whereas the RFLP technique used in this study gave characteristic restriction profiles for each species. Moreover, sequencing of the D1/D2 region allowed not only successful identification of Trichosporon gracile where API could not, but also correct identification of misidentified isolates. In conclusion, the 18S-ITS1-5.8S region appears to be useful in detecting genetic variability among yeast species, which is valuable for taxonomic purposes and for species identification. We have established an RFLP database for yeast species identified in milk samples using the software GelCompar II and the RFLP database constitutes an initial method for veterinary yeast identification. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Application of identification techniques to remote manipulator system flight data

NASA Technical Reports Server (NTRS)

Shepard, G. D.; Lepanto, J. A.; Metzinger, R. W.; Fogel, E.

1983-01-01

This paper addresses the application of identification techniques to flight data from the Space Shuttle Remote Manipulator System (RMS). A description of the remote manipulator, including structural and control system characteristics, sensors, and actuators is given. A brief overview of system identification procedures is presented, and the practical aspects of implementing system identification algorithms are discussed. In particular, the problems posed by desampling rate, numerical error, and system nonlinearities are considered. Simulation predictions of damping, frequency, and system order are compared with values identified from flight data to support an evaluation of RMS structural and control system models. Finally, conclusions are drawn regarding the application of identification techniques to flight data obtained from a flexible space structure.

Comparison of the techniques for the identification of the epidural space using the loss-of-resistance technique or an automated syringe - results of a randomized double-blind study.

PubMed

Duniec, Larysa; Nowakowski, Piotr; Sieczko, Jakub; Chlebus, Marcin; Łazowski, Tomasz

2016-01-01

The conventional, loss of resistance technique for identification of the epidural space is highly dependent on the anaesthetist's personal experience and is susceptible to technical errors. Therefore, an alternative, automated technique was devised to overcome the drawbacks of the traditional method. The aim of the study was to compare the efficacy of epidural space identification and the complication rate between the two groups - the automatic syringe and conventional loss of resistance methods. 47 patients scheduled for orthopaedic and gynaecology procedures under epidural anaesthesia were enrolled into the study. The number of attempts, ease of epidural space identification, complication rate and the patients' acceptance regarding the two techniques were evaluated. The majority of blocks were performed by trainee anaesthetists (91.5%). No statistical difference was found between the number of needle insertion attempts (1 vs. 2), the efficacy of epidural anaesthesia or the number of complications between the groups. The ease of epidural space identification, as assessed by an anaesthetist, was significantly better (P = 0.011) in the automated group (87.5% vs. 52.4%). A similar number of patients (92% vs. 94%) in both groups stated they would accept epidural anaesthesia in the future. The automated and loss of resistance methods of epidural space identification were proved to be equivalent in terms of efficacy and safety. Since the use of the automated technique may facilitate epidural space identification, it may be regarded as useful technique for anaesthetists inexperienced in epidural anaesthesia, or for trainees.

Automatic detection of adverse events to predict drug label changes using text and data mining techniques.

PubMed

Gurulingappa, Harsha; Toldo, Luca; Rajput, Abdul Mateen; Kors, Jan A; Taweel, Adel; Tayrouz, Yorki

2013-11-01

The aim of this study was to assess the impact of automatically detected adverse event signals from text and open-source data on the prediction of drug label changes. Open-source adverse effect data were collected from FAERS, Yellow Cards and SIDER databases. A shallow linguistic relation extraction system (JSRE) was applied for extraction of adverse effects from MEDLINE case reports. Statistical approach was applied on the extracted datasets for signal detection and subsequent prediction of label changes issued for 29 drugs by the UK Regulatory Authority in 2009. 76% of drug label changes were automatically predicted. Out of these, 6% of drug label changes were detected only by text mining. JSRE enabled precise identification of four adverse drug events from MEDLINE that were undetectable otherwise. Changes in drug labels can be predicted automatically using data and text mining techniques. Text mining technology is mature and well-placed to support the pharmacovigilance tasks. Copyright © 2013 John Wiley & Sons, Ltd.

Optical Fiber Protection

NASA Technical Reports Server (NTRS)

1999-01-01

F&S Inc. developed and commercialized fiber optic and microelectromechanical systems- (MEMS) based instrumentation for harsh environments encountered in the aerospace industry. The NASA SBIR programs have provided F&S the funds and the technology to develop ruggedized coatings and coating techniques that are applied during the optical fiber draw process. The F&S optical fiber fabrication facility and developed coating methods enable F&S to manufacture specialty optical fiber with custom designed refractive index profiles and protective or active coatings. F&S has demonstrated sputtered coatings using metals and ceramics and combinations of each, and has also developed techniques to apply thin coatings of specialized polyimides formulated at NASA Langley Research Center. With these capabilities, F&S has produced cost-effective, reliable instrumentation and sensors capable of withstanding temperatures up to 800? C and continues building commercial sales with corporate partners and private funding. More recently, F&S has adapted the same sensing platforms to provide the rapid detection and identification of chemical and biological agents

A comprehensive review on vanilla flavor: extraction, isolation and quantification of vanillin and others constituents.

PubMed

Sinha, Arun K; Sharma, Upendra K; Sharma, Nandini

2008-06-01

Vanilla, being the world's most popular flavoring materials, finds extensive applications in food, beverages, perfumery and pharmaceutical industry. With the high demand and limited supply of vanilla pods and the continuing increase in their cost, numerous efforts of blending and adulteration in natural vanilla extracts have been reported. Thus, to ensure the quality of vanilla extracts and vanilla-containing products, it is important to develop techniques to verify their authenticity. Quantitatively, vanillin is the major compound present in the vanilla pods and the determination of vanillin is a vital consideration in natural vanilla extracts. This paper provides a comprehensive account of different extraction processes and chromatographic techniques applied for the separation, identification and determination of chemical constituents of vanilla. The review also provides an account of different methods applied for the quantification and the authentification of chemical constituents of vanilla extract. As the various properties of vanilla are attributed to its main constituent vanillin, its physico-chemical and bioactive properties have also been outlined.

DCE-MRI: a review and applications in veterinary oncology.

PubMed

Boss, M Keara; Muradyan, N; Thrall, D E

2013-06-01

Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) is a functional imaging technique that assesses the physiology of tumour tissue by exploiting abnormal tumour microvasculature. Advances made through DCE-MRI include improvement in the diagnosis of cancer, optimization of treatment choices, assessment of treatment efficacy and non-invasive identification of prognostic information. DCE-MRI enables quantitative assessment of tissue vessel density, integrity, and permeability, and this information can be applied to study of angiogenesis, hypoxia and the evaluation of various biomarkers. Reproducibility of DCE-MRI results is important in determining the significance of observed changes in the parameters. As improvements are made towards the utility of DCE-MRI and interpreting biologic associations, the technique will be applied more frequently in the study of cancer in animals. Given the importance of tumour perfusion with respect to tumour oxygenation and drug delivery, the use of DCE-MRI is a convenient and powerful way to gain basic information about a tumour. © 2011 John Wiley & Sons Ltd.

Personal identification based on blood vessels of retinal fundus images

NASA Astrophysics Data System (ADS)

Fukuta, Keisuke; Nakagawa, Toshiaki; Hayashi, Yoshinori; Hatanaka, Yuji; Hara, Takeshi; Fujita, Hiroshi

2008-03-01

Biometric technique has been implemented instead of conventional identification methods such as password in computer, automatic teller machine (ATM), and entrance and exit management system. We propose a personal identification (PI) system using color retinal fundus images which are unique to each individual. The proposed procedure for identification is based on comparison of an input fundus image with reference fundus images in the database. In the first step, registration between the input image and the reference image is performed. The step includes translational and rotational movement. The PI is based on the measure of similarity between blood vessel images generated from the input and reference images. The similarity measure is defined as the cross-correlation coefficient calculated from the pixel values. When the similarity is greater than a predetermined threshold, the input image is identified. This means both the input and the reference images are associated to the same person. Four hundred sixty-two fundus images including forty-one same-person's image pairs were used for the estimation of the proposed technique. The false rejection rate and the false acceptance rate were 9.9×10 -5% and 4.3×10 -5%, respectively. The results indicate that the proposed method has a higher performance than other biometrics except for DNA. To be used for practical application in the public, the device which can take retinal fundus images easily is needed. The proposed method is applied to not only the PI but also the system which warns about misfiling of fundus images in medical facilities.

Isolation and identification of phenolic compounds from rum aged in oak barrels by high-speed countercurrent chromatography/high-performance liquid chromatography-diode array detection-electrospray ionization mass spectrometry and screening for antioxidant activity.

PubMed

Regalado, Erik L; Tolle, Sebastian; Pino, Jorge A; Winterhalter, Peter; Menendez, Roberto; Morales, Ana R; Rodríguez, José L

2011-10-14

Beverages, especially wines are well-known to contain a variety of health-beneficial bioactive substances, mainly of phenolic nature which frequently exhibit antioxidant activity. Significant information is available about the separation and identification of polyphenols from some beverages by chromatographic and spectroscopic techniques, but considerably poor is chemical data related to the polyphenolic content in rums. In this paper, a method involving the all-liquid chromatographic technique of high-speed countercurrent chromatography (HSCCC) combined with high-performance liquid chromatography coupled with diode-array detection and electrospray ionization mass spectrometry (HPLC-DAD-ESI-MS(n)) has been successfully applied for separation and identification of phenolic compounds in an aged rum. Besides, the phenolic fraction (PF) was assayed for its antioxidant effects using three different free radical in vitro assays (DPPH·, RO(2)· and spontaneous lipid peroxidation (LPO) on brain homogenates) and on ferric reducing antioxidant power (FRAP). Results showed that PF potently scavenged DPPH and strongly scavenged peroxyl radicals compared to ascorbic acid and butylated hydroxytoluene (BHT); and almost equally inhibited LPO on brain homogenates subjected to spontaneous LPO when compared to quercetin. Moreover, PF also exhibited strong reducing power. This chemical analysis illustrates the rich array of phenols in the aged rum and represents a rapid and suitable method for the isolation and identification of phenolic compounds from mixtures of considerable complexity, achieving high purity and reproducibility with the use of two separation steps. Copyright © 2011 Elsevier B.V. All rights reserved.

Estimation et validation des derivees de stabilite et controle du modele dynamique non-lineaire d'un drone a voilure fixe

NASA Astrophysics Data System (ADS)

Courchesne, Samuel

Knowledge of the dynamic characteristics of a fixed-wing UAV is necessary to design flight control laws and to conceive a high quality flight simulator. The basic features of a flight mechanic model include the properties of mass, inertia and major aerodynamic terms. They respond to a complex process involving various numerical analysis techniques and experimental procedures. This thesis focuses on the analysis of estimation techniques applied to estimate problems of stability and control derivatives from flight test data provided by an experimental UAV. To achieve this objective, a modern identification methodology (Quad-M) is used to coordinate the processing tasks from multidisciplinary fields, such as parameter estimation modeling, instrumentation, the definition of flight maneuvers and validation. The system under study is a non-linear model with six degrees of freedom with a linear aerodynamic model. The time domain techniques are used for identification of the drone. The first technique, the equation error method is used to determine the structure of the aerodynamic model. Thereafter, the output error method and filter error method are used to estimate the aerodynamic coefficients values. The Matlab scripts for estimating the parameters obtained from the American Institute of Aeronautics and Astronautics (AIAA) are used and modified as necessary to achieve the desired results. A commendable effort in this part of research is devoted to the design of experiments. This includes an awareness of the system data acquisition onboard and the definition of flight maneuvers. The flight tests were conducted under stable flight conditions and with low atmospheric disturbance. Nevertheless, the identification results showed that the filter error method is most effective for estimating the parameters of the drone due to the presence of process noise and measurement. The aerodynamic coefficients are validated using a numerical analysis of the vortex method. In addition, a simulation model incorporating the estimated parameters is used to compare the behavior of states measured. Finally, a good correspondence between the results is demonstrated despite a limited number of flight data. Keywords: drone, identification, estimation, nonlinear, flight test, system, aerodynamic coefficient.

Time domain nonlinear SMA damper force identification approach and its numerical validation

NASA Astrophysics Data System (ADS)

Xin, Lulu; Xu, Bin; He, Jia

2012-04-01

Most of the currently available vibration-based identification approaches for structural damage detection are based on eigenvalues and/or eigenvectors extracted from vibration measurements and, strictly speaking, are only suitable for linear system. However, the initiation and development of damage in engineering structures under severe dynamic loadings are typical nonlinear procedure. Studies on the identification of restoring force which is a direct indicator of the extent of the nonlinearity have received increasing attention in recent years. In this study, a date-based time domain identification approach for general nonlinear system was developed. The applied excitation and the corresponding response time series of the structure were used for identification by means of standard least-square techniques and a power series polynomial model (PSPM) which was utilized to model the nonlinear restoring force (NRF). The feasibility and robustness of the proposed approach was verified by a 2 degree-of-freedoms (DOFs) lumped mass numerical model equipped with a shape memory ally (SMA) damper mimicking nonlinear behavior. The results show that the proposed data-based time domain method is capable of identifying the NRF in engineering structures without any assumptions on the mass distribution and the topology of the structure, and provides a promising way for damage detection in the presence of structural nonlinearities.

Adaptive infinite impulse response system identification using modified-interior search algorithm with Lèvy flight.

PubMed

Kumar, Manjeet; Rawat, Tarun Kumar; Aggarwal, Apoorva

2017-03-01

In this paper, a new meta-heuristic optimization technique, called interior search algorithm (ISA) with Lèvy flight is proposed and applied to determine the optimal parameters of an unknown infinite impulse response (IIR) system for the system identification problem. ISA is based on aesthetics, which is commonly used in interior design and decoration processes. In ISA, composition phase and mirror phase are applied for addressing the nonlinear and multimodal system identification problems. System identification using modified-ISA (M-ISA) based method involves faster convergence, single parameter tuning and does not require derivative information because it uses a stochastic random search using the concepts of Lèvy flight. A proper tuning of control parameter has been performed in order to achieve a balance between intensification and diversification phases. In order to evaluate the performance of the proposed method, mean square error (MSE), computation time and percentage improvement are considered as the performance measure. To validate the performance of M-ISA based method, simulations has been carried out for three benchmarked IIR systems using same order and reduced order system. Genetic algorithm (GA), particle swarm optimization (PSO), cat swarm optimization (CSO), cuckoo search algorithm (CSA), differential evolution using wavelet mutation (DEWM), firefly algorithm (FFA), craziness based particle swarm optimization (CRPSO), harmony search (HS) algorithm, opposition based harmony search (OHS) algorithm, hybrid particle swarm optimization-gravitational search algorithm (HPSO-GSA) and ISA are also used to model the same examples and simulation results are compared. Obtained results confirm the efficiency of the proposed method. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Validation of MALDI-TOF MS for rapid classification and identification of lactic acid bacteria, with a focus on isolates from traditional fermented foods in Northern Vietnam.

PubMed

Doan, N T L; Van Hoorde, K; Cnockaert, M; De Brandt, E; Aerts, M; Le Thanh, B; Vandamme, P

2012-10-01

To evaluate the potential use of MALDI-TOF MS for fast and reliable classification and identification of lactic acid bacteria (LAB) from traditional fermented foods. A total of 119 strains of LAB from fermented meat (nem chua) were analysed with both (GTG)(5)-PCR fingerprinting and MALDI-TOF MS. Cluster analysis of the profiles revealed five species represented by a single isolate both in (GTG)(5)-PCR and in MALDI-TOF MS; five species grouped alike for (GTG)(5)-PCR and for MALDI-TOF MS; however, differences in minimal similarity between the delineated (GTG)(5)-PCR and MALDI-TOF MS clusters could be observed; three species showed more heterogeneity in their MALDI-TOF MS profiles compared to their (GTG)(5)-PCR profiles; two species, each represented by a single MALDI-TOF cluster, were subdivided in the corresponding (GTG)(5)-PCR dendrogram. As proof of the identification potential of MALDI-TOF MS, LAB diversity from one fermented mustard sample was analysed using MALDI-TOF MS. PheS gene sequencing was used for validation. MALDI-TOF MS is a powerful, fast, reliable and cost-effective technique for the identification of LAB associated with the production of fermented foods. Food LAB can be identified using MALDI-TOF MS, and its application could possibly be extended to other food matrices and/or other food-derived micro-organisms. © 2012 The Authors. Letters in Applied Microbiology © 2012 The Society for Applied Microbiology.

Raman identification of cuneiform tablet pigments: emphasis and colour technology in ancient Mesopotamian mid-third millennium.

PubMed

Chiriu, Daniele; Ricci, Pier Carlo; Carbonaro, Carlo Maria; Nadali, Davide; Polcaro, Andrea; Collins, Paul

2017-03-01

Cuneiform tablets tell the life and culture of Sumerian people in a sort of black and white tale because of the binary engraving technique. A leading question arises: did Mesopotamian people apply some kind of colour to decorate their tablets or to put emphasis on selected words? Some administrative and literary Sumerian cuneiform tablets of mid-third Millennium B.C. from the site of Kish (central Mesopotamia, modern Iraq) were dug up in twentieth-century and stored at the Ashmolean Museum of the Oxford University. Non-destructive micro-Raman spectroscopy is a powerful technique to detect the presence of residual pigments eventually applied to the engraving signs. Yellow, orange, red and white pigments have been detected and a possible identification has been proposed in this work. In particular yellow pigments are identified as Crocoite (PbCrO 4 ), Lead stannate (Pb 2 SnO 4 ); red pigments - hematite (Fe 2 O 3 ) and cuprite (Cu 2 O); White pigments - Lead carbonate (PbCO 3 ), calcium phosphate (Ca 3 (PO 4 ) 2 ), titanium dioxide (TiO 2 ), gypsum (CaSO 4 .2H 2 O); orange pigment a composition of red and yellow compounds. These results suggest that Sumerian people invented a new editorial style, to overcome the binary logic of engraving process and catch the reader's eye by decorating cuneiform tablets. Finally, the coloured rendering of the tablet in their original view is proposed.

Laser micro-etching of metal prostheses for personal identification

PubMed Central

Ganapathy, Dhanraj; Sivaswamy, Vinay; Sekhar, Prathap

2017-01-01

Denture marking techniques play a vital role in establishing personal identification in suitable clinical and forensic situations. The denture marking techniques are categorized broadly into additive and ablative methods. Additive methods involve embedding or impregnation of markers for establishing personal identity. Ablative methods involve partial removal of the denture surface thereby providing a marking for identification. Engraving and etching methods are the commonly used ablative methods. Ablative methods can be of contact and noncontact subtypes. Laser micro-etching is a precise noncontact ablative denture marking technique that could be used for prostheses-guided personal identification. PMID:28584473

Laser micro-etching of metal prostheses for personal identification.

PubMed

Ganapathy, Dhanraj; Sivaswamy, Vinay; Sekhar, Prathap

2017-01-01

Denture marking techniques play a vital role in establishing personal identification in suitable clinical and forensic situations. The denture marking techniques are categorized broadly into additive and ablative methods. Additive methods involve embedding or impregnation of markers for establishing personal identity. Ablative methods involve partial removal of the denture surface thereby providing a marking for identification. Engraving and etching methods are the commonly used ablative methods. Ablative methods can be of contact and noncontact subtypes. Laser micro-etching is a precise noncontact ablative denture marking technique that could be used for prostheses-guided personal identification.

An overview of recent advances in system identification

NASA Technical Reports Server (NTRS)

Juang, Jer-Nan

1994-01-01

This paper presents an overview of the recent advances in system identification for modal testing and control of large flexible structures. Several techniques are discussed including the Observer/Kalman Filter Identification, the Observer/Controller Identification, and the State-Space System Identification in the Frequency Domain. The System/Observer/Controller Toolbox developed at NASA Langley Research Center is used to show the applications of these techniques to real aerospace structures such as the Hubble spacecraft telescope and the active flexible aircraft wing.

Criteria for opiate identification using liquid chromatography linked to tandem mass spectrometry: problems in routine practice.

PubMed

Fox, Elizabeth J; Twigger, Shirley; Allen, Keith R

2009-01-01

Liquid chromatography linked to tandem mass spectrometry (LC/MS/MS) is being increasingly used for drug confirmation. At present, no official criteria exist for drug identification using this technique although the European Union (EU) criteria for compound identification have been adopted. These criteria are evaluated with respect to opiate confirmation by LC/MS/MS and problems highlighted. Urine samples screened positive for opiates by immunoassay were subjected to confirmation by LC/MS/MS using multiple reaction monitoring (MRM) and two separate buffer systems of pH 6.8 and 8.0, respectively. The EU criteria for compound identification were applied for confirmation of morphine, 6-monoacetylmorphine (6MAM), codeine and dihydrocodeine (DHC). Using the pH 6.8 buffer, confirmation could be achieved for 84%, 94%, 96% and 95%, respectively, for samples demonstrating MRM chromatographic peaks at retention times for morphine, 6MAM, codeine and DHC. Failure to meet the EU criteria was mainly attributed to low signal-to-noise (S:N) ratios or excessively high drug concentrations. Isobaric interferences and poor chromatography were also contributing factors. The identification of morphine was considerably improved with chromatography at pH 8.0 owing to resolution of interferences. Oxycodone metabolites were a potential problem for the identification of DHC. Isobaric interferences can pose a problem with drug identification using LC/MS/MS. Optimizing chromatographic conditions is important to overcome these interferences. Consideration needs to be given to investigating drug metabolites as well as parent drugs in method development.

Accurate Identification of Cancerlectins through Hybrid Machine Learning Technology.

PubMed

Zhang, Jieru; Ju, Ying; Lu, Huijuan; Xuan, Ping; Zou, Quan

2016-01-01

Cancerlectins are cancer-related proteins that function as lectins. They have been identified through computational identification techniques, but these techniques have sometimes failed to identify proteins because of sequence diversity among the cancerlectins. Advanced machine learning identification methods, such as support vector machine and basic sequence features (n-gram), have also been used to identify cancerlectins. In this study, various protein fingerprint features and advanced classifiers, including ensemble learning techniques, were utilized to identify this group of proteins. We improved the prediction accuracy of the original feature extraction methods and classification algorithms by more than 10% on average. Our work provides a basis for the computational identification of cancerlectins and reveals the power of hybrid machine learning techniques in computational proteomics.

Identification of triacylglycerol using automated annotation of high resolution multistage mass spectral trees.

PubMed

Wang, Xiupin; Peng, Qingzhi; Li, Peiwu; Zhang, Qi; Ding, Xiaoxia; Zhang, Wen; Zhang, Liangxiao

2016-10-12

High complexity of identification for non-target triacylglycerols (TAGs) is a major challenge in lipidomics analysis. To identify non-target TAGs, a powerful tool named accurate MS(n) spectrometry generating so-called ion trees is used. In this paper, we presented a technique for efficient structural elucidation of TAGs on MS(n) spectral trees produced by LTQ Orbitrap MS(n), which was implemented as an open source software package, or TIT. The TIT software was used to support automatic annotation of non-target TAGs on MS(n) ion trees from a self-built fragment ion database. This database includes 19108 simulate TAG molecules from a random combination of fatty acids and corresponding 500582 self-built multistage fragment ions (MS ≤ 3). Our software can identify TAGs using a "stage-by-stage elimination" strategy. By utilizing the MS(1) accurate mass and referenced RKMD, the TIT software can discriminate unique elemental composition candidates. The regiospecific isomers of fatty acyl chains will be distinguished using MS(2) and MS(3) fragment spectra. We applied the algorithm to the selection of 45 TAG standards and demonstrated that the molecular ions could be 100% correctly assigned. Therefore, the TIT software could be applied to TAG identification in complex biological samples such as mouse plasma extracts. Copyright © 2016 Elsevier B.V. All rights reserved.

Apps to promote physical activity among adults: a review and content analysis

PubMed Central

2014-01-01

Background In May 2013, the iTunes and Google Play stores contained 23,490 and 17,756 smartphone applications (apps) categorized as Health and Fitness, respectively. The quality of these apps, in terms of applying established health behavior change techniques, remains unclear. Methods The study sample was identified through systematic searches in iTunes and Google Play. Search terms were based on Boolean logic and included AND combinations for physical activity, healthy lifestyle, exercise, fitness, coach, assistant, motivation, and support. Sixty-four apps were downloaded, reviewed, and rated based on the taxonomy of behavior change techniques used in the interventions. Mean and ranges were calculated for the number of observed behavior change techniques. Using nonparametric tests, we compared the number of techniques observed in free and paid apps and in iTunes and Google Play. Results On average, the reviewed apps included 5 behavior change techniques (range 2–8). Techniques such as self-monitoring, providing feedback on performance, and goal-setting were used most frequently, whereas some techniques such as motivational interviewing, stress management, relapse prevention, self-talk, role models, and prompted barrier identification were not. No differences in the number of behavior change techniques between free and paid apps, or between the app stores were found. Conclusions The present study demonstrated that apps promoting physical activity applied an average of 5 out of 23 possible behavior change techniques. This number was not different for paid and free apps or between app stores. The most frequently used behavior change techniques in apps were similar to those most frequently used in other types of physical activity promotion interventions. PMID:25059981

A system identification technique based on the random decrement signatures. Part 2: Experimental results

NASA Technical Reports Server (NTRS)

Bedewi, Nabih E.; Yang, Jackson C. S.

1987-01-01

Identification of the system parameters of a randomly excited structure may be treated using a variety of statistical techniques. Of all these techniques, the Random Decrement is unique in that it provides the homogeneous component of the system response. Using this quality, a system identification technique was developed based on a least-squares fit of the signatures to estimate the mass, damping, and stiffness matrices of a linear randomly excited system. The results of an experiment conducted on an offshore platform scale model to verify the validity of the technique and to demonstrate its application in damage detection are presented.

Applications of multi-frequency single beam sonar fisheries analysis methods for seep quantification and characterization

NASA Astrophysics Data System (ADS)

Price, V.; Weber, T.; Jerram, K.; Doucet, M.

2016-12-01

The analysis of multi-frequency, narrow-band single-beam acoustic data for fisheries applications has long been established, with methodology focusing on characterizing targets in the water column by utilizing complex algorithms and false-color time series data to create and compare frequency response curves for dissimilar biological groups. These methods were built on concepts developed for multi-frequency analysis of satellite imagery for terrestrial analysis and have been applied to a broad range of data types and applications. Single-beam systems operating at multiple frequencies are also used for the detection and identification of seeps in water column data. Here we incorporate the same analysis and visualization techniques used for fisheries applications to attempt to characterize and quantify seeps by creating and comparing frequency response curves and applying false coloration to shallow and deep multi-channel seep data. From this information, we can establish methods to differentiate bubble size in the echogram and differentiate seep composition. These techniques are also useful in differentiating plume content from biological noise (volume reverberation) created by euphausid layers and fish with gas-filled swim bladders. The combining of the multiple frequencies using false coloring and other image analysis techniques after applying established normalization and beam pattern correction algorithms is a novel approach to quantitatively describing seeps. Further, this information could be paired with geological models, backscatter, and bathymetry data to assess seep distribution.

[Groundwater organic pollution source identification technology system research and application].

PubMed

Wang, Xiao-Hong; Wei, Jia-Hua; Cheng, Zhi-Neng; Liu, Pei-Bin; Ji, Yi-Qun; Zhang, Gan

2013-02-01

Groundwater organic pollutions are found in large amount of locations, and the pollutions are widely spread once onset; which is hard to identify and control. The key process to control and govern groundwater pollution is how to control the sources of pollution and reduce the danger to groundwater. This paper introduced typical contaminated sites as an example; then carried out the source identification studies and established groundwater organic pollution source identification system, finally applied the system to the identification of typical contaminated sites. First, grasp the basis of the contaminated sites of geological and hydrogeological conditions; determine the contaminated sites characteristics of pollutants as carbon tetrachloride, from the large numbers of groundwater analysis and test data; then find the solute transport model of contaminated sites and compound-specific isotope techniques. At last, through groundwater solute transport model and compound-specific isotope technology, determine the distribution of the typical site of organic sources of pollution and pollution status; invest identified potential sources of pollution and sample the soil to analysis. It turns out that the results of two identified historical pollution sources and pollutant concentration distribution are reliable. The results provided the basis for treatment of groundwater pollution.

Investigating Montara platform oil spill accident by implementing RST-OIL approach.

NASA Astrophysics Data System (ADS)

Satriano, Valeria; Ciancia, Emanuele; Coviello, Irina; Di Polito, Carmine; Lacava, Teodosio; Pergola, Nicola; Tramutoli, Valerio

2016-04-01

Oil Spills represent one of the most harmful events to marine ecosystems and their timely detection is crucial for their mitigation and management. The potential of satellite data for their detection and monitoring has been largely investigated. Traditional satellite techniques usually identify oil spill presence applying a fixed threshold scheme only after the occurrence of an event, which make them not well suited for their prompt identification. The Robust Satellite Technique (RST) approach, in its oil spill detection version (RST-OIL), being based on the comparison of the latest satellite acquisition with its historical value, previously identified, allows the automatic and near real-time detection of events. Such a technique has been already successfully applied on data from different sources (AVHRR-Advanced Very High Resolution Radiometer and MODIS-Moderate Resolution Imaging Spectroradiometer) showing excellent performance in detecting oil spills both during day- and night-time conditions, with an high level of sensitivity (detection also of low intensity events) and reliability (no false alarm on scene). In this paper, RST-OIL has been implemented on MODIS thermal infrared data for the analysis of the Montara Platform (Timor Sea - Australia) oil spill disaster occurred in August 2009. Preliminary achievements are presented and discussed in this paper.

Comparing the Identification of Recommendations by Different Accident Investigators Using a Common Methodology

NASA Technical Reports Server (NTRS)

Johnson, Chris W.; Oltedal, H. A.; Holloway, C. M.

