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Sample records for pattern identification technique

  1. Automatic identification of oculomotor behavior using pattern recognition techniques.

    PubMed

    Korda, Alexandra I; Asvestas, Pantelis A; Matsopoulos, George K; Ventouras, Errikos M; Smyrnis, Nikolaos P

    2015-05-01

    In this paper, a methodological scheme for identifying distinct patterns of oculomotor behavior such as saccades, microsaccades, blinks and fixations from time series of eye's angular displacement is presented. The first step of the proposed methodology involves signal detrending for artifacts removal and estimation of eye's angular velocity. Then, feature vectors from fourteen first-order statistical features are formed from each angular displacement and velocity signal using sliding, fixed-length time windows. The obtained feature vectors are used for training and testing three artificial neural network classifiers, connected in cascade. The three classifiers discriminate between blinks and non-blinks, fixations and non-fixations and saccades and microsaccades, respectively. The proposed methodology was tested on a dataset from 1392 subjects, each performing three oculomotor fixation conditions. The average overall accuracy of the three classifiers, with respect to the manual identification of eye movements by experts, was 95.9%. The proposed methodological scheme provided better results than the well-known Velocity Threshold algorithm, which was used for comparison. The findings of the present study indicate that the utilization of pattern recognition techniques in the task of identifying the various eye movements may provide accurate and robust results. PMID:25836568

  2. 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. PMID:24589835

  3. Near-infrared spectroscopy and pattern recognition techniques applied to the identification of Jinhua ham

    NASA Astrophysics Data System (ADS)

    Li, Honglian; Zhao, Zhilei; Pang, Yanping; Wu, Guancheng; Wang, Yanfeng; Li, Xiaoting

    2009-11-01

    Near-infrared (NIR) diffuse reflectance spectroscopy and pattern recognition techniques are applied to develop a fast identification method of Jinhua ham. The samples are collected from different manufactures and they are nineteen Jinhua ham samples and four Xuanwei ham samples. NIR spectra are pretreated with second derivative calculation and vector normalization. The pattern recognition techniques which are cluster analysis, conformity test and principal component analysis (PCA) are separately used to qualify Jinhua ham. The three methods can all distinguish Jinhua ham successfully. The result indicated that a 100 % recognition ration is achieved by the methods and the PCA method is the best one. Overall, NIR reflectance spectroscopy using pattern recognition is shown to have significant potential as a rapid and accurate method for identification of ham.

  4. 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.

  5. Application of pattern recognition techniques to the identification of aerospace acoustic sources

    NASA Technical Reports Server (NTRS)

    Fuller, Chris R.; Obrien, Walter F.; Cabell, Randolph H.

    1988-01-01

    A pattern recognition system was developed that successfully recognizes simulated spectra of five different types of transportation noise sources. The system generates hyperplanes during a training stage to separate the classes and correctly classify unknown patterns in classification mode. A feature selector in the system reduces a large number of features to a smaller optimal set, maximizing performance and minimizing computation.

  6. Pattern recognition technique

    NASA Technical Reports Server (NTRS)

    Hong, J. P.

    1971-01-01

    Technique operates regardless of pattern rotation, translation or magnification and successfully detects out-of-register patterns. It improves accuracy and reduces cost of various optical character recognition devices and page readers and provides data input to computer.

  7. Identification of combustible material with piezoelectric crystal sensor array using pattern-recognition techniques.

    PubMed

    He, X W; Xing, W L; Fang, Y H

    1997-11-01

    A promising way of increasing the selectivity and sensitivity of gas sensors is to treat the signals from a number of different gas sensors with pattern recognition (PR) method. A gas sensor array with seven piezoelectric crystals each coated with a different partially selective coating material was constructed to identify four kinds of combustible materials which generate smoke containing different components. The signals from the sensors were analyzed with both conventional multivariate analysis, stepwise discriminant analysis (SDA), and artificial neural networks (ANN) models. The results show that the predictions were even better with ANN models. In our experiment, we have reported a new method for training data selection, 'training set stepwise expending method' to solve the problem that the network can not converge at the beginning of the training. We also discussed how the parameters of neural networks, learning rate eta, momentum term alpha and few bad training data affect the performance of neural networks. PMID:18966950

  8. Techniques for Specifying Bug Patterns

    SciTech Connect

    Quinlan, D J; Vuduc, R W; Misherghi, G

    2007-04-30

    We present our on-going work to develop techniques for specifying source code signatures of bug patterns. Specifically, we discuss two approaches. The first approach directly analyzes a program in the intermediate representation (IR) of the ROSE compiler infrastructure using ROSE's API. The second analyzes the program using the bddbddb system of Lam, Whaley, et al.. In this approach, we store the IR produced by ROSE as a relational database, express patterns as declarative inference rules on relations in the language Datalog, and bddbddb implements the Datalog programs using binary decision diagram (BDD) techniques. Both approaches readily apply to large-scale applications, since ROSE provides full type analysis, control flow, and other available analysis information. In this paper, we primarily consider bug patterns expressed with respect to the structure of the source code or the control flow, or both. More complex techniques to specify patterns that are functions of data flow properties may be addressed by either of the above approaches, but are not directly treated here. Our Datalog-based work includes explicit support for expressing patterns on the use of the Message Passing Interface (MPI) in parallel distributed memory programs. We show examples of this on-going work as well.

  9. Discrimination and identification of acoustic transient patterns

    NASA Astrophysics Data System (ADS)

    Ballas, J. A.; Howard, J. H., Jr.

    1981-08-01

    The relation between the discrimination and the identification of acoustic patterns can be addressed psychophysically or cognitively. The psychophysical approach predicts a monotonic relationship between performance on the two tasks. Cognitively, the relationship may depend upon the type of structure encoded from the patterns. Structure based upon similarities in runs could enhance discrimination but degrade identification. Hierarchical structural encoding might enhance both tasks. The relationship was investigated in three dual task experiments. In one experiment, trial and error learning was used whereas in the other two, observation of positive examples was used. All three experiments indicated that discrimination was superior to identification, and that the concurrent identification task improved discrimination performance above what has been obtained in single task discrimination studies. The effects of structure in the two tasks were equivocal but implied that the type of structured encoding is important and may be influenced by the procedure used to acquire the patterns.

  10. Identification techniques for SARSAT signals

    NASA Astrophysics Data System (ADS)

    El-Naga, S.; Carter, C. R.

    1987-03-01

    A process for the identification of emergency locator transmitter (ELT) signals related to search and rescue satellite-aided tracking (SARSAT) is presented. The ELT identification process is particularly important in order to increase the probability of detection and eliminate sources of interference from the data set. A set of ELT signal parameters is introduced and methods for estimating these parameters are developed. A theoretical analysis and performance evaluation of these methods is provided.

  11. 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. PMID:14535661

  12. Comparison of two dissimilar modal identification techniques

    NASA Technical Reports Server (NTRS)

    Pappa, Richard S.; Schenk, Axel; Niedbal, Norbert; Klusowski, Erhard

    1992-01-01

    Recent laboratory results using a refined phase resonance method and the eigensystem realization algorithm on the same test structure are reported. These methods are dissimilar modal identification techniques suitable for future large spacecraft. The theory, application approach, and results obtained for each technique are summarized and compared. Although both methods worked well in this investigation, significant differences occurred in some identified mode shapes. Comparison of independently derived modal parameters provides the means for disclosing such discrepancies in flight projects.

  13. Interpretation techniques. [image enhancement and pattern recognition

    NASA Technical Reports Server (NTRS)

    Dragg, J. L.

    1974-01-01

    The image enhancement and geometric correction and registration techniques developed and/or demonstrated on ERTS data are relatively mature and greatly enhance the utility of the data for a large variety of users. Pattern recognition was improved by the use of signature extension, feature extension, and other classification techniques. Many of these techniques need to be developed and generalized to become operationally useful. Advancements in the mass precision processing of ERTS were demonstrated, providing the hope for future earth resources data to be provided in a more readily usable state. Also in evidence is an increasing and healthy interaction between the techniques developers and the user/applications investigators.

  14. Speech recognition based on pattern recognition techniques

    NASA Astrophysics Data System (ADS)

    Rabiner, Lawrence R.

    1990-05-01

    Algorithms for speech recognition can be characterized broadly as pattern recognition approaches and acoustic phonetic approaches. To date, the greatest degree of success in speech recognition has been obtained using pattern recognition paradigms. The use of pattern recognition techniques were applied to the problems of isolated word (or discrete utterance) recognition, connected word recognition, and continuous speech recognition. It is shown that understanding (and consequently the resulting recognizer performance) is best to the simplest recognition tasks and is considerably less well developed for large scale recognition systems.

  15. Decision Tree Technique for Particle Identification

    SciTech Connect

    Quiller, Ryan

    2003-09-05

    Particle identification based on measurements such as the Cerenkov angle, momentum, and the rate of energy loss per unit distance (-dE/dx) is fundamental to the BaBar detector for particle physics experiments. It is particularly important to separate the charged forms of kaons and pions. Currently, the Neural Net, an algorithm based on mapping input variables to an output variable using hidden variables as intermediaries, is one of the primary tools used for identification. In this study, a decision tree classification technique implemented in the computer program, CART, was investigated and compared to the Neural Net over the range of momenta, 0.25 GeV/c to 5.0 GeV/c. For a given subinterval of momentum, three decision trees were made using different sets of input variables. The sensitivity and specificity were calculated for varying kaon acceptance thresholds. This data was used to plot Receiver Operating Characteristic curves (ROC curves) to compare the performance of the classification methods. Also, input variables used in constructing the decision trees were analyzed. It was found that the Neural Net was a significant contributor to decision trees using dE/dx and the Cerenkov angle as inputs. Furthermore, the Neural Net had poorer performance than the decision tree technique, but tended to improve decision tree performance when used as an input variable. These results suggest that the decision tree technique using Neural Net input may possibly increase accuracy of particle identification in BaBar.

  16. Patterning techniques for next generation IC's

    NASA Astrophysics Data System (ADS)

    Balasinski, A.

    2007-12-01

    Reduction of linear critical dimensions (CDs) beyond 45 nm would require significant increase of the complexity of pattern definition process. In this work, we discuss the key successor methodology to the current optical lithography, the Double Patterning Technique (DPT). We compare the complexity of CAD solutions, fab equipment, and wafer processing with its competitors, such as the nanoimprint (NIL) and the extreme UV (EUV) techniques. We also look ahead to the market availability for the product families enabled using the novel patterning solutions. DPT is often recognized as the most viable next generation lithography as it utilizes the existing equipment and processes and is considered a stop-gap solution before the advanced NIL or EUV equipment is developed. Using design for manufacturability (DfM) rules, DPT can drive the k1 factor down to 0.13. However, it faces a variety of challenges, from new mask overlay strategies, to layout pattern split, novel OPC, increased CD tolerances, new etch techniques, as well as long processing time, all of which compromise its return on investment (RoI). In contrast, it can be claimed e.g., that the RoI is the highest for the NIL but this technology bears significant risk. For all novel patterning techniques, the key questions remain: when and how should they be introduced, what is their long-term potential, when should they be replaced, and by what successor technology. We summarize the unpublished results of several panel discussions on DPT at the recent SPIE/BACUS conferences.

  17. DISTANT GALAXY IDENTIFICATION TECHNIQUE IN HUBBLE FIELD

    NASA Technical Reports Server (NTRS)

    2002-01-01

    Series of four panels that illustrate the distant-galaxy identification technique. Four panels that show (top to bottom, or right to left when rotated correctly) F814W filter, F606W filter, F450W filter, and F300W filter images, or near-infrared through near-ultraviolet images. The identified galaxy is prominent in the near-infrared image but totally absent in any of the other images. It is this spectroscopic signature that identifies this galaxy as a very distant object. Credit: Ken Lanzetta and Amos Yahil (State University of New York at Stony Brook), and NASA

  18. Rugoscopy: Human identification by computer-assisted photographic superimposition technique

    PubMed Central

    Mohammed, Rezwana Begum; Patil, Rajendra G.; Pammi, V. R.; Sandya, M. Pavana; Kalyan, Siva V.; Anitha, A.

    2013-01-01

    Background: Human identification has been studied since fourteenth century and it has gradually advanced for forensic purposes. Traditional methods such as dental, fingerprint, and DNA comparisons are probably the most common techniques used in this context, allowing fast and secure identification processes. But, in circumstances where identification of an individual by fingerprint or dental record comparison is difficult, palatal rugae may be considered as an alternative source of material. Aim: The present study was done to evaluate the individualistic nature and use of palatal rugae patterns for personal identification and also to test the efficiency of computerized software for forensic identification by photographic superimposition of palatal photographs obtained from casts. Materials and Methods: Two sets of Alginate impressions were made from the upper arches of 100 individuals (50 males and 50 females) with one month interval in between and the casts were poured. All the teeth except the incisors were removed to ensure that only the palate could be used in identification process. In one set of the casts, the palatal rugae were highlighted with a graphite pencil. All the 200 casts were randomly numbered, and then, they were photographed with a 10.1 Mega Pixel Kodak digital camera using standardized method. Using computerized software, the digital photographs of the models without highlighting the palatal rugae were overlapped over the images (transparent) of the palatal rugae with highlighted palatal rugae, in order to identify the pairs by superimposition technique. Incisors were remained and used as landmarks to determine the magnification required to bring the two set of photographs to the same size, in order to make perfect superimposition of images. Results: The result of the overlapping of the digital photographs of highlighted palatal rugae over normal set of models without highlighted palatal rugae resulted in 100% positive identification. Conclusion

  19. Automatic seagrass pattern identification on sonar images

    NASA Astrophysics Data System (ADS)

    Rahnemoonfar, Maryam; Rahman, Abdullah

    2016-05-01

    Natural and human-induced disturbances are resulting in degradation and loss of seagrass. Freshwater flooding, severe meteorological events and invasive species are among the major natural disturbances. Human-induced disturbances are mainly due to boat propeller scars in the shallow seagrass meadows and anchor scars in the deeper areas. Therefore, there is a vital need to map seagrass ecosystems in order to determine worldwide abundance and distribution. Currently there is no established method for mapping the pothole or scars in seagrass. One of the most precise sensors to map the seagrass disturbance is side scan sonar. Here we propose an automatic method which detects seagrass potholes in sonar images. Side scan sonar images are notorious for having speckle noise and uneven illumination across the image. Moreover, disturbance presents complex patterns where most segmentation techniques will fail. In this paper, by applying mathematical morphology technique and calculating the local standard deviation of the image, the images were enhanced and the pothole patterns were identified. The proposed method was applied on sonar images taken from Laguna Madre in Texas. Experimental results show the effectiveness of the proposed method.

  20. Patterning enhancement techniques by reactive ion etch

    NASA Astrophysics Data System (ADS)

    Honda, Masanobu; Yatsuda, Koichi

    2012-03-01

    The root causes of issues in state-of-the-arts resist mask are low plasma tolerance in etch and resolution limit in lithography. This paper introduces patterning enhancement techniques (PETs) by reactive ion etch (RIE) that solve the above root causes. Plasma tolerance of resist is determined by the chemical structure of resin. We investigated a hybrid direct current (DC) / radio frequency (RF) RIE to enhance the plasma tolerance with several gas chemistries. The DC/RF hybrid RIE is a capacitive coupled plasma etcher with a superimposed DC voltage, which generates a ballistic electron beam. We clarified the mechanism of resist modification, which resulted in higher plasma tolerance[1]. By applying an appropriate gas to DC superimposed (DCS) plasma, etch resistance and line width roughness (LWR) of resist were improved. On the other hand, RIE can patch resist mask. RIE does not only etch but also deposits polymer onto the sidewall with sedimentary type gases. In order to put the deposition technique by RIE in practical use, it is very important to select an appropriate gas chemistry, which can shrink CD and etch BARC. By applying this new technique, we successfully fabricated a 35-nm hole pattern with a minimum CD variation.

  1. Automated Coronal Loop Identification Using Digital Image Processing Techniques

    NASA Technical Reports Server (NTRS)

    Lee, Jong K.; Gary, G. Allen; Newman, Timothy S.

    2003-01-01

    The results of a master thesis project on a study of computer algorithms for automatic identification of optical-thin, 3-dimensional solar coronal loop centers from extreme ultraviolet and X-ray 2-dimensional images will be presented. These center splines are proxies of associated magnetic field lines. The project is pattern recognition problems in which there are no unique shapes or edges and in which photon and detector noise heavily influence the images. The study explores extraction techniques using: (1) linear feature recognition of local patterns (related to the inertia-tensor concept), (2) parametric space via the Hough transform, and (3) topological adaptive contours (snakes) that constrains curvature and continuity as possible candidates for digital loop detection schemes. We have developed synthesized images for the coronal loops to test the various loop identification algorithms. Since the topology of these solar features is dominated by the magnetic field structure, a first-order magnetic field approximation using multiple dipoles provides a priori information in the identification process. Results from both synthesized and solar images will be presented.

  2. Event Networks and the Identification of Crime Pattern Motifs.

    PubMed

    Davies, Toby; Marchione, Elio

    2015-01-01

    In this paper we demonstrate the use of network analysis to characterise patterns of clustering in spatio-temporal events. Such clustering is of both theoretical and practical importance in the study of crime, and forms the basis for a number of preventative strategies. However, existing analytical methods show only that clustering is present in data, while offering little insight into the nature of the patterns present. Here, we show how the classification of pairs of events as close in space and time can be used to define a network, thereby generalising previous approaches. The application of graph-theoretic techniques to these networks can then offer significantly deeper insight into the structure of the data than previously possible. In particular, we focus on the identification of network motifs, which have clear interpretation in terms of spatio-temporal behaviour. Statistical analysis is complicated by the nature of the underlying data, and we provide a method by which appropriate randomised graphs can be generated. Two datasets are used as case studies: maritime piracy at the global scale, and residential burglary in an urban area. In both cases, the same significant 3-vertex motif is found; this result suggests that incidents tend to occur not just in pairs, but in fact in larger groups within a restricted spatio-temporal domain. In the 4-vertex case, different motifs are found to be significant in each case, suggesting that this technique is capable of discriminating between clustering patterns at a finer granularity than previously possible. PMID:26605544

  3. Event Networks and the Identification of Crime Pattern Motifs

    PubMed Central

    2015-01-01

    In this paper we demonstrate the use of network analysis to characterise patterns of clustering in spatio-temporal events. Such clustering is of both theoretical and practical importance in the study of crime, and forms the basis for a number of preventative strategies. However, existing analytical methods show only that clustering is present in data, while offering little insight into the nature of the patterns present. Here, we show how the classification of pairs of events as close in space and time can be used to define a network, thereby generalising previous approaches. The application of graph-theoretic techniques to these networks can then offer significantly deeper insight into the structure of the data than previously possible. In particular, we focus on the identification of network motifs, which have clear interpretation in terms of spatio-temporal behaviour. Statistical analysis is complicated by the nature of the underlying data, and we provide a method by which appropriate randomised graphs can be generated. Two datasets are used as case studies: maritime piracy at the global scale, and residential burglary in an urban area. In both cases, the same significant 3-vertex motif is found; this result suggests that incidents tend to occur not just in pairs, but in fact in larger groups within a restricted spatio-temporal domain. In the 4-vertex case, different motifs are found to be significant in each case, suggesting that this technique is capable of discriminating between clustering patterns at a finer granularity than previously possible. PMID:26605544

  4. Normalized GNSS interference pattern technique for altimetry.

    PubMed

    Ribot, Miguel Angel; Kucwaj, Jean-Christophe; Botteron, Cyril; Reboul, Serge; Stienne, Georges; Leclère, Jérôme; Choquel, Jean-Bernard; Farine, Pierre-André; Benjelloun, Mohammed

    2014-01-01

    It is well known that reflected signals from Global Navigation Satellite Systems (GNSS) can be used for altimetry applications, such as monitoring of water levels and determining snow height. Due to the interference of these reflected signals and the motion of satellites in space, the signal-to-noise ratio (SNR) measured at the receiver slowly oscillates. The oscillation rate is proportional to the change in the propagation path difference between the direct and reflected signals, which depends on the satellite elevation angle. Assuming a known receiver position, it is possible to compute the distance between the antenna and the surface of reflection from the measured oscillation rate. This technique is usually known as the interference pattern technique (IPT). In this paper, we propose to normalize the measurements in order to derive an alternative model of the SNR variations. From this model, we define a maximum likelihood estimate of the antenna height that reduces the estimation time to a fraction of one period of the SNR variation. We also derive the Cramér-Rao lower bound for the IPT and use it to assess the sensitivity of different parameters to the estimation of the antenna height. Finally, we propose an experimental framework, and we use it to assess our approach with real GPS L1 C/A signals. PMID:24922453

  5. Normalized GNSS Interference Pattern Technique for Altimetry

    PubMed Central

    Ribot, Miguel Angel; Kucwaj, Jean-Christophe; Botteron, Cyril; Reboul, Serge; Stienne, Georges; Leclère, Jérôme; Choquel, Jean-Bernard; Farine, Pierre-André; Benjelloun, Mohammed

    2014-01-01

    It is well known that reflected signals from Global Navigation Satellite Systems (GNSS) can be used for altimetry applications, such as monitoring of water levels and determining snow height. Due to the interference of these reflected signals and the motion of satellites in space, the signal-to-noise ratio (SNR) measured at the receiver slowly oscillates. The oscillation rate is proportional to the change in the propagation path difference between the direct and reflected signals, which depends on the satellite elevation angle. Assuming a known receiver position, it is possible to compute the distance between the antenna and the surface of reflection from the measured oscillation rate. This technique is usually known as the interference pattern technique (IPT). In this paper, we propose to normalize the measurements in order to derive an alternative model of the SNR variations. From this model, we define a maximum likelihood estimate of the antenna height that reduces the estimation time to a fraction of one period of the SNR variation. We also derive the Cramér–Rao lower bound for the IPT and use it to assess the sensitivity of different parameters to the estimation of the antenna height. Finally, we propose an experimental framework, and we use it to assess our approach with real GPS L1 C/A signals. PMID:24922453

  6. Susceptibility Patterns and Molecular Identification of Trichosporon Species

    PubMed Central

    Rodriguez-Tudela, Juan L.; Diaz-Guerra, Teresa M.; Mellado, Emilia; Cano, Virginia; Tapia, Cecilia; Perkins, Alexander; Gomez-Lopez, Alicia; Rodero, Laura; Cuenca-Estrella, Manuel

    2005-01-01

    The physiological patterns, the sequence polymorphisms of the internal transcriber spacer (ITS), and intergenic spacer regions (IGS) of the rRNA genes and the antifungal susceptibility profile were evaluated for their ability to identify Trichosporon spp. and their specificity for the identification of 49 clinical isolates of Trichosporon spp. Morphological and biochemical methodologies were unable to differentiate among the Trichosporon species. ITS sequencing was also unable to differentiate several species. However, IGS1 sequencing unambiguously identified all Trichosporon isolates. Following the results of DNA-based identification, Trichosporon asahii was the species most frequently isolated from deep sites (15 of 25 strains; 60%). In the main, other Trichosporon species were recovered from cutaneous samples. The majority of T. asahii, T. faecale, and T. coremiiforme clinical isolates exhibited resistance in vitro to amphotericin B, with geometric mean (GM) MICs >4 μg/ml. The other species of Trichosporon did not show high MICs of amphotericin B, and GM MICs were <1 μg/ml. Azole agents were active in vitro against the majority of clinical strains. The most potent compound in vitro was voriconazole, with a GM MIC ≤0.14 μg/ml. The sequencing of IGS correctly identified Trichosporon isolates; however, this technique is not available in many clinical laboratories, and strains should be dispatched to reference centers where these complex methods are available. Therefore, it seems to be more practical to perform antifungal susceptibility testing of all isolates belonging to Trichosporon spp., since correct identification could take several weeks, delaying the indication of an antifungal agent which exhibits activity against the infectious strain. PMID:16189076

  7. THE IDENTIFICATION AND TESTING OF INTERACTION PATTERNS

    EPA Science Inventory

    This paper presents a method for identifying and assessing the significance of interaction patterns among various chemicals and chemical classes of importance to regulatory toxicologists. To this end, efforts were made to assemble and evaluate experimental data on toxicologically...

  8. The development of two-dimensional object identification techniques

    NASA Technical Reports Server (NTRS)

    Lebby, Gary; Sherrod, Earnest E.

    1989-01-01

    This report marks the end of the first year of an anticipated three year effort to study methods for numerically identifying objects according to shape in two dimensions. The method is based upon comparing the unit gradient of an observed object and the unit gradient of a standard object over a specified range of points. The manner in which the gradients are compared forms the basis of a shape recognition scheme, which is then applied to simple closed plane figures. The gradient based method is calibrated by using various distorted objects in comparison with a set of standard reference objects. The use of pattern recognition techniques for computer identification of two-dimensional figures will be investigated during the second and third years of this project.

  9. Identification of biomolecules by terahertz spectroscopy and fuzzy pattern recognition

    NASA Astrophysics Data System (ADS)

    Chen, Tao; Li, Zhi; Mo, Wei

    2013-04-01

    An approach for automatic identification of terahertz (THz) spectra of biomolecules is proposed based on principal component analysis (PCA) and fuzzy pattern recognition in this paper, and THz transmittance spectra of some typical amino acid and saccharide biomolecular samples are investigated to prove its feasibility. Firstly, PCA is applied to reduce the dimensionality of the original spectrum data and extract features of the data. Secondly, instead of the original spectrum variables, the selected principal component scores matrix is fed into the model of fuzzy pattern recognition, where a principle of fuzzy closeness based optimization is employed to identify those samples. Results demonstrate that THz spectroscopy combined with PCA and fuzzy pattern recognition can be efficiently utilized for automatic identification of biomolecules. The proposed approach provides a new effective method in the detection and identification of biomolecules using THz spectroscopy.

  10. Identification of biomolecules by terahertz spectroscopy and fuzzy pattern recognition.

    PubMed

    Chen, Tao; Li, Zhi; Mo, Wei

    2013-04-01

    An approach for automatic identification of terahertz (THz) spectra of biomolecules is proposed based on principal component analysis (PCA) and fuzzy pattern recognition in this paper, and THz transmittance spectra of some typical amino acid and saccharide biomolecular samples are investigated to prove its feasibility. Firstly, PCA is applied to reduce the dimensionality of the original spectrum data and extract features of the data. Secondly, instead of the original spectrum variables, the selected principal component scores matrix is fed into the model of fuzzy pattern recognition, where a principle of fuzzy closeness based optimization is employed to identify those samples. Results demonstrate that THz spectroscopy combined with PCA and fuzzy pattern recognition can be efficiently utilized for automatic identification of biomolecules. The proposed approach provides a new effective method in the detection and identification of biomolecules using THz spectroscopy. PMID:23357678

  11. A novel online adaptive time delay identification technique

    NASA Astrophysics Data System (ADS)

    Bayrak, Alper; Tatlicioglu, Enver

    2016-05-01

    Time delay is a phenomenon which is common in signal processing, communication, control applications, etc. The special feature of time delay that makes it attractive is that it is a commonly faced problem in many systems. A literature search on time-delay identification highlights the fact that most studies focused on numerical solutions. In this study, a novel online adaptive time-delay identification technique is proposed. This technique is based on an adaptive update law through a minimum-maximum strategy which is firstly applied to time-delay identification. In the design of the adaptive identification law, Lyapunov-based stability analysis techniques are utilised. Several numerical simulations were conducted with Matlab/Simulink to evaluate the performance of the proposed technique. It is numerically demonstrated that the proposed technique works efficiently in identifying both constant and disturbed time delays, and is also robust to measurement noise.

  12. Structural damage identification using mathematical optimization techniques

    NASA Technical Reports Server (NTRS)

    Shen, Mo-How Herman

    1991-01-01

    An identification procedure is proposed to identify damage characteristics (location and size of the damage) from dynamic measurements. This procedure was based on minimization of the mean-square measure of difference between measurement data (natural frequencies and mode shapes) and the corresponding predictions obtained from the computational model. The procedure is tested for simulated damage in the form of stiffness changes in a simple fixed free spring mass system and symmetric cracks in a simply supported Bernoulli Euler beam. It is shown that when all the mode information is used in the identification procedure it is possible to uniquely determine the damage properties. Without knowing the complete set of modal information, a restricted region in the initial data space has been found for realistic and convergent solution from the identification process.

  13. Deconvolution/identification techniques for nonnegative signals

    SciTech Connect

    Goodman, D.M.; Yu, D.R.

    1991-11-01

    Several methods for solving the nonparametric deconvolution/identification problem when the unknown is nonnegative are presented. First we consider the constrained least squares method and discuss three ways to estimate the regularization parameter: the discrepancy principle, Mallow`s C{sub L}, and generalized cross validation. Next we consider maximum entropy methods. Last, we present a new conjugate gradient algorithm. A preliminary comparison is presented; detailed Monte-Carlo experiments will be presented at the conference. 13 refs.

  14. PIDA:A new algorithm for pattern identification.

    PubMed

    Putonti, C; Pettitt, Bm; Reid, Jg; Fofanov, Y

    2007-01-01

    Algorithms for motif identification in sequence space have predominately been focused on recognizing patterns of a fixed length containing regions of perfect conservation with possible regions of unconstrained sequence. Such motifs can be found in everything from proteins with distinct active sites to non-coding RNAs with specific structural elements that are necessary to maintain functionality. In the event that an insertion/deletion has occurred within an unconstrained portion of the pattern, it is possible that the pattern retains its functionality. In such a case the length of the pattern is now variable and may be overlooked when utilizing existing motif detection methods. The Pattern Island Detection Algorithm (PIDA) presented here has been developed to recognize patterns that have occurrences of varying length within sequences of any size alphabet. PIDA works by identifying all regions of perfect conservation (for lengths longer than a user-specified threshold), and then builds those conservation "islands" into fixed-length patterns. Next the algorithm modifies these fixed-length patterns by identifying additional (and different) islands that can be incorporated into each pattern through insertions/deletions within the "water" separating the islands. To provide some benchmarks for this analysis, PIDA was used to search for patterns within randomly generated sequences as well as sequences known to contain conserved patterns. For each of the patterns found, the statistical significance is calculated based upon the pattern's likelihood to appear by chance, thus providing a means to determine those patterns which are likely to have a functional role. The PIDA approach to motif finding is designed to perform best when searching for patterns of variable length although it is also able to identify patterns of a fixed length. PIDA has been created to be as generally applicable as possible since there are a variety of sequence problems of this type. The algorithm was

  15. Dynamic two-dimensional beam-pattern steering technique

    NASA Technical Reports Server (NTRS)

    Zhou, Shaomin; Yeh, Pochi; Liu, Hua-Kuang

    1993-01-01

    A dynamic two-dimensional laser-beam-pattern steering technique using photorefractive holograms in conjunction with electrically addressed spatial light modulators is proposed and investigated. The experimental results demonstrate the dynamic steering of random combinations of basis beam patterns. The proposed method has the advantages of random beam-pattern combination, good beam intensity uniformity, and higher diffraction efficiency compared with conventional methods.

  16. PIDA:A new algorithm for pattern identification

    PubMed Central

    Putonti, C; Pettitt, BM; Reid, JG; Fofanov, Y

    2009-01-01

    Algorithms for motif identification in sequence space have predominately been focused on recognizing patterns of a fixed length containing regions of perfect conservation with possible regions of unconstrained sequence. Such motifs can be found in everything from proteins with distinct active sites to non-coding RNAs with specific structural elements that are necessary to maintain functionality. In the event that an insertion/deletion has occurred within an unconstrained portion of the pattern, it is possible that the pattern retains its functionality. In such a case the length of the pattern is now variable and may be overlooked when utilizing existing motif detection methods. The Pattern Island Detection Algorithm (PIDA) presented here has been developed to recognize patterns that have occurrences of varying length within sequences of any size alphabet. PIDA works by identifying all regions of perfect conservation (for lengths longer than a user-specified threshold), and then builds those conservation “islands” into fixed-length patterns. Next the algorithm modifies these fixed-length patterns by identifying additional (and different) islands that can be incorporated into each pattern through insertions/deletions within the “water” separating the islands. To provide some benchmarks for this analysis, PIDA was used to search for patterns within randomly generated sequences as well as sequences known to contain conserved patterns. For each of the patterns found, the statistical significance is calculated based upon the pattern’s likelihood to appear by chance, thus providing a means to determine those patterns which are likely to have a functional role. The PIDA approach to motif finding is designed to perform best when searching for patterns of variable length although it is also able to identify patterns of a fixed length. PIDA has been created to be as generally applicable as possible since there are a variety of sequence problems of this type. The

  17. Serial identification of EEG patterns using adaptive wavelet-based analysis

    NASA Astrophysics Data System (ADS)

    Nazimov, A. I.; Pavlov, A. N.; Nazimova, A. A.; Grubov, V. V.; Koronovskii, A. A.; Sitnikova, E.; Hramov, A. E.

    2013-10-01

    A problem of recognition specific oscillatory patterns in the electroencephalograms with the continuous wavelet-transform is discussed. Aiming to improve abilities of the wavelet-based tools we propose a serial adaptive method for sequential identification of EEG patterns such as sleep spindles and spike-wave discharges. This method provides an optimal selection of parameters based on objective functions and enables to extract the most informative features of the recognized structures. Different ways of increasing the quality of patterns recognition within the proposed serial adaptive technique are considered.

  18. Lightness identification of patterned three-dimensional, real objects

    PubMed Central

    Robilotto, Rocco; Zaidi, Qasim

    2010-01-01

    Conventional studies of lightness constancy have almost exclusively used flat plain stimuli and have shown that lightness matches across illuminants cannot be explained by physical matches of reflectance or luminance. The perceptual qualities that underlie lightness judgments still remain largely unknown. Real objects are often 3-D and patterned, giving additional cues for identification. We examine the perceptual strategies that underlie material identification of real objects. Stimuli were randomly crumpled papers printed with achromatic patterns with precisely calibrated mean reflectance and reflectance contrast, placed in backgrounds under varying levels of illumination. Observers were asked to identify objects based on physical reflectance differences. Reflectance identification functions were simulated by simple models that perform object identification based on dissimilarities in perceived brightness (luminance dissimilarity modified by light adaptation) or perceived contrast (contrast dissimilarity modified by mean luminance). The reflectance identification results were also recreated in two control experiments, using identical stimuli conditions, where choices were based explicitly on dissimilarities in perceived brightness or contrast. Rather than a reverse optics model of lightness perception where observers first estimate illuminant intensity and then extract relative lightness by discounting the illuminant, this study supports the use of simple percepts such as brightness and contrast. PMID:16489856

  19. Advantages and Limitations of the RICH Technique for Particle Identification

    SciTech Connect

    Ratcliff, Blair N.; /SLAC

    2011-11-07

    The ring imaging Cherenkov (RICH) technique for hadronic particle identification (PID) is described. The advantages and limitations of RICH PID counters are compared with those of other classic PID techniques, such as threshold Cherenkov counters, ionization loss (dE/dx) in tracking devices, and time of flight (TOF) detectors.

  20. User Identification Using Gait Patterns on UbiFloorII

    PubMed Central

    Yun, Jaeseok

    2011-01-01

    This paper presents a system of identifying individuals by their gait patterns. We take into account various distinguishable features that can be extracted from a user’s gait and then divide them into two classes: walking pattern and stepping pattern. The conditions we assume are that our target environments are domestic areas, the number of users is smaller than 10, and all users ambulate with bare feet considering the everyday lifestyle of the Korean home. Under these conditions, we have developed a system that identifies individuals’ gait patterns using our biometric sensor, UbiFloorII. We have created UbiFloorII to collect walking samples and created software modules to extract the user’s gait pattern. To identify the users based on the gait patterns extracted from walking samples over UbiFloorII, we have deployed multilayer perceptron network, a feedforward artificial neural network model. The results show that both walking pattern and stepping pattern extracted from users’ gait over the UbiFloorII are distinguishable enough to identify the users and that fusing two classifiers at the matching score level improves the recognition accuracy. Therefore, our proposed system may provide unobtrusive and automatic user identification methods in ubiquitous computing environments, particularly in domestic areas. PMID:22163758

  1. Maximum likelihood estimation of label imperfections and its use in the identification of mislabeled patterns

    NASA Technical Reports Server (NTRS)

    Chittineni, C. B.

    1979-01-01

    The problem of estimating label imperfections and the use of the estimation in identifying mislabeled patterns is presented. Expressions for the maximum likelihood estimates of classification errors and a priori probabilities are derived from the classification of a set of labeled patterns. Expressions also are given for the asymptotic variances of probability of correct classification and proportions. Simple models are developed for imperfections in the labels and for classification errors and are used in the formulation of a maximum likelihood estimation scheme. Schemes are presented for the identification of mislabeled patterns in terms of threshold on the discriminant functions for both two-class and multiclass cases. Expressions are derived for the probability that the imperfect label identification scheme will result in a wrong decision and are used in computing thresholds. The results of practical applications of these techniques in the processing of remotely sensed multispectral data are presented.

  2. Identification and interpretation of patterns in rocket engine data

    NASA Technical Reports Server (NTRS)

    Lo, Ching F.

    1993-01-01

    The goal of our research is to analyze ground test data, to identify patterns associated with the anomalous engine behavior. On the basis of this analysis, it is the task of our project to develop a Pattern Identification and Detection System which detects anomalous engine behavior in the early stages of fault development significantly earlier than the indication provided by either redline detection mechanism or human expert analysis. Early detection of these anomalies is challenging because of the large amount of noise presence in the data. In the presence of this noise, early indication of anomalies becomes even more difficult to distinguish from fluctuations in normal steady state operation.

  3. Parameter estimation techniques for LTP system identification

    NASA Astrophysics Data System (ADS)

    Nofrarias Serra, Miquel

    LISA Pathfinder (LPF) is the precursor mission of LISA (Laser Interferometer Space Antenna) and the first step towards gravitational waves detection in space. The main instrument onboard the mission is the LTP (LISA Technology Package) whose scientific goal is to test LISA's drag-free control loop by reaching a differential acceleration noise level between two masses in √ geodesic motion of 3 × 10-14 ms-2 / Hz in the milliHertz band. The mission is not only challenging in terms of technology readiness but also in terms of data analysis. As with any gravitational wave detector, attaining the instrument performance goals will require an extensive noise hunting campaign to measure all contributions with high accuracy. But, opposite to on-ground experiments, LTP characterisation will be only possible by setting parameters via telecommands and getting a selected amount of information through the available telemetry downlink. These two conditions, high accuracy and high reliability, are the main restrictions that the LTP data analysis must overcome. A dedicated object oriented Matlab Toolbox (LTPDA) has been set up by the LTP analysis team for this purpose. Among the different toolbox methods, an essential part for the mission are the parameter estimation tools that will be used for system identification during operations: Linear Least Squares, Non-linear Least Squares and Monte Carlo Markov Chain methods have been implemented as LTPDA methods. The data analysis team has been testing those methods with a series of mock data exercises with the following objectives: to cross-check parameter estimation methods and compare the achievable accuracy for each of them, and to develop the best strategies to describe the physics underlying a complex controlled experiment as the LTP. In this contribution we describe how these methods were tested with simulated LTP-like data to recover the parameters of the model and we report on the latest results of these mock data exercises.

  4. Analysis of enamel rod end patterns on tooth surface for personal identification--ameloglyphics.

    PubMed

    Manjunath, Krishnappa; Sivapathasundharam, Balasundharam; Saraswathi, Thillai R

    2012-05-01

    Ameloglyphics is the study of enamel rod end patterns on a tooth surface. Our aim was to study the in vivo analysis of enamel rod end patterns on tooth surfaces for personal identification. In this study, the maxillary left canine and 1st premolar of 30 men and 30 women were included. The cellulose acetate peel technique was used to record enamel rod endings on tooth surfaces. Photomicrographs of the acetate peel imprint were subjected to VeriFinger Standard SDK v5.0 software for obtaining enamel rod end patterns. All 120 enamel rod end patterns were subjected to visual analysis and biometric analysis. Biometric analysis revealed that the enamel rod end pattern is unique for each tooth in an individual. It shows both intra- and interindividual variation. Enamel rod end patterns were unique between the male and female subjects. Visual analysis showed that wavy branched subpattern was the predominant subpattern observed among examined teeth. Hence, ameloglyphics is a reliable technique for personal identification. PMID:22329965

  5. A machine vision identification technique from range images

    NASA Technical Reports Server (NTRS)

    Kehtarnavaz, N.; Mohan, S.

    1988-01-01

    An orientation-independent identification technique from three-dimensional surface maps or range images is developed. Given the range image of an object, it is decomposed into orientation-independent patches using the sign of Gaussian curvature. A relational graph is then set up such that a node represents a patch and an edge represents the adjacency of two patches. The identification of the object is achieved by matching its graph representation to a number of model graphs. The matching is performed by employing the best-first search strategy. Examples of real range images show the merit of the technique.

  6. Patterns of Cognitive Strengths and Weaknesses: Identification Rates, Agreement, and Validity for Learning Disabilities Identification

    ERIC Educational Resources Information Center

    Miciak, Jeremy; Fletcher, Jack M.; Stuebing, Karla K.; Vaughn, Sharon; Tolar, Tammy D.

    2014-01-01

    Few empirical investigations have evaluated learning disabilities (LD) identification methods based on a pattern of cognitive strengths and weaknesses (PSW). This study investigated the reliability and validity of two proposed PSW methods: the concordance/discordance method (C/DM) and cross battery assessment (XBA) method. Cognitive assessment…

  7. Biometric Identification Using Holographic Radar Imaging Techniques

    SciTech Connect

    McMakin, Douglas L.; Sheen, David M.; Hall, Thomas E.; Kennedy, Mike O.; Foote, Harlan P.

    2007-04-01

    Pacific Northwest National Laboratory researchers have been at the forefront of developing innovative screening systems to enhance security and a novel imaging system to provide custom-fit clothing using holographic radar imaging techniques. First-of-a-kind cylindrical holographic imaging systems have been developed to screen people at security checkpoints for the detection of concealed, body worn, non-metallic threats such as plastic and liquid explosives, knifes and contraband. Another embodiment of this technology is capable of obtaining full sized body measurements in near real time without the person under surveillance removing their outer garments. Radar signals readily penetrate clothing and reflect off the water in skin. This full body measurement system is commercially available for best fitting ready to wear clothing, which was the first “biometric” application for this technology. One compelling feature of this technology for security biometric applications is that it can see effectively through disguises, appliances and body hair.

  8. Identification of human pathogens isolated from blood using microarray hybridisation and signal pattern recognition

    PubMed Central

    Wiesinger-Mayr, Herbert; Vierlinger, Klemens; Pichler, Rudolf; Kriegner, Albert; Hirschl, Alexander M; Presterl, Elisabeth; Bodrossy, Levente; Noehammer, Christa

    2007-01-01

    Background Pathogen identification in clinical routine is based on the cultivation of microbes with subsequent morphological and physiological characterisation lasting at least 24 hours. However, early and accurate identification is a crucial requisite for fast and optimally targeted antimicrobial treatment. Molecular biology based techniques allow fast identification, however discrimination of very closely related species remains still difficult. Results A molecular approach is presented for the rapid identification of pathogens combining PCR amplification with microarray detection. The DNA chip comprises oligonucleotide capture probes for 25 different pathogens including Gram positive cocci, the most frequently encountered genera of Enterobacteriaceae, non-fermenter and clinical relevant Candida species. The observed detection limits varied from 10 cells (e.g. E. coli) to 105 cells (S. aureus) per mL artificially spiked blood. Thus the current low sensitivity for some species still represents a barrier for clinical application. Successful discrimination of closely related species was achieved by a signal pattern recognition approach based on the k-nearest-neighbour method. A prototype software providing this statistical evaluation was developed, allowing correct identification in 100 % of the cases at the genus and in 96.7 % at the species level (n = 241). Conclusion The newly developed molecular assay can be carried out within 6 hours in a research laboratory from pathogen isolation to species identification. From our results we conclude that DNA microarrays can be a useful tool for rapid identification of closely related pathogens particularly when the protocols are adapted to the special clinical scenarios. PMID:17697354

  9. Pattern recognition for identification of lysozyme droplet solution chemistry.

    PubMed

    Gorr, Heather Meloy; Xiong, Ziye; Barnard, John A

    2014-03-01

    Pattern formation during evaporation of a colloidal sessile droplet is a phenomenon relevant to a wide variety of scientific disciplines. The patterns remaining on the substrate are indicative of the transport mechanisms and phase transitions occurring during evaporation and may reflect the solution chemistry of the fluid [1-18]. Pattern formation during evaporation of droplets of biofluids has also been examined and these complex patterns may reflect the health of the patient [23-31]. Automatic detection of variations in the fluid composition based on these deposit patterns could lead to rapid screening for diagnostic or quality control purposes. In this study, a pattern recognition algorithm is presented to differentiate between deposits containing various solution compositions. The deposits studied are from droplets of simplified, model biological fluids of aqueous lysozyme and NaCl solutions. For the solution concentrations examined here, the deposit patterns are dependent upon the initial solution composition. Deposit images are represented by extracting features using the Gabor wavelet, similar to the method used for iris recognition. Two popular pattern recognition algorithms are used to classify the deposits. The k-means clustering algorithm is used to test if incremental changes in solution concentration result in reproducible and statistically interpretable variations in the deposit patterns. The k-nearest neighbor algorithm is also used to classify the deposit images by solution concentration based on a set of training images for each class. Here, we demonstrate that the deposit patterns may act as a "fingerprint" for identification of solution chemistry. The results of this study are very promising, with classification accuracies of 90-97.5%. PMID:24342799

  10. Patterns of Cognitive Strengths and Weaknesses: Identification Rates, Agreement, and Validity for Learning Disabilities Identification

    PubMed Central

    Miciak, Jeremy; Fletcher, Jack M.; Stuebing, Karla; Vaughn, Sharon; Tolar, Tammy D.

    2014-01-01

    Purpose Few empirical investigations have evaluated LD identification methods based on a pattern of cognitive strengths and weaknesses (PSW). This study investigated the reliability and validity of two proposed PSW methods: the concordance/discordance method (C/DM) and cross battery assessment (XBA) method. Methods Cognitive assessment data for 139 adolescents demonstrating inadequate response to intervention was utilized to empirically classify participants as meeting or not meeting PSW LD identification criteria using the two approaches, permitting an analysis of: (1) LD identification rates; (2) agreement between methods; and (3) external validity. Results LD identification rates varied between the two methods depending upon the cut point for low achievement, with low agreement for LD identification decisions. Comparisons of groups that met and did not meet LD identification criteria on external academic variables were largely null, raising questions of external validity. Conclusions This study found low agreement and little evidence of validity for LD identification decisions based on PSW methods. An alternative may be to use multiple measures of academic achievement to guide intervention. PMID:24274155

  11. Identification of apolipoprotein using feature selection technique

    PubMed Central

    Tang, Hua; Zou, Ping; Zhang, Chunmei; Chen, Rong; Chen, Wei; Lin, Hao

    2016-01-01

    Apolipoprotein is a kind of protein which can transport the lipids through the lymphatic and circulatory systems. The abnormal expression level of apolipoprotein always causes angiocardiopathy. Thus, correct recognition of apolipoprotein from proteomic data is very crucial to the comprehension of cardiovascular system and drug design. This study is to develop a computational model to predict apolipoproteins. In the model, the apolipoproteins and non-apolipoproteins were collected to form benchmark dataset. On the basis of the dataset, we extracted the g-gap dipeptide composition information from residue sequences to formulate protein samples. To exclude redundant information or noise, the analysis of various (ANOVA)-based feature selection technique was proposed to find out the best feature subset. The support vector machine (SVM) was selected as discrimination algorithm. Results show that 96.2% of sensitivity and 99.3% of specificity were achieved in five-fold cross-validation. These findings open new perspectives to improve apolipoproteins prediction by considering the specific dipeptides. We expect that these findings will help to improve drug development in anti-angiocardiopathy disease. PMID:27443605

  12. Identification of apolipoprotein using feature selection technique.

    PubMed

    Tang, Hua; Zou, Ping; Zhang, Chunmei; Chen, Rong; Chen, Wei; Lin, Hao

    2016-01-01

    Apolipoprotein is a kind of protein which can transport the lipids through the lymphatic and circulatory systems. The abnormal expression level of apolipoprotein always causes angiocardiopathy. Thus, correct recognition of apolipoprotein from proteomic data is very crucial to the comprehension of cardiovascular system and drug design. This study is to develop a computational model to predict apolipoproteins. In the model, the apolipoproteins and non-apolipoproteins were collected to form benchmark dataset. On the basis of the dataset, we extracted the g-gap dipeptide composition information from residue sequences to formulate protein samples. To exclude redundant information or noise, the analysis of various (ANOVA)-based feature selection technique was proposed to find out the best feature subset. The support vector machine (SVM) was selected as discrimination algorithm. Results show that 96.2% of sensitivity and 99.3% of specificity were achieved in five-fold cross-validation. These findings open new perspectives to improve apolipoproteins prediction by considering the specific dipeptides. We expect that these findings will help to improve drug development in anti-angiocardiopathy disease. PMID:27443605

  13. Deconvolution/identification techniques for 1-D transient signals

    SciTech Connect

    Goodman, D.M.

    1990-10-01

    This paper discusses a variety of nonparametric deconvolution and identification techniques that we have developed for application to 1-D transient signal problems. These methods are time-domain techniques that use direct methods for matrix inversion. Therefore, they are not appropriate for large data'' problems. These techniques involve various regularization methods and permit the use of certain kinds of a priori information in estimating the unknown. These techniques have been implemented in a package using standard FORTRAN that should make the package readily transportable to most computers. This paper is also meant to be an instruction manual for the package. 25 refs., 17 figs., 1 tab.

  14. Development of evaluation method for software hazard identification techniques

    SciTech Connect

    Huang, H. W.; Chen, M. H.; Shih, C.; Yih, S.; Kuo, C. T.; Wang, L. H.; Yu, Y. C.; Chen, C. W.

    2006-07-01

    This research evaluated the applicable software hazard identification techniques nowadays, such as, Preliminary Hazard Analysis (PHA), Failure Modes and Effects Analysis (FMEA), Fault Tree Analysis (FTA), Markov chain modeling, Dynamic Flow-graph Methodology (DFM), and simulation-based model analysis; and then determined indexes in view of their characteristics, which include dynamic capability, completeness, achievability, detail, signal/noise ratio, complexity, and implementation cost. By this proposed method, the analysts can evaluate various software hazard identification combinations for specific purpose. According to the case study results, the traditional PHA + FMEA + FTA (with failure rate) + Markov chain modeling (with transfer rate) combination is not competitive due to the dilemma for obtaining acceptable software failure rates. However, the systematic architecture of FTA and Markov chain modeling is still valuable for realizing the software fault structure. The system centric techniques, such as DFM and simulation-based model-analysis, show the advantage on dynamic capability, achievability, detail, signal/noise ratio. However, their disadvantages are the completeness complexity and implementation cost. This evaluation method can be a platform to reach common consensus for the stakeholders. Following the evolution of software hazard identification techniques, the evaluation results could be changed. However, the insight of software hazard identification techniques is much more important than the numbers obtained by the evaluation. (authors)

  15. Detection, identification, and quantification techniques for spills of hazardous chemicals

    NASA Technical Reports Server (NTRS)

    Washburn, J. F.; Sandness, G. A.

    1977-01-01

    The first 400 chemicals listed in the Coast Guard's Chemical Hazards Response Information System were evaluated with respect to their detectability, identifiability, and quantifiability by 12 generalized remote and in situ sensing techniques. Identification was also attempted for some key areas in water pollution sensing technology.

  16. Accuracy of Using Visual Identification of White Sharks to Estimate Residency Patterns

    PubMed Central

    Delaney, David G.; Johnson, Ryan; Bester, Marthán N.; Gennari, Enrico

    2012-01-01

    Determining the residency of an aquatic species is important but challenging and it remains unclear what is the best sampling methodology. Photo-identification has been used extensively to estimate patterns of animals' residency and is arguably the most common approach, but it may not be the most effective approach in marine environments. To examine this, in 2005, we deployed acoustic transmitters on 22 white sharks (Carcharodon carcharias) in Mossel Bay, South Africa to quantify the probability of detecting these tagged sharks by photo-identification and different deployment strategies of acoustic telemetry equipment. Using the data collected by the different sampling approaches (detections from an acoustic listening station deployed under a chumming vessel versus those from visual sightings and photo-identification), we quantified the methodologies' probability of detection and determined if the sampling approaches, also including an acoustic telemetry array, produce comparable results for patterns of residency. Photo-identification had the lowest probability of detection and underestimated residency. The underestimation is driven by various factors primarily that acoustic telemetry monitors a large area and this reduces the occurrence of false negatives. Therefore, we propose that researchers need to use acoustic telemetry and also continue to develop new sampling approaches as photo-identification techniques are inadequate to determine residency. Using the methods presented in this paper will allow researchers to further refine sampling approaches that enable them to collect more accurate data that will result in better research and more informed management efforts and policy decisions. PMID:22514662

  17. Biological agent detection and identification using pattern recognition

    NASA Astrophysics Data System (ADS)

    Braun, Jerome J.; Glina, Yan; Judson, Nicholas; Transue, Kevin D.

    2005-05-01

    This paper discusses a novel approach for the automatic identification of biological agents. The essence of the approach is a combination of gene expression, microarray-based sensing, information fusion, machine learning and pattern recognition. Integration of these elements is a distinguishing aspect of the approach, leading to a number of significant advantages. Amongst them are the applicability to various agent types including bacteria, viruses, toxins, and other, ability to operate without the knowledge of a pathogen's genome sequence and without the need for bioagent-speciific materials or reagents, and a high level of extensibility. Furthermore, the approach allows detection of uncatalogued agents, including emerging pathogens. The approach offers a promising avenue for automatic identification of biological agents for applications such as medical diagnostics, bioforensics, and biodefense.

  18. An experimental modal testing/identification technique for personal computers

    NASA Technical Reports Server (NTRS)

    Roemer, Michael J.; Schlonski, Steven T.; Mook, D. Joseph

    1990-01-01

    A PC-based system for mode shape identification is evaluated. A time-domain modal identification procedure is utilized to identify the mode shapes of a beam apparatus from discrete time-domain measurements. The apparatus includes a cantilevered aluminum beam, four accelerometers, four low-pass filters, and the computer. The method's algorithm is comprised of an identification algorithm: the Eigensystem Realization Algorithm (ERA) and an estimation algorithm called Minimum Model Error (MME). The identification ability of this algorithm is compared with ERA alone, a frequency-response-function technique, and an Euler-Bernoulli beam model. Detection of modal parameters and mode shapes by the PC-based time-domain system is shown to be accurate in an application with an aluminum beam, while mode shapes identified by the frequency-domain technique are not as accurate as predicted. The new method is shown to be significantly less sensitive to noise and poorly excited modes than other leading methods. The results support the use of time-domain identification systems for mode shape prediction.

  19. Rapid identification of single microbes by various Raman spectroscopic techniques

    NASA Astrophysics Data System (ADS)

    Rösch, Petra; Harz, Michaela; Schmitt, Michael; Peschke, Klaus-Dieter; Ronneberger, Olaf; Burkhardt, Hans; Motzkus, Hans-Walter; Lankers, Markus; Hofer, Stefan; Thiele, Hans; Popp, Jürgen

    2006-02-01

    A fast and unambiguous identification of microorganisms is necessary not only for medical purposes but also in technical processes such as the production of pharmaceuticals. Conventional microbiological identification methods are based on the morphology and the ability of microbes to grow under different conditions on various cultivation media depending on their biochemical properties. These methods require pure cultures which need cultivation of at least 6 h but normally much longer. Recently also additional methods to identify bacteria are established e.g. mass spectroscopy, polymerase chain reaction (PCR), flow cytometry or fluorescence spectroscopy. Alternative approaches for the identification of microorganisms are vibrational spectroscopic techniques. With Raman spectroscopy a spectroscopic fingerprint of the microorganisms can be achieved. Using UV-resonance Raman spectroscopy (UVRR) macromolecules like DNA/RNA and proteins are resonantly enhanced. With an excitation wavelength of e.g. 244 nm it is possible to determine the ratio of guanine/cytosine to all DNA bases which allows a genotypic identification of microorganisms. The application of UVRR requires a large amount of microorganisms (> 10 6 cells) e.g. at least a micro colony. For the analysis of single cells micro-Raman spectroscopy with an excitation wavelength of 532 nm can be used. Here, the obtained information is from all type of molecules inside the cells which lead to a chemotaxonomic identification. In this contribution we show how wavelength dependent Raman spectroscopy yields significant molecular information applicable for the identification of microorganisms on a single cell level.

  20. Immunoblot technique to visualise serum pepsinogen A isozymogen patterns.

    PubMed Central

    Zwiers, A; Toonstra, C; Pals, G; Donker, A J; Meuwissen, S G; ten Kate, R W

    1990-01-01

    Pepsinogen A (PGA) isozymogen patterns in urine and gastric mucosa can be visualised in non-denatured polyacrylamide gel electrophoresis by showing proteolytic activity after the conversion of pepsinogen into pepsin by acid. This method is not suitable for visualising PGA patterns in serum due to low PGA concentrations. To obtain a more sensitive visualisation method an immunoblotting technique was developed. PGA isozymogen patterns from urine and sonified gastric mucosa specimens obtained by immunoblotting were identical with those obtained by activity staining. The immunostaining method was at least 50 times more sensitive. PGA isozymogen patterns could be visualised in serum. Preliminary results suggest that the PGA patterns in serum and gastric mucosa are identical. As an association has been found between the genetically determined PGA isozymogen patterns in gastric mucosa and gastric malignancies in man, immunoblotting of PGA isozymogens in serum may provide a screening tool for subjects at risk of malignant gastric disease. Images PMID:2229438

  1. HIV coreceptor tropism determination and mutational pattern identification.

    PubMed

    Shen, Hui-Shuang; Yin, Jason; Leng, Fei; Teng, Rui-Fang; Xu, Chao; Xia, Xia-Yu; Pan, Xian-Ming

    2016-01-01

    In the early stages of infection, Human Immunodeficiency Virus Type 1 (HIV-1) generally selects CCR5 as the primary coreceptor for entering the host cell. As infection progresses, the virus evolves and may exhibit a coreceptor-switch to CXCR4. Accurate determination coreceptor usage and identification key mutational patterns associated tropism switch are essential for selection of appropriate therapies and understanding mechanism of coreceptor change. We developed a classifier composed of two coreceptor-specific weight matrices (CMs) based on a full-scale dataset. For this classifier, we found an AUC of 0.97, an accuracy of 95.21% and an MCC of 0.885 (sensitivity 92.92%; specificity 95.54%) in a ten-fold cross-validation, outperforming all other methods on an independent dataset (13% higher MCC value than geno2pheno and 15% higher MCC value than PSSM). A web server (http://spg.med.tsinghua.edu.cn/CM.html) based on our classifier was provided. Patterns of genetic mutations that occur along with coreceptor transitions were further identified based on the score of each sequence. Six pairs of one-AA mutational patterns and three pairs of two-AA mutational patterns were identified to associate with increasing propensity for X4 tropism. These mutational patterns offered new insights into the mechanism of coreceptor switch and aided in monitoring coreceptor switch. PMID:26883082

  2. Feature extraction from light-scatter patterns of Listeria colonies for identification and classification.

    PubMed

    Bayraktar, Bulent; Banada, Padmapriya P; Hirleman, E Daniel; Bhunia, Arun K; Robinson, J Paul; Rajwa, Bartek

    2006-01-01

    Bacterial contamination by Listeria monocytogenes not only puts the public at risk, but also is costly for the food-processing industry. Traditional biochemical methods for pathogen identification require complicated sample preparation for reliable results. Optical scattering technology has been used for identification of bacterial cells in suspension, but with only limited success. Therefore, to improve the efficacy of the identification process using our novel imaging approach, we analyze bacterial colonies grown on solid surfaces. The work presented here demonstrates an application of computer-vision and pattern-recognition techniques to classify scatter patterns formed by Listeria colonies. Bacterial colonies are analyzed with a laser scatterometer. Features of circular scatter patterns formed by bacterial colonies illuminated by laser light are characterized using Zernike moment invariants. Principal component analysis and hierarchical clustering are performed on the results of feature extraction. Classification using linear discriminant analysis, partial least squares, and neural networks is capable of separating different strains of Listeria with a low error rate. The demonstrated system is also able to determine automatically the pathogenicity of bacteria on the basis of colony scatter patterns. We conclude that the obtained results are encouraging, and strongly suggest the feasibility of image-based biodetection systems. PMID:16822056

  3. Whisker spot patterns: a noninvasive method of individual identification of Australian sea lions (Neophoca cinerea)

    PubMed Central

    Osterrieder, Sylvia K.; Salgado Kent, Chandra; Anderson, Carlos J. R.; Parnum, Iain M.; Robinson, Randall W.

    2015-01-01

    Reliable methods for identification of individual animals are advantageous for ecological studies of population demographics and movement patterns. Photographic identification, based on distinguishable patterns, unique shapes, or scars, is an effective technique already used for many species. We tested whether photographs of whisker spot patterns could be used to discriminate among individual Australian sea lion (Neophoca cinerea). Based on images of 53 sea lions, we simulated 5,000 patterns before calculating the probability of duplication in a study population. A total of 99% (± 1.5 SD) of patterns were considered reliable for a population of 50, 98% (± 1.7 SD) for 100, 92% (± 4.7 SD) for 500, and 88% (± 5.7 SD) for 1,000. We tested a semiautomatic approach by matching 16 known individuals at 3 different angles (70°, 90°, and 110°), 2 distances (1 and 2 m), and 6 separate times over a 1-year period. A point-pattern matching algorithm for pairwise comparisons produced 90% correct matches of photographs taken on the same day at 90°. Images of individuals at 1 and 2 m resulted in 89% correct matches, those photographed at different angles and different times (at 90°) resulted in 48% and 73% correct matches, respectively. Our results show that the Chamfer distance transform can effectively be used for individual identification, but only if there is very little variation in photograph angle. This point-pattern recognition application may also work for other otariid species. PMID:26937048

  4. Acoustic source identification using a Generalized Weighted Inverse Beamforming technique

    NASA Astrophysics Data System (ADS)

    Presezniak, Flavio; Zavala, Paulo A. G.; Steenackers, Gunther; Janssens, Karl; Arruda, Jose R. F.; Desmet, Wim; Guillaume, Patrick

    2012-10-01

    In the last years, acoustic source identification has gained special attention, mainly due to new environmental norms, urbanization problems and more demanding acoustic comfort expectation of consumers. From the current methods, beamforming techniques are of common use, since normally demands affordable data acquisition effort, while producing clear source identification in most of the applications. In order to improve the source identification quality, this work presents a method, based on the Generalized Inverse Beamforming, that uses a weighted pseudo-inverse approach and an optimization procedure, called Weighted Generalized Inverse Beamforming. To validate this method, a simple case of two compact sources in close vicinity in coherent radiation was investigated by numerical and experimental assessment. Weighted generalized inverse results are compared to the ones obtained by the conventional beamforming, MUltiple Signal Classification, and Generalized Inverse Beamforming. At the end, the advantages of the proposed method are outlined together with the computational effort increase compared to the Generalized Inverse Beamforming.