2012-01-01

Accident reports play a key role in the safety of complex systems. These reports present the recommendations that are intended to help avoid any recurrence of past failures. However, the value of these findings depends upon the causal analysis that helps to identify the reasons why an accident occurred. Various techniques have been developed to help investigators distinguish root causes from contributory factors and contextual information. This paper presents the results from a study into the individual differences that can arise when a group of investigators independently apply the same technique to identify the causes of an accident. This work is important if we are to increase the consistency and coherence of investigations following major accidents.

Palaeogenetic analysis of (pre)historic artifacts and its significance for anthropology.

PubMed

Burger, J; Hummel, S; Pfeiffer, I; Herrmann, B

2000-03-01

The possibility of isolating ancient DNA (aDNA) from all kinds of (pre)historic anthropogenetic artifacts opens new perspectives. This study applies palaeogenetic techniques to three anthropological issues: 1. Palaeodiet. DNA sequences from organic residues in vessels identify Precolumbian Aztec diet. 2. (Pre)historic husbandry and economic structures. aDNA data can reveal the species and the genetic evolutionary stage of animals and plants and show the manner and the extent of their growth, cultivation, or domestication. 3. Production techniques, use, and functionality. Identification of the plant or animal source of an archaeological find can reveal the use or the function of the find. Examples from a Celtic "sausage-end" and an Aztec "eye salve" are given.

[Controversial Issues in Economic Evaluation (III): health Care Interventions in Special Situations].

PubMed

Espín Balbino, Jaime; Brosa Riestra, Max; Oliva Moreno, Juan; Trapero-Bertran, Marta

2015-01-01

The development of the economic evaluation of health care interventions has become a support tool in making decisions on pricing and reimbursement of new health interventions. The increasingly extensive application of these techniques has led to the identification of particular situations in which, for various reasons, it may be reasonable to take into account special considerations when applying the general principles of economic evaluation. In this article, which closes a series of three, we will discuss, using the Metaplan technique, about the economic evaluation of health interventions in special situations such as rare diseases and end of life treatments, as well as consideration of externalities in assessments, finally pointing out some research areas to solve the main problems identified in these fields.

Optogenetic Approaches to Drug Discovery in Neuroscience and Beyond.

PubMed

Zhang, Hongkang; Cohen, Adam E

2017-07-01

Recent advances in optogenetics have opened new routes to drug discovery, particularly in neuroscience. Physiological cellular assays probe functional phenotypes that connect genomic data to patient health. Optogenetic tools, in particular tools for all-optical electrophysiology, now provide a means to probe cellular disease models with unprecedented throughput and information content. These techniques promise to identify functional phenotypes associated with disease states and to identify compounds that improve cellular function regardless of whether the compound acts directly on a target or through a bypass mechanism. This review discusses opportunities and unresolved challenges in applying optogenetic techniques throughout the discovery pipeline - from target identification and validation, to target-based and phenotypic screens, to clinical trials. Copyright © 2017 Elsevier Ltd. All rights reserved.

Study of different filtering techniques applied to spectra from airborne gamma spectrometry

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

Wilhelm, Emilien; Gutierrez, Sebastien; Reboli, Anne

2015-07-01

One of the features of spectra obtained by airborne gamma spectrometry is low counting statistics due to the short acquisition time (1 s) and the large source-detector distance (40 m). It leads to considerable uncertainty in radionuclide identification and determination of their respective activities from the windows method recommended by the IAEA, especially for low-level radioactivity. The present work compares the results obtained with filters in terms of errors of the filtered spectra with the window method and over the whole gamma energy range. The results are used to determine which filtering technique is the most suitable in combination withmore » some method for total stripping of the spectrum. (authors)« less

Computerized evaluation of holographic interferograms for fatigue crack detection in riveted lap joints

NASA Astrophysics Data System (ADS)

Zhou, Xiang

Using an innovative portable holographic inspection and testing system (PHITS) developed at the Australian Defence Force Academy, fatigue cracks in riveted lap joints can be detected by visually inspecting the abnormal fringe changes recorded on holographic interferograms. In this thesis, for automatic crack detection, some modern digital image processing techniques are investigated and applied to holographic interferogram evaluation. Fringe analysis algorithms are developed for identification of the crack-induced fringe changes. Theoretical analysis of PHITS and riveted lap joints and two typical experiments demonstrate that the fatigue cracks in lightly-clamped joints induce two characteristic fringe changes: local fringe discontinuities at the cracking sites; and the global crescent fringe distribution near to the edge of the rivet hole. Both of the fringe features are used for crack detection in this thesis. As a basis of the fringe feature extraction, an algorithm for local fringe orientation calculation is proposed. For high orientation accuracy and computational efficiency, Gaussian gradient filtering and neighboring direction averaging are used to minimize the effects of image background variations and random noise. The neighboring direction averaging is also used to approximate the fringe directions in centerlines of bright and dark fringes. Experimental results indicate that for high orientation accuracy the scales of the Gaussian filter and neighboring direction averaging should be chosen according to the local fringe spacings. The orientation histogram technique is applied to detect the local fringe discontinuity due to the fatigue cracks. The Fourier descriptor technique is used to characterize the global fringe distribution change from a circular to a crescent distribution with the fatigue crack growth. Experiments and computer simulations are conducted to analyze the detectability and reliability of crack detection using the two techniques. Results demonstrate that the Fourier descriptor technique is more promising in the detection of the short cracks near the edge of the rivet head. However, it is not as reliable as the fringe orientation technique for detection of the long through cracks. For reliability, both techniques should be used in practical crack detection. Neither the Fourier descriptor technique nor the orientation histogram technique have been previously applied to holographic interferometry. While this work related primarily to interferograms of cracked rivets, the techniques would be readily applied to other areas of fringe pattern analysis.

Fission gas bubble identification using MATLAB's image processing toolbox

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

Collette, R.

Automated image processing routines have the potential to aid in the fuel performance evaluation process by eliminating bias in human judgment that may vary from person-to-person or sample-to-sample. This study presents several MATLAB based image analysis routines designed for fission gas void identification in post-irradiation examination of uranium molybdenum (U–Mo) monolithic-type plate fuels. Frequency domain filtration, enlisted as a pre-processing technique, can eliminate artifacts from the image without compromising the critical features of interest. This process is coupled with a bilateral filter, an edge-preserving noise removal technique aimed at preparing the image for optimal segmentation. Adaptive thresholding proved to bemore » the most consistent gray-level feature segmentation technique for U–Mo fuel microstructures. The Sauvola adaptive threshold technique segments the image based on histogram weighting factors in stable contrast regions and local statistics in variable contrast regions. Once all processing is complete, the algorithm outputs the total fission gas void count, the mean void size, and the average porosity. The final results demonstrate an ability to extract fission gas void morphological data faster, more consistently, and at least as accurately as manual segmentation methods. - Highlights: •Automated image processing can aid in the fuel qualification process. •Routines are developed to characterize fission gas bubbles in irradiated U–Mo fuel. •Frequency domain filtration effectively eliminates FIB curtaining artifacts. •Adaptive thresholding proved to be the most accurate segmentation method. •The techniques established are ready to be applied to large scale data extraction testing.« less

A novel and efficient technique for identification and classification of GPCRs.

PubMed

Gupta, Ravi; Mittal, Ankush; Singh, Kuldip

2008-07-01

G-protein coupled receptors (GPCRs) play a vital role in different biological processes, such as regulation of growth, death, and metabolism of cells. GPCRs are the focus of significant amount of current pharmaceutical research since they interact with more than 50% of prescription drugs. The dipeptide-based support vector machine (SVM) approach is the most accurate technique to identify and classify the GPCRs. However, this approach has two major disadvantages. First, the dimension of dipeptide-based feature vector is equal to 400. The large dimension makes the classification task computationally and memory wise inefficient. Second, it does not consider the biological properties of protein sequence for identification and classification of GPCRs. In this paper, we present a novel-feature-based SVM classification technique. The novel features are derived by applying wavelet-based time series analysis approach on protein sequences. The proposed feature space summarizes the variance information of seven important biological properties of amino acids in a protein sequence. In addition, the dimension of the feature vector for proposed technique is equal to 35. Experiments were performed on GPCRs protein sequences available at GPCRs Database. Our approach achieves an accuracy of 99.9%, 98.06%, 97.78%, and 94.08% for GPCR superfamily, families, subfamilies, and subsubfamilies (amine group), respectively, when evaluated using fivefold cross-validation. Further, an accuracy of 99.8%, 97.26%, and 97.84% was obtained when evaluated on unseen or recall datasets of GPCR superfamily, families, and subfamilies, respectively. Comparison with dipeptide-based SVM technique shows the effectiveness of our approach.

Comparison of GC-MS, GC-MRM-MS, and GC × GC to characterise higher plant biomarkers in Tertiary oils and rock extracts

NASA Astrophysics Data System (ADS)

Eiserbeck, Christiane; Nelson, Robert K.; Grice, Kliti; Curiale, Joseph; Reddy, Christopher M.

2012-06-01

Higher plant biomarkers occur in various compound classes with an array of isomers that are challenging to separate and identify. Traditional one-dimensional (1D) gas chromatographic (GC) techniques achieved impressive results in the past, but have reached limitations in many cases. Comprehensive two-dimensional gas chromatography (GC × GC) either coupled to a flame ionization detector (GC × GC-FID) or time-of-flight mass spectrometer (GC × GC-TOFMS) is a powerful tool to overcome the challenges of 1D GC, such as the resolution of unresolved complex mixture (UCM). We studied a number of Tertiary, terrigenous oils, and source rocks from the Arctic and Southeast Asia, with special focus on angiosperm biomarkers, such as oleanoids and lupanoids. Different chromatographic separation and detection techniques such as traditional 1D GC-MS, metastable reaction monitoring (GC-MRM-MS), GC × GC-FID, and GC × GC-TOFMS are compared and applied to evaluate the differences and advantages in their performance for biomarker identification. The measured 22S/(22S + 22R) homohopane ratios for all applied techniques were determined and compare exceptionally well (generally between 2% and 10%). Furthermore, we resolved a variety of angiosperm-derived compounds that co-eluted using 1D GC techniques, demonstrating the superior separation power of GC × GC for these biomarkers, which indicate terrigenous source input and Cretaceous or younger ages. Samples of varying thermal maturity and biodegradation contain higher plant biomarkers from various stages of diagenesis and catagenesis, which can be directly assessed in a GC × GC chromatogram. The analysis of whole crude oils and rock extracts without loss in resolution enables the separation of unstable compounds that are prone to rearrangement (e.g. unsaturated triterpenoids such as taraxer-14-ene) when exposed to fractionation techniques like molecular sieving. GC × GC-TOFMS is particularly valuable for the successful separation of co-eluting components having identical molecular masses and similar fragmentation patterns. Such components co-elute when analysed by 1D GC and cannot be resolved by single-ion-monitoring, which prevents accurate mass spectral assessment for identification or quantification.

Current trends and challenges in sample preparation for metallic nanoparticles analysis in daily products and environmental samples: A review

NASA Astrophysics Data System (ADS)

De la Calle, Inmaculada; Menta, Mathieu; Séby, Fabienne

2016-11-01

Due to the increasing use of nanoparticles (NPs) in consumer products, it becomes necessary to develop different strategies for their detection, identification, characterization and quantification in a wide variety of samples. Since the analysis of NPs in consumer products and environmental samples is particularly troublesome, a detailed description of challenges and limitations is given here. This review mainly focuses on sample preparation procedures applied for the mostly used techniques for metallic and metal oxide NPs characterization in consumer products and most outstanding publications of biological and environmental samples (from 2006 to 2015). We summarize the procedures applied for total metal content, extraction/separation and/or preconcentration of NPs from the matrix, separation of metallic NPs from their ions or from larger particles and NPs' size fractionation. Sample preparation procedures specifically for microscopy are also described. Selected applications in cosmetics, food, other consumer products, biological tissues and environmental samples are presented. Advantages and inconveniences of those procedures are considered. Moreover, selected simplified schemes for NPs sample preparation, as well as usual techniques applied are included. Finally, promising directions for further investigations are discussed.

A database de-identification framework to enable direct queries on medical data for secondary use.

PubMed

Erdal, B S; Liu, J; Ding, J; Chen, J; Marsh, C B; Kamal, J; Clymer, B D

2012-01-01

To qualify the use of patient clinical records as non-human-subject for research purpose, electronic medical record data must be de-identified so there is minimum risk to protected health information exposure. This study demonstrated a robust framework for structured data de-identification that can be applied to any relational data source that needs to be de-identified. Using a real world clinical data warehouse, a pilot implementation of limited subject areas were used to demonstrate and evaluate this new de-identification process. Query results and performances are compared between source and target system to validate data accuracy and usability. The combination of hashing, pseudonyms, and session dependent randomizer provides a rigorous de-identification framework to guard against 1) source identifier exposure; 2) internal data analyst manually linking to source identifiers; and 3) identifier cross-link among different researchers or multiple query sessions by the same researcher. In addition, a query rejection option is provided to refuse queries resulting in less than preset numbers of subjects and total records to prevent users from accidental subject identification due to low volume of data. This framework does not prevent subject re-identification based on prior knowledge and sequence of events. Also, it does not deal with medical free text de-identification, although text de-identification using natural language processing can be included due its modular design. We demonstrated a framework resulting in HIPAA Compliant databases that can be directly queried by researchers. This technique can be augmented to facilitate inter-institutional research data sharing through existing middleware such as caGrid.

Distinguishing time-delayed causal interactions using convergent cross mapping

PubMed Central

Ye, Hao; Deyle, Ethan R.; Gilarranz, Luis J.; Sugihara, George

2015-01-01

An important problem across many scientific fields is the identification of causal effects from observational data alone. Recent methods (convergent cross mapping, CCM) have made substantial progress on this problem by applying the idea of nonlinear attractor reconstruction to time series data. Here, we expand upon the technique of CCM by explicitly considering time lags. Applying this extended method to representative examples (model simulations, a laboratory predator-prey experiment, temperature and greenhouse gas reconstructions from the Vostok ice core, and long-term ecological time series collected in the Southern California Bight), we demonstrate the ability to identify different time-delayed interactions, distinguish between synchrony induced by strong unidirectional-forcing and true bidirectional causality, and resolve transitive causal chains. PMID:26435402

Design and implementation of robust controllers for a gait trainer.

PubMed

Wang, F C; Yu, C H; Chou, T Y

2009-08-01

This paper applies robust algorithms to control an active gait trainer for children with walking disabilities. Compared with traditional rehabilitation procedures, in which two or three trainers are required to assist the patient, a motor-driven mechanism was constructed to improve the efficiency of the procedures. First, a six-bar mechanism was designed and constructed to mimic the trajectory of children's ankles in walking. Second, system identification techniques were applied to obtain system transfer functions at different operating points by experiments. Third, robust control algorithms were used to design Hinfinity robust controllers for the system. Finally, the designed controllers were implemented to verify experimentally the system performance. From the results, the proposed robust control strategies are shown to be effective.

Multi-resolution analysis for ear recognition using wavelet features

NASA Astrophysics Data System (ADS)

Shoaib, M.; Basit, A.; Faye, I.

2016-11-01

Security is very important and in order to avoid any physical contact, identification of human when they are moving is necessary. Ear biometric is one of the methods by which a person can be identified using surveillance cameras. Various techniques have been proposed to increase the ear based recognition systems. In this work, a feature extraction method for human ear recognition based on wavelet transforms is proposed. The proposed features are approximation coefficients and specific details of level two after applying various types of wavelet transforms. Different wavelet transforms are applied to find the suitable wavelet. Minimum Euclidean distance is used as a matching criterion. Results achieved by the proposed method are promising and can be used in real time ear recognition system.

A robust star identification algorithm with star shortlisting

NASA Astrophysics Data System (ADS)

Mehta, Deval Samirbhai; Chen, Shoushun; Low, Kay Soon

2018-05-01

A star tracker provides the most accurate attitude solution in terms of arc seconds compared to the other existing attitude sensors. When no prior attitude information is available, it operates in "Lost-In-Space (LIS)" mode. Star pattern recognition, also known as star identification algorithm, forms the most crucial part of a star tracker in the LIS mode. Recognition reliability and speed are the two most important parameters of a star pattern recognition technique. In this paper, a novel star identification algorithm with star ID shortlisting is proposed. Firstly, the star IDs are shortlisted based on worst-case patch mismatch, and later stars are identified in the image by an initial match confirmed with a running sequential angular match technique. The proposed idea is tested on 16,200 simulated star images having magnitude uncertainty, noise stars, positional deviation, and varying size of the field of view. The proposed idea is also benchmarked with the state-of-the-art star pattern recognition techniques. Finally, the real-time performance of the proposed technique is tested on the 3104 real star images captured by a star tracker SST-20S currently mounted on a satellite. The proposed technique can achieve an identification accuracy of 98% and takes only 8.2 ms for identification on real images. Simulation and real-time results depict that the proposed technique is highly robust and achieves a high speed of identification suitable for actual space applications.

Characterization of the Hydrocarbon Potential and Non-Potential Zones Using Wavelet-Based Fractal Analysis

NASA Astrophysics Data System (ADS)

Mukherjee, Bappa; Roy, P. N. S.

The identification of prospective and dry zone is of major importance from well log data. Truthfulness in the identification of potential zone is a very crucial issue in hydrocarbon exploration. In this line, the problem has received considerable attention and many conventional techniques have been proposed. The purpose of this study is to recognize the hydrocarbon and non-hydrocarbon bearing portion within a reservoir by using the non-conventional technique. The wavelet based fractal analysis (WBFA) has been applied on the wire-line log data in order to obtain the pre-defined hydrocarbon (HC) and non-hydrocarbon (NHC) zones by their self-affine signal nature is demonstrated in this paper. The feasibility of the proposed technique is tested with the help of most commonly used logs, like self-potential, gamma ray, resistivity and porosity log responses. These logs are obtained from the industry to make out several HC and NHC zones of all wells in the study region belonging to the upper Assam basin. The results obtained in this study for a particular log response, where in the case of HC bearing zones, it is found that they are mainly situated in a variety of sandstones lithology which leads to the higher Hurst exponent. Further, the NHC zones found to be analogous to lithology with higher shale content having lower Hurst exponent. The above proposed technique can overcome the chance of miss interpretation in conventional reservoir characterization.

Application of infrared spectroscopy and pyrolysis gas chromatography for characterisation of adhesive tapes

NASA Astrophysics Data System (ADS)

Zięba-Palus, Janina; Nowińska, Sabina; Kowalski, Rafał

2016-12-01

Infrared spectroscopy and pyrolysis GC/MS were applied in the comparative analysis of adhesive tapes. By providing information about the polymer composition, it was possible to classify both backings and adhesives of tapes into defined chemical classes. It was found that samples of the same type (of backings and adhesives) and similar infrared spectra can in most cases be effectively differentiated using Py-GC/MS, sometimes based only on the presence of peaks of very low intensity originating from minor components. The results obtained enabled us to draw the conclusion that Py-GC/MS appears to be a valuable analytical technique for examining tapes, which is complementary to infrared spectroscopy. Identification of pyrolysis products enables discrimination of samples. Both methods also provide crucial information that is useful for identification of adhesive tapes found at the crime scene.

Analysis of pilot control strategy

NASA Technical Reports Server (NTRS)

Heffley, R. K.; Hanson, G. D.; Jewell, W. F.; Clement, W. F.

1983-01-01

Methods for nonintrusive identification of pilot control strategy and task execution dynamics are presented along with examples based on flight data. The specific analysis technique is Nonintrusive Parameter Identification Procedure (NIPIP), which is described in a companion user's guide (NASA CR-170398). Quantification of pilot control strategy and task execution dynamics is discussed in general terms followed by a more detailed description of how NIPIP can be applied. The examples are based on flight data obtained from the NASA F-8 digital fly by wire airplane. These examples involve various piloting tasks and control axes as well as a demonstration of how the dynamics of the aircraft itself are identified using NIPIP. Application of NIPIP to the AFTI/F-16 flight test program is discussed. Recommendations are made for flight test applications in general and refinement of NIPIP to include interactive computer graphics.

THz-wave parametric source and its imaging applications

NASA Astrophysics Data System (ADS)

Kawase, Kodo

2004-08-01

Widely tunable coherent terahertz (THz) wave generation has been demonstrated based on the parametric oscillation using MgO doped LiNbO3 crystal pumped by a Q-switched Nd:YAG laser. This method exhibits multiple advantages like wide tunability, coherency and compactness of its system. We have developed a novel basic technology for terahertz (THz) imaging, which allows detection and identification of chemicals by introducing the component spatial pattern analysis. The spatial distributions of the chemicals were obtained from terahertz multispectral transillumination images, using absorption spectra previously measured with a widely tunable THz-wave parametric oscillator. Further we have applied this technique to the detection and identification of illicit drugs concealed in envelopes. The samples we used were methamphetamine and MDMA, two of the most widely consumed illegal drugs in Japan, and aspirin as a reference.

A Comparison of Inductive Sensors in the Characterization of Partial Discharges and Electrical Noise Using the Chromatic Technique.

PubMed

Ardila-Rey, Jorge Alfredo; Montaña, Johny; de Castro, Bruno Albuquerque; Schurch, Roger; Covolan Ulson, José Alfredo; Muhammad-Sukki, Firdaus; Bani, Nurul Aini

2018-03-29

Partial discharges (PDs) are one of the most important classes of ageing processes that occur within electrical insulation. PD detection is a standardized technique to qualify the state of the insulation in electric assets such as machines and power cables. Generally, the classical phase-resolved partial discharge (PRPD) patterns are used to perform the identification of the type of PD source when they are related to a specific degradation process and when the electrical noise level is low compared to the magnitudes of the PD signals. However, in practical applications such as measurements carried out in the field or in industrial environments, several PD sources and large noise signals are usually present simultaneously. In this study, three different inductive sensors have been used to evaluate and compare their performance in the detection and separation of multiple PD sources by applying the chromatic technique to each of the measured signals.

Methodological optimization of tinnitus assessment using prepulse inhibition of the acoustic startle reflex.

PubMed

Longenecker, R J; Galazyuk, A V

2012-11-16

Recently prepulse inhibition of the acoustic startle reflex (ASR) became a popular technique for tinnitus assessment in laboratory animals. This method confers a significant advantage over the previously used time-consuming behavioral approaches utilizing basic mechanisms of conditioning. Although this technique has been successfully used to assess tinnitus in different laboratory animals, many of the finer details of this methodology have not been described enough to be replicated, but are critical for tinnitus assessment. Here we provide detail description of key procedures and methodological issues that provide guidance for newcomers with the process of learning to correctly apply gap detection techniques for tinnitus assessment in laboratory animals. The major categories of these issues include: refinement of hardware for best performance, optimization of stimulus parameters, behavioral considerations, and identification of optimal strategies for data analysis. This article is part of a Special Issue entitled: Tinnitus Neuroscience. Copyright © 2012. Published by Elsevier B.V.

Visual analytics techniques for large multi-attribute time series data

NASA Astrophysics Data System (ADS)

Hao, Ming C.; Dayal, Umeshwar; Keim, Daniel A.

2008-01-01

Time series data commonly occur when variables are monitored over time. Many real-world applications involve the comparison of long time series across multiple variables (multi-attributes). Often business people want to compare this year's monthly sales with last year's sales to make decisions. Data warehouse administrators (DBAs) want to know their daily data loading job performance. DBAs need to detect the outliers early enough to act upon them. In this paper, two new visual analytic techniques are introduced: The color cell-based Visual Time Series Line Charts and Maps highlight significant changes over time in a long time series data and the new Visual Content Query facilitates finding the contents and histories of interesting patterns and anomalies, which leads to root cause identification. We have applied both methods to two real-world applications to mine enterprise data warehouse and customer credit card fraud data to illustrate the wide applicability and usefulness of these techniques.

Joint forensics and watermarking approach for video authentication

NASA Astrophysics Data System (ADS)

Thiemert, Stefan; Liu, Huajian; Steinebach, Martin; Croce-Ferri, Lucilla

2007-02-01

In our paper we discuss and compare the possibilities and shortcomings of both content-fragile watermarking and digital forensics and analyze if the combination of both techniques allows the identification of more than the sum of all manipulations identified by both techniques on their own due to synergetic effects. The first part of the paper discusses the theoretical possibilities offered by a combined approach, in which forensics and watermarking are considered as complementary tools for data authentication or deeply combined together, in order to reduce their error rate and to enhance the detection efficiency. After this conceptual discussion the paper proposes some concrete examples in which the joint approach is applied to video authentication. Some specific forensics techniques are analyzed and expanded to handle efficiently video data. The examples show possible extensions of passive-blind image forgery detection to video data, where the motion and time related characteristics of video are efficiently exploited.

Detection of Gunshot Residues Using Mass Spectrometry

PubMed Central

Blanes, Lucas; Cole, Nerida; Doble, Philip; Roux, Claude

2014-01-01

In recent years, forensic scientists have become increasingly interested in the detection and interpretation of organic gunshot residues (OGSR) due to the increasing use of lead- and heavy metal-free ammunition. This has also been prompted by the identification of gunshot residue- (GSR-) like particles in environmental and occupational samples. Various techniques have been investigated for their ability to detect OGSR. Mass spectrometry (MS) coupled to a chromatographic system is a powerful tool due to its high selectivity and sensitivity. Further, modern MS instruments can detect and identify a number of explosives and additives which may require different ionization techniques. Finally, MS has been applied to the analysis of both OGSR and inorganic gunshot residue (IGSR), although the “gold standard” for analysis is scanning electron microscopy with energy dispersive X-ray microscopy (SEM-EDX). This review presents an overview of the technical attributes of currently available MS and ionization techniques and their reported applications to GSR analysis. PMID:24977168

FEM Techniques for High Stress Detection in Accelerated Fatigue Simulation

NASA Astrophysics Data System (ADS)

Veltri, M.

2016-09-01

This work presents the theory and a numerical validation study in support to a novel method for a priori identification of fatigue critical regions, with the aim to accelerate durability design in large FEM problems. The investigation is placed in the context of modern full-body structural durability analysis, where a computationally intensive dynamic solution could be required to identify areas with potential for fatigue damage initiation. The early detection of fatigue critical areas can drive a simplification of the problem size, leading to sensible improvement in solution time and model handling while allowing processing of the critical areas in higher detail. The proposed technique is applied to a real life industrial case in a comparative assessment with established practices. Synthetic damage prediction quantification and visualization techniques allow for a quick and efficient comparison between methods, outlining potential application benefits and boundaries.

Machine-Learning Techniques Applied to Antibacterial Drug Discovery

PubMed Central

Durrant, Jacob D.; Amaro, Rommie E.

2014-01-01

The emergence of drug-resistant bacteria threatens to catapult humanity back to the pre-antibiotic era. Even now, multi-drug-resistant bacterial infections annually result in millions of hospital days, billions in healthcare costs, and, most importantly, tens of thousands of lives lost. As many pharmaceutical companies have abandoned antibiotic development in search of more lucrative therapeutics, academic researchers are uniquely positioned to fill the resulting vacuum. Traditional high-throughput screens and lead-optimization efforts are expensive and labor intensive. Computer-aided drug discovery techniques, which are cheaper and faster, can accelerate the identification of novel antibiotics in an academic setting, leading to improved hit rates and faster transitions to pre-clinical and clinical testing. The current review describes two machine-learning techniques, neural networks and decision trees, that have been used to identify experimentally validated antibiotics. We conclude by describing the future directions of this exciting field. PMID:25521642

A Review on the Applications of Next Generation Sequencing Technologies as Applied to Food-Related Microbiome Studies

PubMed Central

Cao, Yu; Fanning, Séamus; Proos, Sinéad; Jordan, Kieran; Srikumar, Shabarinath

2017-01-01

The development of next generation sequencing (NGS) techniques has enabled researchers to study and understand the world of microorganisms from broader and deeper perspectives. The contemporary advances in DNA sequencing technologies have not only enabled finer characterization of bacterial genomes but also provided deeper taxonomic identification of complex microbiomes which in its genomic essence is the combined genetic material of the microorganisms inhabiting an environment, whether the environment be a particular body econiche (e.g., human intestinal contents) or a food manufacturing facility econiche (e.g., floor drain). To date, 16S rDNA sequencing, metagenomics and metatranscriptomics are the three basic sequencing strategies used in the taxonomic identification and characterization of food-related microbiomes. These sequencing strategies have used different NGS platforms for DNA and RNA sequence identification. Traditionally, 16S rDNA sequencing has played a key role in understanding the taxonomic composition of a food-related microbiome. Recently, metagenomic approaches have resulted in improved understanding of a microbiome by providing a species-level/strain-level characterization. Further, metatranscriptomic approaches have contributed to the functional characterization of the complex interactions between different microbial communities within a single microbiome. Many studies have highlighted the use of NGS techniques in investigating the microbiome of fermented foods. However, the utilization of NGS techniques in studying the microbiome of non-fermented foods are limited. This review provides a brief overview of the advances in DNA sequencing chemistries as the technology progressed from first, next and third generations and highlights how NGS provided a deeper understanding of food-related microbiomes with special focus on non-fermented foods. PMID:29033905

A system identification technique based on the random decrement signatures. Part 1: Theory and simulation

NASA Technical Reports Server (NTRS)

Bedewi, Nabih E.; Yang, Jackson C. S.

1987-01-01

Identification of the system parameters of a randomly excited structure may be treated using a variety of statistical techniques. Of all these techniques, the Random Decrement is unique in that it provides the homogeneous component of the system response. Using this quality, a system identification technique was developed based on a least-squares fit of the signatures to estimate the mass, damping, and stiffness matrices of a linear randomly excited system. The mathematics of the technique is presented in addition to the results of computer simulations conducted to demonstrate the prediction of the response of the system and the random forcing function initially introduced to excite the system.