  5. [Discordant pattern, visual identification of myocardial viability with PET].

    PubMed

    Alexánderson, E; Ricalde, A; Zerón, J; Talayero, J A; Cruz, P; Adame, G; Mendoza, G; Meave, A

    2006-01-01

    PET (positron emission tomography) as a non-invasive imaging method for studying cardiac perfusion and metabolism has turned into the gold standard for detecting myocardial viability. The utilization of 18 FDG as a tracer for its identification permits to spot the use of exogenous glucose by the myocardium segments. By studying and comparing viability and perfusion results, for which the latter uses tracers such as 13N-ammonia, three different patterns for myocardial viability evaluation arise:. transmural concordant pattern, non-transmural concordant pattern, and the discordant pattern; the last one exemplifies the hibernating myocardium and proves the presence of myocardial viability. The importance of its detection is fundamental for the study of an ischemic patient, since it permits the establishment of and exact diagnosis, prognosis, and the best treatment option. It also allows foreseeing functional recovery of the affected region as well as the ejection fraction rate after revascularization treatment if this is determined as necessary. All these elements regarding viability are determinant in order to reduce adverse events and help improving patients' prognosis. PMID:17315610

  6. Contextual effects in the identification of nonspeech auditory patterns.

    PubMed

    Kidd, Gerald; Richards, Virginia M; Streeter, Timothy; Mason, Christine R; Huang, Rong

    2011-12-01

    This study investigated the benefit of a priori cues in a masked nonspeech pattern identification experiment. Targets were narrowband sequences of tone bursts forming six easily identifiable frequency patterns selected randomly on each trial. The frequency band containing the target was randomized. Maskers were also narrowband sequences of tone bursts chosen randomly on every trial. Targets and maskers were presented monaurally in mutually exclusive frequency bands, producing large amounts of informational masking. Cuing the masker produced a significant improvement in performance, while holding the target frequency band constant provided no benefit. The cue providing the greatest benefit was a copy of the masker presented ipsilaterally before the target-plus-masker. The masker cue presented contralaterally, and a notched-noise cue produced smaller benefits. One possible mechanism underlying these findings is auditory "enhancement" in which the neural response to the target is increased relative to the masker by differential prior stimulation of the target and masker frequency regions. A second possible mechanism provides a benefit to performance by comparing the spectrotemporal correspondence of the cue and target-plus-masker and is effective for either ipsilateral or contralateral cue presentation. These effects improve identification performance by emphasizing spectral contrasts in sequences or streams of sounds. PMID:22225048

  7. Functional module identification in protein interaction networks by interaction patterns

    PubMed Central

    Wang, Yijie; Qian, Xiaoning

    2014-01-01

    Motivation: Identifying functional modules in protein–protein interaction (PPI) networks may shed light on cellular functional organization and thereafter underlying cellular mechanisms. Many existing module identification algorithms aim to detect densely connected groups of proteins as potential modules. However, based on this simple topological criterion of ‘higher than expected connectivity’, those algorithms may miss biologically meaningful modules of functional significance, in which proteins have similar interaction patterns to other proteins in networks but may not be densely connected to each other. A few blockmodel module identification algorithms have been proposed to address the problem but the lack of global optimum guarantee and the prohibitive computational complexity have been the bottleneck of their applications in real-world large-scale PPI networks. Results: In this article, we propose a novel optimization formulation LCP2 (low two-hop conductance sets) using the concept of Markov random walk on graphs, which enables simultaneous identification of both dense and sparse modules based on protein interaction patterns in given networks through searching for LCP2 by random walk. A spectral approximate algorithm SLCP2 is derived to identify non-overlapping functional modules. Based on a bottom-up greedy strategy, we further extend LCP2 to a new algorithm (greedy algorithm for LCP2) GLCP2 to identify overlapping functional modules. We compare SLCP2 and GLCP2 with a range of state-of-the-art algorithms on synthetic networks and real-world PPI networks. The performance evaluation based on several criteria with respect to protein complex prediction, high level Gene Ontology term prediction and especially sparse module detection, has demonstrated that our algorithms based on searching for LCP2 outperform all other compared algorithms. Availability and implementation: All data and code are available at http://www.cse.usf.edu/∼xqian/fmi/slcp2hop

  8. Analytical techniques for direct identification of biosignatures and microorganisms

    NASA Astrophysics Data System (ADS)

    Cid, C.; Garcia-Descalzo, L.; Garcia-Lopez, E.; Postigo, M.; Alcazar, A.; Baquero, F.

    2012-09-01

    Rover missions to potentially habitable ecosystems require portable instruments that use minimal power, require no sample preparation, and provide suitably diagnostic information to an Earth-based exploration team. In exploration of terrestrial analogue environments of potentially habitable ecosystems it is important to screen rapidly for the presence of biosignatures and microorganisms and especially to identify them accurately. In this study, several analytical techniques for the direct identification of biosignatures and microorganisms in different Earth analogues of habitable ecosystems are compared.

  9. A Simplified Pattern Match Algorithm for Star Identification

    NASA Technical Reports Server (NTRS)

    Lee, Michael H.

    1996-01-01

    A true pattern matching star algorithm similar in concept to the Van Bezooijen algorithm is implemented using an iterative approach. This approach allows for a more compact and simple implementation which can be easily adapted to be either an all-sky, no a priori algorithm or a follow on to a direct match algorithm to distinguish between ambiguous matches. Some simple analysis is shown to indicate the likelihood of mis-identifications. The performance of the algorithm for the all-sky, no a priori situation is detailed assuming he SKYMAP star catalog describes the true sky. The impact of errors and omissions in the SKYMAP catalog on performance are investigated. In addition, differing levels of noise in the star observations are assumed and results shown. The implications for possible implementation on-board spacecraft are discussed.

  10. A smart pattern recognition system for the automatic identification of aerospace acoustic sources

    NASA Technical Reports Server (NTRS)

    Cabell, R. H.; Fuller, C. R.

    1989-01-01

    An intelligent air-noise recognition system is described that uses pattern recognition techniques to distinguish noise signatures of five different types of acoustic sources, including jet planes, propeller planes, a helicopter, train, and wind turbine. Information for classification is calculated using the power spectral density and autocorrelation taken from the output of a single microphone. Using this system, as many as 90 percent of test recordings were correctly identified, indicating that the linear discriminant functions developed can be used for aerospace source identification.

  11. Artificial intelligence techniques for clutter identification with polarimetric radar signatures

    NASA Astrophysics Data System (ADS)

    Islam, Tanvir; Rico-Ramirez, Miguel A.; Han, Dawei; Srivastava, Prashant K.

    2012-06-01

    The use of different artificial intelligence (AI) techniques for clutter signals identification in the context of radar based precipitation estimation is presented. The clutter signals considered are because of ground clutter, sea clutter and anomalous propagation whereas the explored AI techniques include the support vector machine (SVM), the artificial neural network (ANN), the decision tree (DT), and the nearest neighbour (NN) systems. Eight different radar measurement combinations comprising of various polarimetric spectral signatures — the reflectivity (ZH), differential reflectivity (ZDR), differential propagation phase (ΦDP), cross-correlation coefficient (ρHV), velocity (V) and spectral width (W) from a C-band polarimetric radar are taken into account as input vectors to the AI systems. The results reveal that all four AI classifiers can identify the clutter echoes with around 98-99% accuracy when all radar input signatures are used. As standalone input vectors, the polarimetric textures of the ΦDP and the ZDR have also demonstrated excellent skills distinguishing clutter echoes with an accuracy of 97-98% approximately. If no polarimetric signature is available, a combination of the texture of ZH, V and W representing typical measurements from a single-polarization Doppler radar may be used for clutter identification, but with a lower accuracy when compared to the use of polarimetric radar measurements. In contrast, the use of ZH or W alone is found less reliable for clutter classification. Among the AI techniques, the SVM has a slightly better score in terms of various clutter identification indicators as compared to the others. Conversely, the NN algorithm has shown a lower performance in identifying the clutter echoes correctly considering the standalone radar signatures as inputs. Despite this, the performance among the different AI techniques is comparable indicating the suitability of the developed systems, and this is further supported when

  12. 30nm half-pitch metal patterning using Moti CD shrink technique and double patterning

    NASA Astrophysics Data System (ADS)

    Versluijs, Janko; De Marneffe, J.-F.; Goossens, Danny; Op de Beeck, Maaike; Vandeweyer, Tom; Wiaux, Vincent; Struyf, Herbert; Maenhoudt, Mireille; Brouri, Mohand; Vertommen, Johan; Kim, Ji Soo; Zhu, Helen; Sadjadi, Reza

    2008-03-01

    Double patterning lithography appears a likely candidate to bridge the gap between water-based immersion lithography and EUV. A double patterning process is discussed for 30nm half-pitch interconnect structures, using 1.2 NA immersion lithography combined with the Motif TM CD shrink technique. An adjusted OPC calculation is required to model the proximity effects of the Motif shrink technique and subsequent metal hard mask (MHM) etch, on top of the lithography based proximity effects. The litho-etch-litho-etch approach is selected to pattern a TiN metal hard mask. This mask is then used to etch the low-k dielectric. The various process steps and challenges encountered are discussed, with the feasibility of this approach demonstrated by successfully transferring a 30nm half-pitch pattern into the MHM.

  13. Application of star identification using pattern matching to space ground systems at GSFC

    NASA Technical Reports Server (NTRS)

    Fink, D.; Shoup, D.

    1994-01-01

    This paper reports the application of pattern recognition techniques for star identification based on those proposed by Van Bezooijen to space ground systems for near-real-time attitude determination. A prototype was developed using these algorithms, which was used to assess the suitability of these techniques for support of the X-Ray Timing Explorer (XTE), Submillimeter Wave Astronomy Satellite (SWAS), and the Solar and Heliospheric Observatory (SOHO) missions. Experience with the prototype was used to refine specifications for the operational system. Different geometry tests appropriate to the mission requirements of XTE, SWAS, and SOHO were adopted. The applications of these techniques to upcoming mission support of XTE, SWAS, and SOHO are discussed.

  14. Identification and interpretation of patterns in rocket engine data

    NASA Astrophysics Data System (ADS)

    Lo, C. F.; Wu, K.; Whitehead, B. A.

    1993-10-01

    A prototype software system was constructed to detect anomalous Space Shuttle Main Engine (SSME) behavior in the early stages of fault development significantly earlier than the indication provided by either redline detection mechanism or human expert analysis. The major task of the research project is to analyze ground test data, to identify patterns associated with the anomalous engine behavior, and to develop a pattern identification and detection system on the basis of this analysis. A prototype expert system which was developed on both PC and Symbolics 3670 lisp machine for detecting anomalies in turbopump vibration data was checked with data from ground tests 902-473, 902-501, 902-519, and 904-097 of the Space Shuttle Main Engine. The neural networks method was also applied to supplement the statistical method utilized in the prototype system to investigate the feasibility in detecting anomalies in turbopump vibration of SSME. In most cases the anomalies detected by the expert system agree with those reported by NASA. On the neural networks approach, the results are given the successful detection rate higher than 95 percent to identify either normal or abnormal running condition based on the experimental data as well as numerical simulation.

  15. Identification and interpretation of patterns in rocket engine data

    NASA Technical Reports Server (NTRS)

    Lo, C. F.; Wu, K.; Whitehead, B. A.

    1993-01-01

    A prototype software system was constructed to detect anomalous Space Shuttle Main Engine (SSME) behavior in the early stages of fault development significantly earlier than the indication provided by either redline detection mechanism or human expert analysis. The major task of the research project is to analyze ground test data, to identify patterns associated with the anomalous engine behavior, and to develop a pattern identification and detection system on the basis of this analysis. A prototype expert system which was developed on both PC and Symbolics 3670 lisp machine for detecting anomalies in turbopump vibration data was checked with data from ground tests 902-473, 902-501, 902-519, and 904-097 of the Space Shuttle Main Engine. The neural networks method was also applied to supplement the statistical method utilized in the prototype system to investigate the feasibility in detecting anomalies in turbopump vibration of SSME. In most cases the anomalies detected by the expert system agree with those reported by NASA. On the neural networks approach, the results are given the successful detection rate higher than 95 percent to identify either normal or abnormal running condition based on the experimental data as well as numerical simulation.

  16. Identification of recurring patterns in fractionated atrial electrograms using new transform coefficients

    PubMed Central

    2012-01-01

    Background Identification of recurrent patterns in complex fractionated atrial electrograms (CFAE) has been used to differentiate paroxysmal from persistent atrial fibrillation (AF). Detection of the atrial CFAE patterns might therefore be assistive in guiding radiofrequency catheter ablation to drivers of the arrhythmia. In this study a technique for robust detection and classification of recurrent CFAE patterns is described. Method CFAE were obtained from the four pulmonary vein ostia, and from the anterior and posterior left atrium, in 10 patients with paroxysmal AF and 10 patients with longstanding persistent AF (216 recordings in total). Sequences 8.4 s in length were analyzed (8,192 sample points, 977 Hz sampling). Among the 216 sequences, two recurrent patterns A and B were substituted for 4 and 5 of the sequences, respectively. To this data, random interference, and random interference + noise were separately added. Basis vectors were constructed using a new transform that is derived from ensemble averaging. Patterns A and B were then detected and classified using a threshold level of Euclidean distance between spectral signatures as constructed with transform coefficients. Results In the presence of interference, sensitivity to detect and distinguish two patterns A and B was 96.2%, while specificity to exclude nonpatterns was 98.0%. In the presence of interference + noise, sensitivity was 89.1% while specificity was 97.0%. Conclusions Transform coefficients computed from ensemble averages can be used to succinctly quantify synchronized patterns present in AF data. The technique is useful to automatically detect recurrent patterns in CFAE that are embedded in interference without user bias. This quantitation can be implemented in real-time to map the AF substrate prior to and during catheter ablation. PMID:22260298

  17. Technique and Observation of Angular Gait Patterns in Running

    PubMed Central

    Sykes, K.

    1975-01-01

    A technique for the biomechanical analysis of running is described with specific reference to the angular displacement patterns of the lower limb. From high speed cine film recording profile views of the running gait, the Thigh, Knee and Ankle angles are measured during one complete cycle. Results are presented in the form of vector-space diagrams, namely Thigh-Knee angle and Knee-Ankle angle cyclograms. The diagrams are interpreted and some experimental observations are presented and discussed. The technique provides a useful research tool and a very good `teaching asset' for biomechanical studies of movement.

  18. Computer-Aided Diagnosis Utilizing Interactive Fuzzy Pattern Recognition Techniques

    NASA Astrophysics Data System (ADS)

    Ismail, M. A.

    1984-08-01

    Interactive or display-oriented pattern recognition algorithms can be utilized with advantage in the design of efficient computer-aided diagnostic systems. These visual methods may provide a powerful alternative to the pure numerical approach of data analysis for diagnostic and prognostic purposes. Functional as well as pictorial representation techniques are discussed in conjunction with some newly developed semi-fuzzy classification techniques. The blend between the two methodologies leads to the design of a very flexible, yet powerful diagnostic system. Results obtained when applying the proposed system on a group of patients representing several classes of liver dysfunction are also reported, to demonstrate the effectiveness of the proposed methodology.

  19. Self-amplified optical pattern-recognition technique

    NASA Technical Reports Server (NTRS)

    Liu, Hua-Kuang

    1992-01-01

    A self-amplified optical pattern-recognition technique that utilizes a photorefractive crystal as a real-time volume holographic filter with recording accomplished by means of laser beams of proper polarization and geometric configuration is described. After the holographic filter is recorded, it can be addressed with extremely weak object beams and an even weaker reference beam to obtain a pattern-recognition signal. Because of beam-coupling energy transfer from the input object beam to the diffracted beam, the recognition signal is greatly amplified. Experimental results of this technique using BaTiO3 crystal show that 5 orders of magnitude of amplification of a recognition signal can be obtained.

  20. Vocalisation sound pattern identification in young broiler chickens.

    PubMed

    Fontana, I; Tullo, E; Scrase, A; Butterworth, A

    2016-09-01

    In this study, we describe the monitoring of young broiler chicken vocalisation, with sound recorded and assessed at regular intervals throughout the life of the birds from day 1 to day 38, with a focus on the first week of life. We assess whether there are recognisable, and even predictable, vocalisation patterns based on frequency and sound spectrum analysis, which can be observed in birds at different ages and stages of growth within the relatively short life of the birds in commercial broiler production cycles. The experimental trials were carried out in a farm where the broiler where reared indoor, and audio recording procedures carried out over 38 days. The recordings were made using two microphones connected to a digital recorder, and the sonic data was collected in situations without disturbance of the animals beyond that created by the routine activities of the farmer. Digital files of 1 h duration were cut into short files of 10 min duration, and these sound recordings were analysed and labelled using audio analysis software. Analysis of these short sound files showed that the key vocalisation frequency and patterns changed in relation to increasing age and the weight of the broilers. Statistical analysis showed a significant correlation (P<0.001) between the frequency of vocalisation and the age of the birds. Based on the identification of specific frequencies of the sounds emitted, in relation to age and weight, it is proposed that there is potential for audio monitoring and comparison with 'anticipated' sound patterns to be used to evaluate the status of farmed broiler chicken. PMID:26227085

  1. A simple histochemical technique for the identification of gunshot residue.

    PubMed

    Tschirhart, D L; Noguchi, T T; Klatt, E C

    1991-03-01

    Alizarin red S (ARS) is a commonly used organic dye useful in the histologic identification of calcium deposits. ARS also forms colored reaction products with other metal ions, including barium and lead, which are present in primer residue. In histochemical studies, ARS is shown to identify primer residues from several manufacturers as well as primer residue deposited in tissue, either experimentally or in close-range gunshot wounds. This can be easily accomplished with routine histologic techniques. ARS does not stain gunpowder residue, tattoo pigment, melanin, graphite, india ink, or anthracotic pigment. PMID:2066729

  2. A Study of Hand Back Skin Texture Patterns for Personal Identification and Gender Classification

    PubMed Central

    Xie, Jin; Zhang, Lei; You, Jane; Zhang, David; Qu, Xiaofeng

    2012-01-01

    Human hand back skin texture (HBST) is often consistent for a person and distinctive from person to person. In this paper, we study the HBST pattern recognition problem with applications to personal identification and gender classification. A specially designed system is developed to capture HBST images, and an HBST image database was established, which consists of 1,920 images from 80 persons (160 hands). An efficient texton learning based method is then presented to classify the HBST patterns. First, textons are learned in the space of filter bank responses from a set of training images using the l1 -minimization based sparse representation (SR) technique. Then, under the SR framework, we represent the feature vector at each pixel over the learned dictionary to construct a representation coefficient histogram. Finally, the coefficient histogram is used as skin texture feature for classification. Experiments on personal identification and gender classification are performed by using the established HBST database. The results show that HBST can be used to assist human identification and gender classification. PMID:23012512

  3. A study of hand back skin texture patterns for personal identification and gender classification.

    PubMed

    Xie, Jin; Zhang, Lei; You, Jane; Zhang, David; Qu, Xiaofeng

    2012-01-01

    Human hand back skin texture (HBST) is often consistent for a person and distinctive from person to person. In this paper, we study the HBST pattern recognition problem with applications to personal identification and gender classification. A specially designed system is developed to capture HBST images, and an HBST image database was established, which consists of 1,920 images from 80 persons (160 hands). An efficient texton learning based method is then presented to classify the HBST patterns. First, textons are learned in the space of filter bank responses from a set of training images using the l(1) -minimization based sparse representation (SR) technique. Then, under the SR framework, we represent the feature vector at each pixel over the learned dictionary to construct a representation coefficient histogram. Finally, the coefficient histogram is used as skin texture feature for classification. Experiments on personal identification and gender classification are performed by using the established HBST database. The results show that HBST can be used to assist human identification and gender classification. PMID:23012512

  4. Designed strength identification of concrete by ultrasonic signal processing based on artificial intelligence techniques.

    PubMed

    Kim, Se-Dong; Shin, Dong-Hwan; Lim, Lea-Mook; Lee, Jin; Kim, Sung-Hwan

    2005-07-01

    This paper presents a pattern recognition method to identify the designed strength of concrete by evidence accumulation based on artificial intelligence techniques with multiple feature parameters. Concrete specimens in this experiment, which were designed to have the strengths of 180, 210, 240, 300, and 400 kg/cm2, respectively, have been considered. Variance, zero-crossing, mean frequency, autoregressive (AR) model coefficients, and linear cepstrum coefficients are extracted as feature parameters from ultrasonic signals of concretes. Pattern recognition is carried out through the evidence accumulation procedure using the distances measured with reference parameters. A fuzzy mapping function is introduced to transform the distance for the application of the evidence accumulation method. Results are presented to support the feasibility of the suggested approach for concrete pattern identification. PMID:16212253

  5. Evaluation of the use of fiber optic sensors in identification of fresco fracturing patterns

    NASA Astrophysics Data System (ADS)

    Glisic, Branko; Sigurdardottir, Dorotea; Dobkin, David P.

    2015-04-01

    Ageing of materials and extreme events tend to damage structures, and ancient historical monuments are particularly vulnerable due to their age and long-term exposure to adverse events and influences. As an example, the wall paintings (frescoes) from the seventeenth century BCE found at the archaeological site of Akrotiri (Santorini, Greece) were recovered from volcanic ash in fragments with dimensions ranging from a few centimeters to a few decimeters. Identification of the fracturing patterns is helpful to the process of piecing together the fragments of frescos. Previous work has involved looking at fracturing patterns in frescos that have been reassembled. Recent work has looked at the process by which fractures develop. Current identification techniques involve experimental study of fracture development on plaster molds using a high-speed camera combined with sophisticated algorithms for pattern recognition. However, the use of a high-speed camera is challenging due to very demanding data processing and analysis and some inaccuracies in identification of fracture initialization generated by light conditions. This paper aims to evaluate whether or not short-gauge fiber optic sensors (FOS) based on Fiber Brag-Gratings (FBG), can be used to help identify the fracturing patterns of falling frescoes as a complement to high-speed cameras. In total four tests were performed using surface and embedded sensors on various plaster molds. The data taken by sensors installed on the surface of the mold were more complex to analyze and interpret than the data taken by embedded sensors, since the former reflected combined influence from fracture and bending. While their practicality is challenged by cost, moderately dense arrays of embedded FOS are found to be a plausible complement to the high speed-camera in the experiments.

  6. Emerging endoscopic techniques for the identification of esophageal disease.

    PubMed

    Triadafilopoulos, George; Akiyama, Junichi

    2016-05-01

    Esophageal diseases, both benign and malignant, impose an increasing burden to global health. In the West, gastroesophageal reflux disease (GERD) and Barrett's esophagus are increasing in prevalence and impact. In the East, squamous esophageal cancer remains a large burden, but increasingly, precancerous lesions related to GERD are recognized. We review the various advanced endoscopic techniques that have been developed to improve the accuracy of endoscopic identification of esophageal disease. These techniques are designed to increase the sensitivity of detecting disease and high-risk lesions, enable targeted biopsies, decrease total number of biopsies and costs for surveillance, but also guide therapy in real-time. After proper clinical validation, the widespread use of these technologies will lead to improved outcomes, mostly in cancer prevention. PMID:26753504

  7. Advanced Techniques for Power System Identification from Measured Data

    SciTech Connect

    Pierre, John W.; Wies, Richard; Trudnowski, Daniel

    2008-11-25

    Time-synchronized measurements provide rich information for estimating a power-system's electromechanical modal properties via advanced signal processing. This information is becoming critical for the improved operational reliability of interconnected grids. A given mode's properties are described by its frequency, damping, and shape. Modal frequencies and damping are useful indicators of power-system stress, usually declining with increased load or reduced grid capacity. Mode shape provides critical information for operational control actions. This project investigated many advanced techniques for power system identification from measured data focusing on mode frequency and damping ratio estimation. Investigators from the three universities coordinated their effort with Pacific Northwest National Laboratory (PNNL). Significant progress was made on developing appropriate techniques for system identification with confidence intervals and testing those techniques on field measured data and through simulation. Experimental data from the western area power system was provided by PNNL and Bonneville Power Administration (BPA) for both ambient conditions and for signal injection tests. Three large-scale tests were conducted for the western area in 2005 and 2006. Measured field PMU (Phasor Measurement Unit) data was provided to the three universities. A 19-machine simulation model was enhanced for testing the system identification algorithms. Extensive simulations were run with this model to test the performance of the algorithms. University of Wyoming researchers participated in four primary activities: (1) Block and adaptive processing techniques for mode estimation from ambient signals and probing signals, (2) confidence interval estimation, (3) probing signal design and injection method analysis, and (4) performance assessment and validation from simulated and field measured data. Subspace based methods have been use to improve previous results from block processing

  8. Identification of Reliable Sulcal Patterns of the Human Rolandic Region.

    PubMed

    Mellerio, Charles; Lapointe, Marie-Noël; Roca, Pauline; Charron, Sylvain; Legrand, Laurence; Meder, Jean-François; Oppenheim, Catherine; Cachia, Arnaud

    2016-01-01

    A major feature of the human cortex is its huge morphological variability. Although a comprehensive literature about the sulco-gyral pattern of the central region is available from post-mortem data, a reliable and reproducible characterization from in vivo data is still lacking. The aim of this study is to test the reliability of morphological criteria of the central region sulci used in post-mortem data, when applied to in vivo magnetic resonance imaging (MRI) data. Thirty right-handed healthy individuals were included in the study. Automated segmentation and three dimensional (3D) surface-based rendering were obtained from clinical 3D T1-weighted MRI. Two senior radiologists labeled the three sulci composing the central region (precentral [PreCS], central [CS] and postcentral [PostCS]) and analyzed their morphological variations using 47 standard criteria derived from Ono's atlas based on post-mortem data. For each criterion, inter-rater concordance and comparison with the occurrence frequency provided in Ono's atlas were estimated. Overall, the sulcal pattern criteria derived from MRI data were highly reproducible between the raters with a high mean inter-rater concordance in the three sulci (CS: κ = 0.92 in left hemisphere/κ = 0.91 in right hemisphere; PreCS: κ = 0.91/κ = 0.93; PostCS: κ = 0.84/0.79). Only a very limited number of sulcal criteria significantly differed between the in vivo and the post-mortem data (CS: 2 criteria in the left hemisphere/3 criteria in the right hemisphere; PreCS: 3 in the left and right hemispheres; PostCS: 3 in the left hemisphere and 5 in the right hemisphere). Our study provides a comprehensive description of qualitative sulcal patterns in the central region from in vivo clinical MRI with high agreement with previous post-mortem data. Such identification of reliable sulcal patterns of the central region visible with standard clinical MRI data paves the way for the detection of subtle variations of the central sulcation

  9. Identification of Reliable Sulcal Patterns of the Human Rolandic Region

    PubMed Central

    Mellerio, Charles; Lapointe, Marie-Noël; Roca, Pauline; Charron, Sylvain; Legrand, Laurence; Meder, Jean-François; Oppenheim, Catherine; Cachia, Arnaud

    2016-01-01

    A major feature of the human cortex is its huge morphological variability. Although a comprehensive literature about the sulco-gyral pattern of the central region is available from post-mortem data, a reliable and reproducible characterization from in vivo data is still lacking. The aim of this study is to test the reliability of morphological criteria of the central region sulci used in post-mortem data, when applied to in vivo magnetic resonance imaging (MRI) data. Thirty right-handed healthy individuals were included in the study. Automated segmentation and three dimensional (3D) surface-based rendering were obtained from clinical 3D T1-weighted MRI. Two senior radiologists labeled the three sulci composing the central region (precentral [PreCS], central [CS] and postcentral [PostCS]) and analyzed their morphological variations using 47 standard criteria derived from Ono’s atlas based on post-mortem data. For each criterion, inter-rater concordance and comparison with the occurrence frequency provided in Ono’s atlas were estimated. Overall, the sulcal pattern criteria derived from MRI data were highly reproducible between the raters with a high mean inter-rater concordance in the three sulci (CS: κ = 0.92 in left hemisphere/κ = 0.91 in right hemisphere; PreCS: κ = 0.91/κ = 0.93; PostCS: κ = 0.84/0.79). Only a very limited number of sulcal criteria significantly differed between the in vivo and the post-mortem data (CS: 2 criteria in the left hemisphere/3 criteria in the right hemisphere; PreCS: 3 in the left and right hemispheres; PostCS: 3 in the left hemisphere and 5 in the right hemisphere). Our study provides a comprehensive description of qualitative sulcal patterns in the central region from in vivo clinical MRI with high agreement with previous post-mortem data. Such identification of reliable sulcal patterns of the central region visible with standard clinical MRI data paves the way for the detection of subtle variations of the central sulcation

  10. FIP: A pattern recognition program for fuel spill identification. Final technical report, August 1993-August 1995

    SciTech Connect

    Faruque, A.; Lavine, B.K.; Mayfield, H.T.

    1996-05-01

    Gas Chromatography and pattern recognition methods (GC-PR) constitute a powerful tool for investigating complex environmental problems e.g., realistically analyze large chromatographic data sets and to seek meaningful relationships between chemical constitution and source variables. Recently, out laboratory has investigated the potential of GC-PR as a method for typing fields in order to directly relate a spill sample to its source. A graphic user interface (GUl) based interactive software called FIP (fuel identification program) has been developed. The development of this software system takes advantage of the high performance computational and visualization routines of the MATLAB programming environment. Both neural networks and statistical pattern recognition techniques are implemented. FIP employs covariance stabilization of the data to ensure correct classification of the gas chromatograms of weathered and unweathered jet fuels.

  11. 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.

  12. CD-measurement technique for hole patterns on stencil mask

    NASA Astrophysics Data System (ADS)

    Ishikawa, Mikio; Yusa, Satoshi; Takikawa, Tadahiko; Fujita, Hiroshi; Sano, Hisatake; Hoga, Morihisa; Hayashi, Naoya

    2004-12-01

    EB lithography has a potential to successfully form hole patterns as small as 80 nm with a stencil mask. In a previous paper we proposed a technique using a HOLON dual-mode critical dimension (CD) SEM ESPA-75S in the transmission mode for CD measurement of line-and-space patterns on a stencil mask. In this paper we extend our effort of developing a CD measurement technique to contact hole features and determine it in comparison of measured values between features on mask and those printed on wafer. We have evaluated the width method and the area methods using designed 80-500 nm wide contact hole patterns on a large area membrane mask and their resist images on wafer printed by a LEEPL3000. We find that 1) the width method and the area methods show an excellent mask-wafer correlation for holes over 110 nm, and 2) the area methods show a better mask-wafer correlation than the width method does for holes below 110 nm. We conclude that the area calculated from the transmission SEM image is more suitable in defining the hole dimensions than the width for contact holes on a stencil mask.

  13. 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.

  14. Pattern recognition techniques in microarray data analysis: a survey.

    PubMed

    Valafar, Faramarz

    2002-12-01

    Recent development of technologies (e.g., microarray technology) that are capable of producing massive amounts of genetic data has highlighted the need for new pattern recognition techniques that can mine and discover biologically meaningful knowledge in large data sets. Many researchers have begun an endeavor in this direction to devise such data-mining techniques. As such, there is a need for survey articles that periodically review and summarize the work that has been done in the area. This article presents one such survey. The first portion of the paper is meant to provide the basic biology (mostly for non-biologists) that is required in such a project. This part is only meant to be a starting point for those experts in the technical fields who wish to embark on this new area of bioinformatics. The second portion of the paper is a survey of various data-mining techniques that have been used in mining microarray data for biological knowledge and information (such as sequence information). This survey is not meant to be treated as complete in any form, since the area is currently one of the most active, and the body of research is very large. Furthermore, the applications of the techniques mentioned here are not meant to be taken as the most significant applications of the techniques, but simply as examples among many. PMID:12594081

  15. Behavioral pattern identification for structural health monitoring in complex systems

    NASA Astrophysics Data System (ADS)

    Gupta, Shalabh

    Estimation of structural damage and quantification of structural integrity are critical for safe and reliable operation of human-engineered complex systems, such as electromechanical, thermofluid, and petrochemical systems. Damage due to fatigue crack is one of the most commonly encountered sources of structural degradation in mechanical systems. Early detection of fatigue damage is essential because the resulting structural degradation could potentially cause catastrophic failures, leading to loss of expensive equipment and human life. Therefore, for reliable operation and enhanced availability, it is necessary to develop capabilities for prognosis and estimation of impending failures, such as the onset of wide-spread fatigue crack damage in mechanical structures. This dissertation presents information-based online sensing of fatigue damage using the analytical tools of symbolic time series analysis ( STSA). Anomaly detection using STSA is a pattern recognition method that has been recently developed based upon a fixed-structure, fixed-order Markov chain. The analysis procedure is built upon the principles of Symbolic Dynamics, Information Theory and Statistical Pattern Recognition. The dissertation demonstrates real-time fatigue damage monitoring based on time series data of ultrasonic signals. Statistical pattern changes are measured using STSA to monitor the evolution of fatigue damage. Real-time anomaly detection is presented as a solution to the forward (analysis) problem and the inverse (synthesis) problem. (1) the forward problem - The primary objective of the forward problem is identification of the statistical changes in the time series data of ultrasonic signals due to gradual evolution of fatigue damage. (2) the inverse problem - The objective of the inverse problem is to infer the anomalies from the observed time series data in real time based on the statistical information generated during the forward problem. A computer-controlled special

  16. Pattern recognition techniques and the measurement of solar magnetic fields

    NASA Astrophysics Data System (ADS)

    Lopez Ariste, Arturo; Rees, David E.; Socas-Navarro, Hector; Lites, Bruce W.

    2001-11-01

    Measuring vector magnetic fields in the solar atmosphere using the profiles of the Stokes parameters of polarized spectral lines split by the Zeeman effect is known as Stokes Inversion. This inverse problem is usually solved by least-squares fitting of the Stokes profiles. However least-squares inversion is too slow for the new generation of solar instruments (THEMIS, SOLIS, Solar-B, ...) which will produce an ever-growing flood of spectral data. The solar community urgently requires a new approach capable of handling this information explosion, preferably in real-time. We have successfully applied pattern recognition and machine learning techniques to tackle this problem. For example, we have developed PCA-inversion, a database search technique based on Principal Component Analysis of the Stokes profiles. Search is fast because it is carried out in low dimensional PCA feature space, rather than the high dimensional space of the spectral signals. Such a data compression approach has been widely used for search and retrieval in many areas of data mining. PCA-inversion is the basis of a new inversion code called FATIMA (Fast Analysis Technique for the Inversion of Magnetic Atmospheres). Tests on data from HAO's Advanced Stokes Polarimeter show that FATIMA isover two orders of magnitude faster than least squares inversion. Initial tests on an alternative code (DIANNE - Direct Inversion based on Artificial Neural NEtworks) show great promise of achieving real-time performance. In this paper we present the latest achievements of FATIMA and DIANNE, two powerful examples of how pattern recognition techniques can revolutionize data analysis in astronomy.

  17. Chemical Detection and Identification Techniques for Exobiology Flight Experiments

    NASA Technical Reports Server (NTRS)

    Kojiro, Daniel R.; Sheverev, Valery A.; Khromov, Nikolai A.

    2002-01-01

    Exobiology flight experiments require highly sensitive instrumentation for in situ analysis of the volatile chemical species that occur in the atmospheres and surfaces of various bodies within the solar system. The complex mixtures encountered place a heavy burden on the analytical Instrumentation to detect and identify all species present. The minimal resources available onboard for such missions mandate that the instruments provide maximum analytical capabilities with minimal requirements of volume, weight and consumables. Advances in technology may be achieved by increasing the amount of information acquired by a given technique with greater analytical capabilities and miniaturization of proven terrestrial technology. We describe here methods to develop analytical instruments for the detection and identification of a wide range of chemical species using Gas Chromatography. These efforts to expand the analytical capabilities of GC technology are focused on the development of detectors for the GC which provide sample identification independent of the GC retention time data. A novel new approach employs Penning Ionization Electron Spectroscopy (PIES).

  18. Classification of Camellia (Theaceae) Species Using Leaf Architecture Variations and Pattern Recognition Techniques

    PubMed Central

    Lee, Sean; Nitin, Mantri

    2012-01-01

    Leaf characters have been successfully utilized to classify Camellia (Theaceae) species; however, leaf characters combined with supervised pattern recognition techniques have not been previously explored. We present results of using leaf morphological and venation characters of 93 species from five sections of genus Camellia to assess the effectiveness of several supervised pattern recognition techniques for classifications and compare their accuracy. Clustering approach, Learning Vector Quantization neural network (LVQ-ANN), Dynamic Architecture for Artificial Neural Networks (DAN2), and C-support vector machines (SVM) are used to discriminate 93 species from five sections of genus Camellia (11 in sect. Furfuracea, 16 in sect. Paracamellia, 12 in sect. Tuberculata, 34 in sect. Camellia, and 20 in sect. Theopsis). DAN2 and SVM show excellent classification results for genus Camellia with DAN2's accuracy of 97.92% and 91.11% for training and testing data sets respectively. The RBF-SVM results of 97.92% and 97.78% for training and testing offer the best classification accuracy. A hierarchical dendrogram based on leaf architecture data has confirmed the morphological classification of the five sections as previously proposed. The overall results suggest that leaf architecture-based data analysis using supervised pattern recognition techniques, especially DAN2 and SVM discrimination methods, is excellent for identification of Camellia species. PMID:22235330

  19. Phenomena Identification and Ranking Technique (PIRT) Panel Meeting Summary Report

    SciTech Connect

    Mark Holbrook

    2007-07-01

    Phenomena Identification and Ranking Technique (PIRT) is a systematic way of gathering information from experts on a specific subject and ranking the importance of the information. NRC, in collaboration with DOE and the working group, conducted the PIRT exercises to identify safety-relevant phenomena for NGNP, and to assess and rank the importance and knowledge base for each phenomenon. The overall objective was to provide NRC with an expert assessment of the safety-relevant NGNP phenomena, and an overall assessment of R and D needs for NGNP licensing. The PIRT process was applied to five major topical areas relevant to NGNP safety and licensing: (1) thermofluids and accident analysis (including neutronics), (2) fission product transport, (3) high temperature materials, (4) graphite, and (5) process heat for hydrogen cogeneration.

  20. System identification and model reduction using modulating function techniques

    NASA Technical Reports Server (NTRS)

    Shen, Yan

    1993-01-01

    Weighted least squares (WLS) and adaptive weighted least squares (AWLS) algorithms are initiated for continuous-time system identification using Fourier type modulating function techniques. Two stochastic signal models are examined using the mean square properties of the stochastic calculus: an equation error signal model with white noise residuals, and a more realistic white measurement noise signal model. The covariance matrices in each model are shown to be banded and sparse, and a joint likelihood cost function is developed which links the real and imaginary parts of the modulated quantities. The superior performance of above algorithms is demonstrated by comparing them with the LS/MFT and popular predicting error method (PEM) through 200 Monte Carlo simulations. A model reduction problem is formulated with the AWLS/MFT algorithm, and comparisons are made via six examples with a variety of model reduction techniques, including the well-known balanced realization method. Here the AWLS/MFT algorithm manifests higher accuracy in almost all cases, and exhibits its unique flexibility and versatility. Armed with this model reduction, the AWLS/MFT algorithm is extended into MIMO transfer function system identification problems. The impact due to the discrepancy in bandwidths and gains among subsystem is explored through five examples. Finally, as a comprehensive application, the stability derivatives of the longitudinal and lateral dynamics of an F-18 aircraft are identified using physical flight data provided by NASA. A pole-constrained SIMO and MIMO AWLS/MFT algorithm is devised and analyzed. Monte Carlo simulations illustrate its high-noise rejecting properties. Utilizing the flight data, comparisons among different MFT algorithms are tabulated and the AWLS is found to be strongly favored in almost all facets.

  1. Whole-pattern fitting technique in serial femtosecond nanocrystallography

    PubMed Central

    Dilanian, Ruben A.; Williams, Sophie R.; Martin, Andrew V.; Streltsov, Victor A.; Quiney, Harry M.

    2016-01-01

    Serial femtosecond X-ray crystallography (SFX) has created new opportunities in the field of structural analysis of protein nanocrystals. The intensity and timescale characteristics of the X-ray free-electron laser sources used in SFX experiments necessitate the analysis of a large collection of individual crystals of variable shape and quality to ultimately solve a single, average crystal structure. Ensembles of crystals are commonly encountered in powder diffraction, but serial crystallography is different because each crystal is measured individually and can be oriented via indexing and merged into a three-dimensional data set, as is done for conventional crystallography data. In this way, serial femtosecond crystallography data lie in between conventional crystallography data and powder diffraction data, sharing features of both. The extremely small sizes of nanocrystals, as well as the possible imperfections of their crystallite structure, significantly affect the diffraction pattern and raise the question of how best to extract accurate structure-factor moduli from serial crystallography data. Here it is demonstrated that whole-pattern fitting techniques established for one-dimensional powder diffraction analysis can be feasibly extended to higher dimensions for the analysis of merged SFX diffraction data. It is shown that for very small crystals, whole-pattern fitting methods are more accurate than Monte Carlo integration methods that are currently used. PMID:27006776

  2. Rapid identification of chromosomal rearrangements by PRINS technique

    SciTech Connect

    Pellestor, F.; Giradet, A.; Andreo, B.

    1994-09-01

    Chromosomal rearrangements contribute significantly to human reproductive failure, malformation/mental retardation syndromes and carcinogenesis. The variety of structural rearrangements is almost infinite and an identification by conventional cytogenetics is often labor intensive and may remain doubtful. Recent advances in molecular cytogenetics have provided new tools for detecting chromosomal abnormalities. The fluorescence in situ hybridization (FISH) procedure is actually the most employed technique and has led to numerous clinical applications. However, techniques required to produce suitable probes are time consuming and not accessible to all cytogenetics laboratories. The PRimed In Situ labeling (PRINS) method provides an alternate way for in situ chromosome screening. In this procedure, the chromosomal detection is performed by in situ annealing of a specific primer and subsequent primer extension by a Taq DNA polymerase in the presence of labeled nucleotides. Application of PRINS in clinical diagnosis is still limited. We have developed a semi-automatic PRINS protocol and used it to identify the origin of several chromosomal abnormalities. We report here the results of studies of three structural rearrangements: a translocation t(21;21), a supernumerary ring marker chromosome 18 and a complex chromosome 13 mosaicism involving a 13;13 Robertsonian translocation and a ring chromosome 13.

  3. Frequency Analysis Techniques for Identification of Viral Genetic Data

    PubMed Central

    Trifonov, Vladimir; Rabadan, Raul

    2010-01-01

    Environmental metagenomic samples and samples obtained as an attempt to identify a pathogen associated with the emergence of a novel infectious disease are important sources of novel microorganisms. The low costs and high throughput of sequencing technologies are expected to allow for the genetic material in those samples to be sequenced and the genomes of the novel microorganisms to be identified by alignment to those in a database of known genomes. Yet, for various biological and technical reasons, such alignment might not always be possible. We investigate a frequency analysis technique which on one hand allows for the identification of genetic material without relying on alignment and on the other hand makes possible the discovery of nonoverlapping contigs from the same organism. The technique is based on obtaining signatures of the genetic data and defining a distance/similarity measure between signatures. More precisely, the signatures of the genetic data are the frequencies of k-mers occurring in them, with k being a natural number. We considered an entropy-based distance between signatures, similar to the Kullback-Leibler distance in information theory, and investigated its ability to categorize negative-sense single-stranded RNA (ssRNA) viral genetic data. Our conclusion is that in this viral context, the technique provides a viable way of discovering genetic relationships without relying on alignment. We envision that our approach will be applicable to other microbial genetic contexts, e.g., other types of viruses, and will be an important tool in the discovery of novel microorganisms. PMID:20824103

  4. Use of Semisupervised Clustering and Feature-Selection Techniques for Identification of Co-expressed Genes.

    PubMed

    Saha, Sriparna; Alok, Abhay Kumar; Ekbal, Asif

    2016-07-01

    Studying the patterns hidden in gene-expression data helps to understand the functionality of genes. In general, clustering techniques are widely used for the identification of natural partitionings from the gene expression data. In order to put constraints on dimensionality, feature selection is the key issue because not all features are important from clustering point of view. Moreover some limited amount of supervised information can help to fine tune the obtained clustering solution. In this paper, the problem of simultaneous feature selection and semisupervised clustering is formulated as a multiobjective optimization (MOO) task. A modern simulated annealing-based MOO technique namely AMOSA is utilized as the background optimization methodology. Here, features and cluster centers are represented in the form of a string and the assignment of genes to different clusters is done using a point symmetry-based distance. Six optimization criteria based on several internal and external cluster validity indices are utilized. In order to generate the supervised information, a popular clustering technique, Fuzzy C-mean, is utilized. Appropriate subset of features, proper number of clusters and the proper partitioning are determined using the search capability of AMOSA. The effectiveness of this proposed semisupervised clustering technique, Semi-FeaClustMOO, is demonstrated on five publicly available benchmark gene-expression datasets. Comparison results with the existing techniques for gene-expression data clustering again reveal the superiority of the proposed technique. Statistical and biological significance tests have also been carried out. PMID:26208367

  5. Novel Patterned Films by Free-Radical Polymerization Techniques

    NASA Astrophysics Data System (ADS)

    Ward, Jennifer H.; Peppas, Nicholas A.

    2000-03-01

    We have developed novel techniques for the preparation of micropatterned structures by the block copolymerization of thin layers using UV free-radical polymerizations. The process involves polymerizing the first layer in the presence of an iniferter (initiator-transfer agent-terminator) with a dithiocarbamate group to make a photosensitive polymer. Upon application of a second monomer layer on the first polymer layer and irradiation, a copolymer is formed between the two layers. Patterns are created on the films by applying a mask and selectively irradiating the surface. Applications of this type of material are in biomaterials and biosensors for the selective adhesion of cells and proteins. We have successfully polymerized poly(ethylene glycol) (PEG) onto a layer of poly(methyl methacrylate) (PMMA) in the presence of tetraethylthiuran disulfide. Cells will adhere to the exposed PMMA areas but not to the PEG surfaces. This work has been supported by National Science Foundation grant No. DGE-9972770.

  6. Novel organosilicone materials and patterning techniques for nanoimprint lithography

    NASA Astrophysics Data System (ADS)

    Pina, Carlos Alberto

    Nanoimprint Lithography (NIL) is a high-throughput patterning technique that allows the fabrication of nanostructures with great precision. It has been listed on the International Technology Roadmap for Semiconductors (ITRS) as a candidate technology for future generation Si chip manufacturing. In nanoimprint Lithography a resist material, e.g. a thermoplastic polymer, is placed in contact with a mold and then mechanically deformed under an applied load to transfer the nano-features on the mold surface into the resist. The success of NIL relies heavily in the capability of fabricating nanostructures on different types of materials. Thus, a key factor for NIL implementation in industrial settings is the development of advanced materials suitable as the nanoimprint resist. This dissertation focuses on the engineering of new polymer materials suitable as NIL resist. A variety of silicone-based polymer precursors were synthesized and formulated for NIL applications. High throughput and high yield nanopatterning was successfully achieved. Furthermore, additional capabilities of the developed materials were explored for a range of NIL applications such as their use as flexible, UV-transparent stamps and silicon compatible etching layers. Finally, new strategies were investigated to expand the NIL potentiality. High throughput, non-residual layer imprinting was achieved with the newly developed resist materials. In addition, several strategies were designed for the precise control of nanoscale size patterned structures with multifunctional resist systems by post-imprinting modification of the pattern size. These developments provide NIL with a new set of tools for a variety of additional important applications.

  7. COMPARISON OF SIMCA PATTERN RECOGNITION & LIBRARY SEARCH IDENTIFICATION OF HAZARDOUS COMPOUNDS FROM MASS SPECTRA

    EPA Science Inventory

    SIMCA pattern recognition methods have been applied to mass spectral data from a target list of hazardous chemicals. cheme has been proposed for classification and identification of five classes of compounds including aromatics, chlorocarbons, bromocarbons, hydrocarbons, and poly...

  8. COMPARISON OF SIMCA PATTERN RECOGNITION AND LIBRARY SEARCH IDENTIFICATION OF HAZARDOUS COMPOUNDS FROM MASS SPECTRA

    EPA Science Inventory

    SIMCA pattern recognition methods have been applied to mass spectral data from a target list of hazardous chemicals. cheme has been proposed for classification and identification of five classes of compounds including aromatics, chlorocarbons, bromocarbons, hydrocarbons, and poly...

  9. Molecular Formula Identification Using Isotope Pattern Analysis and Calculation of Fragmentation Trees

    PubMed Central

    Dührkop, Kai; Hufsky, Franziska; Böcker, Sebastian

    2014-01-01

    We present the results of a fully automated de novo approach for identification of molecular formulas in the CASMI 2013 contest. Only results for Category 1 (molecular formula identification) were submitted. Our approach combines isotope pattern analysis and fragmentation pattern analysis and is completely independent from any (spectral and structural) database. We correctly identified the molecular formula for ten out of twelve challenges, being the best automated method competing in this category. PMID:26819880

  10. New laser technique for the identification of molecular transitions.

    NASA Technical Reports Server (NTRS)

    Skribanowitz, N.; Kelly, M. J.; Feld, M. S.

    1972-01-01

    A laser technique is proposed which may be useful for the assignment of molecular spectra in the visible and infrared regions. The method is based on the resonant interaction of two monochromatic fields with a Doppler-broadened three-level system. Under the appropriate conditions the absorption line shape of one of the transitions shows a complex structure over a narrow section of the Doppler profile, and for sufficiently high laser power the line shape splits into a number of narrow peaks. Analysis of the resulting intensity pattern leads to unambiguous assignment of the angular momentum quantum numbers of the three levels involved. A simple set of rules is given to facilitate interpretation of spectra. The line shapes discussed are also relevant to monochromatic optical pumping of gases and unidirectional laser amplifiers.

  11. Design space exploration for early identification of yield limiting patterns

    NASA Astrophysics Data System (ADS)

    Li, Helen; Zou, Elain; Lee, Robben; Hong, Sid; Liu, Square; Wang, JinYan; Du, Chunshan; Zhang, Recco; Madkour, Kareem; Ali, Hussein; Hsu, Danny; Kabeel, Aliaa; ElManhawy, Wael; Kwan, Joe

    2016-03-01

    In order to resolve the causality dilemma of which comes first, accurate design rules or real designs, this paper presents a flow for exploration of the layout design space to early identify problematic patterns that will negatively affect the yield. A new random layout generating method called Layout Schema Generator (LSG) is reported in this paper, this method generates realistic design-like layouts without any design rule violation. Lithography simulation is then used on the generated layout to discover the potentially problematic patterns (hotspots). These hotspot patterns are further explored by randomly inducing feature and context variations to these identified hotspots through a flow called Hotspot variation Flow (HSV). Simulation is then performed on these expanded set of layout clips to further identify more problematic patterns. These patterns are then classified into design forbidden patterns that should be included in the design rule checker and legal patterns that need better handling in the RET recipes and processes.

  12. Damage identification techniques via modal curvature analysis: Overview and comparison

    NASA Astrophysics Data System (ADS)

    Dessi, Daniele; Camerlengo, Gabriele

    2015-02-01

    This paper aims to compare several damage identification methods based on the analysis of modal curvature and related quantities (natural frequencies and modal strain energy) by evaluating their performances on the same test case, a damaged Euler-Bernoulli beam. Damage is modelled as a localized and uniform reduction of stiffness so that closed-form expressions of the mode-shape curvatures can be analytically computed and data accuracy, which affects final results, can be controlled. The selected techniques belong to two categories: one includes several methods that need reference data for detecting structural modifications due to damage, the second group, including the modified Laplacian operator and the fractal dimension, avoids the knowledge of the undamaged behavior for issuing a damage diagnosis. To explain better the different performances of the methods, the mathematical formulation has been revised in some cases so as to fit into a common framework where the underlying hypotheses are clearly stated. Because the various damage indexes are calculated on 'exact' data, a sensitivity analysis has been carried out with respect to the number of points where curvature information is available, to the position of damage between adjacent points, to the modes involved in the index computation. In this way, this analysis intends to point out comparatively the capability of locating and estimating damage of each method along with some critical issues already present with noiseless data.

  13. Connecting Self-Esteem and Achievement: Diversity in Academic Identification and Dis-Identification Patterns among Black College Students

    ERIC Educational Resources Information Center

    Hope, Elan C.; Chavous, Tabbye M.; Jagers, Robert J.; Sellers, Robert M.

    2013-01-01

    Using a person-oriented approach, we explored patterns of self-esteem and achievement among 324 Black college students across the freshman college year and identified four academic identification profiles. Multivariate analyses revealed profile differences in academic and psychological outcomes at beginning and end of freshman year (academic…

  14. Applications of pattern recognition techniques to online fault detection

    SciTech Connect

    Singer, R.M.; Gross, K.C.; King, R.W.

    1993-11-01

    A common problem to operators of complex industrial systems is the early detection of incipient degradation of sensors and components in order to avoid unplanned outages, to orderly plan for anticipated maintenance activities and to assure continued safe operation. In such systems, there usually are a large number of sensors (upwards of several thousand is not uncommon) serving many functions, ranging from input to control systems, monitoring of safety parameters and component performance limits, system environmental conditions, etc. Although sensors deemed to measure important process conditions are generally alarmed, the alarm set points usually are just high-low limits and the operator`s response to such alarms is based on written procedures and his or her experience and training. In many systems this approach has been successful, but in situations where the cost of a forced outage is high an improved method is needed. In such cases it is desirable, if not necessary, to detect disturbances in either sensors or the process prior to any actual failure that could either shut down the process or challenge any safety system that is present. Recent advances in various artificial intelligence techniques have provided the opportunity to perform such functions of early detection and diagnosis. In this paper, the experience gained through the application of several pattern-recognition techniques to the on-line monitoring and incipient disturbance detection of several coolant pumps and numerous sensors at the Experimental Breeder Reactor-II (EBR-II) which is located at the Idaho National Engineering Laboratory is presented.

  15. System and technique for retrieving depth information about a surface by projecting a composite image of modulated light patterns

    NASA Technical Reports Server (NTRS)

    Hassebrook, Laurence G. (Inventor); Lau, Daniel L. (Inventor); Guan, Chun (Inventor)

    2008-01-01

    A technique, associated system and program code, for retrieving depth information about at least one surface of an object. Core features include: projecting a composite image comprising a plurality of modulated structured light patterns, at the object; capturing an image reflected from the surface; and recovering pattern information from the reflected image, for each of the modulated structured light patterns. Pattern information is preferably recovered for each modulated structured light pattern used to create the composite, by performing a demodulation of the reflected image. Reconstruction of the surface can be accomplished by using depth information from the recovered patterns to produce a depth map/mapping thereof. Each signal waveform used for the modulation of a respective structured light pattern, is distinct from each of the other signal waveforms used for the modulation of other structured light patterns of a composite image; these signal waveforms may be selected from suitable types in any combination of distinct signal waveforms, provided the waveforms used are uncorrelated with respect to each other. The depth map/mapping to be utilized in a host of applications, for example: displaying a 3-D view of the object; virtual reality user-interaction interface with a computerized device; face--or other animal feature or inanimate object--recognition and comparison techniques for security or identification purposes; and 3-D video teleconferencing/telecollaboration.

  16. System and technique for retrieving depth information about a surface by projecting a composite image of modulated light patterns

    NASA Technical Reports Server (NTRS)

    Hassebrook, Laurence G. (Inventor); Lau, Daniel L. (Inventor); Guan, Chun (Inventor)

    2010-01-01

    A technique, associated system and program code, for retrieving depth information about at least one surface of an object, such as an anatomical feature. Core features include: projecting a composite image comprising a plurality of modulated structured light patterns, at the anatomical feature; capturing an image reflected from the surface; and recovering pattern information from the reflected image, for each of the modulated structured light patterns. Pattern information is preferably recovered for each modulated structured light pattern used to create the composite, by performing a demodulation of the reflected image. Reconstruction of the surface can be accomplished by using depth information from the recovered patterns to produce a depth map/mapping thereof. Each signal waveform used for the modulation of a respective structured light pattern, is distinct from each of the other signal waveforms used for the modulation of other structured light patterns of a composite image; these signal waveforms may be selected from suitable types in any combination of distinct signal waveforms, provided the waveforms used are uncorrelated with respect to each other. The depth map/mapping to be utilized in a host of applications, for example: displaying a 3-D view of the object; virtual reality user-interaction interface with a computerized device; face--or other animal feature or inanimate object--recognition and comparison techniques for security or identification purposes; and 3-D video teleconferencing/telecollaboration.

  17. Identification of Polygonal Patterns on Venus Using Mathematical Morphology

    NASA Technical Reports Server (NTRS)

    Moreels, P.; Smrekar, S. E.

    2001-01-01

    We develop a detection and recognition model to fully automatize the identification of polygonal faults present in many of the Magellan SAR images. Our segmentation model is based on a modified watershed algorithm. Additional information is contained in the original extended abstract.

  18. An Autonomous Star Identification Algorithm Based on One-Dimensional Vector Pattern for Star Sensors.

    PubMed

    Luo, Liyan; Xu, Luping; Zhang, Hua

    2015-01-01

    In order to enhance the robustness and accelerate the recognition speed of star identification, an autonomous star identification algorithm for star sensors is proposed based on the one-dimensional vector pattern (one_DVP). In the proposed algorithm, the space geometry information of the observed stars is used to form the one-dimensional vector pattern of the observed star. The one-dimensional vector pattern of the same observed star remains unchanged when the stellar image rotates, so the problem of star identification is simplified as the comparison of the two feature vectors. The one-dimensional vector pattern is adopted to build the feature vector of the star pattern, which makes it possible to identify the observed stars robustly. The characteristics of the feature vector and the proposed search strategy for the matching pattern make it possible to achieve the recognition result as quickly as possible. The simulation results demonstrate that the proposed algorithm can effectively accelerate the star identification. Moreover, the recognition accuracy and robustness by the proposed algorithm are better than those by the pyramid algorithm, the modified grid algorithm, and the LPT algorithm. The theoretical analysis and experimental results show that the proposed algorithm outperforms the other three star identification algorithms. PMID:26198233

  19. An Autonomous Star Identification Algorithm Based on One-Dimensional Vector Pattern for Star Sensors

    PubMed Central

    Luo, Liyan; Xu, Luping; Zhang, Hua

    2015-01-01

    In order to enhance the robustness and accelerate the recognition speed of star identification, an autonomous star identification algorithm for star sensors is proposed based on the one-dimensional vector pattern (one_DVP). In the proposed algorithm, the space geometry information of the observed stars is used to form the one-dimensional vector pattern of the observed star. The one-dimensional vector pattern of the same observed star remains unchanged when the stellar image rotates, so the problem of star identification is simplified as the comparison of the two feature vectors. The one-dimensional vector pattern is adopted to build the feature vector of the star pattern, which makes it possible to identify the observed stars robustly. The characteristics of the feature vector and the proposed search strategy for the matching pattern make it possible to achieve the recognition result as quickly as possible. The simulation results demonstrate that the proposed algorithm can effectively accelerate the star identification. Moreover, the recognition accuracy and robustness by the proposed algorithm are better than those by the pyramid algorithm, the modified grid algorithm, and the LPT algorithm. The theoretical analysis and experimental results show that the proposed algorithm outperforms the other three star identification algorithms. PMID:26198233

  20. Recurrence Methods for the Identification of Morphogenetic Patterns

    PubMed Central

    Facchini, Angelo; Mocenni, Chiara

    2013-01-01

    This paper addresses the problem of identifying the parameters involved in the formation of spatial patterns in nonlinear two dimensional systems. To this aim, we perform numerical experiments on a prototypical model generating morphogenetic Turing patterns, by changing both the spatial frequency and shape of the patterns. The features of the patterns and their relationship with the model parameters are characterized by means of the Generalized Recurrence Quantification measures. We show that the recurrence measures Determinism and Recurrence Entropy, as well as the distribution of the line lengths, allow for a full characterization of the patterns in terms of power law decay with respect to the parameters involved in the determination of their spatial frequency and shape. A comparison with the standard two dimensional Fourier transform is performed and the results show a better performance of the recurrence indicators in identifying a reliable connection with the spatial frequency of the patterns. Finally, in order to evaluate the robustness of the estimation of the power low decay, extensive simulations have been performed by adding different levels of noise to the patterns. PMID:24066062

  1. Quantitative Identification and Analysis of Sub-Seismic Extensional Structure System: Technique Schemes and Processes

    NASA Astrophysics Data System (ADS)

    Ou, C.; Chen, W.

    2014-12-01

    Quantitative characterization of complex sub-seismic extensional structure system that essentially controls petroleum exploitation is difficult to implement in seismic profile interpretation. This research, based on a case study in block M of Myanmar, established a set of quantitative treatment schemes and technique processes for the identification of sub-seismic low-displacement (SSLD) extensional faults or fractures upon structural deformation restoration and geometric inversion. Firstly, the master-subsidiary inheritance relations and configuration characterization of the seismic-scale extensional fault systems are determined by analyzing the structural pattern. Besides, three-dimensional (3D) pattern and characteristics of the seismic-scale extensional structure have been illustrated by 3D structure model built upon seismic sections. Moreover, according to the dilatancy obtained from structural restoration on the basis of inclined shear method, as well as the fracture-flow index, potential SSLD extensional faults or fractures have been quantitatively identified. Application of the technique processes to the sub-seismic low-displacement extensional structures in block M in Myanmar is instructive to quantitatively interpret those SSLD extensional structure systems in practice. The work was supported by National Basic Research Program of China (2014CB239205) and the National Science and Technology Major Project of China (20011ZX05030-005-003).