Tandem Mass Spectrum Sequencing: An Alternative to Database Search Engines in Shotgun Proteomics.

PubMed

Muth, Thilo; Rapp, Erdmann; Berven, Frode S; Barsnes, Harald; Vaudel, Marc

2016-01-01

Protein identification via database searches has become the gold standard in mass spectrometry based shotgun proteomics. However, as the quality of tandem mass spectra improves, direct mass spectrum sequencing gains interest as a database-independent alternative. In this chapter, the general principle of this so-called de novo sequencing is introduced along with pitfalls and challenges of the technique. The main tools available are presented with a focus on user friendly open source software which can be directly applied in everyday proteomic workflows.

Advanced Health Management of a Brushless Direct Current Motor/Controller

NASA Technical Reports Server (NTRS)

Pickett, R. D.

2003-01-01

This effort demonstrates that health management can be taken to the component level for electromechanical systems. The same techniques can be applied to take any health management system to the component level, based on the practicality of the implementation for that particular system. This effort allows various logic schemes to be implemented for the identification and management of failures. By taking health management to the component level, integrated vehicle health management systems can be enhanced by protecting box-level avionics from being shut down in order to isolate a failed computer.

Neuromuscular properties of different spastic human joints vary systematically.

PubMed

Mirbagheri, M M; Settle, K

2010-01-01

We quantified the mechanical abnormalities of the spastic wrist in chronic stroke survivors, and determined whether these findings were representative of those recorded at the elbow and ankle joints. System identification techniques were used to characterize the mechanical abnormalities of these joints and to identify the contribution of intrinsic and reflex stiffness to these abnormalities. Modulation of intrinsic and reflex stiffness with the joint angle was studied by applying PRBS perturbations to the joints at different joint angles over the range of motion. Age-matched healthy subjects were used as control.

Determining the orientation of a chiral substrate using full-hemisphere angle-resolved photoelectron spectroscopy.

PubMed

Tadich, A; Riley, J; Thomsen, L; Cowie, B C C; Gladys, M J

2011-10-21

Chiral interfaces and substrates are of increasing importance in the field of enantioselective chemistry. To fully understand the enantiospecific interactions between chiral adsorbate molecules and the chiral substrate, it is vital that the chiral orientation of the substrate is known. In this Letter we demonstrate that full-hemisphere angle-resolved photoemission permits straightforward identification of the orientation of a chiral surface. The technique can be applied to any solid state system for which photoemission measurements are possible. © 2011 American Physical Society

Effective use of ERTS multisensor data in the Northern Great Plains

NASA Technical Reports Server (NTRS)

Myers, V. I.; Westin, F. C.; Horton, M. L.; Lewis, J. K. (Principal Investigator)

1974-01-01

The author has identified the following significant results. ERTS imagery was used as a tool in the identification and refinement of soil association areas; to classify land use patterns between crop and fallow fields; to identify corn, soybeans, and oats; and to identify broad generalized range ecosystems. Various data handling techniques were developed and applied to accomplish these tasks. A map outlining soil associations and relative land values was completed on a base mosaic of ERTS imagery and is included as an appendix to the report.

Application of ERTS-1 imagery to the study of caribou movements and winter dispersal in relation to prevailing snowcover

NASA Technical Reports Server (NTRS)

Lent, P. C. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Step-wise discriminate analysis has demonstrated the feasibility of feature identification using linear discriminate functions of ERTS-1 MSS band densities and their ratios. The analysis indicated that features such as small streams can be detected even when they are in dark mountain shadow. The potential utility of this and similar analytic techniques appears considerable, and the limits it can be applied to analysis of ERTS-1 imagery are not yet fully known.

New Applications of Portable Raman Spectroscopy in Agri-Bio-Photonics

NASA Astrophysics Data System (ADS)

Voronine, Dmitri; Scully, Rob; Sanders, Virgil

2014-03-01

Modern optical techniques based on Raman spectroscopy are being used to monitor and analyze the health of cattle, crops and their natural environment. These optical tools are now available to perform fast, noninvasive analysis of live animals and plants in situ. We will report new applications of a portable handheld Raman spectroscopy to identification and taxonomy of plants. In addition, detection of organic food residues will be demonstrated. Advantages and limitations of current portable instruments will be discussed with suggestions for improved performance by applying enhanced Raman spectroscopic schemes.

High resolution spectroscopic mapping imaging applied in situ to multilayer structures for stratigraphic identification of painted art objects

NASA Astrophysics Data System (ADS)

Karagiannis, Georgios Th.

2016-04-01

The development of non-destructive techniques is a reality in the field of conservation science. These techniques are usually not so accurate, as the analytical micro-sampling techniques, however, the proper development of soft-computing techniques can improve their accuracy. In this work, we propose a real-time fast acquisition spectroscopic mapping imaging system that operates from the ultraviolet to mid infrared (UV/Vis/nIR/mIR) area of the electromagnetic spectrum and it is supported by a set of soft-computing methods to identify the materials that exist in a stratigraphic structure of paint layers. Particularly, the system acquires spectra in diffuse-reflectance mode, scanning in a Region-Of-Interest (ROI), and having wavelength range from 200 up to 5000 nm. Also, a fuzzy c-means clustering algorithm, i.e., the particular soft-computing algorithm, produces the mapping images. The evaluation of the method was tested on a byzantine painted icon.

An evaluation of machine processing techniques of ERTS-1 data for user applications. [urban land use and soil association mapping in Indiana

NASA Technical Reports Server (NTRS)

Landgrebe, D.

1974-01-01

A broad study is described to evaluate a set of machine analysis and processing techniques applied to ERTS-1 data. Based on the analysis results in urban land use analysis and soil association mapping together with previously reported results in general earth surface feature identification and crop species classification, a profile of general applicability of this procedure is beginning to emerge. Put in the hands of a user who knows well the information needed from the data and also is familiar with the region to be analyzed it appears that significantly useful information can be generated by these methods. When supported by preprocessing techniques such as the geometric correction and temporal registration capabilities, final products readily useable by user agencies appear possible. In parallel with application, through further research, there is much potential for further development of these techniques both with regard to providing higher performance and in new situations not yet studied.

Portraits of Benvenuto Cellini and Anthropological Methods of Their Identification

ERIC Educational Resources Information Center

Nasobin, Oleg

2016-01-01

Modern methods of biometric identification are increasingly applied in order to attribute works of art. They are based on developments in the 19th century anthropological methods. So, this article describes how the successional anthropological methods were applied for the identification of Benvenuto Cellini's portraits. Objective comparison of…

A Comparison of Direction Finding Results From an FFT Peak Identification Technique With Those From the Music Algorithm

DTIC Science & Technology

1991-07-01

MUSIC ALGORITHM (U) by L.E. Montbrland go I July 1991 CRC REPORT NO. 1438 Ottawa I* Government of Canada Gouvsrnweient du Canada I o DParunnt of...FINDING RESULTS FROM AN FFT PEAK IDENTIFICATION TECHNIQUE WITH THOSE FROM THE MUSIC ALGORITHM (U) by L.E. Montbhrand CRC REPORT NO. 1438 July 1991...Ottawa A Comparison of Direction Finding Results From an FFT Peak Identification Technique With Those From the Music Algorithm L.E. Montbriand Abstract A

Post-acquisition data mining techniques for LC-MS/MS-acquired data in drug metabolite identification.

PubMed

Dhurjad, Pooja Sukhdev; Marothu, Vamsi Krishna; Rathod, Rajeshwari

2017-08-01

Metabolite identification is a crucial part of the drug discovery process. LC-MS/MS-based metabolite identification has gained widespread use, but the data acquired by the LC-MS/MS instrument is complex, and thus the interpretation of data becomes troublesome. Fortunately, advancements in data mining techniques have simplified the process of data interpretation with improved mass accuracy and provide a potentially selective, sensitive, accurate and comprehensive way for metabolite identification. In this review, we have discussed the targeted (extracted ion chromatogram, mass defect filter, product ion filter, neutral loss filter and isotope pattern filter) and untargeted (control sample comparison, background subtraction and metabolomic approaches) post-acquisition data mining techniques, which facilitate the drug metabolite identification. We have also discussed the importance of integrated data mining strategy.

User oriented ERTS-1 images. [vegetation identification in Canada through image enhancement

NASA Technical Reports Server (NTRS)

Shlien, S.; Goodenough, D.

1974-01-01

Photographic reproduction of ERTS-1 images are capable of displaying only a portion of the total information available from the multispectral scanner. Methods are being developed to generate ERTS-1 images oriented towards special users such as agriculturists, foresters, and hydrologists by applying image enhancement techniques and interactive statistical classification schemes. Spatial boundaries and linear features can be emphasized and delineated using simple filters. Linear and nonlinear transformations can be applied to the spectral data to emphasize certain ground information. An automatic classification scheme was developed to identify particular ground cover classes such as fallow, grain, rape seed or various vegetation covers. The scheme applies the maximum likelihood decision rule to the spectral information and classifies the ERTS-1 image on a pixel by pixel basis. Preliminary results indicate that the classifier has limited success in distinguishing crops, but is well adapted for identifying different types of vegetation.

Biometric Authentication for Gender Classification Techniques: A Review

NASA Astrophysics Data System (ADS)

Mathivanan, P.; Poornima, K.

2017-12-01

One of the challenging biometric authentication applications is gender identification and age classification, which captures gait from far distance and analyze physical information of the subject such as gender, race and emotional state of the subject. It is found that most of the gender identification techniques have focused only with frontal pose of different human subject, image size and type of database used in the process. The study also classifies different feature extraction process such as, Principal Component Analysis (PCA) and Local Directional Pattern (LDP) that are used to extract the authentication features of a person. This paper aims to analyze different gender classification techniques that help in evaluating strength and weakness of existing gender identification algorithm. Therefore, it helps in developing a novel gender classification algorithm with less computation cost and more accuracy. In this paper, an overview and classification of different gender identification techniques are first presented and it is compared with other existing human identification system by means of their performance.

Identification Of Natural Dyes On Archaeological Textile Objects Using Laser Induced Fluorescent Technique

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

Abdel-Kareem, O.; Eltokhy, A.; Harith, M. A.

2011-09-22

This study aims to evaluate the use of Laser Fluorescent as a non-destructive technique for identification of natural dyes on archaeological textile objects. In this study wool textile samples were dyed with 10 natural dyes such as cochineal, cutch, henna, indigo, Lac, madder, safflower, saffron, sumac and turmeric. These dyes common present on archaeological textile objects to be used as standard dyed textile samples. These selected natural dyes will be used as known references that can be used a guide to identify unknown archaeological dyes. The dyed textile samples were investigated with laser radiation in different wavelengths to detect themore » best wavelengths for identification each dye. This study confirms that Laser Florescent is very useful and a rapid technique can be used as a non-destructive technique for identification of natural dyes on archaeological textile objects. The results obtained with this study can be a guide for all conservators in identification of natural organic dyes on archaeological textile objects.« less

Identification Of Natural Dyes On Archaeological Textile Objects Using Laser Induced Fluorescent Technique

NASA Astrophysics Data System (ADS)

Abdel-Kareem, O.; Eltokhy, A.; Harith, M. A.

2011-09-01

This study aims to evaluate the use of Laser Fluorescent as a non-destructive technique for identification of natural dyes on archaeological textile objects. In this study wool textile samples were dyed with 10 natural dyes such as cochineal, cutch, henna, indigo, Lac, madder, safflower, saffron, sumac and turmeric. These dyes common present on archaeological textile objects to be used as standard dyed textile samples. These selected natural dyes will be used as known references that can be used a guide to identify unknown archaeological dyes. The dyed textile samples were investigated with laser radiation in different wavelengths to detect the best wavelengths for identification each dye. This study confirms that Laser Florescent is very useful and a rapid technique can be used as a non-destructive technique for identification of natural dyes on archaeological textile objects. The results obtained with this study can be a guide for all conservators in identification of natural organic dyes on archaeological textile objects.

Modal identification of dynamic mechanical systems

NASA Astrophysics Data System (ADS)

Srivastava, R. K.; Kundra, T. K.

1992-07-01

This paper reviews modal identification techniques which are now helping designers all over the world to improve the dynamic behavior of vibrating engineering systems. In this context the need to develop more accurate and faster parameter identification is ever increasing. A new dynamic stiffness matrix based identification method which is highly accurate, fast and system-dynamic-modification compatible is presented. The technique is applicable to all those multidegree-of-freedom systems where full receptance matrix can be experimentally measured.

Cell-Detection Technique for Automated Patch Clamping

NASA Technical Reports Server (NTRS)

McDowell, Mark; Gray, Elizabeth

2008-01-01

A unique and customizable machinevision and image-data-processing technique has been developed for use in automated identification of cells that are optimal for patch clamping. [Patch clamping (in which patch electrodes are pressed against cell membranes) is an electrophysiological technique widely applied for the study of ion channels, and of membrane proteins that regulate the flow of ions across the membranes. Patch clamping is used in many biological research fields such as neurobiology, pharmacology, and molecular biology.] While there exist several hardware techniques for automated patch clamping of cells, very few of those techniques incorporate machine vision for locating cells that are ideal subjects for patch clamping. In contrast, the present technique is embodied in a machine-vision algorithm that, in practical application, enables the user to identify good and bad cells for patch clamping in an image captured by a charge-coupled-device (CCD) camera attached to a microscope, within a processing time of one second. Hence, the present technique can save time, thereby increasing efficiency and reducing cost. The present technique involves the utilization of cell-feature metrics to accurately make decisions on the degree to which individual cells are "good" or "bad" candidates for patch clamping. These metrics include position coordinates (x,y) in the image plane, major-axis length, minor-axis length, area, elongation, roundness, smoothness, angle of orientation, and degree of inclusion in the field of view. The present technique does not require any special hardware beyond commercially available, off-the-shelf patch-clamping hardware: A standard patchclamping microscope system with an attached CCD camera, a personal computer with an imagedata- processing board, and some experience in utilizing imagedata- processing software are all that are needed. A cell image is first captured by the microscope CCD camera and image-data-processing board, then the image data are analyzed by software that implements the present machine-vision technique. This analysis results in the identification of cells that are "good" candidates for patch clamping (see figure). Once a "good" cell is identified, a patch clamp can be effected by an automated patchclamping apparatus or by a human operator. This technique has been shown to enable reliable identification of "good" and "bad" candidate cells for patch clamping. The ultimate goal in further development of this technique is to combine artificial-intelligence processing with instrumentation and controls in order to produce a complete "turnkey" automated patch-clamping system capable of accurately and reliably patch clamping cells with a minimum intervention by a human operator. Moreover, this technique can be adapted to virtually any cellular-analysis procedure that includes repetitive operation of microscope hardware by a human.

Towards large-scale FAME-based bacterial species identification using machine learning techniques.

PubMed

Slabbinck, Bram; De Baets, Bernard; Dawyndt, Peter; De Vos, Paul

2009-05-01

In the last decade, bacterial taxonomy witnessed a huge expansion. The swift pace of bacterial species (re-)definitions has a serious impact on the accuracy and completeness of first-line identification methods. Consequently, back-end identification libraries need to be synchronized with the List of Prokaryotic names with Standing in Nomenclature. In this study, we focus on bacterial fatty acid methyl ester (FAME) profiling as a broadly used first-line identification method. From the BAME@LMG database, we have selected FAME profiles of individual strains belonging to the genera Bacillus, Paenibacillus and Pseudomonas. Only those profiles resulting from standard growth conditions have been retained. The corresponding data set covers 74, 44 and 95 validly published bacterial species, respectively, represented by 961, 378 and 1673 standard FAME profiles. Through the application of machine learning techniques in a supervised strategy, different computational models have been built for genus and species identification. Three techniques have been considered: artificial neural networks, random forests and support vector machines. Nearly perfect identification has been achieved at genus level. Notwithstanding the known limited discriminative power of FAME analysis for species identification, the computational models have resulted in good species identification results for the three genera. For Bacillus, Paenibacillus and Pseudomonas, random forests have resulted in sensitivity values, respectively, 0.847, 0.901 and 0.708. The random forests models outperform those of the other machine learning techniques. Moreover, our machine learning approach also outperformed the Sherlock MIS (MIDI Inc., Newark, DE, USA). These results show that machine learning proves very useful for FAME-based bacterial species identification. Besides good bacterial identification at species level, speed and ease of taxonomic synchronization are major advantages of this computational species identification strategy.

Application of Raman Spectroscopy and Infrared Spectroscopy in the Identification of Breast Cancer.

PubMed

Depciuch, Joanna; Kaznowska, Ewa; Zawlik, Izabela; Wojnarowska, Renata; Cholewa, Marian; Heraud, Philip; Cebulski, Józef

2016-02-01

Raman spectroscopy and infrared (IR) spectroscopy are both techniques that allow for the investigation of vibrating chemical particles. These techniques provide information not only about chemical particles through the identification of functional groups and spectral analysis of so-called "fingerprints", these methods allow for the qualitative and quantitative analyses of chemical substances in the sample. Both of these spectral techniques are frequently being used in biology and medicine in diagnosing illnesses and monitoring methods of therapy. The type of breast cancer found in woman is often a malignant tumor, causing 1.38 million new cases of breast cancer and 458 000 deaths in the world in 2013. The most important risk factors for breast cancer development are: sex, age, family history, specific benign breast conditions in the breast, ionizing radiation, and lifestyle. The main purpose of breast cancer screening tests is to establish early diagnostics and to apply proper treatment. Diagnoses of breast cancer are based on: (1) physical techniques (e.g., ultrasonography, mammography, elastography, magnetic resonance, positron emission tomography [PET]); (2) histopathological techniques; (3) biological techniques; and (4) optical techniques (e.g., photo acoustic imaging, fluorescence tomography). However, none of these techniques provides unique or especially revealing answers. The aim of our study is comparative spectroscopic measurements on patients with the following: normal non-cancerous breast tissue; breast cancer tissues before chemotherapy; breast cancer tissues after chemotherapy; and normal breast tissues received around the cancerous breast region. Spectra collected from breast cancer patients shows changes in amounts of carotenoids and fats. We also observed changes in carbohydrate and protein levels (e.g., lack of amino acids, changes in the concentration of amino acids, structural changes) in comparison with normal breast tissues. This fact verifies that Raman spectroscopy and IR spectroscopy are very useful diagnostic tools that will shed new light in understanding the etiology of breast cancer. © The Author(s) 2016.

Improving Our Odds: Success through Continuous Risk Management

NASA Technical Reports Server (NTRS)

Greenhalgh, Phillip O.

2009-01-01

Launching a rocket, running a business, driving to work and even day-to-day living all involve some degree of risk. Risk is ever present yet not always recognized, adequately assessed and appropriately mitigated. Identification, assessment and mitigation of risk are elements of the risk management component of the "continuous improvement" way of life that has become a hallmark of successful and progressive enterprises. While the application of risk management techniques to provide continuous improvement may be detailed and extensive, the philosophy, ideals and tools can be beneficially applied to all situations. Experiences with the use of risk identification, assessment and mitigation techniques for complex systems and processes are described. System safety efforts and tools used to examine potential risks of the Ares I First Stage of NASA s new Constellation Crew Launch Vehicle (CLV) presently being designed are noted as examples. Recommendations from lessons learned are provided for the application of risk management during the development of new systems as well as for the improvement of existing systems. Lessons learned and suggestions given are also examined for applicability to simple systems, uncomplicated processes and routine personal daily tasks. This paper informs the reader of varied uses of risk management efforts and techniques to identify, assess and mitigate risk for improvement of products, success of business, protection of people and enhancement of personal life.

Microscopic optical path length difference and polarization measurement system for cell analysis

NASA Astrophysics Data System (ADS)

Satake, H.; Ikeda, K.; Kowa, H.; Hoshiba, T.; Watanabe, E.

2018-03-01

In recent years, noninvasive, nonstaining, and nondestructive quantitative cell measurement techniques have become increasingly important in the medical field. These cell measurement techniques enable the quantitative analysis of living cells, and are therefore applied to various cell identification processes, such as those determining the passage number limit during cell culturing in regenerative medicine. To enable cell measurement, we developed a quantitative microscopic phase imaging system based on a Mach-Zehnder interferometer that measures the optical path length difference distribution without phase unwrapping using optical phase locking. The applicability of our phase imaging system was demonstrated by successful identification of breast cancer cells amongst normal cells. However, the cell identification method using this phase imaging system exhibited a false identification rate of approximately 7%. In this study, we implemented a polarimetric imaging system by introducing a polarimetric module to one arm of the Mach-Zehnder interferometer of our conventional phase imaging system. This module was comprised of a quarter wave plate and a rotational polarizer on the illumination side of the sample, and a linear polarizer on the optical detector side. In addition, we developed correction methods for the measurement errors of the optical path length and birefringence phase differences that arose through the influence of elements other than cells, such as the Petri dish. As the Petri dish holding the fluid specimens was transparent, it did not affect the amplitude information; however, the optical path length and birefringence phase differences were affected. Therefore, we proposed correction of the optical path length and birefringence phase for the influence of elements other than cells, as a prerequisite for obtaining highly precise phase and polarimetric images.

The application of machine learning techniques in the clinical drug therapy.

PubMed

Meng, Huan-Yu; Jin, Wan-Lin; Yan, Cheng-Kai; Yang, Huan

2018-05-25

The development of a novel drug is an extremely complicated process that includes the target identification, design and manufacture, and proper therapy of the novel drug, as well as drug dose selection, drug efficacy evaluation, and adverse drug reaction control. Due to the limited resources, high costs, long duration, and low hit-to-lead ratio in the development of pharmacogenetics and computer technology, machine learning techniques have assisted novel drug development and have gradually received more attention by researchers. According to current research, machine learning techniques are widely applied in the process of the discovery of new drugs and novel drug targets, the decision surrounding proper therapy and drug dose, and the prediction of drug efficacy and adverse drug reactions. In this article, we discussed the history, workflow, and advantages and disadvantages of machine learning techniques in the processes mentioned above. Although the advantages of machine learning techniques are fairly obvious, the application of machine learning techniques is currently limited. With further research, the application of machine techniques in drug development could be much more widespread and could potentially be one of the major methods used in drug development. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Guidance on individual monitoring programmes for radioisotopic techniques in molecular and cellular biology.

PubMed

Macías, M T; Navarro, T; Lavara, A; Robredo, L M; Sierra, I; Lopez, M A

2003-01-01

The radioisotope techniques used in molecular and cellular biology involve external and internal irradiation risk. The personal dosemeter may be a reasonable indicator for external irradiation. However, it is necessary to control the possible internal contamination associated with the development of these techniques. The aim of this project is to analyse the most usual techniques and to establish programmes of internal monitoring for specific radionuclides (32P, 35S, 14C, 3H, 125I and 131I). To elaborate these programmes it was necessary to analyse the radioisotope techniques. Two models have been applied (NRPB and IAEA) to the more significant techniques, according to the physical and chemical nature of the radionuclides, their potential importance in occupational exposure and the possible injury to the genetic material of the cell. The results allowed the identification of the techniques with possible risk of internal contamination. It was necessary to identify groups of workers that require individual monitoring. The risk groups have been established among the professionals exposed, according to different parameters: the general characteristics of receptor, the radionuclides used (the same user can work with one, two or three radionuclides at the same time) and the results of the models applied. Also a control group was established. The study of possible intakes in these groups has been made by urinalysis and whole-body counter. The theoretical results are coherent with the experimental results. They have allowed guidance to individual monitoring to be proposed. Basically, the document shows: (1) the analysis of the radiosotopic techniques, taking into account the special containment equipment; (2) the establishment of the need of individual monitoring; and (3) the required frequency of measurements in a routine programme.

A Rigorous Attempt to Verify Interstellar Glycine

NASA Technical Reports Server (NTRS)

Snyder, L. E.; Lovas, F. J.; Hollis, J. M.; Friedel, D. N.; Jewell, P. R.; Remijan, A.; Ilyushin, V. V.; Alekseev, E. A.; Dyubko, S. F.

2004-01-01

In 2003, Kuan, Charnley, and co-workers reported the detection of interstellar glycine (NH2CH2COOH) based on observations of 27 lines in 19 different spectral bands in one or more of the sources Sgr BP(N-LMH), Orion KL, and W51 e1/e2. They supported their detection report with rotational temperature diagrams for all three sources. In this paper, we present essential criteria which can be used in a straightforward analysis technique to confirm the identity of an interstellar asymmetric rotor such as glycine. We use new laboratory measurements of glycine as a basis for applying this analysis technique, both to our previously unpublished 12 m telescope data and to the previously published SEST data of Nummelin and colleagues. We conclude that key lines necessary for an interstellar glycine identification have not yet been found. We identify several common molecular candidates that should be examined further as more likely carriers of the lines reported as glycine. Finally, we illustrate that rotational temperature diagrams used without the support of correct spectroscopic assignments are not a reliable tool for the identification of interstellar molecules. Subject headings: ISM: abundances - ISM: clouds - ISM: individual (Sagittarius B2[N-

Resident lactic acid bacteria in raw milk Canestrato Pugliese cheese.

PubMed

Aquilanti, L; Dell'Aquila, L; Zannini, E; Zocchetti, A; Clementi, F

2006-08-01

Investigation of the autochthonous lactic acid bacteria (LAB) population of the raw milk protected designation of origin Canestrato Pugliese cheese using phenotypic and genotypic methodologies. Thirty phenotypic assays and three molecular techniques (restriction fragment length polymorphism, partial sequencing of the 16S rRNA gene and recA multiplex PCR assay) were applied to the identification of 304 isolates from raw milk Canestrato Pugliese cheese. As a result, 168 of 207 isolates identified were ascribed to genus Enterococcus, 25 to Lactobacillus, 13 to Lactococcus and one to Leuconostoc. More in details among the lactobacilli, the species Lactobacillus brevis and Lactobacillus plantarum were predominant, including 13 and 10 isolates respectively, whereas among the lactococci, Lactococcus lactis subsp.cremoris [corrected] was the species more frequently detected (seven isolates). Except for the enterococci, phenotypic tests were not reliable enough for the identification of the isolates, if not combined to the genotype-based molecular techniques. The polyphasic approach utilized allowed 10 different LAB species to be detected; thus suggesting the appreciable LAB diversity of the autochthonous microbial population of the Canestrato Pugliese cheese. A comprehensive study of the resident raw milk Canestrato Pugliese cheese microbial population has been undertaken.

Application of 57Fe Mössbauer spectroscopy as a tool for mining exploration of bornite (Cu5FeS4) copper ore

NASA Astrophysics Data System (ADS)

Gainov, R. R.; Vagizov, F. G.; Golovanevskiy, V. A.; Ksenofontov, V. A.; Klingelhöfer, G.; Klekovkina, V. V.; Shumilova, T. G.; Pen'kov, I. N.

2014-04-01

Nuclear resonance methods, including Mössbauer spectroscopy,are considered as unique techniques suitable for remote on-line mineralogical analysis. The employment of these methods provides potentially significant commercial benefits for mining industry. As applied to copper sulfide ores, Mössbauer spectroscopy method is suitable for the analysis noted. Bornite (formally Cu5FeS4) is a significant part of copper ore and identification of its properties is important for economic exploitation of commercial copper ore deposits. A series of natural bornite samples was studied by 57Fe Mössbauer spectroscopy. Two aspects were considered: reexamination of 57Fe Mössbauer properties of natural bornite samples and their stability irrespective of origin and potential use of miniaturized Mössbauer spectrometers MIMOS II for in-situ bornite identification. The results obtained show a number of potential benefits of introducing the available portative Mössbauer equipment into the mining industry for express mineralogical analysis. In addition, results of some preliminary 63,65Cu nuclear quadrupole resonance (NQR) studies of bornite are reported and their merits with Mössbauer techniques for bornite detection discussed.

Secure method for biometric-based recognition with integrated cryptographic functions.

PubMed

Chiou, Shin-Yan

2013-01-01

Biometric systems refer to biometric technologies which can be used to achieve authentication. Unlike cryptography-based technologies, the ratio for certification in biometric systems needs not to achieve 100% accuracy. However, biometric data can only be directly compared through proximal access to the scanning device and cannot be combined with cryptographic techniques. Moreover, repeated use, improper storage, or transmission leaks may compromise security. Prior studies have attempted to combine cryptography and biometrics, but these methods require the synchronization of internal systems and are vulnerable to power analysis attacks, fault-based cryptanalysis, and replay attacks. This paper presents a new secure cryptographic authentication method using biometric features. The proposed system combines the advantages of biometric identification and cryptographic techniques. By adding a subsystem to existing biometric recognition systems, we can simultaneously achieve the security of cryptographic technology and the error tolerance of biometric recognition. This method can be used for biometric data encryption, signatures, and other types of cryptographic computation. The method offers a high degree of security with protection against power analysis attacks, fault-based cryptanalysis, and replay attacks. Moreover, it can be used to improve the confidentiality of biological data storage and biodata identification processes. Remote biometric authentication can also be safely applied.

Fitting Flux Ropes to a Global MHD Solution: A Comparison of Techniques. Appendix 1

NASA Technical Reports Server (NTRS)

Riley, Pete; Linker, J. A.; Lionello, R.; Mikic, Z.; Odstrcil, D.; Hidalgo, M. A.; Cid, C.; Hu, Q.; Lepping, R. P.; Lynch, B. J.