  2. Quantitative identification and analysis of sub-seismic extensional structure system: technique schemes and processes

    NASA Astrophysics Data System (ADS)

    Chenghua, Ou; Chen, Wei; Ma, Zhonggao

    2015-06-01

    Quantitative characterization of complex sub-seismic extensional structure system that essentially controls petroleum exploitation is difficult to implement in seismic profile interpretation. This research, based on a case study in block M of Myanmar, established a set of quantitative treatment schemes and technique processes for the identification of sub-seismic low-displacement (SSLD) extensional faults or fractures upon structural deformation restoration and geometric inversion. Firstly, the master-subsidiary inheritance relations and configuration of the seismic-scale extensional fault systems are determined by analyzing the structural pattern. Besides, three-dimensional (3D) pattern and characteristics of the seismic-scale extensional structure have been illustrated by a 3D structure model built upon seismic sections. Moreover, according to the dilatancy obtained from structural restoration on the basis of inclined shear method, as well as the fracture-flow index, potential SSLD extensional faults or fractures have been quantitatively identified. Application of the technique processes to the sub-seismic low-displacement extensional structures in block M in Myanmar is instructive to quantitatively interpret those SSLD extensional structure systems in practice.

  3. An exploratory statistical approach to depression pattern identification

    NASA Astrophysics Data System (ADS)

    Feng, Qing Yi; Griffiths, Frances; Parsons, Nick; Gunn, Jane

    2013-02-01

    Depression is a complex phenomenon thought to be due to the interaction of biological, psychological and social factors. Currently depression assessment uses self-reported depressive symptoms but this is limited in the degree to which it can characterise the different expressions of depression emerging from the complex causal pathways that are thought to underlie depression. In this study, we aimed to represent the different patterns of depression with pattern values unique to each individual, where each value combines all the available information about an individual’s depression. We considered the depressed individual as a subsystem of an open complex system, proposed Generalized Information Entropy (GIE) to represent the general characteristics of information entropy of the system, and then implemented Maximum Entropy Estimates to derive equations for depression patterns. We also introduced a numerical simulation method to process the depression related data obtained by the Diamond Cohort Study which has been underway in Australia since 2005 involving 789 people. Unlike traditional assessment, we obtained a unique value for each depressed individual which gives an overall assessment of the depression pattern. Our work provides a novel way to visualise and quantitatively measure the depression pattern of the depressed individual which could be used for pattern categorisation. This may have potential for tailoring health interventions to depressed individuals to maximize health benefit.

  4. Identification of Vibrotactile Patterns Encoding Obstacle Distance Information.

    PubMed

    Kim, Yeongmi; Harders, Matthias; Gassert, Roger

    2015-01-01

    Delivering distance information of nearby obstacles from sensors embedded in a white cane-in addition to the intrinsic mechanical feedback from the cane-can aid the visually impaired in ambulating independently. Haptics is a common modality for conveying such information to cane users, typically in the form of vibrotactile signals. In this context, we investigated the effect of tactile rendering methods, tactile feedback configurations and directions of tactile flow on the identification of obstacle distance. Three tactile rendering methods with temporal variation only, spatio-temporal variation and spatial/temporal/intensity variation were investigated for two vibration feedback configurations. Results showed a significant interaction between tactile rendering method and feedback configuration. Spatio-temporal variation generally resulted in high correct identification rates for both feedback configurations. In the case of the four-finger vibration, tactile rendering with spatial/temporal/intensity variation also resulted in high distance identification rate. Further, participants expressed their preference for the four-finger vibration over the single-finger vibration in a survey. Both preferred rendering methods with spatio-temporal variation and spatial/temporal/intensity variation for the four-finger vibration could convey obstacle distance information with low workload. Overall, the presented findings provide valuable insights and guidance for the design of haptic displays for electronic travel aids for the visually impaired. PMID:25807569

  5. Development of a direct match technique for star identification on the SWAS mission

    NASA Technical Reports Server (NTRS)

    Daniel, Walter K.; Correll, Thomas E.; Anderson, Mark O.

    1995-01-01

    A direct match technique for star identification was developed for use with the star tracker on the SWAS (Submillimeter Wave Astronomy Satellite) spacecraft. In this technique, tracker searches are used in a two-step process for an implicit direct match star identification. A simulation of the star acquisition process was created and used in the preparation of guide star selection requirements. Flight software implementing this star acquisition technique has been developed and tested.

  6. Identification of Potential Fishing Grounds Using Geospatial Technique

    NASA Astrophysics Data System (ADS)

    Abdullah, Muhammad

    2016-07-01

    Fishery resources surveys using actual sampling and data collection methods require extensive ship time and sampling time. Informative data from satellite plays a vital role in fisheries application. Satellite Remote Sensing techniques can be used to detect fish aggregation just like visual fish identification ultimately these techniques can be used to predict the potential fishing zones by measuring the parameters which affect the distribution of fishes. Remote sensing is a time saving technique to locate fishery resources along the coast. Pakistan has a continental shelf area of 50,270 km2 and coastline length of 1,120 km. The total maritime zone of Pakistan is over 30 percent of the land area. Fishery plays an important role in the national economy. The marine fisheries sector is the main component, contributing about 57 percent in terms of production. Fishery is the most important economic activity in the villages and towns along the coast, and in most of the coastal villages and settlements it is the sole source of employment and income generation. Fishing by fishermen is done on the sole basis of repeated experiments and collection of information from other fishermen. Often they are in doubt about the location of potential fishing zones. This leads to waste of time and money, adversely affecting fishermen incomes and over or under-exploitation of fishing zones. The main purpose of this study was to map potential fishing grounds by identifying various environmental parameters which impact fish aggregation along the Pakistan coastline. The primary reason of this study is the fact that the fishing communities of Pakistan's coastal regions are extremely poor and lack knowledge of the modern tools and techniques that may be incorporated to enhance their yield and thus, improve their livelihood. Using geospatial techniques in order to accurately map the potential fishing zones based on sea surface temperature (SST) and chlorophyll -a content, in conjunction with

  7. Identification of Potential Fishing Grounds Using Geospatial Technique

    NASA Astrophysics Data System (ADS)

    Abdullah, Muhammad

    2016-07-01

    Fishery resources surveys using actual sampling and data collection methods require extensive ship time and sampling time. Informative data from satellite plays a vital role in fisheries application. Satellite Remote Sensing techniques can be used to detect fish aggregation just like visual fish identification ultimately these techniques can be used to predict the potential fishing zones by measuring the parameters which affect the distribution of fishes. Remote sensing is a time saving technique to locate fishery resources along the coast. Pakistan has a continental shelf area of 50,270 km2 and coastline length of 1,120 km. The total maritime zone of Pakistan is over 30 percent of the land area. Fishery plays an important role in the national economy. The marine fisheries sector is the main component, contributing about 57 percent in terms of production. Fishery is the most important economic activity in the villages and towns along the coast, and in most of the coastal villages and settlements it is the sole source of employment and income generation. Fishing by fishermen is done on the sole basis of repeated experiments and collection of information from other fishermen. Often they are in doubt about the location of potential fishing zones. This leads to waste of time and money, adversely affecting fishermen incomes and over or under-exploitation of fishing zones. The main purpose of this study was to map potential fishing grounds by identifying various environmental parameters which impact fish aggregation along the Pakistan coastline. The primary reason of this study is the fact that the fishing communities of Pakistan's coastal regions are extremely poor and lack knowledge of the modern tools and techniques that may be incorporated to enhance their yield and thus, improve their livelihood. Using geospatial techniques in order to accurately map the potential fishing zones based on sea surface temperature (SST) and chlorophyll -a content, in conjunction with

  8. Identification of seismically susceptible areas in western Himalaya using pattern recognition

    NASA Astrophysics Data System (ADS)

    Mridula; Sinvhal, Amita; Wason, Hans Raj

    2016-06-01

    Seismicity in the western Himalayas is highly variable. Several historical and instrumentally recorded devastating earthquakes originated in the western Himalayas which are part of the Alpine-Himalayan belt. Earthquakes cause tremendous loss of life and to the built environment. The amount of loss in terms of life and infrastructure has been rising continuously due to significant increase in population and infrastructure. This study is an attempt to identify seismically susceptible areas in western Himalaya, using pattern recognition technique. An area between latitude 29∘-36∘N and longitude 73∘-80∘E was considered for this study. Pattern recognition starts with identification, selection and extraction of features from seismotectonic data. These features are then subjected to discriminant analysis and the study area was classified into three categories, viz., Area A: most susceptible area, Area B: moderately susceptible area, and Area C: least susceptible area. Results show that almost the entire states of Himachal Pradesh and Uttarakhand and a portion of Jammu & Kashmir are classified as Area A, while most of Jammu & Kashmir is classified as Area B and the Indo-Gangetic plains are classified as Area C.

  9. Assessment of missile hazards: identification of reference fragmentation patterns.

    PubMed

    Gubinelli, Gianfilippo; Cozzani, Valerio

    2009-04-30

    Industrial accidents involving fragment projection were investigated. The analysis of fracture mechanics fundamentals allowed the exploration of the relations between the fracture characteristics and the final event leading to equipment collapse. Reference fragmentation patterns were defined on the basis of the geometrical characteristics of the categories of process vessels that are more frequently involved in fragmentation accidents. Primary scenarios leading to fragment projection were correlated to specific fragmentation patterns. A database reporting a detailed analysis of more than 140 vessel fragmentation events provided the data needed to support and validate the approach. The available data also allowed the calculation of the expected probability of fragment projection following vessel fragmentation, and the probability of the alternative fragmentation patterns with respect to the different accidental scenarios, based on the observed frequencies over the available data set. PMID:18752892

  10. Palatal Rugae Patterns as a Bioindicator for Forensic Identification in Kodava and Tibetan Populations of India

    PubMed Central

    Shetty, Deeksha Kiran; Mali, Sheetal; Divakar, Hegde Deepak; Amit, Patil; Dhairaysheel, Edake; Harsh, Unadkat

    2015-01-01

    Background: Palatal rugae are distinct to each individual and are highly specific to each individual as their fingerprints. Rugae pattern are specific to different racial groups making it convenient for population identification. Palatal rugae retain their shape throughout life and hence can be useful as an identification tool. The present study aimed at analyzing the differences in rugae pattern among Kodavas and Tibetan populations of Coorg, India and to examine if there was a difference in the rugae pattern between males and females within each group. Materials and Methods: The study comprised of 30 participants between 18 and 30 years of age, equally distributed between genders from each group. Examination of maxillary cast after tracing the rugae patterns was carried out. Rugae pattern was classified as “straight,” “wavy,” “curved,” “circular” and “unification.” Statistical analysis was done using SPSS 16 software. Non-parametric Mann–Whitney test was used for pairwise comparison of two populations. Mann–Whitney two-tailed test was used to test the difference between males and females. Results: Results showed that wavy pattern was highest for both the groups. Circular rugae were totally absent in both the groups. There was a significant difference between Kodavas (mean = 1.000) and Tibetans (mean = 0.13) for unification pattern (P = 0.001). Conclusion: Palatal rugae patterns can be used as a bioindicator for human identification. PMID:26668483

  11. Effect of Herbal Prescriptions in Accordance with Pattern Identification in Acute Cerebral Infarction Patients: Based on Fire-Heat Pattern

    PubMed Central

    Jung, WooSang; Park, JungMi; Moon, SangKwan; Hyun, Sangho

    2015-01-01

    Objectives. This study was conducted to verify the necessity of corresponding prescription to the diagnosed pattern in acute cerebral infarction patients. Methods. We studied cerebral infarction patients hospitalized within 30 days after the ictus. Forty-four clinical indicators, Motricity Index (MI) score, Scandinavian Stroke Scale (SSS) score, and herbal prescriptions were checked twice, two weeks apart. The probability of each pattern was calculated based on the clinical indicators. Changes in MI score, SSS score, and the probability of fire-heat pattern were compared between the pattern-prescription correspondence group and the noncorrespondence group. Results. Increments of MI score and SSS score in the correspondence group were significantly greater than those of the noncorrespondence group (p = 0.003, p = 0.001) while the baseline score of the two groups showed no significant difference. Probability of fire-heat pattern decreased significantly in the correspondence group (p = 0.013) while the noncorrespondence group showed no significant difference after the treatment. Conclusion. Acute cerebral infarction patients who are diagnosed as fire-heat pattern showed better improvement in dysfunctions caused by the disease when they took the pattern corresponding prescriptions. This study provides evidence for the necessity and usefulness of pattern identification in Traditional Korean Medicine. PMID:26523149

  12. Identification of statistical patterns in complex systems via symbolic time series analysis.

    PubMed

    Gupta, Shalabh; Khatkhate, Amol; Ray, Asok; Keller, Eric

    2006-10-01

    Identification of statistical patterns from observed time series of spatially distributed sensor data is critical for performance monitoring and decision making in human-engineered complex systems, such as electric power generation, petrochemical, and networked transportation. This paper presents an information-theoretic approach to identification of statistical patterns in such systems, where the main objective is to enhance structural integrity and operation reliability. The core concept of pattern identification is built upon the principles of Symbolic Dynamics, Automata Theory, and Information Theory. To this end, a symbolic time series analysis method has been formulated and experimentally validated on a special-purpose test apparatus that is designed for data acquisition and real-time analysis of fatigue damage in polycrystalline alloys. PMID:17063932

  13. Scleroderma capillary pattern identification using texture descriptors and ensemble classification.

    PubMed

    Schaefer, Gerald; Krawczyk, Bartosz; Doshi, Niraj P; Merla, Arcangelo

    2013-01-01

    Various connective tissue diseases lead to morphological alternations of blood capillaries. Consequently, observation of the capillaries at the finger nailfold - nailfold capillaroscopy (NC) - is a standard method for diagnosing diseases such as scleroderma or Raynaud's phenomenon. This is typically performed through manual inspection by an expert to lead to a determination of one of the established NC scleroderma patterns (early, active, and late). In this paper, we present an automated method of analysing nailfold capillaroscopy images and categorising them into NC patterns. For this purpose, we extract a carefully chosen set of texture features from the images and employ an ensemble classification approach to arrive at decisions for each captured finger which are then aggregated to form a diagnosis for the patient. Experimental results on a set of 60 NC images from 16 subjects demonstrate the accuracy and usefulness of our presented approach. PMID:24110975

  14. Yangon River Geomorphology Identification and its Enviromental Imapacts Analsysi by Optical and Radar Sensing Techniques

    NASA Astrophysics Data System (ADS)

    Lwin, A.; Khaing, M. M.

    2012-07-01

    The Yangon river, also known as the Rangoon river, is about 40 km long (25miles), and flows from southern Myanmar as an outlet of the Irrawaddy (Ayeyarwady) river into the Ayeyarwady delta. The Yangon river drains the Pegu Mountains; both the Yangon and the Pathein rivers enter the Ayeyarwady at the delta. Fluvial geomorphology is based primarily on rivers of manageable dimensions. The emphasis is on geomorphology, sedimentology of Yangon river and techniques for their identification and management. Present techniques such as remote sensing have made it easier to investigate and interpret in details analysis of river geomorphology. In this paper, attempt has been made the complicated issues of geomorphology, sedimentation patterns and management of river system and evolution studied. The analysis was carried out for the impact of land use/ land cover (LULC) changes on stream flow patterns. The hydrologic response to intense, flood producing rainfall events bears the signatures of the geomorphic structure of the channel network and of the characteristic slope lengths defining the drainage density of the basin. The interpretation of the hydrologic response as the travel time distribution of a water particle randomly injected in a distributed manner across the landscape inspired many geomorphic insights. In 2008, Cyclone Nargis was seriously damaged to mangrove area and its biodiversity system in and around of Yangon river terraces. A combination of digital image processing techniques was employed for enhancement and classification process. It is observed from the study that middle infra red band (0.77mm - 0.86mm) is highly suitable for mapping mangroves. Two major classes of mangroves, dense and open mangroves were delineated from the digital data.

  15. A damage identification technique based on embedded sensitivity analysis and optimization processes

    NASA Astrophysics Data System (ADS)

    Yang, Chulho; Adams, Douglas E.

    2014-07-01

    A vibration based structural damage identification method, using embedded sensitivity functions and optimization algorithms, is discussed in this work. The embedded sensitivity technique requires only measured or calculated frequency response functions to obtain the sensitivity of system responses to each component parameter. Therefore, this sensitivity analysis technique can be effectively used for the damage identification process. Optimization techniques are used to minimize the difference between the measured frequency response functions of the damaged structure and those calculated from the baseline system using embedded sensitivity functions. The amount of damage can be quantified directly in engineering units as changes in stiffness, damping, or mass. Various factors in the optimization process and structural dynamics are studied to enhance the performance and robustness of the damage identification process. This study shows that the proposed technique can improve the accuracy of damage identification with less than 2 percent error of estimation.

  16. 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.

  17. Playing tag with ANN: boosted top identification with pattern recognition

    NASA Astrophysics Data System (ADS)

    Almeida, Leandro G.; Backović, Mihailo; Cliche, Mathieu; Lee, Seung J.; Perelstein, Maxim

    2015-07-01

    Many searches for physics beyond the Standard Model at the Large Hadron Collider (LHC) rely on top tagging algorithms, which discriminate between boosted hadronic top quarks and the much more common jets initiated by light quarks and gluons. We note that the hadronic calorimeter (HCAL) effectively takes a "digital image" of each jet, with pixel intensities given by energy deposits in individual HCAL cells. Viewed in this way, top tagging becomes a canonical pattern recognition problem. With this motivation, we present a novel top tagging algorithm based on an Artificial Neural Network (ANN), one of the most popular approaches to pattern recognition. The ANN is trained on a large sample of boosted tops and light quark/gluon jets, and is then applied to independent test samples. The ANN tagger demonstrated excellent performance in a Monte Carlo study: for example, for jets with p T in the 1100-1200 GeV range, 60% top-tag efficiency can be achieved with a 4% mis-tag rate. We discuss the physical features of the jets identified by the ANN tagger as the most important for classification, as well as correlations between the ANN tagger and some of the familiar top-tagging observables and algorithms.

  18. Identification of spatiotemporal patterns of biophysical droughts in Iran

    NASA Astrophysics Data System (ADS)

    Kamali, Bahareh; Abbaspour, Karim; Yang, Hong

    2015-04-01

    This study aims to identify historical patterns of meteorological, hydrological, and agricultural (inclusively biophysical) droughts in Iran over the last forty years. Standardized precipitation index (SPI), standardized runoff index (SRI), and soil moisture deficit index (SMDI) were used to represent the three types of droughts, respectively. Variables required for calculating the indices were obtained from a SWAT (Soil and Water Assessment Tool) model constructed for the country. The model was calibrated based on monthly runoff using the Sequential Uncertainty Fitting (SUFI-2) algorithm in SWAT-CUP. The indices were compared across temporal and spatial dimensions. Drought characteristics including number of events, start, end, duration and severity were derived to identify areas most prone to drought events. The results on provincial level show a variety of spatiotemporal patterns in different drought aspects over the country. The summary of analysis ranked drought events based on short-term severe droughts to multi-year duration events. Our analyses on three types of droughts provide a basis for further studies concerning drought impacts under future climate change and water resource management strategies in semi-arid areas.

  19. 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.

  20. Identification of Error Patterns in Terminal-Area ATC Communications

    NASA Technical Reports Server (NTRS)

    Quinn, Cheryl; Walter, Kim E.; Rosekind, Mark R. (Technical Monitor)

    1997-01-01

    Advancing air traffic management technologies have enabled a greater number of aircraft to use the same airspace more effectively. As aircraft separations are reduced and final approaches are more finely timed, there is less room for error. The present study examined 122 terminal-area, loss-of-separation and procedure violation incidents reported to the Aviation Safety Reporting System (ASRS) by air traffic controllers. Narrative description codes were used for the incidents for type of violation, contributing factors, recovery strategies, and consequences. Usually multiple errors occurred prior to the violation. Error sequences were analyzed and common patterns of errors were identified. In half of the incidents, errors were noticed in time to correct mistakes. Of these, almost 43% committed additional errors during the recovery attempt. This analysis shows that redundancies in the present air traffic control system may not be sufficient to support large increases in traffic density. Error prevention and design considerations for air traffic management systems are discussed.

  1. The Identification of Specific Methylation Patterns across Different Cancers

    PubMed Central

    Li, Jie; Liu, Hongbo; Wang, Fang; Wei, Yanjun; Su, Jianzhong; Zhang, Dongwei; Liu, Tiefu; Zhang, Yan

    2015-01-01

    Abnormal DNA methylation is known as playing an important role in the tumorgenesis. It is helpful for distinguishing the specificity of diagnosis and therapeutic targets for cancers based on characteristics of DNA methylation patterns across cancers. High throughput DNA methylation analysis provides the possibility to comprehensively filter the epigenetics diversity across various cancers. We integrated whole-genome methylation data detected in 798 samples from seven cancers. The hierarchical clustering revealed the existence of cancer-specific methylation pattern. Then we identified 331 differentially methylated genes across these cancers, most of which (266) were specifically differential methylation in unique cancer. A DNA methylation correlation network (DMCN) was built based on the methylation correlation between these genes. It was shown the hubs in the DMCN were inclined to cancer-specific genes in seven cancers. Further survival analysis using the part of genes in the DMCN revealed high-risk group and low-risk group were distinguished by seven biomarkers (PCDHB15, WBSCR17, IGF1, GYPC, CYGB, ACTG2, and PRRT1) in breast cancer and eight biomarkers (ZBTB32, OR51B4, CCL8, TMEFF2, SALL3, GPSM1, MAGEA8, and SALL1) in colon cancer, respectively. At last, a protein-protein interaction network was introduced to verify the biological function of differentially methylated genes. It was shown that MAP3K14, PTN, ACVR1 and HCK sharing different DNA methylation and gene expression across cancers were relatively high degree distribution in PPI network. The study suggested that not only the identified cancer-specific genes provided reference for individual treatment but also the relationship across cancers could be explained by differential DNA methylation. PMID:25774687

  2. The diagnostic criteria of blood-stasis syndrome: considerations for standardization of pattern identification.

    PubMed

    Li, Si-ming; Xu, Hao; Chen, Ke-ji

    2014-07-01

    Pattern identification (PI), also called Bian Zheng ([symbols; see text]), syndrome differentiation, pattern diagnosis, or pattern classification, is the basic principle and the key concept of Chinese medicine (CM). The core of PI is CM syndrome, on which CM theory, therapeutic method, prescribing formula and the use of Chinese herbal medicine are basically based. PI, in fact, is another classification method anticipated to improve the clinical efficacy. How to make an exact PI seems to be very important for taking full advantage of PI in clinical practice. Therefore, the establishment of diagnostic criterion of pattern has been the prerequisite for the standardization of PI. In recent years, a lot of diagnostic criteria of different CM patterns have been formulated. Taking the diagnostic criteria for blood-stasis syndrome as a model, the methodologies and considerations in establishing a pattern diagnostic criterion were discussed in this paper, which might be of great reference value in future PI standardization research. PMID:24610412

  3. The NLP Swish Pattern: An Innovative Visualizing Technique.

    ERIC Educational Resources Information Center

    Masters, Betsy J.; And Others

    1991-01-01

    Describes swish pattern, one of many innovative therapeutic interventions that developers of neurolinguistic programing (NLP) have contributed to counseling profession. Presents brief overview of NLP followed by an explanation of the basic theory and expected outcomes of the swish. Presents description of the intervention process and case studies…

  4. Development of Instrumental Techniques for Color Assessment of Camouflage Patterns

    ERIC Educational Resources Information Center

    Fang, Gang

    2012-01-01

    Camouflage fabrics are produced on a large scale for use in the US military and other applications. One of the highest volume camouflage fabrics is known as the Universal Camouflage Pattern (UCP) which is produced for the US Department of Defense. At present, no standard measurement-based color quality control method exists for camouflage…

  5. Nurses' Behaviors and Visual Scanning Patterns May Reduce Patient Identification Errors

    ERIC Educational Resources Information Center

    Marquard, Jenna L.; Henneman, Philip L.; He, Ze; Jo, Junghee; Fisher, Donald L.; Henneman, Elizabeth A.

    2011-01-01

    Patient identification (ID) errors occurring during the medication administration process can be fatal. The aim of this study is to determine whether differences in nurses' behaviors and visual scanning patterns during the medication administration process influence their capacities to identify patient ID errors. Nurse participants (n = 20)…

  6. ArcAtlas in the Classroom: Pattern Identification, Description, and Explanation

    ERIC Educational Resources Information Center

    DeMers, Michael N.; Vincent, Jeffrey S.

    2007-01-01

    The use of geographic information systems (GIS) in the classroom provides a robust and effective method of teaching the primary spatial skills of identification, description, and explanation of spatial pattern. A major handicap for the development of GIS-based learning experiences, especially for non-GIS specialist educators, is the availability…

  7. SPARCoC: A New Framework for Molecular Pattern Discovery and Cancer Gene Identification

    PubMed Central

    Ma, Shiqian; Johnson, Daniel; Ashby, Cody; Xiong, Donghai; Cramer, Carole L.; Moore, Jason H.; Zhang, Shuzhong; Huang, Xiuzhen

    2015-01-01

    It is challenging to cluster cancer patients of a certain histopathological type into molecular subtypes of clinical importance and identify gene signatures directly relevant to the subtypes. Current clustering approaches have inherent limitations, which prevent them from gauging the subtle heterogeneity of the molecular subtypes. In this paper we present a new framework: SPARCoC (Sparse-CoClust), which is based on a novel Common-background and Sparse-foreground Decomposition (CSD) model and the Maximum Block Improvement (MBI) co-clustering technique. SPARCoC has clear advantages compared with widely-used alternative approaches: hierarchical clustering (Hclust) and nonnegative matrix factorization (NMF). We apply SPARCoC to the study of lung adenocarcinoma (ADCA), an extremely heterogeneous histological type, and a significant challenge for molecular subtyping. For testing and verification, we use high quality gene expression profiling data of lung ADCA patients, and identify prognostic gene signatures which could cluster patients into subgroups that are significantly different in their overall survival (with p-values < 0.05). Our results are only based on gene expression profiling data analysis, without incorporating any other feature selection or clinical information; we are able to replicate our findings with completely independent datasets. SPARCoC is broadly applicable to large-scale genomic data to empower pattern discovery and cancer gene identification. PMID:25768286

  8. 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. PMID:25965304

  9. Identification of Fissionable Materials Using the Tagged Neutron Technique

    SciTech Connect

    R.P. Keegan, J.P. Hurley, J.R. Tinsley, R. Trainham

    2009-06-30

    This summary describes experiments to detect and identify fissionable materials using the tagged neutron technique. The objective of this work is to enhance homeland security capability to find fissionable material that may be smuggled inside shipping boxes, containers, or vehicles. The technique distinguishes depleted uranium from lead, steel, and tungsten. Future work involves optimizing the technique to increase the count rate by many orders of magnitude and to build in the additional capability to image hidden fissionable materials. The tagged neutron approach is very different to other techniques based on neutron die-away or photo-fission. This work builds on the development of the Associated Particle Imaging (API) technique at the Special Technologies Laboratory (STL) [1]. Similar investigations have been performed by teams at the Oak Ridge National Laboratory (ORNL), the Khlopin Radium Institute in Russia, and by the EURITRACK collaboration in the European Union [2,3,4].

  10. Identification Of Natural Dyes On Archaeological Textile Objects Using Laser Induced Fluorescent Technique

    SciTech Connect

    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 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.

  11. 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.

  12. Failed fuel identification techniques for liquid-metal cooled reactors

    SciTech Connect

    Lambert, J.D.B.; Gross, K.C.; Mikaili, R.; Frank, S.M.; Cutforth, D.C.; Angelo, P.L.

    1995-06-01

    The Experimental Breeder Reactor II (EBR-II), located in Idaho and operated for the US Department of Energy by Argonne National Laboratory, has been used as an irradiation testbed for LMR fuels and components for thirty years. During this time many endurance tests have been carried out with experimental LMR metal, oxide, carbide and nitride fuel elements, in which cladding failures were intentionally allowed to occur. This paper describes methods that have been developed for the detection, identification and verification of fuel failures.

  13. Identification of cancer protein biomarkers using proteomic techniques

    SciTech Connect

    Mor, Gil G; Ward, David C; Bray-Ward, Patricia

    2015-03-10

    The claimed invention describes methods to diagnose or aid in the diagnosis of cancer. The claimed methods are based on the identification of biomarkers which are particularly well suited to discriminate between cancer subjects and healthy subjects. These biomarkers were identified using a unique and novel screening method described herein. The biomarkers identified herein can also be used in the prognosis and monitoring of cancer. The invention comprises the use of leptin, prolactin, OPN and IGF-II for diagnosing, prognosis and monitoring of ovarian cancer.

  14. Identification of cancer protein biomarkers using proteomic techniques

    DOEpatents

    Mor, Gil G.; Ward, David C.; Bray-Ward, Patricia

    2010-02-23

    The claimed invention describes methods to diagnose or aid in the diagnosis of cancer. The claimed methods are based on the identification of biomarkers which are particularly well suited to discriminate between cancer subjects and healthy subjects. These biomarkers were identified using a unique and novel screening method described herein. The biomarkers identified herein can also be used in the prognosis and monitoring of cancer. The invention comprises the use of leptin, prolactin, OPN and IGF-II for diagnosing, prognosis and monitoring of ovarian cancer.

  15. Identification of critical circulation patterns in head catchments

    NASA Astrophysics Data System (ADS)

    Alam, M. M.; Bárdossy, A.

    2009-04-01

    Owing to the global changing climate and increase in mean earth surface temperature, variations in local scale weather are commonly observed. The variations in weather are more important when they are considered with respect to extreme weather conditions as slight changes in them may incur high costs and/or affect human life. Close relationship between atmospheric circulation and meteorological variables has been established thus surface weather variables such as temperature and precipitation on a certain day can be directly linked to prevailing atmospheric circulation. This study identifies and investigates critical circulation patterns (CP's) responsible for the historical floods in the four head catchments in southern Germany. Given the small size of catchments under study, CP's are classified with respect to daily discharge differences on 1 day lag instead of daily precipitation. This way the quick reaction time of the catchment could be captured in the CP definition. Daily Mean sea level pressure has been used as large scale predictor. Identified CP's are investigated for extreme wet and dry precipitation indices such as maximum number of days exceeding certain thresholds, maximum number of consecutive wet and dry days, greatest 3 and 5 day precipitation amounts, mean wet-day persistence and different percentiles of precipitation.

  16. Single-Round Patterned DNA Library Microarray Aptamer Lead Identification

    PubMed Central

    Martin, Jennifer A.; Mirau, Peter A.; Chushak, Yaroslav; Chávez, Jorge L.; Naik, Rajesh R.; Hagen, Joshua A.; Kelley-Loughnane, Nancy

    2015-01-01

    A method for identifying an aptamer in a single round was developed using custom DNA microarrays containing computationally derived patterned libraries incorporating no information on the sequences of previously reported thrombin binding aptamers. The DNA library was specifically designed to increase the probability of binding by enhancing structural complexity in a sequence-space confined environment, much like generating lead compounds in a combinatorial drug screening library. The sequence demonstrating the highest fluorescence intensity upon target addition was confirmed to bind the target molecule thrombin with specificity by surface plasmon resonance, and a novel imino proton NMR/2D NOESY combination was used to screen the structure for G-quartet formation. We propose that the lack of G-quartet structure in microarray-derived aptamers may highlight differences in binding mechanisms between surface-immobilized and solution based strategies. This proof-of-principle study highlights the use of a computational driven methodology to create a DNA library rather than a SELEX based approach. This work is beneficial to the biosensor field where aptamers selected by solution based evolution have proven challenging to retain binding function when immobilized on a surface. PMID:26075138

  17. [Spatial distribution pattern of Pontania dolichura larvae and sampling technique].

    PubMed

    Zhang, Feng; Chen, Zhijie; Zhang, Shulian; Zhao, Huiyan

    2006-03-01

    In this paper, the spatial distribution pattern of Pontania dolichura larvae was analyzed with Taylor's power law, Iwao's distribution function, and six aggregation indexes. The results showed that the spatial distribution pattern of P. dolichura larvae was of aggregated, and the basic component of the distribution was individual colony, with the aggregation intensity increased with density. On branches, the aggregation was caused by the adult behavior of laying eggs and the spatial position of leaves, while on leaves, the aggregation was caused by the spatial position of news leaves in spring when m < 2.37, and by the spatial position of news leaves in spring and the behavior of eclosion and laying eggs when m > 2.37. By using the parameters alpha and beta in Iwao's m * -m regression equation, the optimal and sequential sampling numbers were determined. PMID:16724746

  18. Immobilization, stabilization and patterning techniques for enzyme based sensor systems.

    SciTech Connect

    Flounders, A.W.; Carichner, S.C.; Singh, A.K.; Volponi, J.V.; Schoeniger, J.S.; Wally, K.

    1997-01-01

    Sandia National Laboratories has recently opened the Chemical and Radiation Detection Laboratory (CRDL) in Livermore CA to address the detection needs of a variety of government agencies (e.g., Department of Energy, Environmental Protection Agency, Department of Agriculture) as well as provide a fertile environment for the cooperative development of new industrial technologies. This laboratory consolidates a variety of existing chemical and radiation detection efforts and enables Sandia to expand into the novel area of biochemically based sensors. One aspect of this biosensor effort is further development and optimization of enzyme modified field effect transistors (EnFETs). Recent work has focused upon covalent attachment of enzymes to silicon dioxide and silicon nitride surfaces for EnFET fabrication. They are also investigating methods to pattern immobilized proteins; a critical component for development of array-based sensor systems. Novel enzyme stabilization procedures are key to patterning immobilized enzyme layers while maintaining enzyme activity. Results related to maximized enzyme loading, optimized enzyme activity and fluorescent imaging of patterned surfaces will be presented.

  19. Identification of Data Structures and Relationships by Matrix Reordering Techniques.

    ERIC Educational Resources Information Center

    McCormick, William T., Jr.; And Others

    Presented are the results of a study conducted to develop algorithms for ordering and organizing data that can be presented in a two-dimensional matrix form. The purpose of the work was to develop methods to extract latent data patterns, grouping, and structural relationships which are not apparent from the raw matrix data. The algorithms…

  20. A new computer-assisted technique to aid personal identification.

    PubMed

    De Angelis, Danilo; Sala, Remo; Cantatore, Angela; Grandi, Marco; Cattaneo, Cristina

    2009-07-01

    The paper describes a procedure aimed at identification from two-dimensional (2D) images (video-surveillance tapes, for example) by comparison with a three-dimensional (3D) facial model of a suspect. The application is intended to provide a tool which can help in analyzing compatibility or incompatibility between a criminal and a suspect's facial traits. The authors apply the concept of "geometrically compatible images". The idea is to use a scanner to reconstruct a 3D facial model of a suspect and to compare it to a frame extracted from the video-surveillance sequence which shows the face of the perpetrator. Repositioning and reorientation of the 3D model according to subject's face framed in the crime scene photo are manually accomplished, after automatic resizing. Repositioning and reorientation are performed in correspondence of anthropometric landmarks, distinctive for that person and detected both on the 2D face and on the 3D model. In this way, the superimposition between the original two-dimensional facial image and the three-dimensional one is obtained and a judgment is formulated by an expert on the basis of the fit between the anatomical facial districts of the two subjects. The procedure reduces the influence of face orientation and may be a useful tool in identification. PMID:19082838

  1. Comparison of two numerical techniques for aerodynamic model identification

    NASA Technical Reports Server (NTRS)

    Verhaegen, M. H.

    1987-01-01

    An algorithm, called the Minimal Residual QR algorithm, is presented to solve subset regression problems. It is shown that this scheme can be used as a numerically reliable implementation of the stepwise regression technique, which is widely used to identify an aerodynamic model from flight test data. This capability as well as the numerical superiority of this scheme over the stepwise regression technique is demonstrated in an experimental simulation study.

  2. Coordinated Parameter Identification Technique for the Inertial Parameters of Non-Cooperative Target

    PubMed Central

    Ning, Xin; Zhang, Teng; Wu, Yaofa; Zhang, Pihui; Zhang, Jiawei; Li, Shuai; Yue, Xiaokui; Yuan, Jianping

    2016-01-01

    Space operations will be the main space missions in the future. This paper focuses on the precise operations for non-cooperative target, and researches of coordinated parameter identification (CPI) which allows the motion of multi-joints. The contents of this paper are organized: (1) Summarize the inertial parameters identification techniques which have been conducted now, and the technique based on momentum conservation is selected for reliability and realizability; (2) Elaborate the basic principles and primary algorithm of coordinated parameter identification, and analyze some special problems in calculation (3) Numerical simulation of coordinated identification technique by an case study on non-cooperative target of spacecraft mounting dual-arm with six joints is done. The results show that the coordinated parameter identification technique could get all the inertial parameters of the target in 3D by one-time identification, and does not need special configuration or driven joints, moreover the results are highly precise and save much more time than traditional ones. PMID:27116187

  3. Identification of Dominant Excitation Patterns and Sources of Atrial Fibrillation by Causality Analysis.

    PubMed

    Rodrigo, Miguel; Climent, Andreu M; Liberos, Alejandro; Calvo, David; Fernández-Avilés, Francisco; Berenfeld, Omer; Atienza, Felipe; Guillem, Maria S

    2016-08-01

    Burden of atrial fibrillation (AF) can be reduced by ablation of sources of electrical impulses driving AF but driver identification is still challenging. This study presents a new methodology based on causality analysis that allows identifying the hierarchically dominant areas driving AF. Identification of dominant propagation patterns was achieved by computing causal relations between intracardiac multi-electrode catheter recordings of four paroxysmal AF patients during sinus rhythm, pacing and AF. In addition, realistic mathematical models of the atria during AF were used to validate the methodology both in the presence and absence of dominant frequency (DF) gradients. During electrical pacing, sources of propagation patterns detected by causality analysis were consistent with the location of the stimulating catheter. During AF, propagation patterns presented temporal variability, but a dominant direction accounted for significantly more propagations than other directions (49 ± 15% vs. 14 ± 13% or less, p < 0.01). Both in patients with a DF gradient and in mathematical models, causal maps allowed the identification of sites responsible for maintenance of AF. Causal maps allowed the identification of atrial dominant sites. In particular, causality analysis resulted in stable dominant cause-effect propagation directions during AF and could serve as a guide for performing ablation procedures in AF patients. PMID:26850022

  4. New techniques for clay mineral identification by remote sensing

    SciTech Connect

    Abrams, M.J.; Goetz, A.F.H.; Lang, H.

    1983-03-01

    In the past three years there have been major advancements in our ability to identify clay minerals by remote sensing. Multispectral scanners, including NASA's Thematic Mapper Simulator (analog for Landsat-D Thematic Mapper) have had several broad-band channels in the wavelength region of 1.0 to 2.5 ..mu..m. In particular, the wavelength region 2.0 to 2.5 ..mu..m contains diagnostic spectral-absorption features for most layered silicates. Computer processing of image data obtained with these scanners has allowed the identification of the presence of clay minerals, without, however, being able to identify specific mineralogies. Studies of areas with known hydrocarbon deposits and porphyry copper deposits have demonstrated the value of this information for rock-type discrimination and recognition of hydrothermal alteration zones. Non-imaging, narrow-band radiometers and spectrometers have been used in the field, from aircraft, and from space to identify individual mineralogical constituents. This can be done because of diagnostic spectral absorption features in the 2.0 to 2.5 ..mu..m region characteristic of different clay types. Preliminary analysis of SMIRR data over Egypt showed that kaolinite, carbonate rocks, and possibly montmorillonite, could be identified directly. Plans are currently under way for development of narrow-band imaging systems which will be capable of producing maps showing the surface distribution of individual clay types. This will represent a major step in remote sensing, by allowing unique identification of minerals rather than the current ability only to discriminate among materials. Applications of this technology will provide geologists with a powerful new tool for resource exploration and general geologic mapping problems.

  5. IDENTIFICATION OF SOURCES OF GROUNDWATER SALINIZATION USING GEOCHEMICAL TECHNIQUES

    EPA Science Inventory

    This report deals with salt-water sources that commonly mix and deteriorate fresh ground water. t reviews characteristics of salt-water sources and geochemical techniques that can be used to identify these sources after mixing has occurred. The report is designed to assist invest...

  6. Comparison of Three Statistical Classification Techniques for Maser Identification

    NASA Astrophysics Data System (ADS)

    Manning, Ellen M.; Holland, Barbara R.; Ellingsen, Simon P.; Breen, Shari L.; Chen, Xi; Humphries, Melissa

    2016-04-01

    We applied three statistical classification techniques-linear discriminant analysis (LDA), logistic regression, and random forests-to three astronomical datasets associated with searches for interstellar masers. We compared the performance of these methods in identifying whether specific mid-infrared or millimetre continuum sources are likely to have associated interstellar masers. We also discuss the interpretability of the results of each classification technique. Non-parametric methods have the potential to make accurate predictions when there are complex relationships between critical parameters. We found that for the small datasets the parametric methods logistic regression and LDA performed best, for the largest dataset the non-parametric method of random forests performed with comparable accuracy to parametric techniques, rather than any significant improvement. This suggests that at least for the specific examples investigated here accuracy of the predictions obtained is not being limited by the use of parametric models. We also found that for LDA, transformation of the data to match a normal distribution led to a significant improvement in accuracy. The different classification techniques had significant overlap in their predictions; further astronomical observations will enable the accuracy of these predictions to be tested.

  7. Symbolic document image compression based on pattern matching techniques

    NASA Astrophysics Data System (ADS)

    Shiah, Chwan-Yi; Yen, Yun-Sheng

    2011-10-01

    In this paper, a novel compression algorithm for Chinese document images is proposed. Initially, documents are segmented into readable components such as characters and punctuation marks. Similar patterns within the text are found by shape context matching and grouped to form a set of prototype symbols. Text redundancies can be removed by replacing repeated symbols by their corresponding prototype symbols. To keep the compression visually lossless, we use a multi-stage symbol clustering procedure to group similar symbols and to ensure that there is no visible error in the decompressed image. In the encoding phase, the resulting data streams are encoded by adaptive arithmetic coding. Our results show that the average compression ratio is better than the international standard JBIG2 and the compressed form of a document image is suitable for a content-based keyword searching operation.

  8. A novel system identification technique for improved wearable hemodynamics assessment.

    PubMed

    Wiens, Andrew D; Inan, Omer T

    2015-05-01

    Recent advances have led to renewed interest in ballistocardiography (BCG), a noninvasive measure of the small movements of the body due to cardiovascular events. A broad range of platforms have been developed and verified for BCG measurement including beds, chairs, and weighing scales: while the body is coupled to such a platform, the cardiogenic movements are measured. Wearable BCG, measured with an accelerometer affixed to the body, may enable continuous, or more regular, monitoring during the day; however, the signals from such wearable BCGs represent local or distal accelerations of skin and tissue rather than the whole body. In this paper, we propose a novel method to reconstruct the BCG measured with a weighing scale (WS BCG) from a wearable sensor via a training step to remove these local effects. Preliminary validation of this method was performed with 15 subjects: the wearable sensor was placed at three locations on the surface of the body while WS BCG measurements were recorded simultaneously. A regularized system identification approach was used to reconstruct the WS BCG from the wearable BCG. Preliminary results suggest that the relationship between local and central disturbances is highly dependent on both the individual and the location where the accelerometer is placed on the body and that these differences can be resolved via calibration to accurately measure changes in cardiac output and contractility from a wearable sensor. Such measurements could be highly effective, for example, for improved monitoring of heart failure patients at home. PMID:25561589

  9. Documentation of procedures for textural/spatial pattern recognition techniques

    NASA Technical Reports Server (NTRS)

    Haralick, R. M.; Bryant, W. F.

    1976-01-01

    A C-130 aircraft was flown over the Sam Houston National Forest on March 21, 1973 at 10,000 feet altitude to collect multispectral scanner (MSS) data. Existing textural and spatial automatic processing techniques were used to classify the MSS imagery into specified timber categories. Several classification experiments were performed on this data using features selected from the spectral bands and a textural transform band. The results indicate that (1) spatial post-processing a classified image can cut the classification error to 1/2 or 1/3 of its initial value, (2) spatial post-processing the classified image using combined spectral and textural features produces a resulting image with less error than post-processing a classified image using only spectral features and (3) classification without spatial post processing using the combined spectral textural features tends to produce about the same error rate as a classification without spatial post processing using only spectral features.

  10. Modeling XV-15 tilt-rotor aircraft dynamics by frequency and time-domain identification techniques

    NASA Technical Reports Server (NTRS)

    Tischler, Mark B.; Kaletka, Juergen

    1987-01-01

    Models of the open-loop hover dynamics of the XV-15 Tilt-Rotor Aircraft are extracted from flight data using two approaches: frequency domain and time-domain identification. Both approaches are reviewed and the identification results are presented and compared in detail. The extracted models are compared favorably, with the differences associated mostly with the inherent weighing of each technique. Step responses are used to show that the predictive capability of the models from both techniques is excellent. Based on the results of this study, the relative strengths and weaknesses of the frequency and time-domain techniques are summarized and a proposal for a coordinated parameter identification approach is presented.

  11. A Novel System Identification Technique for Improved Wearable Hemodynamics Assessment

    PubMed Central

    Wiens, Andrew D.; Inan, Omer T.

    2015-01-01

    Recent advances have led to renewed interest in ballistocardiography (BCG), a non-invasive measure of the small reaction forces on the body from cardiovascular events. A broad range of platforms have been developed and verified for BCG measurement including beds, chairs, and weighing scales: while the body is coupled to such a platform, the cardiogenic movements of the center-of-mass (COM) are measured. Wearable BCG, measured with an accelerometer affixed to the body, may enable continuous, or more regular, monitoring during the day; however, the signals from such wearable BCGs represent local or distal accelerations of skin and tissue rather than the displacement of the body's COM. In this paper we propose a novel method to reconstruct the COM BCG from a wearable sensor via a training step to remove these local effects. Preliminary validation of this method was performed with fifteen subjects: the wearable sensor was placed at three locations on the surface of the body while COM BCG measurements were recorded simultaneously with a modified weighing scale. A regularized system identification approach was used to reconstruct the COM BCG from the wearable signal. Preliminary results suggest that the relationship between local and central forces is highly dependent on both the individual and the location where the wearable sensor is placed on the body and that these differences can be resolved via calibration to accurately measure changes in cardiac output and contractility from a wearable sensor. Such measurements could be highly effective, for example, for improved monitoring of heart failure patients at home. PMID:25561589

  12. Identification and spatial patterns of coastal water pollution sources based on GIS and chemometric approach.

    PubMed

    Zhou, Feng; Guo, Huai-Cheng; Liu, Yong; Hao, Ze-Jia

    2007-01-01

    Comprehensive and joint applications of GIS and chemometric approach were applied in identification and spatial patterns of coastal water pollution sources with a large data set (5 years (2000-2004), 17 parameters) obtained through coastal water monitoring of Southern Water Control Zone in Hong Kong. According to cluster analysis the pollution degree was significantly different between September-next May (the 1st period) and June-August (the 2nd period). Based on these results, four potential pollution sources, such as organic/eutrophication pollution, natural pollution, mineral/anthropic pollution and fecal pollution were identified by factor analysis/principal component analysis. Then the factor scores of each monitoring site were analyzed using inverse distance weighting method, and the results indicated degree of the influence by various potential pollution sources differed among the monitoring sites. This study indicated that hybrid approach was useful and effective for identification of coastal water pollution source and spatial patterns. PMID:17966867

  13. 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.

  14. Identification techniques for phenomenological models of hysteresis based on the conjugate gradient method

    NASA Astrophysics Data System (ADS)

    Andrei, Petru; Oniciuc, Liviu; Stancu, Alexandru; Stoleriu, Laurentiu

    2007-09-01

    An identification technique for the parameters of phenomenological models of hysteresis is presented. The basic idea of our technique is to set up a system of equations for the parameters of the model as a function of known quantities on the major or minor hysteresis loops (e.g. coercive force, susceptibilities at various points, remanence), or other magnetization curves. This system of equations can be either over or underspecified and is solved by using the conjugate gradient method. Numerical results related to the identification of parameters in the Energetic, Jiles-Atherton, and Preisach models are presented.

  15. Underwater DVI: Simple fingerprint technique for positive identification.

    PubMed

    Khoo, Lay See; Hasmi, Ahmad Hafizam; Mahmood, Mohd Shah; Vanezis, Peter

    2016-09-01

    An underwater disaster can be declared when a maritime accident occurred or when an aircraft is plunged into water area, be it ocean, sea or river. Nevertheless, handling of human remains in an underwater recovery operation is often a difficult and demanding task as working conditions may be challenging with poor to no visibility, location of remains at considerable depths and associated hazards from surrounding water. A case of the recent helicopter crash, into a famous river in Sarawak, domiciled by huge crocodiles, is discussed in this paper. Search and recovery team as well as the combat divers from the Special Elite Troop Commando, known as VAT 69, were deployed to the scene to perform the underwater recovery to search for all the victims on board involving five Malaysians with a pilot of Philippines nationality. This paper highlights the limitations and challenges faced during the underwater search and recovery. All the bodies recovered were in moderate decomposition stage with crushed injuries and mutilated face and body. A simple and conventional fingerprint technique were used to record the fingerprint. The prints impressions were later photographed using a smartphone and transferred back to the RMP headquarters in Kuala Lumpur for fingerprint match by using WhatsApp Messenger, a phone application. All the first five victims were identified within an average of 10min. The last victim recovered was the pilot. For foreign nationals, the Immigration Department of Malaysia will record the prints of both index fingers only. The lifting of the fingerprint of the last victim was the most challenging in which only one index finger left that can be used for comparison. A few techniques were attempted using the black printer's ink, glass and tape techniques for the last victim. Subsequently, images of the prints impression were taken using the same smartphone with additional macro lens attached to it to enhance the resolution. The images were transferred to the RMP

  16. Gas-liquid two-phase flow pattern identification by ultrasonic echoes reflected from the inner wall of a pipe

    NASA Astrophysics Data System (ADS)

    Liang, Fachun; Zheng, Hongfeng; Yu, Hao; Sun, Yuan

    2016-03-01

    A novel ultrasonic pulse echo method is proposed for flow pattern identification in a horizontal pipe with gas-liquid two-phase flow. A trace of echoes reflected from the pipe’s internal wall rather than the gas-liquid interface is used for flow pattern identification. Experiments were conducted in a horizontal air-water two-phase flow loop. Two ultrasonic transducers with central frequency of 5 MHz were mounted at the top and bottom of the pipe respectively. The experimental results show that the ultrasonic reflection coefficient of the wall-gas interface is much larger than that of the wall-liquid interface due to the large difference in the acoustic impedance of gas and liquid. The stratified flow, annular flow and slug flow can be successfully recognized using the attenuation ratio of the echoes. Compared with the conventional ultrasonic echo measurement method, echoes reflected from the inner surface of a pipe wall are independent of gas-liquid interface fluctuation, sound speed, and gas and liquid superficial velocities, which makes the method presented a promising technique in field practice.

  17. Patterning of gold nanoparticles on fluoropolymer films by using patterned surface grafting and layer-by-layer deposition techniques.

    PubMed

    Jung, Chang-Hee; Hwang, In-Tae; Jung, Chan-Hee; Choi, Jae-Hak; Kwon, Oh-Sun; Shin, Kwanwoo

    2013-09-11

    The patterning of gold nanoparticles (GNPs) on the surface of a fluoropolymer substrate by using patterned surface grafting and layer-by-layer deposition techniques is described. The surface of a poly(tetrafluoroethylene-co-perfluorovinyl ether) (PFA) substrate was selectively implanted with 150 keV proton ions. Peroxide groups were successfully formed on the implanted PFA surface, and their concentration depended on the fluence. Acrylic acid was graft polymerized onto the implanted regions of the PFA substrate, resulting in well-defined patterns of poly(acrylic acid) (PAA) on the PFA substrate. The surface properties of the PAA-patterned PFA surface, such as chemical compositions, wettability, and morphology, were investigated. The surface analysis results revealed that PAA was definitely present on the implanted regions of the PFA surface, and the degree of grafting was dependent on three factors: fluence, grafting time, and monomer concentration. Furthermore, GNP patterns were generated on the prepared PAA-patterned PFA surface by layer-by-layer deposition of GNPs and poly(diallyldimethyl ammonium chloride). The multilayers of GNPs were deposited only onto the PAA-grafted regions separated by bare PFA regions, and the resulting GNP patterns exhibited good electrical conductivity. PMID:23927646

  18. Determination of pattern centre in EBSD using the moving-screen technique

    SciTech Connect

    Richardson, Dave; Carpenter, D. A.; Pugh, J. L.; Mooney, L. R.

    2007-09-01

    The 'moving-screen' or 'pattern magnification' method of calibration for electron backscatter diffraction (EBSD) was reformulated to develop a high-precision technique requiring no crystallographic knowledge of the specimen and no initial estimates of the calibration parameters. The technique depends upon the accurate displacement of the screen and camera assembly. Corresponding points are selected, interactively, from EBSD patterns. It is suggested that, as an alternative, the selection of points from the Hough transform could lead to a completely automated routine.

  19. Phase demodulation from a single fringe pattern based on a correlation technique.

    PubMed

    Robin, Eric; Valle, Valéry

    2004-08-01

    We present a method for determining the demodulated phase from a single fringe pattern. This method, based on a correlation technique, searches in a zone of interest for the degree of similarity between a real fringe pattern and a mathematical model. This method, named modulated phase correlation, is tested with different examples. PMID:15298408

  20. Automated identification of cancerous smears using various competitive intelligent techniques.

    PubMed

    Dounias, G; Bjerregaard, B; Jantzen, J; Tsakonas, A; Ampazis, N; Panagi, G; Panourgias, E

    2006-01-01

    In this study the performance of various intelligent methodologies is compared in the task of pap-smear diagnosis. The selected intelligent methodologies are briefly described and explained, and then, the acquired results are presented and discussed for their comprehensibility and usefulness to medical staff, either for fault diagnosis tasks, or for the construction of automated computer-assisted classification of smears. The intelligent methodologies used for the construction of pap-smear classifiers, are different clustering approaches, feature selection, neuro-fuzzy systems, inductive machine learning, genetic programming, and second order neural networks. Acquired results reveal the power of most intelligent techniques to obtain high quality solutions in this difficult problem of medical diagnosis. Some of the methods obtain almost perfect diagnostic accuracy in test data, but the outcome lacks comprehensibility. On the other hand, results scoring high in terms of comprehensibility are acquired from some methods, but with the drawback of achieving lower diagnostic accuracy. The experimental data used in this study were collected at a previous stage, for the purpose of combining intelligent diagnostic methodologies with other existing computer imaging technologies towards the construction of an automated smear cell classification device. PMID:16525690

  1. 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.

  2. Methicillin-resistant Staphylococcus aureus (MRSA): identification and susceptibility testing techniques.

    PubMed

    Reygaert, Wanda

    2009-01-01

    Many traditional techniques are useful for identification of MRSA strains, including techniques for detection of penicillin-resistance, such as the nitrocefin disk. Techniques for assessing methicillin-resistance vary from growth on special media or at a lower temperature, to detection of the mecA gene by manual (latex agglutination) and automated (PCR) methods. Technique development is now geared toward making MRSA identification more rapid. Real-time PCR has sped MRSA detection, but can be costly. Resistance to other drugs is also an issue. Clindamycin resistance may need to be induced, so a special disk diffusion test can be performed. Vancomycin resistance is becoming an issue, so alternative drugs need to be identified. Drugs that are currently available for MRSA infections include: daptomycin, linezolid, quinupristin/dalfopristin, and tigecycline. Drugs that are in the development phase include: ceftobiprole, dalbavancin, oritavancin, and telavancin. These drugs provide a promising arsenal against MRSA. PMID:19534447

  3. Improvement of sub-20nm pattern quality with dose modulation technique for NIL template production

    NASA Astrophysics Data System (ADS)

    Yagawa, Keisuke; Ugajin, Kunihiro; Suenaga, Machiko; Kanamitsu, Shingo; Motokawa, Takeharu; Hagihara, Kazuki; Arisawa, Yukiyasu; Kobayashi, Sachiko; Saito, Masato; Ito, Masamitsu

    2016-04-01

    Nanoimprint lithography (NIL) technology is in the spotlight as a next-generation semiconductor manufacturing technique for integrated circuits at 22 nm and beyond. NIL is the unmagnified lithography technique using template which is replicated from master templates. On the other hand, master templates are currently fabricated by electron-beam (EB) lithography[1]. In near future, finer patterns less than 15nm will be required on master template and EB data volume increases exponentially. So, we confront with a difficult challenge. A higher resolution EB mask writer and a high performance fabrication process will be required. In our previous study, we investigated a potential of photomask fabrication process for finer patterning and achieved 15.5nm line and space (L/S) pattern on template by using VSB (Variable Shaped Beam) type EB mask writer and chemically amplified resist. In contrast, we found that a contrast loss by backscattering decreases the performance of finer patterning. For semiconductor devices manufacturing, we must fabricate complicated patterns which includes high and low density simultaneously except for consecutive L/S pattern. Then it's quite important to develop a technique to make various size or coverage patterns all at once. In this study, a small feature pattern was experimentally formed on master template with dose modulation technique. This technique makes it possible to apply the appropriate exposure dose for each pattern size. As a result, we succeed to improve the performance of finer patterning in bright field area. These results show that the performance of current EB lithography process have a potential to fabricate NIL template.

  4. 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

  5. Identification of the motor laryngeal nerves - a new electrical stimulation technique.

    PubMed

    Spahn, J G; Bizal, J; Ferguson, S; Lingeman, R E

    1981-11-01

    Head and neck surgeons are familiar with the technique of identifying motor nerves in the head and neck region by using electrical stimulation especially in the identification of the facial and the spinal accessory nerves. The identification of the motor laryngeal nerves by electrical stimulation intra-operatively has been described; but, the difficulty of visualization of intrinsic laryngeal muscle movement has prevented the wide spread use of this technique. This paper will introduce a simple, safe and reliable method to allow the surgeon to recognize true vocal cord movement while stimulating the recurrent laryngeal nerve. The movement of a two inch 27 gauge needle placed through the cricothyroid membrane into the ipsilateral true vocal cord permits identification of intrinsic laryngeal muscle movement during electrical stimulation of the recurrent laryngeal nerve. This method has been successfully used in confirming conductivity of the laryngeal nerve during thyroid surgery, Zenker's diverticulum surgery, cricotracheal trauma and recurrent nerve neurectomy for spasmodic dysphonia. PMID:7300536

  6. Evaluation of palatal rugae pattern in establishing identification and sex determination in Nalgonda children

    PubMed Central

    Thabitha, Rani S.; Reddy, Rajendra E.; Manjula, M.; Sreelakshmi, N.; Rajesh, A.; Kumar, Vinay L.

    2015-01-01

    Background: Establishing individual identification of a decedent only by dental means is a mammoth task in forensic odontology. Palatal rugae's uniqueness, its resistance to heat, and stability throughout life have been proved by its use as an alternative aid in individual identification where comparison of fingerprints and other records is difficult. Aims and Objectives: The aim of the present study was to analyze the role of palatal rugoscopy in personal identification and sex determination of Nalgonda pediatric population. Materials and Methods: The study group consisted of 100 children having mixed dentition within the age range of 8–11 years, residing in Nalgonda district. Palatal rugae pattern, shape of the incisive papillae, length of the median palatal raphae, and shape of the dental arches were analyzed using Chi-square and Mann-Whitney tests between males and females. Results: Wavy and curved patterns appeared to be most prevalent in both males and females but with no significant difference. The number of primary rugae in females and secondary rugae in males, on left side of the palate, was significantly more than their counterparts (P < 0.05). When rugae unification was observed, diverging type was significantly more in males than in females. Parabolic dental arch form, elliptical type of incisive papilla, and medium length of median palatal raphae was observed in majority of the subjects. Conclusion: The present study hypothesizes the uniqueness of the rugae in personal identification as no two palates showed similar type of rugae in either of the genders. The rugae pattern also contributes minimally towards sex determination as there was no significant difference observed between the two variables. PMID:26816465

  7. Shape identification technique for a two-dimensional elliptic system by boundary integral equation method

    NASA Technical Reports Server (NTRS)

    Kojima, Fumio

    1989-01-01

    The geometrical structure of the boundary shape for a two-dimensional boundary value problem is identified. The output least square identification method is considered for estimating partially unknown boundary shapes. A numerical parameter estimation technique using the spline collocation method is proposed.

  8. Multi-expert and hybrid connectionist approach for pattern recognition: speaker identification task.

    PubMed

    Bennani, Y

    1994-09-01

    This paper presents and evaluates a modular/hybrid connectionist system for speaker identification. Modularity has emerged as a powerful technique for reducing the complexity of connectionist systems, allowing a priori knowledge to be incorporated into their design. In problems where training data are scarce, such modular systems are likely to generalize significantly better than a monolithic connectionist system. In addition, modules are not restricted to be connectionist: hybrid systems, with e.g. Hidden Markov Models (HMMs), can be designed, combining the advantages of connectionist and non-connectionist approaches. Text independent speaker identification is an inherently complex task where the amount of training data is often limited. It thus provides an ideal domain to test the validity of the modular/hybrid connectionist approach. An architecture is developed in this paper which achieves this identification, based upon the cooperation of several connectionist modules, together with an HMM module. When tested on a population of 102 speakers extracted from the DARPA-TIMIT database, perfect identification was obtained. Overall, our recognition results are among the best for any text-independent speaker identification system handling this population size. In a specific comparison with a system based on multivariate auto-regressive models, the modular/hybrid connectionist approach was found to be significantly better in terms of both accuracy and speed. Our design also allows for easy incorporation of new speakers. PMID:7866626

  9. A diagnostic technique used to obtain cross range radiation centers from antenna patterns

    NASA Technical Reports Server (NTRS)

    Lee, T. H.; Burnside, W. D.

    1988-01-01

    A diagnostic technique to obtain cross range radiation centers based on antenna radiation patterns is presented. This method is similar to the synthetic aperture processing of scattered fields in the radar application. Coherent processing of the radiated fields is used to determine the various radiation centers associated with the far-zone pattern of an antenna for a given radiation direction. This technique can be used to identify an unexpected radiation center that creates an undesired effect in a pattern; on the other hand, it can improve a numerical simulation of the pattern by identifying other significant mechanisms. Cross range results for two 8' reflector antennas are presented to illustrate as well as validate that technique.

  10. Computer-Assisted Generation of Patterns and Virtual Reality Techniques for Fashion Design

    NASA Astrophysics Data System (ADS)

    Naud, Mickael; Richard, Paul; Chapeau-Blondeau, François

    2009-03-01

    We present a methodology for the design of aesthetic patterns and their visualization on virtual clothes. Generated patterns are directly mapped on the dress of a virtual mannequin. Furthermore, patterns sets may be interactively mapped on the virtual dress using a specific 3D interaction technique called Back-and-Forth. Pattern generation involves different mathematical approaches such as iterated function systems (IFS) and nonlinear trajectory models. Both model parameters and color space exploration is performed through a simple user interface. This work contributes to promote both computer assistance in the context of mass customization for fashion design.