2004-01-01

Flux rope fitting (FRF) techniques are an invaluable tool for extracting information about the properties of a subclass of CMEs in the solar wind. However, it has proven difficult to assess their accuracy since the underlying global structure of the CME cannot be independently determined from the data. In contrast, large-scale MHD simulations of CME evolution can provide both a global view as well as localized time series at specific points in space. In this study we apply 5 different fitting techniques to 2 hypothetical time series derived from MHD simulation results. Independent teams performed the analysis of the events in "blind tests", for which no information, other than the time series, was provided. F rom the results, we infer the following: (1) Accuracy decreases markedly with increasingly glancing encounters; (2) Correct identification of the boundaries of the flux rope can be a significant limiter; and (3) Results from techniques that infer global morphology must be viewed with caution. In spite of these limitations, FRF techniques remain a useful tool for describing in situ observations of flux rope CMEs.

System identification of closed-loop cardiovascular control: effects of posture and autonomic blockade

NASA Technical Reports Server (NTRS)

Mullen, T. J.; Appel, M. L.; Mukkamala, R.; Mathias, J. M.; Cohen, R. J.

1997-01-01

We applied system identification to the analysis of fluctuations in heart rate (HR), arterial blood pressure (ABP), and instantaneous lung volume (ILV) to characterize quantitatively the physiological mechanisms responsible for the couplings between these variables. We characterized two autonomically mediated coupling mechanisms [the heart rate baroreflex (HR baroreflex) and respiratory sinus arrhythmia (ILV-HR)] and two mechanically mediated coupling mechanisms [the blood pressure wavelet generated with each cardiac contraction (circulatory mechanics) and the direct mechanical effects of respiration on blood pressure (ILV-->ABP)]. We evaluated the method in humans studied in the supine and standing postures under control conditions and under conditions of beta-sympathetic and parasympathetic pharmacological blockades. Combined beta-sympathetic and parasympathetic blockade abolished the autonomically mediated couplings while preserving the mechanically mediated coupling. Selective autonomic blockade and postural changes also altered the couplings in a manner consistent with known physiological mechanisms. System identification is an "inverse-modeling" technique that provides a means for creating a closed-loop model of cardiovascular regulation for an individual subject without altering the underlying physiological control mechanisms.

Variety identification of brown sugar using short-wave near infrared spectroscopy and multivariate calibration

NASA Astrophysics Data System (ADS)

Yang, Haiqing; Wu, Di; He, Yong

2007-11-01

Near-infrared spectroscopy (NIRS) with the characteristics of high speed, non-destructiveness, high precision and reliable detection data, etc. is a pollution-free, rapid, quantitative and qualitative analysis method. A new approach for variety discrimination of brown sugars using short-wave NIR spectroscopy (800-1050nm) was developed in this work. The relationship between the absorbance spectra and brown sugar varieties was established. The spectral data were compressed by the principal component analysis (PCA). The resulting features can be visualized in principal component (PC) space, which can lead to discovery of structures correlative with the different class of spectral samples. It appears to provide a reasonable variety clustering of brown sugars. The 2-D PCs plot obtained using the first two PCs can be used for the pattern recognition. Least-squares support vector machines (LS-SVM) was applied to solve the multivariate calibration problems in a relatively fast way. The work has shown that short-wave NIR spectroscopy technique is available for the brand identification of brown sugar, and LS-SVM has the better identification ability than PLS when the calibration set is small.

Future perspectives toward the early definition of a multivariate decision-support scheme employed in clinical decision making for senior citizens.

PubMed

Frantzidis, Christos A; Gilou, Sotiria; Billis, Antonis; Karagianni, Maria; Bratsas, Charalampos D; Bamidis, Panagiotis

2016-03-01

Recent neuroscientific studies focused on the identification of pathological neurophysiological patterns (emotions, geriatric depression, memory impairment and sleep disturbances) through computerised clinical decision-support systems. Almost all these research attempts employed either resting-state condition (e.g. eyes-closed) or event-related potentials extracted during a cognitive task known to be affected by the disease under consideration. This Letter reviews existing data mining techniques and aims to enhance their robustness by proposing a holistic decision framework dealing with comorbidities and early symptoms' identification, while it could be applied in realistic occasions. Multivariate features are elicited and fused in order to be compared with average activities characteristic of each neuropathology group. A proposed model of the specific cognitive function which may be based on previous findings (a priori information) and/or validated by current experimental data should be then formed. So, the proposed scheme facilitates the early identification and prevention of neurodegenerative phenomena. Neurophysiological semantic annotation is hypothesised to enhance the importance of the proposed framework in facilitating the personalised healthcare of the information society and medical informatics research community.

An adaptive learning control system for large flexible structures

NASA Technical Reports Server (NTRS)

Thau, F. E.

1985-01-01

The objective of the research has been to study the design of adaptive/learning control systems for the control of large flexible structures. In the first activity an adaptive/learning control methodology for flexible space structures was investigated. The approach was based on using a modal model of the flexible structure dynamics and an output-error identification scheme to identify modal parameters. In the second activity, a least-squares identification scheme was proposed for estimating both modal parameters and modal-to-actuator and modal-to-sensor shape functions. The technique was applied to experimental data obtained from the NASA Langley beam experiment. In the third activity, a separable nonlinear least-squares approach was developed for estimating the number of excited modes, shape functions, modal parameters, and modal amplitude and velocity time functions for a flexible structure. In the final research activity, a dual-adaptive control strategy was developed for regulating the modal dynamics and identifying modal parameters of a flexible structure. A min-max approach was used for finding an input to provide modal parameter identification while not exceeding reasonable bounds on modal displacement.

Multiplex-PCR As a Rapid and Sensitive Method for Identification of Meat Species in Halal-Meat Products.

PubMed

Alikord, Mahsa; Keramat, Javad; Kadivar, Mahdi; Momtaz, Hassan; Eshtiaghi, Mohammad N; Homayouni-Rad, Aziz

2017-01-01

Species identification and authentication in meat products are important subjects for ensuring the health of consumers. The multiplex-PCR amplification and species- specific primer set were used for the identification of horse, donkey, pig and other ruminants in raw and processed meat products. Oligonucleotid primers were designed and patented for amplification of species-specific mitochondrial DNA sequences of each species and samples were prepared from binary meat mixtures. The results showed that meat species were accurately determined in all combinations by multiplex-PCR, and the sensitivity of this method was 0.001 ng, rendering this technique open to and suitable for use in industrial meat products. It is concluded that more fraud is seen in lower percentage industrial meat products than in higher percentage ones. There was also more fraud found in processed products than in raw ones. This rapid and useful test is recommended for quality control firms for applying more rigorous controls over industrial meat products, for the benefit of target consumers. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Cryogenic Vibrational Spectroscopy Provides Unique Fingerprints for Glycan Identification.

PubMed

Masellis, Chiara; Khanal, Neelam; Kamrath, Michael Z; Clemmer, David E; Rizzo, Thomas R

2017-10-01

The structural characterization of glycans by mass spectrometry is particularly challenging. This is because of the high degree of isomerism in which glycans of the same mass can differ in their stereochemistry, attachment points, and degree of branching. Here we show that the addition of cryogenic vibrational spectroscopy to mass and mobility measurements allows one to uniquely identify and characterize these complex biopolymers. We investigate six disaccharide isomers that differ in their stereochemistry, attachment point of the glycosidic bond, and monosaccharide content, and demonstrate that we can identify each one unambiguously. Even disaccharides that differ by a single stereogenic center or in the monosaccharide sequence order show distinct vibrational fingerprints that would clearly allow their identification in a mixture, which is not possible by ion mobility spectrometry/mass spectrometry alone. Moreover, this technique can be applied to larger glycans, which we demonstrate by distinguishing isomeric branched and linear pentasaccharides. The creation of a database containing mass, collision cross section, and vibrational fingerprint measurements for glycan standards should allow unambiguous identification and characterization of these biopolymers in mixtures, providing an enabling technology for all fields of glycoscience. Graphical Abstract ᅟ.

A measurement fusion method for nonlinear system identification using a cooperative learning algorithm.

PubMed

Xia, Youshen; Kamel, Mohamed S

2007-06-01

Identification of a general nonlinear noisy system viewed as an estimation of a predictor function is studied in this article. A measurement fusion method for the predictor function estimate is proposed. In the proposed scheme, observed data are first fused by using an optimal fusion technique, and then the optimal fused data are incorporated in a nonlinear function estimator based on a robust least squares support vector machine (LS-SVM). A cooperative learning algorithm is proposed to implement the proposed measurement fusion method. Compared with related identification methods, the proposed method can minimize both the approximation error and the noise error. The performance analysis shows that the proposed optimal measurement fusion function estimate has a smaller mean square error than the LS-SVM function estimate. Moreover, the proposed cooperative learning algorithm can converge globally to the optimal measurement fusion function estimate. Finally, the proposed measurement fusion method is applied to ARMA signal and spatial temporal signal modeling. Experimental results show that the proposed measurement fusion method can provide a more accurate model.

The UAB Informatics Institute and 2016 CEGS N-GRID de-identification shared task challenge.

PubMed

Bui, Duy Duc An; Wyatt, Mathew; Cimino, James J

2017-11-01

Clinical narratives (the text notes found in patients' medical records) are important information sources for secondary use in research. However, in order to protect patient privacy, they must be de-identified prior to use. Manual de-identification is considered to be the gold standard approach but is tedious, expensive, slow, and impractical for use with large-scale clinical data. Automated or semi-automated de-identification using computer algorithms is a potentially promising alternative. The Informatics Institute of the University of Alabama at Birmingham is applying de-identification to clinical data drawn from the UAB hospital's electronic medical records system before releasing them for research. We participated in a shared task challenge by the Centers of Excellence in Genomic Science (CEGS) Neuropsychiatric Genome-Scale and RDoC Individualized Domains (N-GRID) at the de-identification regular track to gain experience developing our own automatic de-identification tool. We focused on the popular and successful methods from previous challenges: rule-based, dictionary-matching, and machine-learning approaches. We also explored new techniques such as disambiguation rules, term ambiguity measurement, and used multi-pass sieve framework at a micro level. For the challenge's primary measure (strict entity), our submissions achieved competitive results (f-measures: 87.3%, 87.1%, and 86.7%). For our preferred measure (binary token HIPAA), our submissions achieved superior results (f-measures: 93.7%, 93.6%, and 93%). With those encouraging results, we gain the confidence to improve and use the tool for the real de-identification task at the UAB Informatics Institute. Copyright © 2017 Elsevier Inc. All rights reserved.

Diagnostic use of 3 techniques for identification of microsporidian spores among AIDS patients in Portugal.

PubMed

Matos, Olga; Lobo, Maria L; Gonçalves, Luzia; Antunes, Francisco

2002-01-01

The calcofluor stain (CF), the monoclonal antibody (MAb) 3B6 indirect immunofluorescence assay (IFA) and the modified trichrome blue stain (MT) were compared in terms of their reproducibility in a routine laboratory and in order to evaluate the percentage of cases of microsporidiosis in Portuguese HIV patients. A total of 166 faeces samples, 71 pulmonary specimens and 43 urine samples were studied using the 3 techniques. CF had a high sensitivity and a moderate specificity when applied to faeces samples. The sensitivity was lower with pulmonary specimens. The method is easy and quick to perform but readings take a long time to obtain. The MAb 3B6 IFA had a good to excellent sensitivity when applied to faeces and urine samples, but moderate sensitivity in pulmonary specimens. Readings were quick and easy to obtain, but the assay took longer to perform than the other 2 techniques. There was a greater correlation between the results obtained with the MT and MAb 3B6 IFA techniques than between those obtained with the MT and CF techniques. In conclusion, the MT performed better than the MAb 3B6 IFA and CF and continues to have an important place in a routine laboratory for the diagnosis of microsporidiosis. This work also confirms the existence of a relatively high proportion (30%) of cases of infection with Microsporidia, especially intestinal microsporidiosis, in HIV patients in Portugal.

Identification of flame transfer functions in the presence of intrinsic thermoacoustic feedback and noise

NASA Astrophysics Data System (ADS)

Jaensch, Stefan; Merk, Malte; Emmert, Thomas; Polifke, Wolfgang

2018-05-01

The Large Eddy Simulation/System Identification (LES/SI) approach is a general and efficient numerical method for deducing a Flame Transfer Function (FTF) from the LES of turbulent reacting flow. The method may be summarised as follows: a simulated flame is forced with a broadband excitation signal. The resulting fluctuations of the reference velocity and of the global heat release rate are post-processed via SI techniques in order to estimate a low-order model of the flame dynamics. The FTF is readily deduced from the low-order model. The SI method most frequently applied in aero- and thermo-acoustics has been Wiener-Hopf Inversion (WHI). This method is known to yield biased estimates in situations with feedback, thus it was assumed that non-reflective boundary conditions are required to generate accurate results with the LES/SI approach. Recent research has shown that the FTF is part of the so-called Intrinsic ThermoAcoustic (ITA) feedback loop. Hence, identifying an FTF from a compressible LES is always a closed-loop problem, and consequently one should expect that the WHI would yield biased results. However, several studies proved that WHI results compare favourably with validation data. To resolve this apparent contradiction, a variety of identification methods are compared against each other, including models designed for closed-loop identification. In agreement with theory, we show that the estimate given by WHI does not converge to the actual FTF. Fortunately, the error made is small if excitation amplitudes can be set such that the signal-to-noise ratio is large, but not large enough to trigger nonlinear flame dynamics. Furthermore, we conclude that non-reflective boundary conditions are not essentially necessary to apply the LES/SI approach.

Direct PCR of indigenous and invasive mosquito species: a time- and cost-effective technique of mosquito barcoding.

PubMed

Werblow, A; Flechl, E; Klimpel, S; Zittra, C; Lebl, K; Kieser, K; Laciny, A; Silbermayr, K; Melaun, C; Fuehrer, H-P

2016-03-01

Millions of people die each year as a result of pathogens transmitted by mosquitoes. However, the morphological identification of mosquito species can be difficult even for experts. The identification of morphologically indistinguishable species, such as members of the Anopheles maculipennis complex (Diptera: Culicidae), and possible hybrids, such as Culex pipiens pipiens/Culex pipiens molestus (Diptera: Culicidae), presents a major problem. In addition, the detection and discrimination of newly introduced species can be challenging, particularly to researchers without previous experience. Because of their medical importance, the clear identification of all relevant mosquito species is essential. Using the direct polymerase chain reaction (PCR) method described here, DNA amplification without prior DNA extraction is possible and thus species identification after sequencing can be achieved. Different amounts of tissue (leg, head; larvae or adult) as well as different storage conditions (dry, ethanol, -20 and -80 °C) and storage times were successfully applied and showed positive results after amplification and gel electrophoresis. Overall, 28 different indigenous and non-indigenous mosquito species were analysed using a gene fragment of the COX1 gene for species differentiation and identification by sequencing this 658-bp fragment. Compared with standard PCR, this method is time- and cost-effective and could thus improve existing surveillance and control programmes. © 2015 The Authors. Medical and Veterinary Entomology published by John Wiley & Sons Ltd on behalf of Royal Entomological Society.

Petro-mineralogy and geochemistry as tools of provenance analysis on archaeological pottery: Study of Inka Period ceramics from Paria, Bolivia

NASA Astrophysics Data System (ADS)

Szilágyi, V.; Gyarmati, J.; Tóth, M.; Taubald, H.; Balla, M.; Kasztovszky, Zs.; Szakmány, Gy.

2012-07-01

This paper summarized the results of comprehensive petro-mineralogical and geochemical (archeometrical) investigation of Inka Period ceramics excavated from Inka (A.D. 1438-1535) and Late Intermediate Period (A.D. 1000/1200-1438) sites of the Paria Basin (Dept. Oruro, Bolivia). Applying geological analytical techniques we observed a complex and important archaeological subject of the region and the era, the cultural-economic influence of the conquering Inkas in the provincial region of Paria appearing in the ceramic material. According to our results, continuity and changes of raw material utilization and pottery manufacturing techniques from the Late Intermediate to the Inka Period are characterized by analytical methods. The geological field survey provided efficient basis for the identification of utilized raw material sources. On the one hand, ceramic supply of both eras proved to be based almost entirely on local and near raw material sources. So, imperial handicraft applied local materials but with sophisticated imperial techniques in Paria. On the other hand, Inka Imperial and local-style vessels also show clear differences in their material which suggests that sources and techniques functioned already in the Late Intermediate Period subsisted even after the Inka conquest of the Paria Basin. Based on our geological investigations, pottery supply system of the Paria region proved to be rather complex during the Inka Period.

Protein folding optimization based on 3D off-lattice model via an improved artificial bee colony algorithm.

PubMed

Li, Bai; Lin, Mu; Liu, Qiao; Li, Ya; Zhou, Changjun

2015-10-01

Protein folding is a fundamental topic in molecular biology. Conventional experimental techniques for protein structure identification or protein folding recognition require strict laboratory requirements and heavy operating burdens, which have largely limited their applications. Alternatively, computer-aided techniques have been developed to optimize protein structures or to predict the protein folding process. In this paper, we utilize a 3D off-lattice model to describe the original protein folding scheme as a simplified energy-optimal numerical problem, where all types of amino acid residues are binarized into hydrophobic and hydrophilic ones. We apply a balance-evolution artificial bee colony (BE-ABC) algorithm as the minimization solver, which is featured by the adaptive adjustment of search intensity to cater for the varying needs during the entire optimization process. In this work, we establish a benchmark case set with 13 real protein sequences from the Protein Data Bank database and evaluate the convergence performance of BE-ABC algorithm through strict comparisons with several state-of-the-art ABC variants in short-term numerical experiments. Besides that, our obtained best-so-far protein structures are compared to the ones in comprehensive previous literature. This study also provides preliminary insights into how artificial intelligence techniques can be applied to reveal the dynamics of protein folding. Graphical Abstract Protein folding optimization using 3D off-lattice model and advanced optimization techniques.

Fingerprint pattern restoration by digital image processing techniques.

PubMed

Wen, Che-Yen; Yu, Chiu-Chung

2003-09-01

Fingerprint evidence plays an important role in solving criminal problems. However, defective (lacking information needed for completeness) or contaminated (undesirable information included) fingerprint patterns make identifying and recognizing processes difficult. Unfortunately. this is the usual case. In the recognizing process (enhancement of patterns, or elimination of "false alarms" so that a fingerprint pattern can be searched in the Automated Fingerprint Identification System (AFIS)), chemical and physical techniques have been proposed to improve pattern legibility. In the identifying process, a fingerprint examiner can enhance contaminated (but not defective) fingerprint patterns under guidelines provided by the Scientific Working Group on Friction Ridge Analysis, Study and Technology (SWGFAST), the Scientific Working Group on Imaging Technology (SWGIT), and an AFIS working group within the National Institute of Justice. Recently, the image processing techniques have been successfully applied in forensic science. For example, we have applied image enhancement methods to improve the legibility of digital images such as fingerprints and vehicle plate numbers. In this paper, we propose a novel digital image restoration technique based on the AM (amplitude modulation)-FM (frequency modulation) reaction-diffusion method to restore defective or contaminated fingerprint patterns. This method shows its potential application to fingerprint pattern enhancement in the recognizing process (but not for the identifying process). Synthetic and real images are used to show the capability of the proposed method. The results of enhancing fingerprint patterns by the manual process and our method are evaluated and compared.

On-road and wind-tunnel measurement of motorcycle helmet noise.

PubMed

Kennedy, J; Carley, M; Walker, I; Holt, N

2013-09-01

The noise source mechanisms involved in motorcycling include various aerodynamic sources and engine noise. The problem of noise source identification requires extensive data acquisition of a type and level that have not previously been applied. Data acquisition on track and on road are problematic due to rider safety constraints and the portability of appropriate instrumentation. One way to address this problem is the use of data from wind tunnel tests. The validity of these measurements for noise source identification must first be demonstrated. In order to achieve this extensive wind tunnel tests have been conducted and compared with the results from on-track measurements. Sound pressure levels as a function of speed were compared between on track and wind tunnel tests and were found to be comparable. Spectral conditioning techniques were applied to separate engine and wind tunnel noise from aerodynamic noise and showed that the aerodynamic components were equivalent in both cases. The spectral conditioning of on-track data showed that the contribution of engine noise to the overall noise is a function of speed and is more significant than had previously been thought. These procedures form a basis for accurate experimental measurements of motorcycle noise.

Identification of unusual events in multichannel bridge monitoring data using wavelet transform and outlier analysis

NASA Astrophysics Data System (ADS)

Omenzetter, Piotr; Brownjohn, James M. W.; Moyo, Pilate

2003-08-01

Continuously operating instrumented structural health monitoring (SHM) systems are becoming a practical alternative to replace visual inspection for assessment of condition and soundness of civil infrastructure. However, converting large amount of data from an SHM system into usable information is a great challenge to which special signal processing techniques must be applied. This study is devoted to identification of abrupt, anomalous and potentially onerous events in the time histories of static, hourly sampled strains recorded by a multi-sensor SHM system installed in a major bridge structure in Singapore and operating continuously for a long time. Such events may result, among other causes, from sudden settlement of foundation, ground movement, excessive traffic load or failure of post-tensioning cables. A method of outlier detection in multivariate data has been applied to the problem of finding and localizing sudden events in the strain data. For sharp discrimination of abrupt strain changes from slowly varying ones wavelet transform has been used. The proposed method has been successfully tested using known events recorded during construction of the bridge, and later effectively used for detection of anomalous post-construction events.

Anti-theft device staining on banknotes detected by mass spectrometry imaging.

PubMed

Correa, Deleon Nascimento; Zacca, Jorge Jardim; Rocha, Werickson Fortunato de Carvalho; Borges, Rodrigo; de Souza, Wanderley; Augusti, Rodinei; Eberlin, Marcos Nogueira; Vendramini, Pedro Henrique

2016-03-01

We describe the identification and limits of detection of ink staining by mass spectrometry imaging (MSI), as used in anti-theft devices (ATDs). Such ink staining is applied to banknotes during automated teller machine (ATM) explosions. Desorption electrospray ionization (DESI) coupled with high-resolution and high-accuracy orbitrap mass spectrometry (MS) and a moving stage device were applied to obtain 2D molecular images of the major dyes used for staining, that is, 1-methylaminoanthraquinone (MAAQ), rhodamine B (RB) and rhodamine 6G (R6G). MAAQ could not be detected because of its inefficient desorption by DESI from the banknote cellulose surface. By contrast, ATD staining on banknotes is perceptible by the human naked eye only at concentrations higher than 0.2 μg cm(-2), whereas both RB and R6G at concentrations 200 times lower (as low as 0.001 μg cm(-2)) could be easily detected and imaged by DESI-MSI, with selective and specific identification of each analyte and their spatial distribution on samples from suspects. This technique is non-destructive, and no sample preparation is required, which ensures sample preservation for further forensic investigations. Copyright © 2016. Published by Elsevier Ireland Ltd.

A Program for the Identification of the Enterobacteriaceae for Use in Teaching the Principles of Computer Identification of Bacteria.

ERIC Educational Resources Information Center

Hammonds, S. J.

1990-01-01

A technique for the numerical identification of bacteria using normalized likelihoods calculated from a probabilistic database is described, and the principles of the technique are explained. The listing of the computer program is included. Specimen results from the program, and examples of how they should be interpreted, are given. (KR)

Comparison of modal identification techniques using a hybrid-data approach

NASA Technical Reports Server (NTRS)

Pappa, Richard S.

1986-01-01

Modal identification of seemingly simple structures, such as the generic truss is often surprisingly difficult in practice due to high modal density, nonlinearities, and other nonideal factors. Under these circumstances, different data analysis techniques can generate substantially different results. The initial application of a new hybrid-data method for studying the performance characteristics of various identification techniques with such data is summarized. This approach offers new pieces of information for the system identification researcher. First, it allows actual experimental data to be used in the studies, while maintaining the traditional advantage of using simulated data. That is, the identification technique under study is forced to cope with the complexities of real data, yet the performance can be measured unquestionably for the artificial modes because their true parameters are known. Secondly, the accuracy achieved for the true structural modes in the data can be estimated from the accuracy achieved for the artificial modes if the results show similar characteristics. This similarity occurred in the study, for example, for a weak structural mode near 56 Hz. It may even be possible--eventually--to use the error information from the artificial modes to improve the identification accuracy for the structural modes.

Identification of feces by detection of Bacteroides genes.

PubMed

Nakanishi, Hiroaki; Shojo, Hideki; Ohmori, Takeshi; Hara, Masaaki; Takada, Aya; Adachi, Noboru; Saito, Kazuyuki

2013-01-01

In forensic science, the identification of feces is very important in a variety of crime investigations. However, no sensitive and simple fecal identification method using molecular biological techniques has been reported. Here, we focused on the fecal bacteria, Bacteroides uniformis, Bacteroides vulgatus and Bacteroides thetaiotaomicron, and developed a novel fecal identification method by detection of the gene sequences specific to these bacteria in various body (feces, blood, saliva, semen, urine, vaginal fluids and skin surfaces) and forensic (anal adhesions) specimens. Bacterial gene detection was performed by real-time PCR using a minor groove binding probe to amplify the RNA polymerase β-subunit gene of B. uniformis and B. vulgatus, and the α-1-6 mannanase gene of B. thetaiotaomicron. At least one of these bacteria was detected in the feces of 20 donors; the proportions of B. uniformis, B. vulgatus and B. thetaiotaomicron were 95, 85 and 60%, respectively. Bacteroides vulgatus was also detected in one of six vaginal fluid samples, but B. thetaiotaomicron and B. uniformis were not detected in body samples other than feces. Further, we applied this method to forensic specimens from 18 donors. Eighteen anal adhesions also contained at least one of three bacteria; B. uniformis, B. vulgatus and B. thetaiotaomicron were detected in 89, 78 and 56%, respectively, of the specimens. Thus, these bacteria were present at a high frequency in the fecal and forensic specimens, while either B. uniformis or B. vulgatus was detected in all samples. Therefore, B. uniformis and B. vulgatus represent more appropriate target species than B. thetaiotaomicron for the identification of fecal material. If B. vulgatus and/or B. uniformis are detected, it is likely that the sample contains feces. Taken together, our results suggest that the use of molecular biological techniques will aid the detection of feces in forensic practice, although it is possible that the samples contained both feces and vaginal fluid. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

New approach to the differentiation of marble samples using thermal analysis and chemometrics in order to identify provenance

PubMed Central

2014-01-01

Background The possibility of applying a novel chemometric approach which could allow the differentiation of marble samples, all from different quarries located in the Mediterranean basin and frequently used in ancient times for artistic purposes, was investigated. By suggesting tentative or allowing to rule out unlikely attributions, this kind of differentiation could, indeed, be of valuable support to restorers and other professionals in the field of cultural heritage. Experimental data were obtained only using thermal analytical techniques: Thermogravimetry (TG), Derivative Thermogravimetry (DTG) and Differential Thermal Analysis (DTA). Results The extraction of kinetic parameters from the curves obtained using these thermal analytical techniques allowed Activation Energy values to be evaluated together with the logarithm of the Arrhenius pre-exponential factor of the main TG-DTG process. The main data thus obtained after subsequent chemometric evaluation (using Principal Components Analysis) have already proved useful in the identification the original quarry of a small number of archaeological marble finds. Conclusion One of the most evident advantages of the thermoanalytical – chemometric approach adopted seems to be that it allows the certain identification of an unknown find composed of a marble known to be present among the reference samples considered, that is, contained in the reference file. On the other hand with equal certainty it prevents the occurrence of erroneous or highly uncertain identification if the find being tested does not belong to the reference file considered. PMID:24982691

In vivo microcirculation imaging of the sub surface fingertip using correlation mapping optical coherence tomography (cmOCT)

NASA Astrophysics Data System (ADS)

Dsouza, Roshan I.; Zam, Azhar; Subhash, Hrebesh M.; Larin, Kirill V.; Leahy, Martin

2013-02-01

We describe a novel application of correlation mapping optical coherence tomography (cmOCT) for sub-surface fingerprint biometric identification. Fingerprint biometrics including automated fingerprint identification systems, are commonly used to recognise the fingerprint, since they constitute simple, effective and valuable physical evidence. Spoofing of biometric fingerprint devices can be easily done because of the limited information obtained from the surface topography. In order to overcome this limitation a potentially more secure source of information is required for biometric identification applications. In this study, we retrieve the microcirculation map of the subsurface fingertip by use of the cmOCT technique. To increase probing depth of the sub surface microcirculation, an optical clearing agent composed of 75% glycerol in aqueous solution was applied topically and kept in contact for 15 min. OCT intensity images were acquired from commercial research grade swept source OCT system (model OCT1300SS, Thorlabs Inc. USA). A 3D OCT scan of the fingertip was acquired over an area of 5x5 mm using 1024x1024 A-scans in approximately 70 s. The resulting volume was then processed using the cmOCT technique with a 7x7 kernel to provide a microcirculation map. We believe these results will demonstrate an enhanced security level over artificial fingertips. To the best of our knowledge, this is the first demonstration of imaging microcirculation map of the subsurface fingertip.

Direct thermal desorption in the analysis of cheese volatiles by gas chromatography and gas chromatography-mass spectrometry: comparison with simultaneous distillation-extraction and dynamic headspace.

PubMed

Valero, E; Sanz, J; Martínez-Castro, I

2001-06-01

Direct thermal desorption (DTD) has been used as a technique for extracting volatile components of cheese as a preliminary step to their gas chromatographic (GC) analysis. In this study, it is applied to different cheese varieties: Camembert, blue, Chaumes, and La Serena. Volatiles are also extracted using other techniques such as simultaneous distillation-extraction and dynamic headspace. Separation and identification of the cheese components are carried out by GC-mass spectrometry. Approximately 100 compounds are detected in the examined cheeses. The described results show that DTD is fast, simple, and easy to automate; requires only a small amount of sample (approximately 50 mg); and affords quantitative information about the main groups of compounds present in cheeses.