  11. Nanoparticle chemisorption printing technique for conductive silver patterning with submicron resolution

    PubMed Central

    Yamada, Toshikazu; Fukuhara, Katsuo; Matsuoka, Ken; Minemawari, Hiromi; Tsutsumi, Jun'ya; Fukuda, Nobuko; Aoshima, Keisuke; Arai, Shunto; Makita, Yuichi; Kubo, Hitoshi; Enomoto, Takao; Togashi, Takanari; Kurihara, Masato; Hasegawa, Tatsuo

    2016-01-01

    Silver nanocolloid, a dense suspension of ligand-encapsulated silver nanoparticles, is an important material for printing-based device production technologies. However, printed conductive patterns of sufficiently high quality and resolution for industrial products have not yet been achieved, as the use of conventional printing techniques is severely limiting. Here we report a printing technique to manufacture ultrafine conductive patterns utilizing the exclusive chemisorption phenomenon of weakly encapsulated silver nanoparticles on a photoactivated surface. The process includes masked irradiation of vacuum ultraviolet light on an amorphous perfluorinated polymer layer to photoactivate the surface with pendant carboxylate groups, and subsequent coating of alkylamine-encapsulated silver nanocolloids, which causes amine–carboxylate conversion to trigger the spontaneous formation of a self-fused solid silver layer. The technique can produce silver patterns of submicron fineness adhered strongly to substrates, thus enabling manufacture of flexible transparent conductive sheets. This printing technique could replace conventional vacuum- and photolithography-based device processing. PMID:27091238

  12. Nanoparticle chemisorption printing technique for conductive silver patterning with submicron resolution

    NASA Astrophysics Data System (ADS)

    Yamada, Toshikazu; Fukuhara, Katsuo; Matsuoka, Ken; Minemawari, Hiromi; Tsutsumi, Jun'ya; Fukuda, Nobuko; Aoshima, Keisuke; Arai, Shunto; Makita, Yuichi; Kubo, Hitoshi; Enomoto, Takao; Togashi, Takanari; Kurihara, Masato; Hasegawa, Tatsuo

    2016-04-01

    Silver nanocolloid, a dense suspension of ligand-encapsulated silver nanoparticles, is an important material for printing-based device production technologies. However, printed conductive patterns of sufficiently high quality and resolution for industrial products have not yet been achieved, as the use of conventional printing techniques is severely limiting. Here we report a printing technique to manufacture ultrafine conductive patterns utilizing the exclusive chemisorption phenomenon of weakly encapsulated silver nanoparticles on a photoactivated surface. The process includes masked irradiation of vacuum ultraviolet light on an amorphous perfluorinated polymer layer to photoactivate the surface with pendant carboxylate groups, and subsequent coating of alkylamine-encapsulated silver nanocolloids, which causes amine-carboxylate conversion to trigger the spontaneous formation of a self-fused solid silver layer. The technique can produce silver patterns of submicron fineness adhered strongly to substrates, thus enabling manufacture of flexible transparent conductive sheets. This printing technique could replace conventional vacuum- and photolithography-based device processing.

  13. Nanoparticle chemisorption printing technique for conductive silver patterning with submicron resolution.

    PubMed

    Yamada, Toshikazu; Fukuhara, Katsuo; Matsuoka, Ken; Minemawari, Hiromi; Tsutsumi, Jun'ya; Fukuda, Nobuko; Aoshima, Keisuke; Arai, Shunto; Makita, Yuichi; Kubo, Hitoshi; Enomoto, Takao; Togashi, Takanari; Kurihara, Masato; Hasegawa, Tatsuo

    2016-01-01

    Silver nanocolloid, a dense suspension of ligand-encapsulated silver nanoparticles, is an important material for printing-based device production technologies. However, printed conductive patterns of sufficiently high quality and resolution for industrial products have not yet been achieved, as the use of conventional printing techniques is severely limiting. Here we report a printing technique to manufacture ultrafine conductive patterns utilizing the exclusive chemisorption phenomenon of weakly encapsulated silver nanoparticles on a photoactivated surface. The process includes masked irradiation of vacuum ultraviolet light on an amorphous perfluorinated polymer layer to photoactivate the surface with pendant carboxylate groups, and subsequent coating of alkylamine-encapsulated silver nanocolloids, which causes amine-carboxylate conversion to trigger the spontaneous formation of a self-fused solid silver layer. The technique can produce silver patterns of submicron fineness adhered strongly to substrates, thus enabling manufacture of flexible transparent conductive sheets. This printing technique could replace conventional vacuum- and photolithography-based device processing. PMID:27091238

  14. Evaluation of a rapid polymerase chain reaction based identification technique for Vibrio cholerae isolates.

    PubMed

    le Roux, W J; Masoabi, D; de Wet, C M E; Venter, S N

    2004-01-01

    Rapid and accurate identification of waterborne pathogens, such as Vibrio cholerae, in drinking-water sources is important to enable effective resource management and public health protection. Phenotypic systems currently being used for the identification of Vibrio cholerae isolates are time-consuming and the need exists for the development of suitable molecular techniques that can offer both fast and reliable identification. During this study, isolates identified as Vibrio cholerae by means of two different biochemical test systems (API 20E and VITEK 32) were analysed with the polymerase chain reaction (PCR) to compare the reliability of the various identification systems. The selected PCR technique amplified a sequence within the outer membrane protein of Vibrio cholerae, a gene specific for V. cholerae. It was found that out of 243 isolates biochemically identified as V. cholerae with either the API or VITEK system, 21 isolates did not give a positive result with the PCR detection method. Sequencing the 16S rDNA of more than half of these isolates and comparison of the sequences with Internet databases indicated that most of the isolates belonged to the genus Aeromonas. The results indicated that the rapid PCR procedure was more accurate than the API or VITEK systems currently being used for the phenotypic identification of Vibrio cholerae isolates. PMID:15318514

  15. Uniqueness of radiographic patterns of the frontal sinus for personal identification

    PubMed Central

    Karjodkar, Freny R.; Sontakke, Subodh; Sansare, Kaustubh; Salvi, Rohini

    2012-01-01

    Purpose This study was performed to evaluate the uniqueness and reliability of the frontal sinuses by comparing various patterns of frontal sinus as observed on Waters' radiographs for individual identification. Materials and Methods Three Waters' radiographs of 100 individuals, taken on day one, after 6-8 months, and one radiograph with a slight variation in angulation, to mimic conditions out in the field or during autopsy. Three observers were randomly given radiographs from all there packets for comparisons and identification, by the method of superimposition and individual uniqueness. Results The comparative identification by superimposition of the frontal sinus was 100% positive. The size, shape, unilateral or bilateral presence, absence, and septa were observed to be unique in each case; neither had the measurements changed over a period of time. Conclusion The need to establish a reliable, low-cost, and easily reproducible method for human identification prompted the elaboration of technical, precise, and accessible parameters, such as the evaluation of the area, asymmetry, and shape of the frontal sinus. Comparison among each of the frontal sinuses of the 100 people in the sample revealed that no two sinuses are the same, that is, the sinus is unique to each individual. PMID:23301206

  16. Applicability of data mining algorithms in the identification of beach features/patterns on high-resolution satellite data

    NASA Astrophysics Data System (ADS)

    Teodoro, Ana C.

    2015-01-01

    The available beach classification algorithms and sediment budget models are mainly based on in situ parameters, usually unavailable for several coastal areas. A morphological analysis using remotely sensed data is a valid alternative. This study focuses on the application of data mining techniques, particularly decision trees (DTs) and artificial neural networks (ANNs) to an IKONOS-2 image in order to identify beach features/patterns in a stretch of the northwest coast of Portugal. Based on knowledge of the coastal features, five classes were defined. In the identification of beach features/patterns, the ANN algorithm presented an overall accuracy of 98.6% and a kappa coefficient of 0.97. The best DTs algorithm (with pruning) presents an overall accuracy of 98.2% and a kappa coefficient of 0.97. The results obtained through the ANN and DTs were in agreement. However, the ANN presented a classification more sensitive to rip currents. The use of ANNs and DTs for beach classification from remotely sensed data resulted in an increased classification accuracy when compared with traditional classification methods. The association of remotely sensed high-spatial resolution data and data mining algorithms is an effective methodology with which to identify beach features/patterns.

  17. Multi technique amalgamation for enhanced information identification with content based image data.

    PubMed

    Das, Rik; Thepade, Sudeep; Ghosh, Saurav

    2015-01-01

    Image data has emerged as a resourceful foundation for information with proliferation of image capturing devices and social media. Diverse applications of images in areas including biomedicine, military, commerce, education have resulted in huge image repositories. Semantically analogous images can be fruitfully recognized by means of content based image identification. However, the success of the technique has been largely dependent on extraction of robust feature vectors from the image content. The paper has introduced three different techniques of content based feature extraction based on image binarization, image transform and morphological operator respectively. The techniques were tested with four public datasets namely, Wang Dataset, Oliva Torralba (OT Scene) Dataset, Corel Dataset and Caltech Dataset. The multi technique feature extraction process was further integrated for decision fusion of image identification to boost up the recognition rate. Classification result with the proposed technique has shown an average increase of 14.5 % in Precision compared to the existing techniques and the retrieval result with the introduced technique has shown an average increase of 6.54 % in Precision over state-of-the art techniques. PMID:26798574

  18. Evaluation of molecular techniques for identification and enumeration of Raoultella terrigena ATCC 33257 in water purifier efficacy testing.

    PubMed

    Saha, Ratul; Bechanko, Robin; Bestervelt, Lorelle L; Donofrio, Robert S

    2011-09-01

    Raoultella terrigena ATCC 33257, a representative of the coliform group, is commonly used as a challenge organism in water purifier efficacy testing. In addition to being time consuming, traditional culturing techniques and metabolic identification systems (including automated systems) also fail to accurately differentiate this organism from its closely related neighbors belonging to the Enterobacteriaceae group. Molecular-based techniques, such as real-time quantitative polymerase chain reaction (qPCR) and enterobacterial repetitive intergenic consensus (ERIC)-PCR fingerprinting, are preferred methods of detection because of their accuracy, reproducibility, specificity, and sensitivity, along with shorter turnaround time. ERIC-PCR performed with the 1R primer set demonstrated stable unique banding patterns (~800, ~300 bp) for R. terrigena ATCC 33257 different from patterns observed for R. planticola and R. ornithinolytica. The primer pair developed from gyraseA (gyrA) sequence of R. terrigena for the SYBR Green qPCR assay using the AlleleID(®) 7.0 primer probe design software was highly specific and sensitive for the target organism. The sensitivity of the assay was 10(1) colony forming units (CFU)/ml for whole cells and 4.7 fg with genomic DNA. The primer pair was successful in determining the concentration (5.5 ± 0.3 × 10(6) CFU/ml) of R. terrigena from water samples spiked with equal concentration of Escherichia coli and R. terrigena. Based on these results from the ERIC-PCR and the SYBR Green qPCR assay, these molecular techniques can be efficiently used for rapid identification and quantification of R. terrigena during water purifier testing. PMID:21132347

  19. Writing trace identification using ultraviolet Fourier-transform imaging spectroscopy technique

    NASA Astrophysics Data System (ADS)

    Lyu, Hang; Liao, Ningfang; Wu, Wenmin; Li, Yasheng; Cao, Bin

    2015-08-01

    Conventional identification methods of writing traces commonly utilize imaging or spectroscopic techniques which work in visible to near infrared range or short-wave infrared range. Yet they cannot be applied in identifying the erased writing traces. In this study, we perform a research in identification of erased writing traces applying an ultraviolet Fouriertransform imaging spectrometer. Experiments of classifying the reflected ultraviolet spectra of erasable pens are made. The resulting hyperspectral images demonstrate that the erased writing traces on printing paper can be clearly identified by this ultraviolet imaging spectrometer.

  20. 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.

  1. CODEHOP-mediated PCR – A powerful technique for the identification and characterization of viral genomes

    PubMed Central

    Rose, Timothy M

    2005-01-01

    Consensus-Degenerate Hybrid Oligonucleotide Primer (CODEHOP) PCR primers derived from amino acid sequence motifs which are highly conserved between members of a protein family have proven to be highly effective in the identification and characterization of distantly related family members. Here, the use of the CODEHOP strategy to identify novel viruses and obtain sequence information for phylogenetic characterization, gene structure determination and genome analysis is reviewed. While this review describes techniques for the identification of members of the herpesvirus family of DNA viruses, the same methodology and approach is applicable to other virus families. PMID:15769292

  2. Advanced techniques for noise source identification on a large generator unit

    SciTech Connect

    Williams, R.G.D. ); Yang, S.J. )

    1993-03-01

    Power station acoustic noise assessment, which has experienced increased environmental awareness and subsequently more stringent legislation for a number of years, has received and added stimulus due to the recent advent of powerful measurement and analysis techniques including sound intensity and coherence. These experimental techniques are explained and results, for a generator unit, illustrate their value in providing a unique, correlated insight into noise problems. This includes noise quantification, full explanation of site sound pressure level in terms of the various influences and major noise source identification. These techniques are widely applicable and an invaluable aid to any industrial noise problem.

  3. Multiple-technique identification of sibling species of the Anopheles quadrimaculatus complex.

    PubMed

    Narang, S K; Seawright, J A; Mitchell, S E; Kaiser, P E; Carlson, D A

    1993-12-01

    In the past, most researchers used a single technique for identification of cryptic taxa, population structures, biosystematics, and phylogenetic studies. Our experience with the Anopheles quadrimaculatus complex shows the importance of using several methods on individual mosquitoes. This approach consists of analysis of the polytene chromosomes in ovarian nurse cells, gas chromatographic profiles of cuticular hydrocarbons, isozyme electrophoresis, and restriction site analysis of mitochondrial or genomic DNA. We recommend use of this multiple-technique approach when analyzing feral populations for the first time, or for correlating information obtained by investigators using different techniques. PMID:8126484

  4. Maximum likelihood estimation of label imperfection probabilities and its use in the identification of mislabeled patterns. [with application to Landsat MSS data processing

    NASA Technical Reports Server (NTRS)

    Chittineni, C. B.

    1980-01-01

    Estimating label imperfections and the use of estimations in the identification of mislabeled patterns are discussed. Expressions are presented for the asymptotic variances of the probability of correct classification and proportion, and for the maximum likelihood estimates of classification errors and a priori probabilities. Models are developed for imperfections in the labels and classification errors, and expressions are derived for the probability of imperfect label identification schemes resulting in wrong decisions. The expressions are used in computing thresholds and the techniques are given practical applications. The imperfect label identification scheme in the multiclass case is found to amount to establishing a region around each decision surface, and decisions of the label correction scheme are found in close agreement with the analyst-interpreter interpretations of the imagery films. As an example, the application of the maximum likelihood estimation to the processing of Landsat MSS data is discussed.

  5. Palm-Print Pattern Matching Based on Features Using Rabin-Karp for Person Identification

    PubMed Central

    Kanchana, S.; Balakrishnan, G.

    2015-01-01

    Palm-print based individual identification is regarded as an effectual method for identifying persons with high confidence. Palm-print with larger inner surface of hand contains many features such as principle lines, ridges, minutiae points, singular points, and textures. Feature based pattern matching has faced the challenge that the spatial positional variations occur between the training and test samples. To perform effective palm-print features matching, Rabin-Karp Palm-Print Pattern Matching (RPPM) method is proposed in this paper. With the objective of improving the accuracy of pattern matching, double hashing is employed in RPPM method. Multiple patterns of features are matched using the Aho-Corasick Multiple Feature matching procedure by locating the position of the features with finite set of bit values as an input text, improving the cumulative accuracy on hashing. Finally, a time efficient bit parallel ordering presents an efficient variation on matching the palm-print features of test and training samples with minimal time. Experiment is conducted on the factors such as pattern matching efficiency rate, time taken on multiple palm-print feature matching efficiency, and cumulative accuracy on hashing. PMID:26697529

  6. Restriction fragment length polymorphism species-specific patterns in the identification of white truffles.

    PubMed

    Bertini, L; Potenza, L; Zambonelli, A; Amicucci, A; Stocchi, V

    1998-07-15

    A molecular method for the identification of ectomycorrhizae belonging to five species of white truffle is described. The polymerase chain reaction (PCR) and universal primers were used to amplify internal transcribed spacers and 5.8S rDNA, target sequences present in a high number of copies. The amplified products were digested with restriction enzymes in order to detect interspecific polymorphisms. Species-specific restriction fragment length polymorphism patterns were determined for all five species. The use of PCR in conjunction with restriction enzymes provides a sensitive and efficient tool for use in distinguishing ectomycorrhizal species and monitoring inoculated seedlings or field mycorrhizal populations. PMID:9682488

  7. Analytical techniques for the detection and identification of chemical warfare materials from environmental samples

    SciTech Connect

    Beaudry, W.T.; Weimaster, J.F.

    1995-06-01

    The detection and identification of chemical warfare (CW) material in diverse and complex matrices has become increasingly important to support the environmental clean-up of military and industrial sites that were historically used in the research, production, use, storage and/or demilitarization of chemical weapons. Reliable and defensible identification of hazardous materials (HM) is necessary to comply with the increasingly stringent regulations imposed by local, state, and federal agencies which govern handling, treatment, storage, and disposal of HM. In addition, before sites can be reutilized, existing HM must be properly identified so that the proper methods of removal, treatment and disposal can be determined. An overview of sample preparation and analytical techniques for the detection and identification of CW materials is presented in this paper.

  8. A modified technique for fabricating a mirror image wax pattern for an auricular prosthesis.

    PubMed

    Gajdhar, Shaiq; Gajdhar, Sajda Khan; Salakalakonda, Srikanth Reddy; Vasthare, Abubakkar

    2015-01-01

    This article describes a technique for fabricating a wax pattern for an auricular prosthesis by tracing the shape of a sliced cast of the contralateral ear at an interval of 1-mm and transferring the shape of each 1-mm slice to a similar dimension modeling wax sheet. In this way, slices of modeling wax are obtained, which can be reversed and placed over the previous slice to produce a mirror image wax pattern of the contralateral ear. PMID:25277032

  9. Plasma microcontact patterning (PμCP): a technique for the precise control of surface patterning at small-scale.

    PubMed

    Picone, Remigio; Baum, Buzz; McKendry, Rachel

    2014-01-01

    Plasma microcontact patterning (PμCP) is a simple, efficient, and cost-effective method for the precise patterning of molecules on surfaces. It combines the use of low-pressure plasma with an elastomeric 3D mask to spatially control the removal of molecules, such as proteins, from a surface. The entire PμCP process is subdivided into three main steps: surface precoating, plasma micropatterning, and a surface postcoating step. Surfaces are first precoated with a molecular species and then placed in close contact with the 3D mask. This allows the formation of two distinct regions: an un-masked open-region which is accessible to the plasma, from which the surface layer is removed, and, a contact region which is physically protected from exposure to the plasma. In the final step, a second molecule is added to back-fill the pattern generated through plasma-treatment. The PμCP technique allows the patterning of virtually any organic molecules on different surface materials and geometries (e.g., flat, curved surfaces, and 3D microstructures). Moreover, it is a simple and robust procedure. The main advantages of this approach over traditional microcontact printing are twofold: The stability of molecule binding to plasma-treated surfaces, and the separation of the surface functionalization step from the actual micropatterning step, which enables the precise control of concentration and uniformity of patterned molecules. In conclusion, PμCP is a simple way to generate surface patterns that are highly reproducible, stable and uniform, making it a useful method for many applications. PMID:24439280

  10. A new coordination pattern classification to assess gait kinematics when utilising a modified vector coding technique.

    PubMed

    Needham, Robert A; Naemi, Roozbeh; Chockalingam, Nachiappan

    2015-09-18

    A modified vector coding (VC) technique was used to quantify lumbar-pelvic coordination during gait. The outcome measure from the modified VC technique is known as the coupling angle (CA) which can be classified into one of four coordination patterns. This study introduces a new classification for this coordination pattern that expands on a current data analysis technique by introducing the terms in-phase with proximal dominancy, in-phase with distal dominancy, anti-phase with proximal dominancy and anti-phase with distal dominancy. This proposed coordination pattern classification can offer an interpretation of the CA that provides either in-phase or anti-phase coordination information, along with an understanding of the direction of segmental rotations and the segment that is the dominant mover at each point in time. Classifying the CA against the new defined coordination patterns and presenting this information in a traditional time-series format in this study has offered an insight into segmental range of motion. A new illustration is also presented which details the distribution of the CA within each of the coordination patterns and allows for the quantification of segmental dominancy. The proposed illustration technique can have important implications in demonstrating gait coordination data in an easily comprehensible fashion by clinicians and scientists alike. PMID:26303167

  11. Determination of pattern centre in EBSD using the moving-screen technique.

    PubMed

    Carpenter, D A; Pugh, J L; Richardson, G D; Mooney, L R

    2007-09-01

    The 'moving-screen' or 'pattern magnification' method of calibration for electron backscatter diffraction (EBSD) was reformulated to develop a high-precision technique requiring no crystallographic knowledge of the specimen and no initial estimates of the calibration parameters. The technique depends upon the accurate displacement of the screen and camera assembly. Corresponding points are selected, interactively, from EBSD patterns. It is suggested that, as an alternative, the selection of points from the Hough transform could lead to a completely automated routine. PMID:17760619

  12. Comparison of System Identification Techniques for the Hydraulic Manipulator Test Bed (HMTB)

    NASA Technical Reports Server (NTRS)

    Morris, A. Terry

    1996-01-01

    In this thesis linear, dynamic, multivariable state-space models for three joints of the ground-based Hydraulic Manipulator Test Bed (HMTB) are identified. HMTB, housed at the NASA Langley Research Center, is a ground-based version of the Dexterous Orbital Servicing System (DOSS), a representative space station manipulator. The dynamic models of the HMTB manipulator will first be estimated by applying nonparametric identification methods to determine each joint's response characteristics using various input excitations. These excitations include sum of sinusoids, pseudorandom binary sequences (PRBS), bipolar ramping pulses, and chirp input signals. Next, two different parametric system identification techniques will be applied to identify the best dynamical description of the joints. The manipulator is localized about a representative space station orbital replacement unit (ORU) task allowing the use of linear system identification methods. Comparisons, observations, and results of both parametric system identification techniques are discussed. The thesis concludes by proposing a model reference control system to aid in astronaut ground tests. This approach would allow the identified models to mimic on-orbit dynamic characteristics of the actual flight manipulator thus providing astronauts with realistic on-orbit responses to perform space station tasks in a ground-based environment.

  13. Hotspot decorations map plasmonic patterns with the resolution of scanning probe techniques.

    PubMed

    Valev, V K; Silhanek, A V; Jeyaram, Y; Denkova, D; De Clercq, B; Petkov, V; Zheng, X; Volskiy, V; Gillijns, W; Vandenbosch, G A E; Aktsipetrov, O A; Ameloot, M; Moshchalkov, V V; Verbiest, T

    2011-06-01

    In high definition mapping of the plasmonic patterns on the surfaces of nanostructures, the diffraction limit of light remains an important obstacle. Here we demonstrate that this diffraction limit can be completely circumvented. We show that upon illuminating nanostructures made of nickel and palladium, the resulting surface-plasmon pattern is imprinted on the structures themselves; the hotspots (regions of local field enhancement) are decorated with overgrowths, allowing for their subsequent imaging with scanning-probe techniques. The resulting resolution of plasmon pattern imaging is correspondingly improved. PMID:21702624

  14. Integration of Scale Invariant Generator Technique and S-A Technique for Characterizing 2-D Patterns for Information Retrieve

    NASA Astrophysics Data System (ADS)

    Cao, L.; Cheng, Q.

    2004-12-01

    The scale invariant generator technique (SIG) and spectrum-area analysis technique (S-A) were developed independently relevant to the concept of the generalized scale invariance (GSI). The former was developed for characterizing the parameters involved in the GSI for characterizing and simulating multifractal measures whereas the latter was for identifying scaling breaks for decomposition of superimposed multifractal measures caused by multiple geophysical processes. A natural integration of these two techniques may yield a new technique to serve two purposes, on the one hand, that can enrich the power of S-A by increasing the interpretability of decomposed patterns in some applications of S-A and, on the other hand, that can provide a mean to test the uniqueness of multifractality of measures which is essential for application of SIG technique in more complicated environment. The implementation of the proposed technique has been done as a Dynamic Link Library (DLL) in Visual C++. The program can be friendly used for method validation and application in different fields.

  15. Application of a pattern recognition technique to the prediction of tire noise

    NASA Astrophysics Data System (ADS)

    Chiu, Jinn-Tong; Tu, Fu-Yuan

    2015-08-01

    Tire treads are one of the main sources of car noise. To meet the EU's tire noise regulation ECE-R117, a new method using a pattern recognition technique is adopted in this paper to predict noise from tire tread patterns, thus facilitating the design of low-noise tires. When tires come into contact with the road surface, air pumping may occur in the grooves of tire tread patterns. Using the image of a tread pattern, a matrix is constructed by setting the patterns of tire grooves and tread blocks. The length and width of the contact patch are multiplied by weight functions. The resulting sound pressure as a function of time is subjected to a Fourier transform to simulate a 1/3-octave-band sound pressure level. A particle swarm algorithm is adopted to optimize the weighting parameters for the sound pressure in the frequency domain so that simulated values approach the measured noise level. Two sets of optimal weighting parameters associated with the length and width of the contact patch are obtained. Finally, the weight function is used to predict the tread pattern noise of tires in the same series. A comparison of the prediction and experimental results reveals that, in the 1/3-octave band of frequency (800-2000 Hz), average errors in sound pressure are within 2.5 dB. The feasibility of the proposed application of the pattern recognition technique in predicting noise from tire treads is verified.

  16. Pigment Identification on a XIV/XV c. Wooden Crucifix Using Raman and LIBS Techniques

    NASA Astrophysics Data System (ADS)

    Sawczak, M.; Sliwinski, G.; Kaminska, A.; Oujja, M.; Castillejo, M.; Domingo, C.; Klossowska, M.

    The Raman and laser-induced breakdown spectroscopy (LIBS) techniques were applied for the pigment identification in polychrome layers on a fourteenth/fifteenth century wooden crucifix. In the Raman spectra, characteristic bands associated with compounds of the pigment samples taken from different areas of the object are observed. Groups of bands corresponding to the original white, red, and green pigments allow the identification of chalk, vermilion, red lead, malachite, and azurite. From the presence of bands ascribed to Prussian blue (282, 538 cm?1) and chrome yellow (338, 360, 403 cm?1) known since eighteenth century, retouching of some statue parts can be concluded. The elemental composition is obtained from LIBS profiles recorded under excitation at 248 and 266 nm. The gold-leaf technique is identified and the presence of Cu, Pb, Cr, Fe, CN, C2, and Ca agrees with the pigment composition applied for re-touching and observed in the Raman bands.

  17. Ultrasonographic identification of the cricothyroid membrane: best evidence, techniques, and clinical impact.

    PubMed

    Kristensen, M S; Teoh, W H; Rudolph, S S

    2016-09-01

    Inability to identify the cricothyroid membrane by inspection and palpation contributes substantially to the high failure rate of cricothyrotomy. This narrative review summarizes the current evidence for application of airway ultrasonography for identification of the cricothyroid membrane compared with the clinical techniques. We identified the best-documented techniques for bedside use, their success rates, and the necessary training for airway-ultrasound-naïve clinicians. After a short but structured training, the cricothyroid membrane can be identified using ultrasound in difficult patients by previously airway-ultrasound naïve anaesthetists with double the success rate of palpation. Based on the literature, we recommend identifying the cricothyroid membrane before induction of anaesthesia in all patients. Although inspection and palpation may suffice in most patients, the remaining patients will need ultrasonographic identification; a service that we should aim at making available in all locations where anaesthesia is undertaken and where patients with difficult airways could be encountered. PMID:27432055

  18. Correlation techniques to determine model form in robust nonlinear system realization/identification

    NASA Technical Reports Server (NTRS)

    Stry, Greselda I.; Mook, D. Joseph

    1991-01-01

    The fundamental challenge in identification of nonlinear dynamic systems is determining the appropriate form of the model. A robust technique is presented which essentially eliminates this problem for many applications. The technique is based on the Minimum Model Error (MME) optimal estimation approach. A detailed literature review is included in which fundamental differences between the current approach and previous work is described. The most significant feature is the ability to identify nonlinear dynamic systems without prior assumption regarding the form of the nonlinearities, in contrast to existing nonlinear identification approaches which usually require detailed assumptions of the nonlinearities. Model form is determined via statistical correlation of the MME optimal state estimates with the MME optimal model error estimates. The example illustrations indicate that the method is robust with respect to prior ignorance of the model, and with respect to measurement noise, measurement frequency, and measurement record length.

  19. Gender identification of Grasshopper Sparrows comparing behavioral, morphological, and molecular techniques

    USGS Publications Warehouse

    Ammer, F.K.; Wood, P.B.; McPherson, R.J.

    2008-01-01

    Correct gender identification in monomorphic species is often difficult especially if males and females do not display obvious behavioral and breeding differences. We compared gender specific morphology and behavior with recently developed DNA techniques for gender identification in the monomorphic Grasshopper Sparrow (Ammodramus savannarum). Gender was ascertained with DNA in 213 individuals using the 2550F/2718R primer set and 3% agarose gel electrophoresis. Field observations using behavior and breeding characteristics to identify gender matched DNA analyses with 100% accuracy for adult males and females. Gender was identified with DNA for all captured juveniles that did not display gender specific traits or behaviors in the field. The molecular techniques used offered a high level of accuracy and may be useful in studies of dispersal mechanisms and winter assemblage composition in monomorphic species.

  20. Automatic identification of bird targets with radar via patterns produced by wing flapping.

    PubMed

    Zaugg, Serge; Saporta, Gilbert; van Loon, Emiel; Schmaljohann, Heiko; Liechti, Felix

    2008-09-01

    Bird identification with radar is important for bird migration research, environmental impact assessments (e.g. wind farms), aircraft security and radar meteorology. In a study on bird migration, radar signals from birds, insects and ground clutter were recorded. Signals from birds show a typical pattern due to wing flapping. The data were labelled by experts into the four classes BIRD, INSECT, CLUTTER and UFO (unidentifiable signals). We present a classification algorithm aimed at automatic recognition of bird targets. Variables related to signal intensity and wing flapping pattern were extracted (via continuous wavelet transform). We used support vector classifiers to build predictive models. We estimated classification performance via cross validation on four datasets. When data from the same dataset were used for training and testing the classifier, the classification performance was extremely to moderately high. When data from one dataset were used for training and the three remaining datasets were used as test sets, the performance was lower but still extremely to moderately high. This shows that the method generalizes well across different locations or times. Our method provides a substantial gain of time when birds must be identified in large collections of radar signals and it represents the first substantial step in developing a real time bird identification radar system. We provide some guidelines and ideas for future research. PMID:18331979

  1. New pattern recognition system in the e-nose for Chinese spirit identification

    NASA Astrophysics Data System (ADS)

    Hui, Zeng; Qiang, Li; Yu, Gu

    2016-02-01

    This paper presents a new pattern recognition system for Chinese spirit identification by using the polymer quartz piezoelectric crystal sensor based e-nose. The sensors are designed based on quartz crystal microbalance (QCM) principle, and they could capture different vibration frequency signal values for Chinese spirit identification. For each sensor in an 8-channel sensor array, seven characteristic values of the original vibration frequency signal values, i.e., average value (A), root-mean-square value (RMS), shape factor value (Sf), crest factor value (Cf), impulse factor value (If), clearance factor value (CLf), kurtosis factor value (Kv) are first extracted. Then the dimension of the characteristic values is reduced by the principle components analysis (PCA) method. Finally the back propagation (BP) neutral network algorithm is used to recognize Chinese spirits. The experimental results show that the recognition rate of six kinds of Chinese spirits is 93.33% and our proposed new pattern recognition system can identify Chinese spirits effectively. Project supported by the National High Technology Research and Development Program of China (Grant No. 2013AA030901) and the Fundamental Research Funds for the Central Universities, China (Grant No. FRF-TP-14-120A2).