An analysis of pilot error-related aircraft accidents

NASA Technical Reports Server (NTRS)

Kowalsky, N. B.; Masters, R. L.; Stone, R. B.; Babcock, G. L.; Rypka, E. W.

1974-01-01

A multidisciplinary team approach to pilot error-related U.S. air carrier jet aircraft accident investigation records successfully reclaimed hidden human error information not shown in statistical studies. New analytic techniques were developed and applied to the data to discover and identify multiple elements of commonality and shared characteristics within this group of accidents. Three techniques of analysis were used: Critical element analysis, which demonstrated the importance of a subjective qualitative approach to raw accident data and surfaced information heretofore unavailable. Cluster analysis, which was an exploratory research tool that will lead to increased understanding and improved organization of facts, the discovery of new meaning in large data sets, and the generation of explanatory hypotheses. Pattern recognition, by which accidents can be categorized by pattern conformity after critical element identification by cluster analysis.

Subcritical flutter testing and system identification

NASA Technical Reports Server (NTRS)

Houbolt, J. C.

1974-01-01

Treatment is given of system response evaluation, especially in application to subcritical flight and wind tunnel flutter testing of aircraft. An evaluation is made of various existing techniques, in conjuction with a companion survey which reports theoretical and analog experiments made to study the identification of system response characteristics. Various input excitations are considered, and new techniques for analyzing response are explored, particularly in reference to the prevalent practical case where unwanted input noise is present, such as caused by gusts or wind tunnel turbulence. Further developments are also made of system parameter identification techniques.

Multidirectional In Vivo Characterization of Skin Using Wiener Nonlinear Stochastic System Identification Techniques.

PubMed

Parker, Matthew D; Jones, Lynette A; Hunter, Ian W; Taberner, A J; Nash, M P; Nielsen, P M F

2017-01-01

A triaxial force-sensitive microrobot was developed to dynamically perturb skin in multiple deformation modes, in vivo. Wiener static nonlinear identification was used to extract the linear dynamics and static nonlinearity of the force-displacement behavior of skin. Stochastic input forces were applied to the volar forearm and thenar eminence of the hand, producing probe tip perturbations in indentation and tangential extension. Wiener static nonlinear approaches reproduced the resulting displacements with variances accounted for (VAF) ranging 94-97%, indicating a good fit to the data. These approaches provided VAF improvements of 0.1-3.4% over linear models. Thenar eminence stiffness measures were approximately twice those measured on the forearm. Damping was shown to be significantly higher on the palm, whereas the perturbed mass typically was lower. Coefficients of variation (CVs) for nonlinear parameters were assessed within and across individuals. Individual CVs ranged from 2% to 11% for indentation and from 2% to 19% for extension. Stochastic perturbations with incrementally increasing mean amplitudes were applied to the same test areas. Differences between full-scale and incremental reduced-scale perturbations were investigated. Different incremental preloading schemes were investigated. However, no significant difference in parameters was found between different incremental preloading schemes. Incremental schemes provided depth-dependent estimates of stiffness and damping, ranging from 300 N/m and 2 Ns/m, respectively, at the surface to 5 kN/m and 50 Ns/m at greater depths. The device and techniques used in this research have potential applications in areas, such as evaluating skincare products, assessing skin hydration, or analyzing wound healing.

A knowledge-based approach to identification and adaptation in dynamical systems control

NASA Technical Reports Server (NTRS)

Glass, B. J.; Wong, C. M.

1988-01-01

Artificial intelligence techniques are applied to the problems of model form and parameter identification of large-scale dynamic systems. The object-oriented knowledge representation is discussed in the context of causal modeling and qualitative reasoning. Structured sets of rules are used for implementing qualitative component simulations, for catching qualitative discrepancies and quantitative bound violations, and for making reconfiguration and control decisions that affect the physical system. These decisions are executed by backward-chaining through a knowledge base of control action tasks. This approach was implemented for two examples: a triple quadrupole mass spectrometer and a two-phase thermal testbed. Results of tests with both of these systems demonstrate that the software replicates some or most of the functionality of a human operator, thereby reducing the need for a human-in-the-loop in the lower levels of control of these complex systems.

Identification of coupling direction: Application to cardiorespiratory interaction

NASA Astrophysics Data System (ADS)

Rosenblum, Michael G.; Cimponeriu, Laura; Bezerianos, Anastasios; Patzak, Andreas; Mrowka, Ralf

2002-04-01

We consider the problem of experimental detection of directionality of weak coupling between two self-sustained oscillators from bivariate data. We further develop the method introduced by Rosenblum and Pikovsky [Phys. Rev. E 64, 045202 (2001)], suggesting an alternative approach. Next, we consider another framework for identification of directionality, based on the idea of mutual predictability. Our algorithms provide directionality index that shows whether the coupling between the oscillators is unidirectional or bidirectional, and quantifies the asymmetry of bidirectional coupling. We demonstrate the efficiency of three different algorithms in determination of directionality index from short and noisy data. These techniques are then applied to analysis of cardiorespiratory interaction in healthy infants. The results reveal that the direction of coupling between cardiovascular and respiratory systems varies with the age within the first 6 months of life. We find a tendency to change from nearly symmetric bidirectional interaction to nearly unidirectional one (from respiration to the cardiovascular system).

Identification of dominant scattering mechanism in epitaxial graphene on SiC

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

Lin, Jingjing; Guo, Liwei, E-mail: lwguo@iphy.ac.cn, E-mail: chenx29@aphy.iphy.ac.cn; Jia, Yuping

2014-05-05

A scheme of identification of scattering mechanisms in epitaxial graphene (EG) on SiC substrate is developed and applied to three EG samples grown on SiC (0001), (112{sup ¯}0), and (101{sup ¯}0) substrates. Hall measurements combined with defect detection technique enable us to evaluate the individual contributions to the carrier scatterings by defects and by substrates. It is found that the dominant scatterings can be due to either substrate or defects, dependent on the substrate orientations. The EG on SiC (112{sup ¯}0) exhibits a better control over the two major scattering mechanisms and achieves the highest mobility even with a highmore » carrier concentration, promising for high performance graphene-based electronic devices. The method developed here will shed light on major aspects in governing carrier transport in EG to harness it effectively.« less

THz-wave parametric sources and imaging applications

NASA Astrophysics Data System (ADS)

Kawase, Kodo

2004-12-01

We have studied the generation of terahertz (THz) waves by optical parametric processes based on laser light scattering from the polariton mode of nonlinear crystals. Using parametric oscillation of MgO-doped LiNbO3 crystal pumped by a nano-second Q-switched Nd:YAG laser, we have realized a widely tunable coherent THz-wave sources with a simple configuration. We have also developed a novel basic technology for THz imaging, which allows detection and identification of chemicals by introducing the component spatial pattern analysis. The spatial distributions of the chemicals were obtained from terahertz multispectral trasillumination images, using absorption spectra previously measured with a widely tunable THz-wave parametric oscillator. Further we have applied this technique to the detection and identification of illicit drugs concealed in envelopes. The samples we used were methamphetamine and MDMA, two of the most widely consumed illegal drugs in Japan, and aspirin as a reference.

[The application of genome editing in identification of plant gene function and crop breeding].

PubMed

Zhou, Xiang-chun; Xing, Yong-zhong

2016-03-01

Plant genome can be modified via current biotechnology with high specificity and excellent efficiency. Zinc finger nucleases (ZFN), transcription activator-like effector nucleases (TALEN) and clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated 9 (Cas9) system are the key engineered nucleases used in the genome editing. Genome editing techniques enable gene targeted mutagenesis, gene knock-out, gene insertion or replacement at the target sites during the endogenous DNA repair process, including non-homologous end joining (NHEJ) and homologous recombination (HR), triggered by the induction of DNA double-strand break (DSB). Genome editing has been successfully applied in the genome modification of diverse plant species, such as Arabidopsis thaliana, Oryza sativa, and Nicotiana tabacum. In this review, we summarize the application of genome editing in identification of plant gene function and crop breeding. Moreover, we also discuss the improving points of genome editing in crop precision genetic improvement for further study.

Application of DNA-based methods in forensic entomology.

PubMed

Wells, Jeffrey D; Stevens, Jamie R

2008-01-01

A forensic entomological investigation can benefit from a variety of widely practiced molecular genotyping methods. The most commonly used is DNA-based specimen identification. Other applications include the identification of insect gut contents and the characterization of the population genetic structure of a forensically important insect species. The proper application of these procedures demands that the analyst be technically expert. However, one must also be aware of the extensive list of standards and expectations that many legal systems have developed for forensic DNA analysis. We summarize the DNA techniques that are currently used in, or have been proposed for, forensic entomology and review established genetic analyses from other scientific fields that address questions similar to those in forensic entomology. We describe how accepted standards for forensic DNA practice and method validation are likely to apply to insect evidence used in a death or other forensic entomological investigation.

Integration of Real-Time Intraoperative Contrast-Enhanced Ultrasound and Color Doppler Ultrasound in the Surgical Treatment of Spinal Cord Dural Arteriovenous Fistulas.

PubMed

Della Pepa, Giuseppe Maria; Sabatino, Giovanni; Sturiale, Carmelo Lucio; Marchese, Enrico; Puca, Alfredo; Olivi, Alessandro; Albanese, Alessio

2018-04-01

In the surgical treatment of spinal dural arteriovenous fistulas (DAVFs), intraoperative definition of anatomic characteristics of the DAVF and identification of the fistulous point is mandatory to effectively exclude the DAVF. Intraoperative ultrasound and contrast-enhanced ultrasound integrated with color Doppler ultrasound was applied in the surgical setting for a cervical DAVF to identify the fistulous point and evaluate correct occlusion of the fistula. Integration of intraoperative ultrasound and contrast-enhanced ultrasound is a simple, cost-effective technique that provides an opportunity for real-time dynamic visualization of DAVF vascular patterns, identification of the fistulous point, and assessment of correct exclusion. Compared with other intraoperative tools, such as indocyanine green videoangiography, it allows the surgeon to visualize hidden anatomic and vascular structures, minimizing surgical manipulation and guiding the surgeon during resection. Copyright © 2018 Elsevier Inc. All rights reserved.

Category identification of changed land-use polygons in an integrated image processing/geographic information system

NASA Technical Reports Server (NTRS)

Westmoreland, Sally; Stow, Douglas A.

1992-01-01

A framework is proposed for analyzing ancillary data and developing procedures for incorporating ancillary data to aid interactive identification of land-use categories in land-use updates. The procedures were developed for use within an integrated image processsing/geographic information systems (GIS) that permits simultaneous display of digital image data with the vector land-use data to be updated. With such systems and procedures, automated techniques are integrated with visual-based manual interpretation to exploit the capabilities of both. The procedural framework developed was applied as part of a case study to update a portion of the land-use layer in a regional scale GIS. About 75 percent of the area in the study site that experienced a change in land use was correctly labeled into 19 categories using the combination of automated and visual interpretation procedures developed in the study.

Simulation study into the identification of nuclear materials in cargo containers using cosmic rays

NASA Astrophysics Data System (ADS)

Blackwell, T. B.; Kudryavtsev, V. A.

2015-04-01

Muon tomography represents a new type of imaging technique that can be used in detecting high-Z materials. Monte Carlo simulations for muon scattering in different types of target materials are presented. The dependence of the detector capability to identify high-Z targets on spatial resolution has been studied. Muon tracks are reconstructed using a basic point of closest approach (PoCA) algorithm. In this article we report the development of a secondary analysis algorithm that is applied to the reconstructed PoCA points. This algorithm efficiently ascertains clusters of voxels with high average scattering angles to identify `areas of interest' within the inspected volume. Using this approach the effect of other parameters, such as the distance between detectors and the number of detectors per set, on material identification is also presented. Finally, false positive and false negative rates for detecting shielded HEU in realistic scenarios with low-Z clutter are presented.

E-Nose Vapor Identification Based on Dempster-Shafer Fusion of Multiple Classifiers

NASA Technical Reports Server (NTRS)

Li, Winston; Leung, Henry; Kwan, Chiman; Linnell, Bruce R.

2005-01-01

Electronic nose (e-nose) vapor identification is an efficient approach to monitor air contaminants in space stations and shuttles in order to ensure the health and safety of astronauts. Data preprocessing (measurement denoising and feature extraction) and pattern classification are important components of an e-nose system. In this paper, a wavelet-based denoising method is applied to filter the noisy sensor measurements. Transient-state features are then extracted from the denoised sensor measurements, and are used to train multiple classifiers such as multi-layer perceptions (MLP), support vector machines (SVM), k nearest neighbor (KNN), and Parzen classifier. The Dempster-Shafer (DS) technique is used at the end to fuse the results of the multiple classifiers to get the final classification. Experimental analysis based on real vapor data shows that the wavelet denoising method can remove both random noise and outliers successfully, and the classification rate can be improved by using classifier fusion.

Applications of Landsat data and the data base approach

USGS Publications Warehouse

Lauer, D.T.

1986-01-01

A generalized methodology for applying digital Landsat data to resource inventory and assessment tasks is currently being used by several bureaux and agencies within the US Department of the Interior. The methodology includes definition of project objectives and output, identification of source materials, construction of the digital data base, performance of computer-assisted analyses, and generation of output. The USGS, Bureau of Land Management, US Fish and Wildlife Service, Bureau of Indian Affairs, Bureau of Reclamation, and National Park Service have used this generalized methodology to assemble comprehensive digital data bases for resource management. Advanced information processing techniques have been applied to these data bases for making regional environmental surveys on millions of acres of public lands at costs ranging from $0.01 to $0.08 an acre.-Author

Structural identification of triacylglycerol isomers using electron impact excitation of ions from organics (EIEIO).

PubMed

Baba, Takashi; Campbell, J Larry; Le Blanc, J C Yves; Baker, Paul R S

2016-11-01

Electron-induced dissociation or electron impact excitation of ions from organics (EIEIO) was applied to triacylglycerols (TAGs) for in-depth molecular structure analysis using MS. In EIEIO, energetic electrons (∼10 eV) fragmented TAG ions to allow for regioisomeric assignment of identified acyl groups at the sn-2 or sn-1/3 positions of the glycerol backbone. In addition, carbon-carbon double bond locations within the acyl chains could also be assigned by EIEIO. Beyond the analysis of lipid standards, this technique was applied to edible oils and natural lipid extracts to demonstrate the power of this method to provide in-depth structural elucidation of TAG molecular species. Copyright © 2016 by the American Society for Biochemistry and Molecular Biology, Inc.

Identification of Linear and Nonlinear Aerodynamic Impulse Responses Using Digital Filter Techniques

NASA Technical Reports Server (NTRS)

Silva, Walter A.

1997-01-01

This paper discusses the mathematical existence and the numerically-correct identification of linear and nonlinear aerodynamic impulse response functions. Differences between continuous-time and discrete-time system theories, which permit the identification and efficient use of these functions, will be detailed. Important input/output definitions and the concept of linear and nonlinear systems with memory will also be discussed. It will be shown that indicial (step or steady) responses (such as Wagner's function), forced harmonic responses (such as Theodorsen's function or those from doublet lattice theory), and responses to random inputs (such as gusts) can all be obtained from an aerodynamic impulse response function. This paper establishes the aerodynamic impulse response function as the most fundamental, and, therefore, the most computationally efficient, aerodynamic function that can be extracted from any given discrete-time, aerodynamic system. The results presented in this paper help to unify the understanding of classical two-dimensional continuous-time theories with modern three-dimensional, discrete-time theories. First, the method is applied to the nonlinear viscous Burger's equation as an example. Next the method is applied to a three-dimensional aeroelastic model using the CAP-TSD (Computational Aeroelasticity Program - Transonic Small Disturbance) code and then to a two-dimensional model using the CFL3D Navier-Stokes code. Comparisons of accuracy and computational cost savings are presented. Because of its mathematical generality, an important attribute of this methodology is that it is applicable to a wide range of nonlinear, discrete-time problems.

Spot the match – wildlife photo-identification using information theory

PubMed Central

Speed, Conrad W; Meekan, Mark G; Bradshaw, Corey JA

2007-01-01

Background Effective approaches for the management and conservation of wildlife populations require a sound knowledge of population demographics, and this is often only possible through mark-recapture studies. We applied an automated spot-recognition program (I3S) for matching natural markings of wildlife that is based on a novel information-theoretic approach to incorporate matching uncertainty. Using a photo-identification database of whale sharks (Rhincodon typus) as an example case, the information criterion (IC) algorithm we developed resulted in a parsimonious ranking of potential matches of individuals in an image library. Automated matches were compared to manual-matching results to test the performance of the software and algorithm. Results Validation of matched and non-matched images provided a threshold IC weight (approximately 0.2) below which match certainty was not assured. Most images tested were assigned correctly; however, scores for the by-eye comparison were lower than expected, possibly due to the low sample size. The effect of increasing horizontal angle of sharks in images reduced matching likelihood considerably. There was a negative linear relationship between the number of matching spot pairs and matching score, but this relationship disappeared when using the IC algorithm. Conclusion The software and use of easily applied information-theoretic scores of match parsimony provide a reliable and freely available method for individual identification of wildlife, with wide applications and the potential to improve mark-recapture studies without resorting to invasive marking techniques. PMID:17227581

Identification of Linear and Nonlinear Aerodynamic Impulse Responses Using Digital Filter Techniques

NASA Technical Reports Server (NTRS)

Silva, Walter A.

1997-01-01

This paper discusses the mathematical existence and the numerically-correct identification of linear and nonlinear aerodynamic impulse response functions. Differences between continuous-time and discrete-time system theories, which permit the identification and efficient use of these functions, will be detailed. Important input/output definitions and the concept of linear and nonlinear systems with memory will also be discussed. It will be shown that indicial (step or steady) responses (such as Wagner's function), forced harmonic responses (such as Tbeodorsen's function or those from doublet lattice theory), and responses to random inputs (such as gusts) can all be obtained from an aerodynamic impulse response function. This paper establishes the aerodynamic impulse response function as the most fundamental, and, therefore, the most computationally efficient, aerodynamic function that can be extracted from any given discrete-time, aerodynamic system. The results presented in this paper help to unify the understanding of classical two-dimensional continuous-time theories with modem three-dimensional, discrete-time theories. First, the method is applied to the nonlinear viscous Burger's equation as an example. Next the method is applied to a three-dimensional aeroelastic model using the CAP-TSD (Computational Aeroelasticity Program - Transonic Small Disturbance) code and then to a two-dimensional model using the CFL3D Navier-Stokes code. Comparisons of accuracy and computational cost savings are presented. Because of its mathematical generality, an important attribute of this methodology is that it is applicable to a wide range of nonlinear, discrete-time problems.

An automated cross-correlation based event detection technique and its application to surface passive data set

USGS Publications Warehouse

Forghani-Arani, Farnoush; Behura, Jyoti; Haines, Seth S.; Batzle, Mike

2013-01-01

In studies on heavy oil, shale reservoirs, tight gas and enhanced geothermal systems, the use of surface passive seismic data to monitor induced microseismicity due to the fluid flow in the subsurface is becoming more common. However, in most studies passive seismic records contain days and months of data and manually analysing the data can be expensive and inaccurate. Moreover, in the presence of noise, detecting the arrival of weak microseismic events becomes challenging. Hence, the use of an automated, accurate and computationally fast technique for event detection in passive seismic data is essential. The conventional automatic event identification algorithm computes a running-window energy ratio of the short-term average to the long-term average of the passive seismic data for each trace. We show that for the common case of a low signal-to-noise ratio in surface passive records, the conventional method is not sufficiently effective at event identification. Here, we extend the conventional algorithm by introducing a technique that is based on the cross-correlation of the energy ratios computed by the conventional method. With our technique we can measure the similarities amongst the computed energy ratios at different traces. Our approach is successful at improving the detectability of events with a low signal-to-noise ratio that are not detectable with the conventional algorithm. Also, our algorithm has the advantage to identify if an event is common to all stations (a regional event) or to a limited number of stations (a local event). We provide examples of applying our technique to synthetic data and a field surface passive data set recorded at a geothermal site.

Technical management techniques for identification and control of industrial safety and pollution hazards

NASA Technical Reports Server (NTRS)

Campbell, R.; Dyer, M. K.; Hoard, E. G.; Little, D. G.; Taylor, A. C.

1972-01-01

Constructive recommendations are suggested for pollution problems from offshore energy resources industries on outer continental shelf. Technical management techniques for pollution identification and control offer possible applications to space engineering and management.

Identification of Optimum Magnetic Behavior of NanoCrystalline CmFeAl Type Heusler Alloy Powders Using Response Surface Methodology

NASA Astrophysics Data System (ADS)

Srivastava, Y.; Srivastava, S.; Boriwal, L.

2016-09-01

Mechanical alloying is a novelistic solid state process that has received considerable attention due to many advantages over other conventional processes. In the present work, Co2FeAl healer alloy powder, prepared successfully from premix basic powders of Cobalt (Co), Iron (Fe) and Aluminum (Al) in stoichiometric of 60Co-26Fe-14Al (weight %) by novelistic mechano-chemical route. Magnetic properties of mechanically alloyed powders were characterized by vibrating sample magnetometer (VSM). 2 factor 5 level design matrix was applied to experiment process. Experimental results were used for response surface methodology. Interaction between the input process parameters and the response has been established with the help of regression analysis. Further analysis of variance technique was applied to check the adequacy of developed model and significance of process parameters. Test case study was performed with those parameters, which was not selected for main experimentation but range was same. Response surface methodology, the process parameters must be optimized to obtain improved magnetic properties. Further optimum process parameters were identified using numerical and graphical optimization techniques.

Developing a targeted, theory-informed implementation intervention using two theoretical frameworks to address health professional and organisational factors: a case study to improve the management of mild traumatic brain injury in the emergency department.

PubMed

Tavender, Emma J; Bosch, Marije; Gruen, Russell L; Green, Sally E; Michie, Susan; Brennan, Sue E; Francis, Jill J; Ponsford, Jennie L; Knott, Jonathan C; Meares, Sue; Smyth, Tracy; O'Connor, Denise A

2015-05-25

Despite the availability of evidence-based guidelines for the management of mild traumatic brain injury in the emergency department (ED), variations in practice exist. Interventions designed to implement recommended behaviours can reduce this variation. Using theory to inform intervention development is advocated; however, there is no consensus on how to select or apply theory. Integrative theoretical frameworks, based on syntheses of theories and theoretical constructs relevant to implementation, have the potential to assist in the intervention development process. This paper describes the process of applying two theoretical frameworks to investigate the factors influencing recommended behaviours and the choice of behaviour change techniques and modes of delivery for an implementation intervention. A stepped approach was followed: (i) identification of locally applicable and actionable evidence-based recommendations as targets for change, (ii) selection and use of two theoretical frameworks for identifying barriers to and enablers of change (Theoretical Domains Framework and Model of Diffusion of Innovations in Service Organisations) and (iii) identification and operationalisation of intervention components (behaviour change techniques and modes of delivery) to address the barriers and enhance the enablers, informed by theory, evidence and feasibility/acceptability considerations. We illustrate this process in relation to one recommendation, prospective assessment of post-traumatic amnesia (PTA) by ED staff using a validated tool. Four recommendations for managing mild traumatic brain injury were targeted with the intervention. The intervention targeting the PTA recommendation consisted of 14 behaviour change techniques and addressed 6 theoretical domains and 5 organisational domains. The mode of delivery was informed by six Cochrane reviews. It was delivered via five intervention components : (i) local stakeholder meetings, (ii) identification of local opinion leader teams, (iii) a train-the-trainer workshop for appointed local opinion leaders, (iv) local training workshops for delivery by trained local opinion leaders and (v) provision of tools and materials to prompt recommended behaviours. Two theoretical frameworks were used in a complementary manner to inform intervention development in managing mild traumatic brain injury in the ED. The effectiveness and cost-effectiveness of the developed intervention is being evaluated in a cluster randomised trial, part of the Neurotrauma Evidence Translation (NET) program.

Identification of five highly priced tuna species by quantitative real-time polymerase chain reaction.

PubMed

Liu, Shasha; Xu, Kunhua; Wu, Zhigang; Xie, Xiao; Feng, Junli

2016-09-01

Tunas are economically important fishery worldwide, and are often used for commercial processed production. For effective fishery management and protection of consumers' rights, it is important to develop a molecular method to identify species in canned tuna products rapidly and reliably. Here, we have developed a duplex quantitative real-time PCR (qPCR) for identification of five highly priced tuna species (Thunnus maccoyii, Thunnus obesus, Thunnus albacares, Thunnus alalunga and Katsuwonus pelamis) from processed as well as fresh fish. After amplification and sequencing of seven genetic markers commonly used for species identification, 16S rDNA and control region (CR) of mitochondrial DNA were selected as the reference gene markers for genus Thunnus and tuna species identification, respectively. Subsequently, a 73 bp fragment of 16S rDNA and 85-99 bp fragment of CR were simultaneously amplified from each target species by qPCR. The qPCR efficiency of each reaction was calculated according to the standard curves, and the method was validated by amplification DNA extracted from single or mixed tuna specimen. The developed duplex qPCR system was applied to authenticate species of 14 commercial tuna products successfully, which demonstrated it was really a useful and academic technique to identify highly priced tuna species.

Evaluation of a speaker identification system with and without fusion using three databases in the presence of noise and handset effects

NASA Astrophysics Data System (ADS)

S. Al-Kaltakchi, Musab T.; Woo, Wai L.; Dlay, Satnam; Chambers, Jonathon A.

2017-12-01

In this study, a speaker identification system is considered consisting of a feature extraction stage which utilizes both power normalized cepstral coefficients (PNCCs) and Mel frequency cepstral coefficients (MFCC). Normalization is applied by employing cepstral mean and variance normalization (CMVN) and feature warping (FW), together with acoustic modeling using a Gaussian mixture model-universal background model (GMM-UBM). The main contributions are comprehensive evaluations of the effect of both additive white Gaussian noise (AWGN) and non-stationary noise (NSN) (with and without a G.712 type handset) upon identification performance. In particular, three NSN types with varying signal to noise ratios (SNRs) were tested corresponding to street traffic, a bus interior, and a crowded talking environment. The performance evaluation also considered the effect of late fusion techniques based on score fusion, namely, mean, maximum, and linear weighted sum fusion. The databases employed were TIMIT, SITW, and NIST 2008; and 120 speakers were selected from each database to yield 3600 speech utterances. As recommendations from the study, mean fusion is found to yield overall best performance in terms of speaker identification accuracy (SIA) with noisy speech, whereas linear weighted sum fusion is overall best for original database recordings.

System Identification for the Clipper Liberty C96 Wind Turbine

NASA Astrophysics Data System (ADS)

Showers, Daniel

System identification techniques are powerful tools that help improve modeling capabilities of real world dynamic systems. These techniques are well established and have been successfully used on countless systems in many areas. However, wind turbines provide a unique challenge for system identification because of the difficulty in measuring its primary input: wind. This thesis first motivates the problem by demonstrating the challenges with wind turbine system identification using both simulations and real data. It then suggests techniques toward successfully identifying a dynamic wind turbine model including the notion of an effective wind speed and how it might be measured. Various levels of simulation complexity are explored for insights into calculating an effective wind speed. In addition, measurements taken from the University of Minnesota's Clipper Liberty C96 research wind turbine are used for a preliminary investigation into the effective wind speed calculation and system identification of a real world wind turbine.

The Role of Lattice Matching Techniques in the Characterization of Polymorphic Forms.

PubMed

Mighell, Alan D

2011-01-01

An inspection of the recent literature reveals that polymorphism is a frequently encountered phenomenon. The recognition of polymorphic forms plays a vital role in the materials sciences because such structures are characterized by different crystal packing and accordingly have different physical properties. In the pharmaceutical industry, recognition of polymorphic forms can be critical for, in certain cases, a polymorphic form of a drug may be an ineffective therapeutic agent due to its unfavorable physical properties. A check of the recent literature has revealed that in some cases new polymorphic forms are not recognized. In other instances, a supposedly new polymeric form is actually the result of an incorrect structure determination. Fortunately, lattice-matching techniques, which have proved invaluable in the identification and characterization of crystal structures, represent a powerful tool for analyzing polymorphic forms. These lattice-matching methods are based on either of two strategies: (a) the reduced cell strategy-the matching of reduced cells of the respective lattices or (b) the matrix strategy-the determination of a matrix or matrices relating the two lattices coupled with an analysis of the matrix elements. Herein, these techniques are applied to three typical cases-(a) the identification of a new polymorphic form, (b) the demonstration that a substance may not be a new polymorphic form due to missed symmetry, and (c) the evaluation of pseudo polymorphism because of a missed lattice. To identify new polymorphic forms and to prevent errors, it is recommended that these lattice matching techniques become an integral part of the editorial review process of crystallography journals.

Complex chromosomal abnormalities in a patient with HTLV-1 positive T-cell leukemia

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

Hyde, P.; Macera, M.J.; Gogineni, S.K.

HTLV-1 positive adult T-cell leukemia (ATL) is associated with numerous chromosomal abnormalities. The chromosomal rearrangements can be extremely complex and additional material is often present, making precise identification by routine cytogenetic techniques difficult. We report a case of ATL that was established of bone marrow cells by both QFQ and GTG banding techniques revealed a highly complex 49,XX,der(2)t(2;?)(q37;?),+5,+2mar karyotype in the dividing cells. The identical cytogenetic findings were also seen in unstimulated peripheral blood collected one week later. Using the FISH-technique, we applied spectrum green-labeled No. 1- and No. 7-specific WCP, spectrum orange-labeled No. 2- and No. 5-specific WCP (GIBCO/BRL,more » Gaithersburg, MD) and biotin-labeled No. 18-specific WCP (Oncor, Gaithersburg, MD) to metaphase chromosomes. The large marker chromosome was identified as an extra 1q arm, the material attached to the distal 2q was additional 7q. The presence of three No. 5 chromosomes was verified and the small marker was determined to be an extra partial 5p in Robertsonian translocation with an additional partial 18q arm. The karyotype was revised to 49,XX,+1q,der(2)t(2;7)(q37;q22),+5,+t(5;18)(p14{r_arrow}p11::q11{r_arrow}q12). Identification of the numerous chromosomal anomalies associated with the disease by molecular techniques shall lead to a better understanding of this deadly cancer.« less

Identification of Uranium Minerals in Natural U-Bearing Rocks Using Infrared Reflectance Spectroscopy

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

Beiswenger, Toya N.; Gallagher, Neal B.; Myers, Tanya L.

The identification of minerals, including uranium-bearing minerals, is traditionally a labor-intensive-process using x-ray diffraction (XRD), fluorescence, or other solid-phase and wet chemical techniques. While handheld XRD and fluorescence instruments can aid in field identification, handheld infrared reflectance spectrometers can also be used in industrial or field environments, with rapid, non-destructive identification possible via spectral analysis of the solid’s reflectance spectrum. We have recently developed standard laboratory measurement methods for the infrared (IR) reflectance of solids and have investigated using these techniques for the identification of uranium-bearing minerals, using XRD methods for ground-truth. Due to the rich colors of such species,more » including distinctive spectroscopic signatures in the infrared, identification is facile and specific, both for samples that are pure or are partially composed of uranium (e.g. boltwoodite, schoepite, tyuyamunite, carnotite, etc.) or non-uranium minerals. The method can be used to detect not only pure and partial minerals, but is quite sensitive to chemical change such as hydration (e.g. schoepite). We have further applied statistical methods, in particular classical least squares (CLS) and multivariate curve resolution (MCR) for discrimination of such uranium minerals and two uranium pure chemicals (U3O8 and UO2) against common background materials (e.g. silica sand, asphalt, calcite, K-feldspar) with good success. Each mineral contains unique infrared spectral features; some of the IR features are similar or common to entire classes of minerals, typically arising from similar chemical moieties or functional groups in the minerals: phosphates, sulfates, carbonates, etc. These characteristic 2 infrared bands generate the unique (or class-specific) bands that distinguish the mineral from the interferents or backgrounds. We have observed several cases where the chemical moieties that provide the spectral discrimination in the longwave IR do so by generating upward-going reststrahlen bands in the reflectance data, but the same minerals have other weaker (overtone) bands, sometimes from the same chemical groups, that are manifest as downward-going transmission-type features in the midwave and shortwave infrared.« less

TOXICITY IDENTIFICATION EVALUATION (TIE) RESULTS FOR METAL CONTAMINATED SEDIMENTS

EPA Science Inventory

Identification of contaminants in sediment is necessary for sound management decisions on sediment disposal, remediation, determination of ecological risk, and source identification. We have been developing sediment toxicity identification evaluation (TIE) techniques that allow ...

Bring It to the Pitch: Combining Video and Movement Data to Enhance Team Sport Analysis.

PubMed

Stein, Manuel; Janetzko, Halldor; Lamprecht, Andreas; Breitkreutz, Thorsten; Zimmermann, Philipp; Goldlucke, Bastian; Schreck, Tobias; Andrienko, Gennady; Grossniklaus, Michael; Keim, Daniel A

2018-01-01

Analysts in professional team sport regularly perform analysis to gain strategic and tactical insights into player and team behavior. Goals of team sport analysis regularly include identification of weaknesses of opposing teams, or assessing performance and improvement potential of a coached team. Current analysis workflows are typically based on the analysis of team videos. Also, analysts can rely on techniques from Information Visualization, to depict e.g., player or ball trajectories. However, video analysis is typically a time-consuming process, where the analyst needs to memorize and annotate scenes. In contrast, visualization typically relies on an abstract data model, often using abstract visual mappings, and is not directly linked to the observed movement context anymore. We propose a visual analytics system that tightly integrates team sport video recordings with abstract visualization of underlying trajectory data. We apply appropriate computer vision techniques to extract trajectory data from video input. Furthermore, we apply advanced trajectory and movement analysis techniques to derive relevant team sport analytic measures for region, event and player analysis in the case of soccer analysis. Our system seamlessly integrates video and visualization modalities, enabling analysts to draw on the advantages of both analysis forms. Several expert studies conducted with team sport analysts indicate the effectiveness of our integrated approach.

The emergence of top-down proteomics in clinical research

PubMed Central

2013-01-01

Proteomic technology has advanced steadily since the development of 'soft-ionization' techniques for mass-spectrometry-based molecular identification more than two decades ago. Now, the large-scale analysis of proteins (proteomics) is a mainstay of biological research and clinical translation, with researchers seeking molecular diagnostics, as well as protein-based markers for personalized medicine. Proteomic strategies using the protease trypsin (known as bottom-up proteomics) were the first to be developed and optimized and form the dominant approach at present. However, researchers are now beginning to understand the limitations of bottom-up techniques, namely the inability to characterize and quantify intact protein molecules from a complex mixture of digested peptides. To overcome these limitations, several laboratories are taking a whole-protein-based approach, in which intact protein molecules are the analytical targets for characterization and quantification. We discuss these top-down techniques and how they have been applied to clinical research and are likely to be applied in the near future. Given the recent improvements in mass-spectrometry-based proteomics and stronger cooperation between researchers, clinicians and statisticians, both peptide-based (bottom-up) strategies and whole-protein-based (top-down) strategies are set to complement each other and help researchers and clinicians better understand and detect complex disease phenotypes. PMID:23806018

Synchroton and Simulations Techniques Applied to Problems in Materials Science: Catalysts and Azul Maya Pigments

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

Chianelli, R.

2005-01-12

Development of synchrotron techniques for the determination of the structure of disordered, amorphous and surface materials has exploded over the past twenty years due to the increasing availability of high flux synchrotron radiation and the continuing development of increasingly powerful synchrotron techniques. These techniques are available to materials scientists who are not necessarily synchrotron scientists through interaction with effective user communities that exist at synchrotrons such as the Stanford Synchrotron Radiation Laboratory (SSRL). In this article we review the application of multiple synchrotron characterization techniques to two classes of materials defined as ''surface compounds.'' One class of surface compounds aremore » materials like MoS{sub 2-x}C{sub x} that are widely used petroleum catalysts used to improve the environmental properties of transportation fuels. These compounds may be viewed as ''sulfide supported carbides'' in their catalytically active states. The second class of ''surface compounds'' is the ''Maya Blue'' pigments that are based on technology created by the ancient Maya. These compounds are organic/inorganic ''surface complexes'' consisting of the dye indigo and palygorskite, a common clay. The identification of both surface compounds relies on the application of synchrotron techniques as described in this report.« less

Simple and accurate methods for quantifying deformation, disruption, and development in biological tissues

PubMed Central

Boyle, John J.; Kume, Maiko; Wyczalkowski, Matthew A.; Taber, Larry A.; Pless, Robert B.; Xia, Younan; Genin, Guy M.; Thomopoulos, Stavros

2014-01-01

When mechanical factors underlie growth, development, disease or healing, they often function through local regions of tissue where deformation is highly concentrated. Current optical techniques to estimate deformation can lack precision and accuracy in such regions due to challenges in distinguishing a region of concentrated deformation from an error in displacement tracking. Here, we present a simple and general technique for improving the accuracy and precision of strain estimation and an associated technique for distinguishing a concentrated deformation from a tracking error. The strain estimation technique improves accuracy relative to other state-of-the-art algorithms by directly estimating strain fields without first estimating displacements, resulting in a very simple method and low computational cost. The technique for identifying local elevation of strain enables for the first time the successful identification of the onset and consequences of local strain concentrating features such as cracks and tears in a highly strained tissue. We apply these new techniques to demonstrate a novel hypothesis in prenatal wound healing. More generally, the analytical methods we have developed provide a simple tool for quantifying the appearance and magnitude of localized deformation from a series of digital images across a broad range of disciplines. PMID:25165601

Selective structural source identification

NASA Astrophysics Data System (ADS)

Totaro, Nicolas

2018-04-01

In the field of acoustic source reconstruction, the inverse Patch Transfer Function (iPTF) has been recently proposed and has shown satisfactory results whatever the shape of the vibrating surface and whatever the acoustic environment. These two interesting features are due to the virtual acoustic volume concept underlying the iPTF methods. The aim of the present article is to show how this concept of virtual subsystem can be used in structures to reconstruct the applied force distribution. Some virtual boundary conditions can be applied on a part of the structure, called virtual testing structure, to identify the force distribution applied in that zone regardless of the presence of other sources outside the zone under consideration. In the present article, the applicability of the method is only demonstrated on planar structures. However, the final example show how the method can be applied to a complex shape planar structure with point welded stiffeners even in the tested zone. In that case, if the virtual testing structure includes the stiffeners the identified force distribution only exhibits the positions of external applied forces. If the virtual testing structure does not include the stiffeners, the identified force distribution permits to localize the forces due to the coupling between the structure and the stiffeners through the welded points as well as the ones due to the external forces. This is why this approach is considered here as a selective structural source identification method. It is demonstrated that this approach clearly falls in the same framework as the Force Analysis Technique, the Virtual Fields Method or the 2D spatial Fourier transform. Even if this approach has a lot in common with these latters, it has some interesting particularities like its low sensitivity to measurement noise.

Application of Machine Learning to Proteomics Data: Classification and Biomarker Identification in Postgenomics Biology

PubMed Central

Swan, Anna Louise; Mobasheri, Ali; Allaway, David; Liddell, Susan

2013-01-01

Abstract Mass spectrometry is an analytical technique for the characterization of biological samples and is increasingly used in omics studies because of its targeted, nontargeted, and high throughput abilities. However, due to the large datasets generated, it requires informatics approaches such as machine learning techniques to analyze and interpret relevant data. Machine learning can be applied to MS-derived proteomics data in two ways. First, directly to mass spectral peaks and second, to proteins identified by sequence database searching, although relative protein quantification is required for the latter. Machine learning has been applied to mass spectrometry data from different biological disciplines, particularly for various cancers. The aims of such investigations have been to identify biomarkers and to aid in diagnosis, prognosis, and treatment of specific diseases. This review describes how machine learning has been applied to proteomics tandem mass spectrometry data. This includes how it can be used to identify proteins suitable for use as biomarkers of disease and for classification of samples into disease or treatment groups, which may be applicable for diagnostics. It also includes the challenges faced by such investigations, such as prediction of proteins present, protein quantification, planning for the use of machine learning, and small sample sizes. PMID:24116388

Borehole Time Domain Reflectometry in Layered Sandstone: Impact of Measurement Technique on Vadose Zone Process Identification

NASA Astrophysics Data System (ADS)

West, J.; Truss, S. W.

2004-12-01

An investigation is reported into the hydraulic behaviour of the vadose zone of a layered sandstone aquifer using borehole-based Time Domain Reflectometry (TDR). TDR has been widely applied to shallow soils but has seen limited application at greater depth and in cemented lithologies due to the difficulty of installing conventional TDR probes in rock and from boreholes. Here, flat TDR probes that are simply in contact with, rather than inserted within the medium under investigation, have been developed and applied in a field study. Both a commercially available portable packer TDR system (TRIME-B3L Borehole Packer Probe) and specially designed TDR probes, permanently installed in boreholes on grouted-in packers were used to monitor seasonal fluctuations in moisture content in the vadose zone of a layered sandstone over one year under natural rainfall loading. The data show that the vadose zone contains seasonal perched water tables that form when downward percolating moisture reaches layers of fine grained sandstone and siltstone and causes local saturation. The formation of perched water tables is likely to lead to lateral flow bypassing the less permeable, finer layers. This contrasts with behaviour inferred from previous studies of the same aquifer that used borehole radar and resistivity, which suggested its vadose zone behaviour was characterized by uniform downwards migration of wetting fronts. To investigate the impact of measurement technique on observed response, the TDR data reported here were used to produce simulated zero offset profile (ZOP) borehole radar responses. This simulation confirmed the limited ability of ZOP borehole radar to detect key vadose zone processes, because the phenomenon of critical refraction minimizes the sensitivity of the results to high moisture content layers. The study illustrates that inappropriate technique selection results in hydrological process mis-identification, with serious consequences for the usefulness of data in hydrological modeling.

Comparison on three classification techniques for sex estimation from the bone length of Asian children below 19 years old: an analysis using different group of ages.

PubMed

Darmawan, M F; Yusuf, Suhaila M; Kadir, M R Abdul; Haron, H

2015-02-01

Sex estimation is used in forensic anthropology to assist the identification of individual remains. However, the estimation techniques tend to be unique and applicable only to a certain population. This paper analyzed sex estimation on living individual child below 19 years old using the length of 19 bones of left hand applied for three classification techniques, which were Discriminant Function Analysis (DFA), Support Vector Machine (SVM) and Artificial Neural Network (ANN) multilayer perceptron. These techniques were carried out on X-ray images of the left hand taken from an Asian population data set. All the 19 bones of the left hand were measured using Free Image software, and all the techniques were performed using MATLAB. The group of age "16-19" years old and "7-9" years old were the groups that could be used for sex estimation with as their average of accuracy percentage was above 80%. ANN model was the best classification technique with the highest average of accuracy percentage in the two groups of age compared to other classification techniques. The results show that each classification technique has the best accuracy percentage on each different group of age. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Air versus saline in the loss of resistance technique for identification of the epidural space.

PubMed

Antibas, Pedro L; do Nascimento Junior, Paulo; Braz, Leandro G; Vitor Pereira Doles, João; Módolo, Norma S P; El Dib, Regina

2014-07-18

The success of epidural anaesthesia depends on correct identification of the epidural space. For several decades, the decision of whether to use air or physiological saline during the loss of resistance technique for identification of the epidural space has been governed by the personal experience of the anaesthesiologist. Epidural block remains one of the main regional anaesthesia techniques. It is used for surgical anaesthesia, obstetrical analgesia, postoperative analgesia and treatment of chronic pain and as a complement to general anaesthesia. The sensation felt by the anaesthesiologist from the syringe plunger with loss of resistance is different when air is compared with saline (fluid). Frequently fluid allows a rapid change from resistance to non-resistance and increased movement of the plunger. However, the ideal technique for identification of the epidural space remains unclear. • To evaluate the efficacy and safety of both air and saline in the loss of resistance technique for identification of the epidural space.• To evaluate complications related to the air or saline injected. We searched the Cochrane Central Register of Controlled Trials (CENTRAL) (2013, Issue 9), MEDLINE, EMBASE and the Latin American and Caribbean Health Science Information Database (LILACS) (from inception to September 2013). We applied no language restrictions. The date of the most recent search was 7 September 2013. We included randomized controlled trials (RCTs) and quasi-randomized controlled trials (quasi-RCTs) on air and saline in the loss of resistance technique for identification of the epidural space. Two review authors independently assessed trial quality and extracted data. We included in the review seven studies with a total of 852 participants. The methodological quality of the included studies was generally ranked as showing low risk of bias in most domains, with the exception of one study, which did not mask participants. We were able to include data from 838 participants in the meta-analysis. We found no statistically significant differences between participants receiving air and those given saline in any of the outcomes evaluated: inability to locate the epidural space (three trials, 619 participants) (risk ratio (RR) 0.88, 95% confidence interval (CI) 0.33 to 2.31, low-quality evidence); accidental intravascular catheter placement (two trials, 223 participants) (RR 0.90, 95% CI 0.33 to 2.45, low-quality evidence); accidental subarachnoid catheter placement (four trials, 682 participants) (RR 2.95, 95% CI 0.12 to 71.90, low-quality evidence); combined spinal epidural failure (two trials, 400 participants) (RR 0.98, 95% CI 0.44 to 2.18, low-quality evidence); unblocked segments (five studies, 423 participants) (RR 1.66, 95% CI 0.72 to 3.85); and pain measured by VAS (two studies, 395 participants) (mean difference (MD) -0.09, 95% CI -0.37 to 0.18). With regard to adverse effects, we found no statistically significant differences between participants receiving air and those given saline in the occurrence of paraesthesias (three trials, 572 participants) (RR 0.89, 95% CI 0.69 to 1.15); difficulty in advancing the catheter (two trials, 227 participants) (RR 0.91, 95% CI 0.32 to 2.56); catheter replacement (two trials, 501 participants) (RR 0.69, 95% CI 0.26 to 1.83); and postdural puncture headache (one trial, 110 participants) (RR 0.83, 95% CI 0.12 to 5.71). Low-quality evidence shows that results do not differ between air and saline in terms of the loss of resistance technique for identification of the epidural space and reduction of complications. Applicability might be compromised, as most of the results described in this review were obtained from parturient patients. This review underlines the need to conduct well-designed trials in this field. 

Yeast identification: reassessment of assimilation tests as sole universal identifiers.

PubMed

Spencer, J; Rawling, S; Stratford, M; Steels, H; Novodvorska, M; Archer, D B; Chandra, S

2011-11-01

To assess whether assimilation tests in isolation remain a valid method of identification of yeasts, when applied to a wide range of environmental and spoilage isolates. Seventy-one yeast strains were isolated from a soft drinks factory. These were identified using assimilation tests and by D1/D2 rDNA sequencing. When compared to sequencing, assimilation test identifications (MicroLog™) were 18·3% correct, a further 14·1% correct within the genus and 67·6% were incorrectly identified. The majority of the latter could be attributed to the rise in newly reported yeast species. Assimilation tests alone are unreliable as a universal means of yeast identification, because of numerous new species, variability of strains and increasing coincidence of assimilation profiles. Assimilation tests still have a useful role in the identification of common species, such as the majority of clinical isolates. It is probable, based on these results, that many yeast identifications reported in older literature are incorrect. This emphasizes the crucial need for accurate identification in present and future publications. © 2011 The Authors. Letters in Applied Microbiology © 2011 The Society for Applied Microbiology.

High-Throughput Block Optical DNA Sequence Identification.

PubMed

Sagar, Dodderi Manjunatha; Korshoj, Lee Erik; Hanson, Katrina Bethany; Chowdhury, Partha Pratim; Otoupal, Peter Britton; Chatterjee, Anushree; Nagpal, Prashant

2018-01-01

Optical techniques for molecular diagnostics or DNA sequencing generally rely on small molecule fluorescent labels, which utilize light with a wavelength of several hundred nanometers for detection. Developing a label-free optical DNA sequencing technique will require nanoscale focusing of light, a high-throughput and multiplexed identification method, and a data compression technique to rapidly identify sequences and analyze genomic heterogeneity for big datasets. Such a method should identify characteristic molecular vibrations using optical spectroscopy, especially in the "fingerprinting region" from ≈400-1400 cm -1 . Here, surface-enhanced Raman spectroscopy is used to demonstrate label-free identification of DNA nucleobases with multiplexed 3D plasmonic nanofocusing. While nanometer-scale mode volumes prevent identification of single nucleobases within a DNA sequence, the block optical technique can identify A, T, G, and C content in DNA k-mers. The content of each nucleotide in a DNA block can be a unique and high-throughput method for identifying sequences, genes, and other biomarkers as an alternative to single-letter sequencing. Additionally, coupling two complementary vibrational spectroscopy techniques (infrared and Raman) can improve block characterization. These results pave the way for developing a novel, high-throughput block optical sequencing method with lossy genomic data compression using k-mer identification from multiplexed optical data acquisition. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Restart Operator Meta-heuristics for a Problem-Oriented Evolutionary Strategies Algorithm in Inverse Mathematical MISO Modelling Problem Solving

NASA Astrophysics Data System (ADS)

Ryzhikov, I. S.; Semenkin, E. S.

2017-02-01

This study is focused on solving an inverse mathematical modelling problem for dynamical systems based on observation data and control inputs. The mathematical model is being searched in the form of a linear differential equation, which determines the system with multiple inputs and a single output, and a vector of the initial point coordinates. The described problem is complex and multimodal and for this reason the proposed evolutionary-based optimization technique, which is oriented on a dynamical system identification problem, was applied. To improve its performance an algorithm restart operator was implemented.

Laboratory Diagnosis of Infective Endocarditis

PubMed Central

Liesman, Rachael M.; Pritt, Bobbi S.; Maleszewski, Joseph J.

2017-01-01

ABSTRACT Infective endocarditis is life-threatening; identification of the underlying etiology informs optimized individual patient management. Changing epidemiology, advances in blood culture techniques, and new diagnostics guide the application of laboratory testing for diagnosis of endocarditis. Blood cultures remain the standard test for microbial diagnosis, with directed serological testing (i.e., Q fever serology, Bartonella serology) in culture-negative cases. Histopathology and molecular diagnostics (e.g., 16S rRNA gene PCR/sequencing, Tropheryma whipplei PCR) may be applied to resected valves to aid in diagnosis. Herein, we summarize recent knowledge in this area and propose a microbiologic and pathological algorithm for endocarditis diagnosis. PMID:28659319

Detection of soybean rust contamination in soy leaves by FTIR photoacoustic spectroscopy

NASA Astrophysics Data System (ADS)

Andrade, L. H. C.; Freitas, P. G.; Mantovani, B. G.; Figueiredo, M. S.; Lima, R. A.; Lima, S. M.; Rangel, M. A. S.; Mussury, R. M.

2008-01-01

In this work the Photoacoustic Infrared Spectroscopy from 4000 to 400 cm-1 was applied, by the first time to our knowledge, to diagnostic the soy bean rust or Asian rust contamination on soy leafs caused by the fungi Phakopsora pachyrhizi. The obtained results shown that a premature, fast and precise diagnosis can be achieved using this technique before it can be detect by the conventional visual method. The early identification of the fungi infection avoid massive lost in the soy production and decrease the intense use of fungicide whose is necessary when the infection is in advanced stagy.

Input reconstruction of chaos sensors.

PubMed

Yu, Dongchuan; Liu, Fang; Lai, Pik-Yin

2008-06-01

Although the sensitivity of sensors can be significantly enhanced using chaotic dynamics due to its extremely sensitive dependence on initial conditions and parameters, how to reconstruct the measured signal from the distorted sensor response becomes challenging. In this paper we suggest an effective method to reconstruct the measured signal from the distorted (chaotic) response of chaos sensors. This measurement signal reconstruction method applies the neural network techniques for system structure identification and therefore does not require the precise information of the sensor's dynamics. We discuss also how to improve the robustness of reconstruction. Some examples are presented to illustrate the measurement signal reconstruction method suggested.

Research and design on system of asset management based on RFID

NASA Astrophysics Data System (ADS)

Guan, Peng; Du, HuaiChang; Jing, Hua; Zhang, MengYue; Zhang, Meng; Xu, GuiXian

2011-10-01

By analyzing the problems in the current assets management, this thesis proposing RFID technology will be applied to asset management in order to improve the management level of automation and information. This paper designed the equipment identification based on 433MHz RFID tag and reader which was deeply studied on the basis of RFID tag and card reader circuits, and this paper also illustrates the system of asset management. The RS232 converts Ethernet is a innovative technology to transfer data to PC monitor software, and implement system of asset management based on WEB techniques (PHP and MySQL).

The scientific dating of standing buildings.

PubMed

Alcock, Nathaniel W

2017-11-17

The techniques of dendrochronology (tree-ring dating) and radiocarbon (14C) dating are described, as they are applied to historic buildings. Both rely on determining the felling dates of the trees used in their construction. For dendrochronology, the construction of master chronologies and the matching of individual ring-width sequences to them is described and, for radiocarbon dating, the use of tree-ring results in calibration. Results of dating are discussed, ranging from the cathedrals of Peterborough and Beauvais and the development of crown-post roof structures, to the dating and identification of standing medieval peasant houses, particularly those built using cruck construction.

Computational inverse methods of heat source in fatigue damage problems

NASA Astrophysics Data System (ADS)

Chen, Aizhou; Li, Yuan; Yan, Bo

2018-04-01

Fatigue dissipation energy is the research focus in field of fatigue damage at present. It is a new idea to solve the problem of calculating fatigue dissipation energy by introducing inverse method of heat source into parameter identification of fatigue dissipation energy model. This paper introduces the research advances on computational inverse method of heat source and regularization technique to solve inverse problem, as well as the existing heat source solution method in fatigue process, prospects inverse method of heat source applying in fatigue damage field, lays the foundation for further improving the effectiveness of fatigue dissipation energy rapid prediction.

Application of clustering for customer segmentation in private banking

NASA Astrophysics Data System (ADS)

Yang, Xuan; Chen, Jin; Hao, Pengpeng; Wang, Yanbo J.

2015-07-01

With fierce competition in banking industry, more and more banks have realised that accurate customer segmentation is of fundamental importance, especially for the identification of those high-value customers. In order to solve this problem, we collected real data about private banking customers of a commercial bank in China, conducted empirical analysis by applying K-means clustering technique. When determine the K value, we propose a mechanism that meet both academic requirements and practical needs. Through K-means clustering, we successfully segmented the customers into three categories, and features of each group have been illustrated in details.

HLRW management during MR reactor decommissioning in NRC 'Kurchatov Institute'

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

Chesnokov, Alexander; Ivanov, Oleg; Kolyadin, Vyacheslav

2013-07-01

A program of decommissioning of MR research reactor in the Kurchatov institute started in 2008. The decommissioning work presumed a preliminary stage, which included: removal of spent fuel from near reactor storage; removal of spent fuel assemble of metal liquid loop channel from a core; identification, sorting and disposal of radioactive objects from gateway of the reactor; identification, sorting and disposal of radioactive objects from cells of HLRW storage of the Kurchatov institute for radwaste creating form the decommissioning of MR. All these works were performed by a remote controlled means with use of a remote identification methods of highmore » radioactive objects. A distribution of activity along high radiated objects was measured by a collimated radiometer installed on the robot Brokk-90, a gamma image of the object was registered by gamma-visor. Spectrum of gamma radiation was measured by a gamma locator and semiconductor detector system. For identification of a presence of uranium isotopes in the HLRW a technique, based on the registration of characteristic radiation of U, was developed. For fragmentation of high radiated objects was used a cold cutting technique and dust suppression system was applied for reduction of volume activity of aerosols in air. The management of HLRW was performed by remote controlled robots Brokk-180 and Brokk-330. They executed sorting, cutting and parking of high radiated part of contaminated equipment. The use of these techniques allowed to reduce individual and collective doses of personal performed the decommissioning. The average individual dose of the personnel was 1,9 mSv/year in 2011, and the collective dose is estimated by 0,0605 man x Sv/year. Use of the remote control machines enables reducing the number of working personal (20 men) and doses. X-ray spectrometric methods enable determination of a presence of the U in high radiated objects and special cans and separation of them for further spent fuel inspection. The sorting of radwaste enabled shipping of the LLRW and ILRW to special repositories and keeping of the HLRW for decay in the Kurchatov institute repository. (authors)« less

An overview of the essential differences and similarities of system identification techniques

NASA Technical Reports Server (NTRS)

Mehra, Raman K.

1991-01-01

Information is given in the form of outlines, graphs, tables and charts. Topics include system identification, Bayesian statistical decision theory, Maximum Likelihood Estimation, identification methods, structural mode identification using a stochastic realization algorithm, and identification results regarding membrane simulations and X-29 flutter flight test data.

DNA barcoding: an efficient tool to overcome authentication challenges in the herbal market.

PubMed

Mishra, Priyanka; Kumar, Amit; Nagireddy, Akshitha; Mani, Daya N; Shukla, Ashutosh K; Tiwari, Rakesh; Sundaresan, Velusamy

2016-01-01

The past couple of decades have witnessed global resurgence of herbal-based health care. As a result, the trade of raw drugs has surged globally. Accurate and fast scientific identification of the plant(s) is the key to success for the herbal drug industry. The conventional approach is to engage an expert taxonomist, who uses a mix of traditional and modern techniques for precise plant identification. However, for bulk identification at industrial scale, the process is protracted and time-consuming. DNA barcoding, on the other hand, offers an alternative and feasible taxonomic tool box for rapid and robust species identification. For the success of DNA barcode, the barcode loci must have sufficient information to differentiate unambiguously between closely related plant species and discover new cryptic species. For herbal plant identification, matK, rbcL, trnH-psbA, ITS, trnL-F, 5S-rRNA and 18S-rRNA have been used as successful DNA barcodes. Emerging advances in DNA barcoding coupled with next-generation sequencing and high-resolution melting curve analysis have paved the way for successful species-level resolution recovered from finished herbal products. Further, development of multilocus strategy and its application has provided new vistas to the DNA barcode-based plant identification for herbal drug industry. For successful and acceptable identification of herbal ingredients and a holistic quality control of the drug, DNA barcoding needs to work harmoniously with other components of the systems biology approach. We suggest that for effectively resolving authentication challenges associated with the herbal market, DNA barcoding must be used in conjunction with metabolomics along with need-based transcriptomics and proteomics. © 2015 Society for Experimental Biology, Association of Applied Biologists and John Wiley & Sons Ltd.

Bacteriophage Amplification-Coupled Detection and Identification of Bacterial Pathogens

NASA Astrophysics Data System (ADS)

Cox, Christopher R.; Voorhees, Kent J.

Current methods of species-specific bacterial detection and identification are complex, time-consuming, and often require expensive specialized equipment and highly trained personnel. Numerous biochemical and genotypic identification methods have been applied to bacterial characterization, but all rely on tedious microbiological culturing practices and/or costly sequencing protocols which render them impractical for deployment as rapid, cost-effective point-of-care or field detection and identification methods. With a view towards addressing these shortcomings, we have exploited the evolutionarily conserved interactions between a bacteriophage (phage) and its bacterial host to develop species-specific detection methods. Phage amplification-coupled matrix assisted laser desorption time-of-flight mass spectrometry (MALDI-TOF-MS) was utilized to rapidly detect phage propagation resulting from species-specific in vitro bacterial infection. This novel signal amplification method allowed for bacterial detection and identification in as little as 2 h, and when combined with disulfide bond reduction methods developed in our laboratory to enhance MALDI-TOF-MS resolution, was observed to lower the limit of detection by several orders of magnitude over conventional spectroscopy and phage typing methods. Phage amplification has been combined with lateral flow immunochromatography (LFI) to develop rapid, easy-to-operate, portable, species-specific point-of-care (POC) detection devices. Prototype LFI detectors have been developed and characterized for Yersinia pestis and Bacillus anthracis, the etiologic agents of plague and anthrax, respectively. Comparable sensitivity and rapidity was observed when phage amplification was adapted to a species-specific handheld LFI detector, thus allowing for rapid, simple, POC bacterial detection and identification while eliminating the need for bacterial culturing or DNA isolation and amplification techniques.

41 CFR 102-34.190 - What special requirements apply to exempted motor vehicles using District of Columbia or State...

Code of Federal Regulations, 2014 CFR

2014-01-01

... Registering Motor Vehicles Identification Exemptions § 102-34.190 What special requirements apply to exempted... and motor vehicle identification. The agency head must provide the name and signature of that official... requirements apply to exempted motor vehicles using District of Columbia or State license plates? 102-34.190...

41 CFR 102-34.190 - What special requirements apply to exempted motor vehicles using District of Columbia or State...

Code of Federal Regulations, 2010 CFR

2010-07-01

... Registering Motor Vehicles Identification Exemptions § 102-34.190 What special requirements apply to exempted... and motor vehicle identification. The agency head must provide the name and signature of that official... requirements apply to exempted motor vehicles using District of Columbia or State license plates? 102-34.190...

41 CFR 102-34.190 - What special requirements apply to exempted motor vehicles using District of Columbia or State...

Code of Federal Regulations, 2011 CFR

2011-01-01

... Registering Motor Vehicles Identification Exemptions § 102-34.190 What special requirements apply to exempted... and motor vehicle identification. The agency head must provide the name and signature of that official... requirements apply to exempted motor vehicles using District of Columbia or State license plates? 102-34.190...

41 CFR 102-34.190 - What special requirements apply to exempted motor vehicles using District of Columbia or State...

Code of Federal Regulations, 2012 CFR

2012-01-01

... Registering Motor Vehicles Identification Exemptions § 102-34.190 What special requirements apply to exempted... and motor vehicle identification. The agency head must provide the name and signature of that official... requirements apply to exempted motor vehicles using District of Columbia or State license plates? 102-34.190...

41 CFR 102-34.190 - What special requirements apply to exempted motor vehicles using District of Columbia or State...

Code of Federal Regulations, 2013 CFR

2013-07-01

... Registering Motor Vehicles Identification Exemptions § 102-34.190 What special requirements apply to exempted... and motor vehicle identification. The agency head must provide the name and signature of that official... requirements apply to exempted motor vehicles using District of Columbia or State license plates? 102-34.190...

Validation of a computer modelled forensic facial reconstruction technique using CT data from live subjects: a pilot study.

PubMed

Short, Laura J; Khambay, Balvinder; Ayoub, Ashraf; Erolin, Caroline; Rynn, Chris; Wilkinson, Caroline

2014-04-01

Human forensic facial soft tissue reconstructions are used when post-mortem deterioration makes identification difficult by usual means. The aim is to trigger recognition of the in vivo countenance of the individual by a friend or family member. A further use is in the field of archaeology. There are a number of different methods that can be applied to complete the facial reconstruction, ranging from two dimensional drawings, three dimensional clay models and now, with the advances of three dimensional technology, three dimensional computerised modelling. Studies carried out to assess the accuracy of facial reconstructions have produced variable results over the years. Advances in three dimensional imaging techniques in the field of oral and maxillofacial surgery, particularly cone beam computed tomography (CBCT), now provides an opportunity to utilise the data of live subjects and assess the accuracy of the three dimensional computerised facial reconstruction technique. The aim of this study was to assess the accuracy of a computer modelled facial reconstruction technique using CBCT data from live subjects. This retrospective pilot study was carried out at the Glasgow Dental Hospital Orthodontic Department and the Centre of Anatomy and Human Identification, Dundee University School of Life Sciences. Ten patients (5 male and 5 female; mean age 23 years) with mild skeletal discrepancies with pre-surgical cone beam CT data (CBCT) were included in this study. The actual and forensic reconstruction soft tissues were analysed using 3D software to look at differences between landmarks, linear and angular measurements and surface meshes. There were no statistical differences for 18 out of the 23 linear and 7 out of 8 angular measurements between the reconstruction and the target (p<0.05). The use of Procrustes superimposition has highlighted potential problems with soft tissue depth and anatomical landmarks' position. Surface mesh analysis showed that this virtual sculpture technique can be objectively assessed using the distance between the meshes. This study found that the percentage of faces with less than ±2.5mm error ranged from 56% to 90%. This may be improved if Procrustes superimposition could be applied to all the mesh points rather than specific landmarks. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Validation of photo-identification as a mark-recapture method in the spotted eagle ray Aetobatus narinari.

PubMed

González-Ramos, M S; Santos-Moreno, A; Rosas-Alquicira, E F; Fuentes-Mascorro, G

2017-03-01

The spotted eagle ray Aetobatus narinari is characterized by pigmentation patterns that are retained for up to 3·5 years. These pigmentations can be used to identify individuals through photo-identification. Only one study has validated this technique, but no study has estimated the percentage of correct identification of the rays using this technique. In order to carry out demographic research, a reliable photographic identification technique is needed. To achieve this validation for A. narinari, a double-mark system was established over 11 months and photographs of the dorsal surface of 191 rays were taken. Three body parts with distinctive natural patterns were analysed (dorsal surface of the cephalic region, dorsal surface of the pectoral fins and dorsal surface of the pelvic fins) in order to determine the body part that could be used to give the highest percentage of correct identification. The dorsal surface of the pectoral fins of A. narinari provides the most accurate photo-identification to distinguish individuals (88·2%). © 2016 The Fisheries Society of the British Isles.

Network Anomaly Detection Based on Wavelet Analysis

NASA Astrophysics Data System (ADS)

Lu, Wei; Ghorbani, Ali A.

2008-12-01

Signal processing techniques have been applied recently for analyzing and detecting network anomalies due to their potential to find novel or unknown intrusions. In this paper, we propose a new network signal modelling technique for detecting network anomalies, combining the wavelet approximation and system identification theory. In order to characterize network traffic behaviors, we present fifteen features and use them as the input signals in our system. We then evaluate our approach with the 1999 DARPA intrusion detection dataset and conduct a comprehensive analysis of the intrusions in the dataset. Evaluation results show that the approach achieves high-detection rates in terms of both attack instances and attack types. Furthermore, we conduct a full day's evaluation in a real large-scale WiFi ISP network where five attack types are successfully detected from over 30 millions flows.

[THE ROLE OF SYSTEM QUORUM SENSING UNDER CHRONIC UROGENITAL CHLAMYDIA INFECTION].

PubMed

2015-10-01

It is established that system quorum sensing (QS) assure social behavior of bacteria in regulation of genes of virulence and generalization of inflectional inflammatory process under chronic urogenital chlamydia infection. The techniques of gas chromatography and mass-spectrometry were applied to detect molecular markers of generalization of infectious process under urogenital chlamydiasis--activators of QS microbes (lactones, quinolones, furan ethers). The developed diagnostic gas chromatography and mass-spectrometry criteria of indexation of molecular markers under chronic urogenital chlamydia infection have high level of diagnostic sensitivity, specificity and prognostic value of positive and negative result. The application of techniques of gas chromatography and mass-spectrometry permits enhancing effectiveness of diagnostic of chronic inflectional inflammatory diseases of urogenital system of chlamydia etiology with identification of prognostic criteria of generalization of infectious process and subsequent prescription of timely and appropriate therapy

Evaluation of concrete cover by surface wave technique: Identification procedure

NASA Astrophysics Data System (ADS)

Piwakowski, Bogdan; Kaczmarek, Mariusz; Safinowski, Paweł

2012-05-01

Concrete cover degradation is induced by aggressive agents in ambiance, such as moisture, chemicals or temperature variations. Due to degradation usually a thin (a few millimeters thick) surface layer has porosity slightly higher than the deeper sound material. The non destructive evaluation of concrete cover is vital to monitor the integrity of concrete structures and prevent their irreversible damage. In this paper the methodology applied by the classical technique used for ground structure recovery called Multichanel Analysis of Surface Waves is discussed as the NDT tool in civil engineering domain to characterize the concrete cover. In order to obtain the velocity as a function of sample depth the dispersion of surface waves is used as an input for solving inverse problem. The paper describes the inversion procedure and provides the practical example of use of developed system.

[Adverse Effect Predictions Based on Computational Toxicology Techniques and Large-scale Databases].

PubMed

Uesawa, Yoshihiro

2018-01-01

　Understanding the features of chemical structures related to the adverse effects of drugs is useful for identifying potential adverse effects of new drugs. This can be based on the limited information available from post-marketing surveillance, assessment of the potential toxicities of metabolites and illegal drugs with unclear characteristics, screening of lead compounds at the drug discovery stage, and identification of leads for the discovery of new pharmacological mechanisms. This present paper describes techniques used in computational toxicology to investigate the content of large-scale spontaneous report databases of adverse effects, and it is illustrated with examples. Furthermore, volcano plotting, a new visualization method for clarifying the relationships between drugs and adverse effects via comprehensive analyses, will be introduced. These analyses may produce a great amount of data that can be applied to drug repositioning.

Combined empirical mode decomposition and texture features for skin lesion classification using quadratic support vector machine.

PubMed

Wahba, Maram A; Ashour, Amira S; Napoleon, Sameh A; Abd Elnaby, Mustafa M; Guo, Yanhui

2017-12-01

Basal cell carcinoma is one of the most common malignant skin lesions. Automated lesion identification and classification using image processing techniques is highly required to reduce the diagnosis errors. In this study, a novel technique is applied to classify skin lesion images into two classes, namely the malignant Basal cell carcinoma and the benign nevus. A hybrid combination of bi-dimensional empirical mode decomposition and gray-level difference method features is proposed after hair removal. The combined features are further classified using quadratic support vector machine (Q-SVM). The proposed system has achieved outstanding performance of 100% accuracy, sensitivity and specificity compared to other support vector machine procedures as well as with different extracted features. Basal Cell Carcinoma is effectively classified using Q-SVM with the proposed combined features.

Ultrastructural identification of peripheral myelin proteins by a pre-embedding immunogold labeling method.

PubMed

Canron, Marie-Hélène; Bouillot, Sandrine; Favereaux, Alexandre; Petry, Klaus G; Vital, Anne

2003-03-01

Ultrastructural immunolabeling of peripheral nervous system components is an important tool to study the relation between structure and function. Owing to the scarcity of certain antigens and the dense structure of the peripheral nerve, a pre-embedding technique is likely appropriate. After several investigations on procedures for pre-embedding immunolabeling, we propose a method that offers a good compromise between detection of antigenic sites and preservation of morphology at the ultrastructural level, and that is easy to use and suitable for investigations on peripheral nerve biopsies from humans. Pre-fixation by immersion in paraformaldehyde/glutaraldehyde is necessary to stabilize the ultrastructure. Then, ultrasmall gold particles with silver enhancement are advised. Antibodies against myelin protein zero and myelin basic protein were chosen for demonstration. The same technique was applied to localize a 35 kDa myelin protein.

Demographic management in a federated healthcare environment.

PubMed

Román, I; Roa, L M; Reina-Tosina, J; Madinabeitia, G

2006-09-01

The purpose of this paper is to provide a further step toward the decentralization of identification and demographic information about persons by solving issues related to the integration of demographic agents in a federated healthcare environment. The aim is to identify a particular person in every system of a federation and to obtain a unified view of his/her demographic information stored in different locations. This work is based on semantic models and techniques, and pursues the reconciliation of several current standardization works including ITU-T's Open Distributed Processing, CEN's prEN 12967, OpenEHR's dual and reference models, CEN's General Purpose Information Components and CORBAmed's PID service. We propose a new paradigm for the management of person identification and demographic data, based on the development of an open architecture of specialized distributed components together with the incorporation of techniques for the efficient management of domain ontologies, in order to have a federated demographic service. This new service enhances previous correlation solutions sharing ideas with different standards and domains like semantic techniques and database systems. The federation philosophy enforces us to devise solutions to the semantic, functional and instance incompatibilities in our approach. Although this work is based on several models and standards, we have improved them by combining their contributions and developing a federated architecture that does not require the centralization of demographic information. The solution is thus a good approach to face integration problems and the applied methodology can be easily extended to other tasks involved in the healthcare organization.

Signal and array processing techniques for RFID readers

NASA Astrophysics Data System (ADS)

Wang, Jing; Amin, Moeness; Zhang, Yimin

2006-05-01

Radio Frequency Identification (RFID) has recently attracted much attention in both the technical and business communities. It has found wide applications in, for example, toll collection, supply-chain management, access control, localization tracking, real-time monitoring, and object identification. Situations may arise where the movement directions of the tagged RFID items through a portal is of interest and must be determined. Doppler estimation may prove complicated or impractical to perform by RFID readers. Several alternative approaches, including the use of an array of sensors with arbitrary geometry, can be applied. In this paper, we consider direction-of-arrival (DOA) estimation techniques for application to near-field narrowband RFID problems. Particularly, we examine the use of a pair of RFID antennas to track moving RFID tagged items through a portal. With two antennas, the near-field DOA estimation problem can be simplified to a far-field problem, yielding a simple way for identifying the direction of the tag movement, where only one parameter, the angle, needs to be considered. In this case, tracking of the moving direction of the tag simply amounts to computing the spatial cross-correlation between the data samples received at the two antennas. It is pointed out that the radiation patterns of the reader and tag antennas, particularly their phase characteristics, have a significant effect on the performance of DOA estimation. Indoor experiments are conducted in the Radar Imaging and RFID Labs at Villanova University for validating the proposed technique for target movement direction estimations.

Study on the performance of different craniofacial superimposition approaches (II): Best practices proposal.

PubMed

Damas, S; Wilkinson, C; Kahana, T; Veselovskaya, E; Abramov, A; Jankauskas, R; Jayaprakash, P T; Ruiz, E; Navarro, F; Huete, M I; Cunha, E; Cavalli, F; Clement, J; Lestón, P; Molinero, F; Briers, T; Viegas, F; Imaizumi, K; Humpire, D; Ibáñez, O

2015-12-01

Craniofacial superimposition, although existing for one century, is still a controversial technique within the scientific community. Objective and unbiased validation studies over a significant number of cases are required to establish a more solid picture on the reliability. However, there is lack of protocols and standards in the application of the technique leading to contradictory information concerning reliability. Instead of following a uniform methodology, every expert tends to apply his own approach to the problem, based on the available technology and deep knowledge on human craniofacial anatomy, soft tissues, and their relationships. The aim of this study was to assess the reliability of different craniofacial superimposition methodologies and the corresponding technical approaches to this type of identification. With all the data generated, some of the most representative experts in craniofacial identification joined in a discussion intended to identify and agree on the most important issues that have to be considered to properly employ the craniofacial superimposition technique. As a consequence, the consortium has produced the current manuscript, which can be considered the first standard in the field; including good and bad practices, sources of error and uncertainties, technological requirements and desirable features, and finally a common scale for the craniofacial matching evaluation. Such a document is intended to be part of a more complete framework for craniofacial superimposition, to be developed during the FP7-founded project MEPROCS, which will favour and standardize its proper application. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Application of the FICTION technique for the simultaneous detection of immunophenotype and chromosomal abnormalities in routinely fixed, paraffin wax embedded bone marrow trephines

PubMed Central

Korać, P; Jones, M; Dominis, M; Kušec, R; Mason, D Y; Banham, A H; Ventura, R A

2005-01-01

The use of interphase fluorescence in situ hybridisation (FISH) to study cytogenetic abnormalities in routinely fixed paraffin wax embedded tissue has become commonplace over the past decade. However, very few studies have applied FISH to routinely fixed bone marrow trephines (BMTs). This may be because of the acid based decalcification methods that are commonly used during the processing of BMTs, which may adversely affect the suitability of the sample for FISH analysis. For the first time, this report describes the simultaneous application of FISH and immunofluorescent staining (the FICTION technique) to formalin fixed, EDTA decalcified and paraffin wax embedded BMTs. This technique allows the direct correlation of genetic abnormalities to immunophenotype, and therefore will be particularly useful for the identification of genetic abnormalities in specific tumour cells present in BMTs. The application of this to routine clinical practice will assist diagnosis and the detection of minimal residual disease. PMID:16311361

A Comparison of Inductive Sensors in the Characterization of Partial Discharges and Electrical Noise Using the Chromatic Technique

PubMed Central

Ardila-Rey, Jorge Alfredo; Montaña, Johny; Schurch, Roger; Covolan Ulson, José Alfredo; Bani, Nurul Aini

2018-01-01

Partial discharges (PDs) are one of the most important classes of ageing processes that occur within electrical insulation. PD detection is a standardized technique to qualify the state of the insulation in electric assets such as machines and power cables. Generally, the classical phase-resolved partial discharge (PRPD) patterns are used to perform the identification of the type of PD source when they are related to a specific degradation process and when the electrical noise level is low compared to the magnitudes of the PD signals. However, in practical applications such as measurements carried out in the field or in industrial environments, several PD sources and large noise signals are usually present simultaneously. In this study, three different inductive sensors have been used to evaluate and compare their performance in the detection and separation of multiple PD sources by applying the chromatic technique to each of the measured signals. PMID:29596337

Applications of physiological bases of ageing to forensic sciences. Estimation of age-at-death.

PubMed

C Zapico, Sara; Ubelaker, Douglas H

2013-03-01

Age-at-death estimation is one of the main challenges in forensic sciences since it contributes to the identification of individuals. There are many anthropological techniques to estimate the age at death in children and adults. However, in adults this methodology is less accurate and requires population specific references. For that reason, new methodologies have been developed. Biochemical methods are based on the natural process of ageing, which induces different biochemical changes that lead to alterations in cells and tissues. In this review, we describe different attempts to estimate the age in adults based on these changes. Chemical approaches imply modifications in molecules or accumulation of some products. Molecular biology approaches analyze the modifications in DNA and chromosomes. Although the most accurate technique appears to be aspartic acid racemization, it is important to take into account the other techniques because the forensic context and the human remains available will determine the possibility to apply one or another methodology. Copyright © 2013 Elsevier B.V. All rights reserved.

Chirality transfer technique between liquid crystal microdroplets using microfluidic systems

NASA Astrophysics Data System (ADS)

Guo, Jin-kun; Lee, Doyeon; Song, Jang-kun

2018-02-01

Cholesteric liquid crystal (LC) microdroplet is applied in many areas, such as tunable laser, biosensor, information display and security identification, due to its unique optical properties. The topological structure, defects, and photonic crystallinity in the cholesteric liquid crystal (LC) microdroplet can be controlled through the chirality. Here we report an interesting phenomenon that chirality information can be shared among dispersed LC microdroplets in surfactant aqueous solution, which is driven by the transferring of chiral dopant molecules. As a result, we developed an artificial molecule transfer technology which could in situ vary the material composition within the isolated dispersed microdroplets. The molecular transfer is switchable and the transfer speed is controllable by tuning the molecular solubility in continuous phase. Based on this technique, we manipulated, forward and backward, the topological evolution and the photonic crystal band-gap of the dispersed LC droplet. This technique is an easy and powerful experimental tool, and it may be applicable to other fields in optical application, biology, chemistry and material science.

Nanoscale infrared spectroscopy as a non-destructive probe of extraterrestrial samples.

PubMed

Dominguez, Gerardo; Mcleod, A S; Gainsforth, Zack; Kelly, P; Bechtel, Hans A; Keilmann, Fritz; Westphal, Andrew; Thiemens, Mark; Basov, D N

2014-12-09

Advances in the spatial resolution of modern analytical techniques have tremendously augmented the scientific insight gained from the analysis of natural samples. Yet, while techniques for the elemental and structural characterization of samples have achieved sub-nanometre spatial resolution, infrared spectral mapping of geochemical samples at vibrational 'fingerprint' wavelengths has remained restricted to spatial scales >10 μm. Nevertheless, infrared spectroscopy remains an invaluable contactless probe of chemical structure, details of which offer clues to the formation history of minerals. Here we report on the successful implementation of infrared near-field imaging, spectroscopy and analysis techniques capable of sub-micron scale mineral identification within natural samples, including a chondrule from the Murchison meteorite and a cometary dust grain (Iris) from NASA's Stardust mission. Complementary to scanning electron microscopy, energy-dispersive X-ray spectroscopy and transmission electron microscopy probes, this work evidences a similarity between chondritic and cometary materials, and inaugurates a new era of infrared nano-spectroscopy applied to small and invaluable extraterrestrial samples.

Abdominal compression during endoscopy (the Bolster technique) demonstrates hidden Schatzki rings (with videos).

PubMed

Jouhourian, Caroline; Bonis, Peter A; Guelrud, Moises

2016-05-01

Schatzki rings are found in the distal esophagus, are associated with hiatal hernias, and present with intermittent dysphagia to solid foods. They can be identified by radiology (GI series or barium swallow studies) or endoscopy. Rings are not always visualized during endoscopy in patients in whom they are suspected clinically. The Bolster technique involves application of epigastric abdominal pressure, which offers the potential to reveal a Schatzki ring that is otherwise obscured within a reduced hiatal hernia. The aim of this study was to determine whether the Bolster technique improves endoscopic detection of Schatzki rings. We reviewed 30 symptomatic patients with a history of a Schatzki ring in a tertiary care center. The Bolster technique was applied to patients in whom the ring was not visible during standard endoscopy. The main outcome measurement was identification of the Schatzki ring after the Bolster technique. A Schatzki ring was visible during standard endoscopy in 26 of the 30 patients. In the remaining 4, the ring was visible only after the application of the Bolster technique. The Bolster technique is a simple maneuver that can increase detection rates of Schatzki rings during endoscopy. Copyright © 2016 American Society for Gastrointestinal Endoscopy. Published by Elsevier Inc. All rights reserved.

Gearbox damage identification and quantification using stochastic resonance

NASA Astrophysics Data System (ADS)

Mba, Clement U.; Marchesiello, Stefano; Fasana, Alessandro; Garibaldi, Luigi

2018-03-01

Amongst the many new tools used for vibration based mechanical fault diagnosis in rotating machineries, stochastic resonance (SR) has been shown to be able to identify as well as quantify gearbox damage via numerical simulations. To validate the numerical simulation results that were obtained in a previous work by the authors, SR is applied in the present study to data from an experimental gearbox that is representative of an industrial gearbox. Both spur and helical gears are used in the gearbox setup. While the results of the direct application of SR to experimental data do not exactly corroborate the numerical simulation results, applying SR to experimental data in pre-processed form is shown to be quite effective. In addition, it is demonstrated that traditional statistical techniques used for gearbox diagnosis can be used as a reference to check how well SR performs.

Methods and application of system identification in shock and vibration.

NASA Technical Reports Server (NTRS)

Collins, J. D.; Young, J. P.; Kiefling, L.

1972-01-01

A logical picture is presented of current useful system identification techniques in the shock and vibration field. A technology tree diagram is developed for the purpose of organizing and categorizing the widely varying approaches according to the fundamental nature of each. Specific examples of accomplished activity for each identification category are noted and discussed. To provide greater insight into the most current trends in the system identification field, a somewhat detailed description is presented of the essential features of a recently developed technique that is based on making the maximum use of all statistically known information about a system.

Thermal Skin fabrication technology

NASA Technical Reports Server (NTRS)

Milam, T. B.

1972-01-01

Advanced fabrication techniques applicable to Thermal Skin structures were investigated, including: (1) chemical machining; (2) braze bonding; (3) diffusion bonding; and (4) electron beam welding. Materials investigated were nickel and nickel alloys. Sample Thermal Skin panels were manufactured using the advanced fabrication techniques studied and were structurally tested. Results of the program included: (1) development of improved chemical machining processes for nickel and several nickel alloys; (2) identification of design geometry limits; (3) identification of diffusion bonding requirements; (4) development of a unique diffusion bonding tool; (5) identification of electron beam welding limits; and (6) identification of structural properties of Thermal Skin material.

Mapping of HLA- DQ haplotypes in a group of Danish patients with celiac disease.

PubMed

Lund, Flemming; Hermansen, Mette N; Pedersen, Merete F; Hillig, Thore; Toft-Hansen, Henrik; Sölétormos, György

2015-10-01

A cost-effective identification of HLA- DQ risk haplotypes using the single nucleotide polymorphism (SNP) technique has recently been applied in the diagnosis of celiac disease (CD) in four European populations. The objective of the study was to map risk HLA- DQ haplotypes in a group of Danish CD patients using the SNP technique. Cohort A: Among 65 patients with gastrointestinal symptoms we compared the HLA- DQ2 and HLA- DQ8 risk haplotypes obtained by the SNP technique (method 1) with results based on a sequence specific primer amplification technique (method 2) and a technique used in an assay from BioDiagene (method 3). Cohort B: 128 patients with histologically verified CD were tested for CD risk haplotypes (method 1). Patients with negative results were further tested for sub-haplotypes of HLA- DQ2 (methods 2 and 3). Cohort A: The three applied methods provided the same HLA- DQ2 and HLA- DQ8 results among 61 patients. Four patients were negative for the HLA- DQ2 and HLA- DQ8 haplotypes (method 1) but were positive for the HLA- DQ2.5-trans and HLA- DQ2.2 haplotypes (methods 2 and 3). Cohort B: A total of 120 patients were positive for the HLA- DQ2.5-cis and HLA- DQ8 haplotypes (method 1). The remaining seven patients were positive for HLA- DQ2.5-trans or HLA- DQ2.2 haplotypes (methods 2 and 3). One patient was negative with all three HLA methods. The HLA- DQ risk haplotypes were detected in 93.8% of the CD patients using the SNP technique (method 1). The sensitivity increased to 99.2% by combining methods 1 - 3.

Micro-computed tomography in murine models of cerebral cavernous malformations as a paradigm for brain disease.

PubMed

Girard, Romuald; Zeineddine, Hussein A; Orsbon, Courtney; Tan, Huan; Moore, Thomas; Hobson, Nick; Shenkar, Robert; Lightle, Rhonda; Shi, Changbin; Fam, Maged D; Cao, Ying; Shen, Le; Neander, April I; Rorrer, Autumn; Gallione, Carol; Tang, Alan T; Kahn, Mark L; Marchuk, Douglas A; Luo, Zhe-Xi; Awad, Issam A

2016-09-15

Cerebral cavernous malformations (CCMs) are hemorrhagic brain lesions, where murine models allow major mechanistic discoveries, ushering genetic manipulations and preclinical assessment of therapies. Histology for lesion counting and morphometry is essential yet tedious and time consuming. We herein describe the application and validations of X-ray micro-computed tomography (micro-CT), a non-destructive technique allowing three-dimensional CCM lesion count and volumetric measurements, in transgenic murine brains. We hereby describe a new contrast soaking technique not previously applied to murine models of CCM disease. Volumetric segmentation and image processing paradigm allowed for histologic correlations and quantitative validations not previously reported with the micro-CT technique in brain vascular disease. Twenty-two hyper-dense areas on micro-CT images, identified as CCM lesions, were matched by histology. The inter-rater reliability analysis showed strong consistency in the CCM lesion identification and staging (K=0.89, p<0.0001) between the two techniques. Micro-CT revealed a 29% greater CCM lesion detection efficiency, and 80% improved time efficiency. Serial integrated lesional area by histology showed a strong positive correlation with micro-CT estimated volume (r(2)=0.84, p<0.0001). Micro-CT allows high throughput assessment of lesion count and volume in pre-clinical murine models of CCM. This approach complements histology with improved accuracy and efficiency, and can be applied for lesion burden assessment in other brain diseases. Copyright © 2016 Elsevier B.V. All rights reserved.

Identification of unique repeated patterns, location of mutation in DNA finger printing using artificial intelligence technique.

PubMed

Mukunthan, B; Nagaveni, N

2014-01-01

In genetic engineering, conventional techniques and algorithms employed by forensic scientists to assist in identification of individuals on the basis of their respective DNA profiles involves more complex computational steps and mathematical formulae, also the identification of location of mutation in a genomic sequence in laboratories is still an exigent task. This novel approach provides ability to solve the problems that do not have an algorithmic solution and the available solutions are also too complex to be found. The perfect blend made of bioinformatics and neural networks technique results in efficient DNA pattern analysis algorithm with utmost prediction accuracy.

Air pollution source identification

NASA Technical Reports Server (NTRS)

Fordyce, J. S.

1975-01-01

Techniques for air pollution source identification are reviewed, and some results obtained with them are evaluated. Described techniques include remote sensing from satellites and aircraft, on-site monitoring, and the use of injected tracers and pollutants themselves as tracers. The use of a large number of trace elements in ambient airborne particulate matter as a practical means of identifying sources is discussed in detail. Sampling and analysis techniques are described, and it is shown that elemental constituents can be related to specific source types such as those found in the earth's crust and those associated with specific industries. Source identification sytems are noted which utilize charged particle X-ray fluorescence analysis of original field data.

Balancing research and funding using value of information and portfolio tools for nanomaterial risk classification

NASA Astrophysics Data System (ADS)

Bates, Matthew E.; Keisler, Jeffrey M.; Zussblatt, Niels P.; Plourde, Kenton J.; Wender, Ben A.; Linkov, Igor

2016-02-01

Risk research for nanomaterials is currently prioritized by means of expert workshops and other deliberative processes. However, analytical techniques that quantify and compare alternative research investments are increasingly recommended. Here, we apply value of information and portfolio decision analysis—methods commonly applied in financial and operations management—to prioritize risk research for multiwalled carbon nanotubes and nanoparticulate silver and titanium dioxide. We modify the widely accepted CB Nanotool hazard evaluation framework, which combines nano- and bulk-material properties into a hazard score, to operate probabilistically with uncertain inputs. Literature is reviewed to develop uncertain estimates for each input parameter, and a Monte Carlo simulation is applied to assess how different research strategies can improve hazard classification. The relative cost of each research experiment is elicited from experts, which enables identification of efficient research portfolios—combinations of experiments that lead to the greatest improvement in hazard classification at the lowest cost. Nanoparticle shape, diameter, solubility and surface reactivity were most frequently identified within efficient portfolios in our results.

Balancing research and funding using value of information and portfolio tools for nanomaterial risk classification.

PubMed

Bates, Matthew E; Keisler, Jeffrey M; Zussblatt, Niels P; Plourde, Kenton J; Wender, Ben A; Linkov, Igor

2016-02-01

Risk research for nanomaterials is currently prioritized by means of expert workshops and other deliberative processes. However, analytical techniques that quantify and compare alternative research investments are increasingly recommended. Here, we apply value of information and portfolio decision analysis-methods commonly applied in financial and operations management-to prioritize risk research for multiwalled carbon nanotubes and nanoparticulate silver and titanium dioxide. We modify the widely accepted CB Nanotool hazard evaluation framework, which combines nano- and bulk-material properties into a hazard score, to operate probabilistically with uncertain inputs. Literature is reviewed to develop uncertain estimates for each input parameter, and a Monte Carlo simulation is applied to assess how different research strategies can improve hazard classification. The relative cost of each research experiment is elicited from experts, which enables identification of efficient research portfolios-combinations of experiments that lead to the greatest improvement in hazard classification at the lowest cost. Nanoparticle shape, diameter, solubility and surface reactivity were most frequently identified within efficient portfolios in our results.

Prospective performance evaluation of selected common virtual screening tools. Case study: Cyclooxygenase (COX) 1 and 2.

PubMed

Kaserer, Teresa; Temml, Veronika; Kutil, Zsofia; Vanek, Tomas; Landa, Premysl; Schuster, Daniela

2015-01-01

Computational methods can be applied in drug development for the identification of novel lead candidates, but also for the prediction of pharmacokinetic properties and potential adverse effects, thereby aiding to prioritize and identify the most promising compounds. In principle, several techniques are available for this purpose, however, which one is the most suitable for a specific research objective still requires further investigation. Within this study, the performance of several programs, representing common virtual screening methods, was compared in a prospective manner. First, we selected top-ranked virtual screening hits from the three methods pharmacophore modeling, shape-based modeling, and docking. For comparison, these hits were then additionally predicted by external pharmacophore- and 2D similarity-based bioactivity profiling tools. Subsequently, the biological activities of the selected hits were assessed in vitro, which allowed for evaluating and comparing the prospective performance of the applied tools. Although all methods performed well, considerable differences were observed concerning hit rates, true positive and true negative hits, and hitlist composition. Our results suggest that a rational selection of the applied method represents a powerful strategy to maximize the success of a research project, tightly linked to its aims. We employed cyclooxygenase as application example, however, the focus of this study lied on highlighting the differences in the virtual screening tool performances and not in the identification of novel COX-inhibitors. Copyright © 2015 The Authors. Published by Elsevier Masson SAS.. All rights reserved.

Spectroscopic classification of icy satellites of Saturn II: Identification of terrain units on Rhea

NASA Astrophysics Data System (ADS)

Scipioni, F.; Tosi, F.; Stephan, K.; Filacchione, G.; Ciarniello, M.; Capaccioni, F.; Cerroni, P.

2014-05-01

Rhea is the second largest icy satellites of Saturn and it is mainly composed of water ice. Its surface is characterized by a leading hemisphere slightly brighter than the trailing side. The main goal of this work is to identify homogeneous compositional units on Rhea by applying the Spectral Angle Mapper (SAM) classification technique to Rhea’s hyperspectral images acquired by the Visual and Infrared Mapping Spectrometer (VIMS) onboard the Cassini Orbiter in the infrared range (0.88-5.12 μm). The first step of the classification is dedicated to the identification of Rhea’s spectral endmembers by applying the k-means unsupervised clustering technique to four hyperspectral images representative of a limited portion of the surface, imaged at relatively high spatial resolution. We then identified eight spectral endmembers, corresponding to as many terrain units, which mostly distinguish for water ice abundance and ice grain size. In the second step, endmembers are used as reference spectra in SAM classification method to achieve a comprehensive classification of the entire surface. From our analysis of the infrared spectra returned by VIMS, it clearly emerges that Rhea’ surface units shows differences in terms of water ice bands depths, average ice grain size, and concentration of contaminants, particularly CO2 and hydrocarbons. The spectral units that classify optically dark terrains are those showing suppressed water ice bands, a finer ice grain size and a higher concentration of carbon dioxide. Conversely, spectral units labeling brighter regions have deeper water ice absorption bands, higher albedo and a smaller concentration of contaminants. All these variations reflect surface’s morphological and geological structures. Finally, we performed a comparison between Rhea and Dione, to highlight different magnitudes of space weathering effects in the icy satellites as a function of the distance from Saturn.

Seismic risk evaluation aided by IR thermography

NASA Astrophysics Data System (ADS)

Grinzato, E.; Cadelano, G.; Bison, P.; Petracca, A.

2009-05-01

Conservation of buildings in areas at seismic risk must take prevention into account. The safeguard architectonic heritage is an ambitious objective, but a priority for planning programmes at varying levels of decision making. Preservation and restoration activities must be optimized to cover a vast and widespread historical and architectonic heritage present in many countries. Masonry buildings requires an adequate level of knowledge based on the importance of structural geometry, which may include the damage, details of construction and properties of materials. For identification and classification of masonry is necessary to find shape, type and size of the elements, texture, size of mortar joints, assemblage. The recognition can be done through a visual inspection of the surface of walls, which can be examined, where is not visible, removing a layer of plaster. Thermography is an excellent tool for a fast survey and collection of vital information for this purpose, but it is extremely important define a precise procedure in the development of more efficient monitoring tools. Thermography is a non-destructive method that allows recognizing the structural damage below plaster, detecting the presence of discontinuity in masonry, for added storeys, cavity, filled openings, and repairs. Furthermore, the fast identification of subsurface state allows to select areas where other methods either more penetrating or partially destructive have to be applied. The paper reports experimental results achieved in the mainframe of the European project RECES Modiquus. The main aim of the project is to improve methods, techniques and instruments for facing antiseismic options. Both passive and active thermographic techniques have been applied in different weather conditions and time schemes. A dedicated algorithm has been developed to enhance the visibility of wall bonding.

Damage identification in beams using speckle shearography and an optimal spatial sampling

NASA Astrophysics Data System (ADS)

Mininni, M.; Gabriele, S.; Lopes, H.; Araújo dos Santos, J. V.

2016-10-01

Over the years, the derivatives of modal displacement and rotation fields have been used to localize damage in beams. Usually, the derivatives are computed by applying finite differences. The finite differences propagate and amplify the errors that exist in real measurements, and thus, it is necessary to minimize this problem in order to get reliable damage localizations. A way to decrease the propagation and amplification of the errors is to select an optimal spatial sampling. This paper presents a technique where an optimal spatial sampling of modal rotation fields is computed and used to obtain the modal curvatures. Experimental measurements of modal rotation fields of a beam with single and multiple damages are obtained with shearography, which is an optical technique allowing the measurement of full-fields. These measurements are used to test the validity of the optimal sampling technique for the improvement of damage localization in real structures. An investigation on the ability of a model updating technique to quantify the damage is also reported. The model updating technique is defined by the variations of measured natural frequencies and measured modal rotations and aims at calibrating the values of the second moment of area in the damaged areas, which were previously localized.

Illegal hunting cases detected with molecular forensics in Brazil

PubMed Central

2012-01-01

Background Illegal hunting is one of the major threats to vertebrate populations in tropical regions. This unsustainable practice has serious consequences not only for the target populations, but also for the dynamics and structure of tropical ecosystems. Generally, in cases of suspected illegal hunting, the only evidence available is pieces of meat, skin or bone. In these cases, species identification can only be reliably determined using molecular technologies. Here, we reported an investigative study of three cases of suspected wildlife poaching in which molecular biology techniques were employed to identify the hunted species from remains of meat. Findings By applying cytochrome b (cyt-b) and cytochrome oxidase subunit I (COI) molecular markers, the suspected illegal poaching was confirmed by the identification of three wild species, capybara (Hydrochoerus hydrochaeris), Chaco Chachalaca (Ortalis canicollis) and Pampas deer (Ozotoceros bezoarticus). In Brazil, hunting is a criminal offense, and based on this evidence, the defendants were found guilty and punished with fines; they may still be sentenced to prison for a period of 6 to 12 months. Conclusions The genetic analysis used in this investigative study was suitable to diagnose the species killed and solve these criminal investigations. Molecular forensic techniques can therefore provide an important tool that enables local law enforcement agencies to apprehend illegal poachers. PMID:22863070

Secure Method for Biometric-Based Recognition with Integrated Cryptographic Functions

PubMed Central

Chiou, Shin-Yan

2013-01-01

Biometric systems refer to biometric technologies which can be used to achieve authentication. Unlike cryptography-based technologies, the ratio for certification in biometric systems needs not to achieve 100% accuracy. However, biometric data can only be directly compared through proximal access to the scanning device and cannot be combined with cryptographic techniques. Moreover, repeated use, improper storage, or transmission leaks may compromise security. Prior studies have attempted to combine cryptography and biometrics, but these methods require the synchronization of internal systems and are vulnerable to power analysis attacks, fault-based cryptanalysis, and replay attacks. This paper presents a new secure cryptographic authentication method using biometric features. The proposed system combines the advantages of biometric identification and cryptographic techniques. By adding a subsystem to existing biometric recognition systems, we can simultaneously achieve the security of cryptographic technology and the error tolerance of biometric recognition. This method can be used for biometric data encryption, signatures, and other types of cryptographic computation. The method offers a high degree of security with protection against power analysis attacks, fault-based cryptanalysis, and replay attacks. Moreover, it can be used to improve the confidentiality of biological data storage and biodata identification processes. Remote biometric authentication can also be safely applied. PMID:23762851

Identification of Pork Contamination in Meatballs of Indonesia Local Market Using Polymerase Chain Reaction-Restriction Fragment Length Polymorphism (PCR-RFLP) Analysis

PubMed Central

Erwanto, Yuny; Abidin, Mohammad Zainal; Sugiyono, Eko Yasin Prasetyo Muslim; Rohman, Abdul

2014-01-01

This research applied and evaluated a polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) using cytochrome b gene to detect pork contamination in meatballs from local markets in Surabaya and Yogyakarta regions, Indonesia. To confirm the effectiveness and specificity of this fragment, thirty nine DNA samples from different meatball shops were isolated and amplified, and then the PCR amplicon was digested by BseDI restriction enzyme to detect the presence of pork in meatballs. BseDI restriction enzyme was able to cleave porcine cytochrome b gene into two fragments (131 bp and 228 bp). Testing the meatballs from the local market showed that nine of twenty meatball shops in Yogyakarta region were detected to have pork contamination, but there was no pork contamination in meatball shops in Surabaya region. In conclusion, specific PCR amplification of cytochrome b gen and cleaved by BseDI restriction enzymes seems to be a powerful technique for the identification of pork presence in meatball because of its simplicity, specificity and sensitivity. Furthermore, pork contamination intended for commercial products of sausage, nugget, steak and meat burger can be checked. The procedure is also much cheaper than other methods based on PCR, immunodiffusion and other techniques that need expensive equipment. PMID:25178301

Identification of Pork Contamination in Meatballs of Indonesia Local Market Using Polymerase Chain Reaction-Restriction Fragment Length Polymorphism (PCR-RFLP) Analysis.

PubMed

Erwanto, Yuny; Abidin, Mohammad Zainal; Sugiyono, Eko Yasin Prasetyo Muslim; Rohman, Abdul

2014-10-01

This research applied and evaluated a polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) using cytochrome b gene to detect pork contamination in meatballs from local markets in Surabaya and Yogyakarta regions, Indonesia. To confirm the effectiveness and specificity of this fragment, thirty nine DNA samples from different meatball shops were isolated and amplified, and then the PCR amplicon was digested by BseDI restriction enzyme to detect the presence of pork in meatballs. BseDI restriction enzyme was able to cleave porcine cytochrome b gene into two fragments (131 bp and 228 bp). Testing the meatballs from the local market showed that nine of twenty meatball shops in Yogyakarta region were detected to have pork contamination, but there was no pork contamination in meatball shops in Surabaya region. In conclusion, specific PCR amplification of cytochrome b gen and cleaved by BseDI restriction enzymes seems to be a powerful technique for the identification of pork presence in meatball because of its simplicity, specificity and sensitivity. Furthermore, pork contamination intended for commercial products of sausage, nugget, steak and meat burger can be checked. The procedure is also much cheaper than other methods based on PCR, immunodiffusion and other techniques that need expensive equipment.

Discontinuous pH gradient-mediated separation of TiO2-enriched phosphopeptides

PubMed Central

Park, Sung-Soo; Maudsley, Stuart

2010-01-01

Global profiling of phosphoproteomes has proven a great challenge due to the relatively low stoichiometry of protein phosphorylation and poor ionization efficiency in mass spectrometers. Effective, physiologically-relevant, phosphoproteome research relies on the efficient phosphopeptide enrichment from complex samples. Immobilized metal affinity chromatography and titanium dioxide chromatography (TOC) can greatly assist selective phosphopeptide enrichment. However, the complexity of resultant enriched samples is often still high, suggesting that further separation of enriched phosphopeptides is required. We have developed a pH-gradient elution technique for enhanced phosphopeptide identification in conjunction with TOC. Using this process, we have demonstrated its superiority to the traditional ‘one-pot’ strategies for differential protein identification. Our technique generated a highly specific separation of phosphopeptides by an applied pH-gradient between 9.2 and 11.3. The most efficient elution range for high-resolution phosphopeptide separation was between pH 9.2 and 9.4. High-resolution separation of multiply-phosphorylated peptides was primarily achieved using elution ranges > pH 9.4. Investigation of phosphopeptide sequences identified in each pH fraction indicated that phosphopeptides with phosphorylated residues proximal to acidic residues, including glutamic acid, aspartic acid, and other phosphorylated residues, were preferentially eluted at higher pH values. PMID:20946866

Enzymatic Purification of Microplastics in Environmental Samples.

PubMed

Löder, Martin G J; Imhof, Hannes K; Ladehoff, Maike; Löschel, Lena A; Lorenz, Claudia; Mintenig, Svenja; Piehl, Sarah; Primpke, Sebastian; Schrank, Isabella; Laforsch, Christian; Gerdts, Gunnar

2017-12-19

Micro-Fourier transform infrared (micro-FTIR) spectroscopy and Raman spectroscopy enable the reliable identification and quantification of microplastics (MPs) in the lower micron range. Since concentrations of MPs in the environment are usually low, the large sample volumes required for these techniques lead to an excess of coenriched organic or inorganic materials. While inorganic materials can be separated from MPs using density separation, the organic fraction impedes the ability to conduct reliable analyses. Hence, the purification of MPs from organic materials is crucial prior to conducting an identification via spectroscopic techniques. Strong acidic or alkaline treatments bear the danger of degrading sensitive synthetic polymers. We suggest an alternative method, which uses a series of technical grade enzymes for purifying MPs in environmental samples. A basic enzymatic purification protocol (BEPP) proved to be efficient while reducing 98.3 ± 0.1% of the sample matrix in surface water samples. After showing a high recovery rate (84.5 ± 3.3%), the BEPP was successfully applied to environmental samples from the North Sea where numbers of MPs range from 0.05 to 4.42 items m -3 . Experiences with different environmental sample matrices were considered in an improved and universally applicable version of the BEPP, which is suitable for focal plane array detector (FPA)-based micro-FTIR analyses of water, wastewater, sediment, biota, and food samples.

[Contribution of Leishmania identification using polymerase chain reaction--restriction fragment length polymerase for epidemiological studies of cutaneous leishmaniasis in Tunisia].

PubMed

Bousslimi, N; Ben Abda, I; Ben Mously, R; Siala, E; Harrat, Z; Zallagua, N; Bouratbine, A; Aoun, K

2014-02-01

Three forms of cutaneous leishmaniasis (CL) are endemic in Tunisia. The identification of the causative species is useful to complete epidemiological data and to manage the cases. The aim of this study is to assess PCR-RFLP technique in the identification of Leishmania species responsible of CL in Tunisia and to compare the results of this technique to those of isoenzyme analysis. Sixty-one CL lesions were sampled. Dermal samples were tested by culture on NNN medium and analyzed by PCR-RFLP assay targeting the ITS1 region of ribosomal DNA. Species identification was performed by both iso-enzymatic typing for positive cultures and analysis of restriction profiles after enzymatic digestion by HaeIII of the obtained amplicons. Thirty-eight (62%) samples were positive by culture. The iso-enzymatic typing of 32 isolates identified 3 L. infantum, 23 L. major MON-25 and 6 L. tropica MON-8. Sixty samples were positive by PCR. The PCR-RFLP digestion profiles of the 56 PCR products identified 12 L. infantum, 38 L. major and 6 L. tropica. The results of both techniques were concordant in the 32 strains identified by both techniques. Species identification correlated with the geographical distribution of CL forms endemic in Tunisia. Results of PCR-RFLP revealed highly concordant with those of isoenzyme electrophoresis. Thanks to its simplicity, rapidity and ability to be performed directly on biological samples, this technique appears as an interesting alternative for the identification of Leishmania strains responsible of CL in Tunisia. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

Biochemical component identification by plasmonic improved whispering gallery mode optical resonance based sensor

NASA Astrophysics Data System (ADS)

Saetchnikov, Vladimir A.; Tcherniavskaia, Elina A.; Saetchnikov, Anton V.; Schweiger, Gustav; Ostendorf, Andreas

2014-05-01

Experimental data on detection and identification of variety of biochemical agents, such as proteins, microelements, antibiotic of different generation etc. in both single and multi component solutions under varied in wide range concentration analyzed on the light scattering parameters of whispering gallery mode optical resonance based sensor are represented. Multiplexing on parameters and components has been realized using developed fluidic sensor cell with fixed in adhesive layer dielectric microspheres and data processing. Biochemical component identification has been performed by developed network analysis techniques. Developed approach is demonstrated to be applicable both for single agent and for multi component biochemical analysis. Novel technique based on optical resonance on microring structures, plasmon resonance and identification tools has been developed. To improve a sensitivity of microring structures microspheres fixed by adhesive had been treated previously by gold nanoparticle solution. Another technique used thin film gold layers deposited on the substrate below adhesive. Both biomolecule and nanoparticle injections caused considerable changes of optical resonance spectra. Plasmonic gold layers under optimized thickness also improve parameters of optical resonance spectra. Biochemical component identification has been also performed by developed network analysis techniques both for single and for multi component solution. So advantages of plasmon enhancing optical microcavity resonance with multiparameter identification tools is used for development of a new platform for ultra sensitive label-free biomedical sensor.

A genotyping protocol for multiple tissue types from the polyploid tree species Sequoia sempervirens (Cupressaceae)1

PubMed Central

Narayan, Lakshmi; Dodd, Richard S.; O’Hara, Kevin L.

2015-01-01

Premise of the study: Identifying clonal lineages in asexually reproducing plants using microsatellite markers is complicated by the possibility of nonidentical genotypes from the same clonal lineage due to somatic mutations, null alleles, and scoring errors. We developed and tested a clonal identification protocol that is robust to these issues for the asexually reproducing hexaploid tree species coast redwood (Sequoia sempervirens). Methods: Microsatellite data from four previously published and two newly developed primers were scored using a modified protocol, and clones were identified using Bruvo genetic distances. The effectiveness of this clonal identification protocol was assessed using simulations and by genotyping a test set of paired samples of different tissue types from the same trees. Results: Data from simulations showed that our protocol allowed us to accurately identify clonal lineages. Multiple test samples from the same trees were identified correctly, although certain tissue type pairs had larger genetic distances on average. Discussion: The methods described in this paper will allow for the accurate identification of coast redwood clones, facilitating future studies of the reproductive ecology of this species. The techniques used in this paper can be applied to studies of other clonal organisms as well. PMID:25798341

A genotyping protocol for multiple tissue types from the polyploid tree species Sequoia sempervirens (Cupressaceae).

PubMed

Narayan, Lakshmi; Dodd, Richard S; O'Hara, Kevin L

2015-03-01

Identifying clonal lineages in asexually reproducing plants using microsatellite markers is complicated by the possibility of nonidentical genotypes from the same clonal lineage due to somatic mutations, null alleles, and scoring errors. We developed and tested a clonal identification protocol that is robust to these issues for the asexually reproducing hexaploid tree species coast redwood (Sequoia sempervirens). Microsatellite data from four previously published and two newly developed primers were scored using a modified protocol, and clones were identified using Bruvo genetic distances. The effectiveness of this clonal identification protocol was assessed using simulations and by genotyping a test set of paired samples of different tissue types from the same trees. Data from simulations showed that our protocol allowed us to accurately identify clonal lineages. Multiple test samples from the same trees were identified correctly, although certain tissue type pairs had larger genetic distances on average. The methods described in this paper will allow for the accurate identification of coast redwood clones, facilitating future studies of the reproductive ecology of this species. The techniques used in this paper can be applied to studies of other clonal organisms as well.

Aeroservoelastic Uncertainty Model Identification from Flight Data

NASA Technical Reports Server (NTRS)

Brenner, Martin J.

2001-01-01

Uncertainty modeling is a critical element in the estimation of robust stability margins for stability boundary prediction and robust flight control system development. There has been a serious deficiency to date in aeroservoelastic data analysis with attention to uncertainty modeling. Uncertainty can be estimated from flight data using both parametric and nonparametric identification techniques. The model validation problem addressed in this paper is to identify aeroservoelastic models with associated uncertainty structures from a limited amount of controlled excitation inputs over an extensive flight envelope. The challenge to this problem is to update analytical models from flight data estimates while also deriving non-conservative uncertainty descriptions consistent with the flight data. Multisine control surface command inputs and control system feedbacks are used as signals in a wavelet-based modal parameter estimation procedure for model updates. Transfer function estimates are incorporated in a robust minimax estimation scheme to get input-output parameters and error bounds consistent with the data and model structure. Uncertainty estimates derived from the data in this manner provide an appropriate and relevant representation for model development and robust stability analysis. This model-plus-uncertainty identification procedure is applied to aeroservoelastic flight data from the NASA Dryden Flight Research Center F-18 Systems Research Aircraft.

Facile Quantification and Identification Techniques for Reducing Gases over a Wide Concentration Range Using a MOS Sensor in Temperature-Cycled Operation.

PubMed

Schultealbert, Caroline; Baur, Tobias; Schütze, Andreas; Sauerwald, Tilman

2018-03-01

Dedicated methods for quantification and identification of reducing gases based on model-based temperature-cycled operation (TCO) using a single commercial MOS gas sensor are presented. During high temperature phases the sensor surface is highly oxidized, yielding a significant sensitivity increase after switching to lower temperatures (differential surface reduction, DSR). For low concentrations, the slope of the logarithmic conductance during this low-temperature phase is evaluated and can directly be used for quantification. For higher concentrations, the time constant for reaching a stable conductance during the same low-temperature phase is evaluated. Both signals represent the reaction rate of the reducing gas on the strongly oxidized surface at this low temperature and provide a linear calibration curve, which is exceptional for MOS sensors. By determining these reaction rates on different low-temperature plateaus and applying pattern recognition, the resulting footprint can be used for identification of different gases. All methods are tested over a wide concentration range from 10 ppb to 100 ppm (4 orders of magnitude) for four different reducing gases (CO, H₂, ammonia and benzene) using randomized gas exposures.

Facile Quantification and Identification Techniques for Reducing Gases over a Wide Concentration Range Using a MOS Sensor in Temperature-Cycled Operation

PubMed Central

Schultealbert, Caroline; Baur, Tobias; Schütze, Andreas; Sauerwald, Tilman

2018-01-01

Dedicated methods for quantification and identification of reducing gases based on model-based temperature-cycled operation (TCO) using a single commercial MOS gas sensor are presented. During high temperature phases the sensor surface is highly oxidized, yielding a significant sensitivity increase after switching to lower temperatures (differential surface reduction, DSR). For low concentrations, the slope of the logarithmic conductance during this low-temperature phase is evaluated and can directly be used for quantification. For higher concentrations, the time constant for reaching a stable conductance during the same low-temperature phase is evaluated. Both signals represent the reaction rate of the reducing gas on the strongly oxidized surface at this low temperature and provide a linear calibration curve, which is exceptional for MOS sensors. By determining these reaction rates on different low-temperature plateaus and applying pattern recognition, the resulting footprint can be used for identification of different gases. All methods are tested over a wide concentration range from 10 ppb to 100 ppm (4 orders of magnitude) for four different reducing gases (CO, H2, ammonia and benzene) using randomized gas exposures. PMID:29494545

Biometric sample extraction using Mahalanobis distance in Cardioid based graph using electrocardiogram signals.

PubMed

Sidek, Khairul; Khali, Ibrahim

2012-01-01

In this paper, a person identification mechanism implemented with Cardioid based graph using electrocardiogram (ECG) is presented. Cardioid based graph has given a reasonably good classification accuracy in terms of differentiating between individuals. However, the current feature extraction method using Euclidean distance could be further improved by using Mahalanobis distance measurement producing extracted coefficients which takes into account the correlations of the data set. Identification is then done by applying these extracted features to Radial Basis Function Network. A total of 30 ECG data from MITBIH Normal Sinus Rhythm database (NSRDB) and MITBIH Arrhythmia database (MITDB) were used for development and evaluation purposes. Our experimentation results suggest that the proposed feature extraction method has significantly increased the classification performance of subjects in both databases with accuracy from 97.50% to 99.80% in NSRDB and 96.50% to 99.40% in MITDB. High sensitivity, specificity and positive predictive value of 99.17%, 99.91% and 99.23% for NSRDB and 99.30%, 99.90% and 99.40% for MITDB also validates the proposed method. This result also indicates that the right feature extraction technique plays a vital role in determining the persistency of the classification accuracy for Cardioid based person identification mechanism.

Ultra-high performance liquid chromatography coupled to mass spectrometry applied to the identification of valuable phenolic compounds from Eucalyptus wood.

PubMed

Santos, Sónia A O; Vilela, Carla; Freire, Carmen S R; Neto, Carlos Pascoal; Silvestre, Armando J D

2013-11-01

Ultra-high performance liquid chromatography (UHPLC) was applied for the first time in the analysis of wood extracts. The potential of this technique coupled to ion trap mass spectrometry in the rapid and effective detection and identification of bioactive components in complex vegetal samples was demonstrated. Several dozens of compounds were detected in less than 30min of analysis time, corresponding to more than 3-fold reduction in time, when compared to conventional HPLC analysis of similar extracts. The phenolic chemical composition of Eucalyptus grandis, Eucalyptus urograndis (E. grandis×E. urophylla) and Eucalyptus maidenii wood extracts was assessed for the first time, with the identification of 51 phenolic compounds in the three wood extracts. Twenty of these compounds are reported for the first time as Eucalyptus genus components. Ellagic acid and ellagic acid-pentoside are the major components in all extracts, followed by gallic and quinic acids in E. grandis and E. urograndis and ellagic acid-pentoside isomer, isorhamnetin-hexoside and gallic acid in E. maidenii. The antioxidant scavenging activity of the extracts was evaluated, with E. grandis wood extract showing the lowest IC50 value. Moreover, the antioxidant activity of these extracts was higher than that of the commercial antioxidant BHT and of those of the corresponding bark extracts. These results, together with the phenolic content values, open good perspectives for the exploitation of these renewable resources as a source of valuable phenolic compounds. Copyright © 2013 Elsevier B.V. All rights reserved.

Validation of automatic landmark identification for atlas-based segmentation for radiation treatment planning of the head-and-neck region

NASA Astrophysics Data System (ADS)

Leavens, Claudia; Vik, Torbjørn; Schulz, Heinrich; Allaire, Stéphane; Kim, John; Dawson, Laura; O'Sullivan, Brian; Breen, Stephen; Jaffray, David; Pekar, Vladimir

2008-03-01

Manual contouring of target volumes and organs at risk in radiation therapy is extremely time-consuming, in particular for treating the head-and-neck area, where a single patient treatment plan can take several hours to contour. As radiation treatment delivery moves towards adaptive treatment, the need for more efficient segmentation techniques will increase. We are developing a method for automatic model-based segmentation of the head and neck. This process can be broken down into three main steps: i) automatic landmark identification in the image dataset of interest, ii) automatic landmark-based initialization of deformable surface models to the patient image dataset, and iii) adaptation of the deformable models to the patient-specific anatomical boundaries of interest. In this paper, we focus on the validation of the first step of this method, quantifying the results of our automatic landmark identification method. We use an image atlas formed by applying thin-plate spline (TPS) interpolation to ten atlas datasets, using 27 manually identified landmarks in each atlas/training dataset. The principal variation modes returned by principal component analysis (PCA) of the landmark positions were used by an automatic registration algorithm, which sought the corresponding landmarks in the clinical dataset of interest using a controlled random search algorithm. Applying a run time of 60 seconds to the random search, a root mean square (rms) distance to the ground-truth landmark position of 9.5 +/- 0.6 mm was calculated for the identified landmarks. Automatic segmentation of the brain, mandible and brain stem, using the detected landmarks, is demonstrated.