  2. A simple and inexpensive bar-coding technique for denture identification.

    PubMed

    Nalawade, Sonali N; Lagdive, Sanjay B; Gangadhar, Sa; Bhandari, Aruna J

    2011-07-01

    A number of commercial methods for identifying dentures are available. They can be either invasive or noninvasive techniques. The less sophisticated procedures include simple engraving with bur, and more sophisticated procedures use labels or chips. Bar coding system is a way of transferring data to the computer and huge data can be stored as a record. Bar coding can be easily incorporated during acrylization of the denture and thus could be used in individual identification. PMID:22408329

  3. A simple and inexpensive bar-coding technique for denture identification

    PubMed Central

    Nalawade, Sonali N; Lagdive, Sanjay B; Gangadhar, SA; Bhandari, Aruna J

    2011-01-01

    A number of commercial methods for identifying dentures are available. They can be either invasive or noninvasive techniques. The less sophisticated procedures include simple engraving with bur, and more sophisticated procedures use labels or chips. Bar coding system is a way of transferring data to the computer and huge data can be stored as a record. Bar coding can be easily incorporated during acrylization of the denture and thus could be used in individual identification. PMID:22408329

  4. Reliability of System Identification Techniques to Assess Standing Balance in Healthy Elderly

    PubMed Central

    Maier, Andrea B.; Aarts, Ronald G. K. M.; van Gerven, Joop M. A.; Arendzen, J. Hans; Schouten, Alfred C.; Meskers, Carel G. M.; van der Kooij, Herman

    2016-01-01

    Objectives System identification techniques have the potential to assess the contribution of the underlying systems involved in standing balance by applying well-known disturbances. We investigated the reliability of standing balance parameters obtained with multivariate closed loop system identification techniques. Methods In twelve healthy elderly balance tests were performed twice a day during three days. Body sway was measured during two minutes of standing with eyes closed and the Balance test Room (BalRoom) was used to apply four disturbances simultaneously: two sensory disturbances, to the proprioceptive and the visual system, and two mechanical disturbances applied at the leg and trunk segment. Using system identification techniques, sensitivity functions of the sensory disturbances and the neuromuscular controller were estimated. Based on the generalizability theory (G theory), systematic errors and sources of variability were assessed using linear mixed models and reliability was assessed by computing indexes of dependability (ID), standard error of measurement (SEM) and minimal detectable change (MDC). Results A systematic error was found between the first and second trial in the sensitivity functions. No systematic error was found in the neuromuscular controller and body sway. The reliability of 15 of 25 parameters and body sway were moderate to excellent when the results of two trials on three days were averaged. To reach an excellent reliability on one day in 7 out of 25 parameters, it was predicted that at least seven trials must be averaged. Conclusion This study shows that system identification techniques are a promising method to assess the underlying systems involved in standing balance in elderly. However, most of the parameters do not appear to be reliable unless a large number of trials are collected across multiple days. To reach an excellent reliability in one third of the parameters, a training session for participants is needed and at

  5. Stability of Patterns of Behavior in the Butterfly Technique of the Elite Swimmers

    PubMed Central

    Louro, Hugo; Silva, António J.; Anguera, Teresa; Marinho, Daniel A.; Oliveira, Conceição; Conceição, Ana; Campaniço, Jorge

    2010-01-01

    The purpose of this study was to find patterns in the butterfly swimming technique, with an adaptation of the Behavioral Observation System Tech. This, as an instrument for ad-hoc qualitative analysis, enables the study of the stability of the technical implementation. When used in the training of swimmers, analysis can reduce the variability of behavioral tuning swimming technique. Through the analysis of temporal patterns (T-pattern) and a sequence of five cycles running at hand maximum speed, the behavior of four technical Portuguese elite swimmers, with a record of 259 alphanumeric codes and a total of 160 configurations, were studied. The structure of the original instrument, based on a mixed system of categories and formats Field, can record technical features, observed during the execution of hand cycles. The validity was ensured through the index of intra-observer reliability (95%) and inter-observer accuracy (96%). To detect patterns in each swimmer, the Theme 5.0 software was used, which allowed to identify the stable structures of technical performance within a critical interval of time (p <0.05) - t-patterns. The patterns were different, adjusting to the characteristics of technical implementation of the swimmers. It was found that the swimmer can create settings with different levels of structure complexity, depending on the implementation of changes within the hand cycle. Variations of codes in each configuration obtained using the SOCTM, allowed determining the differences between swimmers. However, the records showed a clear behavioral similarity when comparing the result with a general pattern of the butterfly technique. The potential quality of this instrument seems to be important due to the patterns obtained from a temporal sequence. Key points The patterns were different, adjusting to the characteristics of technical implementation of the swimmers. The swimmer can make settings with different levels of structure complexity, depending on the

  6. Developments in techniques for the isolation, enrichment, main culture conditions and identification of spermatogonial stem cells.

    PubMed

    He, Yanan; Chen, Xiaoli; Zhu, Huabin; Wang, Dong

    2015-12-01

    The in vitro culture system of spermatogonial stem cells (SSCs) provides a basis for studies on spermatogenesis, and also contributes to the development of new methods for the preservation of livestock and animal genetic modification. In vitro culture systems have mainly been established for mouse SSCs, but are lacking for farm animals. We reviewed and analyzed the current progress in SSC techniques such as isolation, purification, cultivation and identification. Based on the published studies, we concluded that two-step enzyme digestion and magnetic-activated cell sorting are fast becoming the main methods for isolation and enrichment of SSCs. With regard to the culture systems, serum and feeders were earlier thought to play an important role in the self-renewal and proliferation of SSCs, but serum- and feeder-free culture systems as a means of overcoming the limitations of SSC differentiation in long-term SSC culture are being explored. However, there is still a need to establish more efficient and ideal culture systems that can also be used for SSC culture in larger mammals. Although the lack of SSC-specific surface markers has seriously affected the efficiency of purification and identification, the transgenic study is helpful for our identification of SSCs. Therefore, future studies on SSC techniques should focus on improving serum- and feeder-free culture techniques, and discovering and identifying specific surface markers of SSCs, which will provide new ideas for the optimization of SSC culture systems for mice and promote related studies in farm animals. PMID:25749914

  7. 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.

  8. Personality Patterns of Physicians in Person-Oriented and Technique-Oriented Specialties

    ERIC Educational Resources Information Center

    Borges, Nicole J.; Gibson, Denise D.

    2005-01-01

    This study investigated differences in personality patterns between person-oriented and technique-oriented physicians. It tested an integrative framework by converting the scores on the Personality Research Form (PRF) to the Big-Five factors and built a predictive model of group membership in clinical specialty area. PRF scores from 238 physicians…

  9. Clock drift-tolerant optical bit pattern monitoring technique in asynchronous undersampling system

    NASA Astrophysics Data System (ADS)

    Zhang, Huixing; Zhao, Wei

    2011-10-01

    Based on an asynchronously undersampling system, we present a novel bit pattern monitoring technique in terms of its performance analysis and the implementation aspects. Relying upon an finite impulse response (FIR) filter assisted fine synchronization of the acquired samples, the technique can significantly reduce the random walk clock drift between data signal and sampling source compared to a conventional fine synchronization using a fixed time step. For the performance analysis of this technique, we first present an intuitive understanding of the principle of the FIR filter method under consideration of the filter frequency response. We find that the frequency response of the FIR filter simply serves to extract the spectral component at the aliasing frequency found in the periodogram and diminish all other frequency components. Then we test the tracking limit and discuss the optimized filter length choice of the new bit pattern monitoring technique through numerical examples. It turns out that the optimal filter length is chosen as the one which minimized the measured jitter and can be found iteratively. Finally, we present an experimental verification of this FIR bit pattern synchronization method by measuring and reconstructing bit patterns of 40 Gb/s nonreturn-to-zero and 160 Gb/s return-to-zero data signals, respectively.

  10. Occlusal pattern of cheek teeth in extant Spermophilus: A new approach to the identification of species.

    PubMed

    Popova, Lilia

    2016-06-01

    Discrete characters of the occlusal surface (additional cusps) have been studied to elaborate a new approach to the identification of the Ground Squirrel species Spermophilus odessanus, S. suslicus, S. pygmaeus, S. citellus, and S. xanthoprymnus. Data on the presence/absence of the additional cusps have been represented as star plots and, in addition, have been studied using discriminant function analysis. The species-specific sets of the characters (patterns of bunodonty) have been revealed and are of high diagnostic value. The Citellus-set is defined by the presence of mesostyles and the rareness of the metastylids, paraconules and metaconules, hypostyles and protostyles. The Pygmaeus-set is characterized by the presence of additional cusps in the lower cheek teeth. The Odessanus-oriented set is found in the Spermophilus pygmaeus, S. odessanus, and S. suslicus. The relatively high frequency of additional cusps of the metaloph and the paraloph is characteristic for this set. The Plesiomorphic-set (characters shared by all the studied species and for this reason regarded herein as ancestral) is found in S. xanthoprymnus. The patterns of bunodonty serve as diagnostic criteria only as a whole: the shape of a star plot (relations among the character frequencies), rather than certain character values, is indicative. An optimal level of identification of species is possible based on the combination of the discrete characters mentioned and on the size parameters of the third upper molar. The occlusal sets are intended to remain stable during the time of species existence and seem to correspond to trends in specialization. The functional meaning of the sets can be explained by the dependence between the presence/absence of the discrete characters and the shape of the crown and its main lophs. Each pattern is likely to correspond to a trophic niche, and this niche corresponds to the species. J. Morphol. 277:814-825, 2016. © 2016 Wiley Periodicals, Inc. PMID:27018323

  11. Novel On-wafer Radiation Pattern Measurement Technique for MEMS Actuator Based Reconfigurable Patch Antennas

    NASA Technical Reports Server (NTRS)

    Simons, Rainee N.

    2002-01-01

    The paper presents a novel on-wafer, antenna far field pattern measurement technique for microelectromechanical systems (MEMS) based reconfigurable patch antennas. The measurement technique significantly reduces the time and the cost associated with the characterization of printed antennas, fabricated on a semiconductor wafer or dielectric substrate. To measure the radiation patterns, the RF probe station is modified to accommodate an open-ended rectangular waveguide as the rotating linearly polarized sampling antenna. The open-ended waveguide is attached through a coaxial rotary joint to a Plexiglas(Trademark) arm and is driven along an arc by a stepper motor. Thus, the spinning open-ended waveguide can sample the relative field intensity of the patch as a function of the angle from bore sight. The experimental results include the measured linearly polarized and circularly polarized radiation patterns for MEMS-based frequency reconfigurable rectangular and polarization reconfigurable nearly square patch antennas, respectively.

  12. Novel On-Wafer Radiation Pattern Measurement Technique for MEMS Actuator Based Reconfigurable Patch Antennas

    NASA Astrophysics Data System (ADS)

    Simons, Rainee N.

    2002-10-01

    The paper presents a novel on-wafer, antenna far field pattern measurement technique for microelectromechanical systems (MEMS) based reconfigurable patch antennas. The measurement technique significantly reduces the time and the cost associated with the characterization of printed antennas, fabricated on a semiconductor wafer or dielectric substrate. To measure the radiation patterns, the RF probe station is modified to accommodate an open-ended rectangular waveguide as the rotating linearly polarized sampling antenna. The open-ended waveguide is attached through a coaxial rotary joint to a Plexiglas(Trademark) arm and is driven along an arc by a stepper motor. Thus, the spinning open-ended waveguide can sample the relative field intensity of the patch as a function of the angle from bore sight. The experimental results include the measured linearly polarized and circularly polarized radiation patterns for MEMS-based frequency reconfigurable rectangular and polarization reconfigurable nearly square patch antennas, respectively.

  13. [Methods of a posteriori identification of food patterns in Brazilian children: a systematic review].

    PubMed

    Carvalho, Carolina Abreu de; Fonsêca, Poliana Cristina de Almeida; Nobre, Luciana Neri; Priore, Silvia Eloiza; Franceschini, Sylvia do Carmo Castro

    2016-01-01

    The objective of this study is to provide guidance for identifying dietary patterns using the a posteriori approach, and analyze the methodological aspects of the studies conducted in Brazil that identified the dietary patterns of children. Articles were selected from the Latin American and Caribbean Literature on Health Sciences, Scientific Electronic Library Online and Pubmed databases. The key words were: Dietary pattern; Food pattern; Principal Components Analysis; Factor analysis; Cluster analysis; Reduced rank regression. We included studies that identified dietary patterns of children using the a posteriori approach. Seven studies published between 2007 and 2014 were selected, six of which were cross-sectional and one cohort, Five studies used the food frequency questionnaire for dietary assessment; one used a 24-hour dietary recall and the other a food list. The method of exploratory approach used in most publications was principal components factor analysis, followed by cluster analysis. The sample size of the studies ranged from 232 to 4231, the values of the Kaiser-Meyer-Olkin test from 0.524 to 0.873, and Cronbach's alpha from 0.51 to 0.69. Few Brazilian studies identified dietary patterns of children using the a posteriori approach and principal components factor analysis was the technique most used. PMID:26816172

  14. A novel jet-based nano-hydroxyapatite patterning technique for osteoblast guidance

    PubMed Central

    Li, Xiang; Koller, Garrit; Huang, Jie; Di Silvio, Lucy; Renton, Tara; Esat, Minoo; Bonfield, William; Edirisinghe, Mohan

    2010-01-01

    Surface topography is well known to play a crucial role in influencing cellular responses to an implant material and is therefore important in bone tissue regeneration. A novel jet-based patterning technique, template-assisted electrohydrodynamic atomization spraying, was recently devised to control precisely the surface structure as well as its dimensions. In the present study, a detailed investigation of this patterning process was carried out. A range of nano-hydroxyapatite (nHA) line-shaped patterns <20 µm in width were successfully deposited on a commercially pure Ti surface by controlling the flow of an nHA suspension in an electric field. In vitro studies showed that the nHA patterns generated are capable of regulating the human osteoblast cell attachment and orientation. PMID:19493897

  15. On the identification of damping from non-stationary free decay signals using modern signal processing techniques

    NASA Astrophysics Data System (ADS)

    Ramírez, Ricardo I.; Montejo, Luis A.

    2015-09-01

    A numerical implementation of system identification from non-linear and non-stationary signals is presented. The continuous wavelet transform (CWT) along with the complex Morlet wavelet skeleton curve extraction and Hilbert Transform (HT)-based methodologies are used for identification purposes. A comparison of the advantages of each technique in the analysis of non-stationary free decay systems is presented and improvements to the current methodologies are proposed. The HT approach offered good results in the estimation of the instantaneous amplitude in low damping and non-noisy signals. However, it is highly sensitive to impulses and irregularities in the signal, which affects the proper detection of frequency and amplitude parameters in real-life signals. The CWT exhibited better results for the analysis of noisy signals, from the resulting wavelet map the noise content can be distinguished from the actual system response. That is, the modes show a distinctive pattern in the map allowing proper modal extraction. However, for highly damped non-stationary decaying signals, the results are affected by the decay rate, round-up errors, and edge effects.

  16. Advanced system identification techniques for wind turbine structures with special emphasis on modal parameters

    SciTech Connect

    Bialasiewicz, J.T.

    1995-06-01

    The goal of this research is to develop advanced system identification techniques that can be used to accurately measure the frequency response functions of a wind-turbine structure immersed in wind noise. To allow for accurate identification, the authors have developed a special test signal called the Pseudo-Random Binary Sequence (PRBS). The Matlab program that generates this signal allows the user to interactively tailor its parameters for the frequency range of interest based on the response of the wind turbine under test. By controlling NREL`s Mobile Hydraulic Shaker System, which is attached to the wind turbine structure, the PRBS signal produces the wide-band excitation necessary to perform system identification in the presence of wind noise. The techniques presented here will enable researchers to obtain modal parameters from an operating wind turbine, including frequencies, damping coefficients, and mode shapes. More importantly, the algorithms they have developed and tested (so far using input-output data from a simulated structure) permit state-space representation of the system under test, particularly the modal state space representation. This is the only system description that reveals the internal behavior the system, such as the interaction between the physical parameters, and which, in contrast to transfer functions, is valid for non-zero initial conditions.

  17. Use of cluster counting technique for particle identification in a drift chamber with the cathode strip readout

    SciTech Connect

    Berdnikov, Vladimir V.; Somov, S. V.; Pentchev, Lubomir P.

    2015-07-01

    The possibility of using the clusters counting technique for particle identification in a drift chamber with the cathode strip readout is experimentally investigated. Results of counting of primary ionization clusters on a relativistic particle track, as well as results of computer simulation of pion, kaon, and proton identification in the momentum range of 1–8 GeV/c, are presented.

  18. Pattern recognition and data mining techniques to identify factors in wafer processing and control determining overlay error

    NASA Astrophysics Data System (ADS)

    Lam, Auguste; Ypma, Alexander; Gatefait, Maxime; Deckers, David; Koopman, Arne; van Haren, Richard; Beltman, Jan

    2015-03-01

    On-product overlay can be improved through the use of context data from the fab and the scanner. Continuous improvements in lithography and processing performance over the past years have resulted in consequent overlay performance improvement for critical layers. Identification of the remaining factors causing systematic disturbances and inefficiencies will further reduce overlay. By building a context database, mappings between context, fingerprints and alignment & overlay metrology can be learned through techniques from pattern recognition and data mining. We relate structure (`patterns') in the metrology data to relevant contextual factors. Once understood, these factors could be moved to the known effects (e.g. the presence of systematic fingerprints from reticle writing error or lens and reticle heating). Hence, we build up a knowledge base of known effects based on data. Outcomes from such an integral (`holistic') approach to lithography data analysis may be exploited in a model-based predictive overlay controller that combines feedback and feedforward control [1]. Hence, the available measurements from scanner, fab and metrology equipment are combined to reveal opportunities for further overlay improvement which would otherwise go unnoticed.

  19. Identification of nuclear components degradation by time-frequency ridge pattern

    SciTech Connect

    Park, G. Y.; Lee, C. K.; Kim, J. T.; Ryu, J. S.; Jung, H. S.

    2006-07-01

    A time-frequency analysis (TFA) was applies to the identification of operational status of various components of nuclear power plants, and, in this paper, the TFA is especially applied to the analysis of vibration signals from a pipe where some chemical corrosion is likely to occur by an acidic material being mixed in the coolant of nuclear power plants. A spalling out of the internal material pieces by the so-called flow-accelerated corrosion (FAC) is expected to change the structural vibration of a local point in the pipe, but this effect is too tiny to be recognized from the result of the Fourier transform [1], From the analysis by TFA, it is identified that the TFA can provide important information such as the amplitude fluctuations in the instantaneous frequency of each characteristic frequency. The analysis results show that the peak or ridge pattern of the TFA varied according to the status of the chemical corrosion within the pipe. (authors)

  20. Identification of naphthoylindoles acting on cannabinoid receptors based on their fragmentation patterns under ESI-QTOFMS.

    PubMed

    Sekuła, Karolina; Zuba, Dariusz; Stanaszek, Roman

    2012-05-01

    'Herbal highs' have been advertised as legal and natural substitutes to cannabis, but a detailed examination of these products has revealed that the herbal matrix is laced with synthetic substances that mimic the effects of marijuana. Producers select the ingredients based on the results of scientific studies on the affinities of different chemicals to cannabinoid receptors. Naphthoylindoles have turned out to be the most popular class of substances identified in the products. Legal actions taken in order to tackle the problem of uncontrolled access to one substance have usually resulted in the marketing of derivatives or analogues. In the study, the mass spectral behavior of twelve synthetic cannabinoids from the naphthoylindole family under electrospray ionization (ESI) was investigated. LC-QTOFMS experiments were performed in three modes (low fragmentor voltage, high fragmentor voltage with/without collision energy), and they enabled the identification of protonated molecules and main ions. A general fragmentation pattern under this ionization method was proposed, and mechanisms of ion formation were discussed. The developed procedure allowed the determination of substituent groups of the core naphthoylindole structure and distinction between positional isomers. The obtained results were used for the prediction of the ESI-MS spectra for many naphthoylindoles with a high affinity to cannabinoid receptors. Similarities and differences between ESI-MS and electron impact-MS spectra of naphthoylindoles were discussed. The developed identification process was presented on an example of an analysis of an unknown herbal material, in which JWH-007 was finally identified. Knowledge of the fragmentation mechanisms of naphthoylindoles could also be used by other researchers for identification of unknown substances in this chemical family. PMID:22576877

  1. Differentiation of opium and poppy straw using capillary electrophoresis and pattern recognition techniques.

    PubMed

    Reid, Raymond G; Durham, David G; Boyle, Susanne P; Low, Ann S; Wangboonskul, Jinda

    2007-12-12

    Opium samples from four different locations and poppy straw from different plant varieties have been assayed using micellar capillary electrophoresis incorporating a sweeping technique. Individual alkaloids (morphine, codeine, papaverine, noscapine, thebaine, oripavine, reticuline and narceine) were quantitatively determined in the different samples by a validated capillary electrophoresis method. Unsupervised pattern recognition of the opium samples and the poppy straw samples using hierarchical cluster analysis (HCA) and principal component analysis (PCA), showed distinct clusters. Supervised pattern recognition using soft independent modelling of class analogy (SIMCA) was performed to show individual groupings and allow unknown samples to be classified according to the models built using the CZE assay results. PMID:18022406

  2. Species Identification of Food Contaminating Beetles by Recognizing Patterns in Microscopic Images of Elytra Fragments.

    PubMed

    Park, Su Inn; Bisgin, Halil; Ding, Hongjian; Semey, Howard G; Langley, Darryl A; Tong, Weida; Xu, Joshua

    2016-01-01

    A crucial step of food contamination inspection is identifying the species of beetle fragments found in the sample, since the presence of some storage beetles is a good indicator of insanitation or potential food safety hazards. The current pratice, visual examination by human analysts, is time consuming and requires several years of experience. Here we developed a species identification algorithm which utilizes images of microscopic elytra fragments. The elytra, or hardened forewings, occupy a large portion of the body, and contain distinctive patterns. In addition, elytra fragments are more commonly recovered from processed food products than other body parts due to their hardness. As a preliminary effort, we chose 15 storage product beetle species frequently detected in food inspection. The elytra were then separated from the specimens and imaged under a microscope. Both global and local characteristics were quantified and used as feature inputs to artificial neural networks for species classification. With leave-one-out cross validation, we achieved overall accuracy of 80% through the proposed global and local features, which indicates that our proposed features could differentiate these species. Through examining the overall and per species accuracies, we further demonstrated that the local features are better suited than the global features for species identification. Future work will include robust testing with more beetle species and algorithm refinement for a higher accuracy. PMID:27341524

  3. Species Identification of Food Contaminating Beetles by Recognizing Patterns in Microscopic Images of Elytra Fragments

    PubMed Central

    Park, Su Inn; Bisgin, Halil; Ding, Hongjian; Semey, Howard G.; Langley, Darryl A.; Tong, Weida

    2016-01-01

    A crucial step of food contamination inspection is identifying the species of beetle fragments found in the sample, since the presence of some storage beetles is a good indicator of insanitation or potential food safety hazards. The current pratice, visual examination by human analysts, is time consuming and requires several years of experience. Here we developed a species identification algorithm which utilizes images of microscopic elytra fragments. The elytra, or hardened forewings, occupy a large portion of the body, and contain distinctive patterns. In addition, elytra fragments are more commonly recovered from processed food products than other body parts due to their hardness. As a preliminary effort, we chose 15 storage product beetle species frequently detected in food inspection. The elytra were then separated from the specimens and imaged under a microscope. Both global and local characteristics were quantified and used as feature inputs to artificial neural networks for species classification. With leave-one-out cross validation, we achieved overall accuracy of 80% through the proposed global and local features, which indicates that our proposed features could differentiate these species. Through examining the overall and per species accuracies, we further demonstrated that the local features are better suited than the global features for species identification. Future work will include robust testing with more beetle species and algorithm refinement for a higher accuracy. PMID:27341524

  4. A sequence identification measurement model to investigate the implicit learning of metrical temporal patterns.

    PubMed

    Schultz, Benjamin G; Stevens, Catherine J; Keller, Peter E; Tillmann, Barbara

    2013-01-01

    Implicit learning (IL) occurs unconsciously and without intention. Perceptual fluency is the ease of processing elicited by previous exposure to a stimulus. It has been assumed that perceptual fluency is associated with IL. However, the role of perceptual fluency following IL has not been investigated in temporal pattern learning. Two experiments by Schultz, Stevens, Keller, and Tillmann demonstrated the IL of auditory temporal patterns using a serial reaction-time task and a generation task based on the process dissociation procedure. The generation task demonstrated that learning was implicit in both experiments via motor fluency, that is, the inability to suppress learned information. With the aim to disentangle conscious and unconscious processes, we analyze unreported recognition data associated with the Schultz et al. experiments using the sequence identification measurement model. The model assumes that perceptual fluency reflects unconscious processes and IL. For Experiment 1, the model indicated that conscious and unconscious processes contributed to recognition of temporal patterns, but that unconscious processes had a greater influence on recognition than conscious processes. In the model implementation of Experiment 2, there was equal contribution of conscious and unconscious processes in the recognition of temporal patterns. As Schultz et al. demonstrated IL in both experiments using a generation task, and the conditions reported here in Experiments 1 and 2 were identical, two explanations are offered for the discrepancy in model and behavioral results based on the two tasks: 1) perceptual fluency may not be necessary to infer IL, or 2) conscious control over implicitly learned information may vary as a function of perceptual fluency and motor fluency. PMID:24086461

  5. Identification of natural metabolites in mixture: a pattern recognition strategy based on (13)C NMR.

    PubMed

    Hubert, Jane; Nuzillard, Jean-Marc; Purson, Sylvain; Hamzaoui, Mahmoud; Borie, Nicolas; Reynaud, Romain; Renault, Jean-Hugues

    2014-03-18

    Because of their highly complex metabolite profile, the chemical characterization of bioactive natural extracts usually requires time-consuming multistep purification procedures to achieve the structural elucidation of pure individual metabolites. The aim of the present work was to develop a dereplication strategy for the identification of natural metabolites directly within mixtures. Exploiting the polarity range of metabolites, the principle was to rapidly fractionate a multigram quantity of a crude extract by centrifugal partition extraction (CPE). The obtained fractions of simplified chemical composition were subsequently analyzed by (13)C NMR. After automatic collection and alignment of (13)C signals across spectra, hierarchical clustering analysis (HCA) was performed for pattern recognition. As a result, strong correlations between (13)C signals of a single structure within the mixtures of the fraction series were visualized as chemical shift clusters. Each cluster was finally assigned to a molecular structure with the help of a locally built (13)C NMR chemical shift database. The proof of principle of this strategy was achieved on a simple model mixture of commercially available plant secondary metabolites and then applied to a bark extract of the African tree Anogeissus leiocarpus Guill. & Perr. (Combretaceae). Starting from 5 g of this genuine extract, the fraction series was generated by CPE in only 95 min. (13)C NMR analyses of all fractions followed by pattern recognition of (13)C chemical shifts resulted in the unambiguous identification of seven major compounds, namely, sericoside, trachelosperogenin E, ellagic acid, an epimer mixture of (+)-gallocatechin and (-)-epigallocatechin, 3,3'-di-O-methylellagic acid 4'-O-xylopyranoside, and 3,4,3'-tri-O-methylflavellagic acid 4'-O-glucopyranoside. PMID:24555703

  6. Identification and quantification of individual volatile organic compounds in a binary mixture by SAW multisensor array and pattern recognition analysis

    NASA Astrophysics Data System (ADS)

    Penza, M.; Cassano, G.; Tortorella, F.

    2002-06-01

    We have developed a surface acoustic wave (SAW) multisensor array with five acoustic sensing elements configured as two-port resonator 433.92 MHz oscillators and a reference SAW element to recognize different individual components and determine their concentrations in a binary mixture of volatile organic compounds (VOCs) such as methanol and acetone, in the ranges 15-130 and 50-250 ppm, respectively. The SAW sensors have been specifically coated by various sensing thin films such as arachidic acid, carbowax, behenic acid, triethanolamine or acrylated polysiloxane, operating at room temperature. By using the relative frequency change as the output signal of the SAW multisensor array with an artificial neural network (ANN), a recognition system has been realized for the identification and quantification of tested VOCs. The features of the SAW multisensor array exposed to a binary component organic mixture of methanol and acetone have been extracted from the output signals of five SAW sensors by pattern recognition (PARC) techniques, such as principal component analysis (PCA). An organic vapour pattern classifier has been implemented by using a multilayer neural network with a backpropagation learning algorithm. The normalized responses of a reduced set of SAW sensors or selected principal components scores have been used as inputs for a feed-forward multilayer perceptron (MLP), resulting in a 70% correct recognition rate with the normalized responses of the four SAW sensors and in an enhanced 80% correct recognition rate with the first two principal components of the original data consisting of the normalized responses of the four SAW sensors. The prediction of the individual vapour concentrations has been tackled with PCA for features extraction and by using the first two principal components scores as inputs to a feed-forward MLP consisting of a gating network, which decides which of three specific subnets should be used to determine the output concentration: the

  7. [Molecular techniques for detection and identification of pathogens in food: advantages and limitations].

    PubMed

    Palomino-Camargo, Carolina; González-Muñoz, Yuniesky

    2014-01-01

    Foodborne diseases, caused by pathogenic microorganisms, are a major public health problem worldwide. Microbiological methods commonly used in the detection of these foodborne pathogens are laborious and time consuming. This situation, coupled with the demand for immediate results and with technological advances, has led to the development of a wide range of rapid methods in recent decades. On this basis, this review describes the advantages and limitations of the main molecular methods used in detection and identification of foodborne pathogens. To this end, we considered how recent the information was published, the objective analysis of the topic and its scope. Recent literature reports a significant number of alternative, sensitive and selective molecular techniques for detection, enumeration and identification of pathogenic microorganisms in food. Polymerase chain reaction (PCR) is the most popular platform, while high performance sequencing is emerging as a technique of wide applicability for the future. However, even with all the advantages of these new methodologies, their limitations should not be overlooked. For example, molecular methods are not standardized protocols, which hinders its use in some cases. For this reason, hard work should be done to overcome these limitations and improve the application of these techniques in complex matrices such as food systems. PMID:25418655

  8. Neutron Detection With Ultra-Fast Digitizer and Pulse Identification Techniques on DIII-D

    NASA Astrophysics Data System (ADS)

    Zhu, Y. B.; Heidbrink, W. W.; Piglowski, D. A.

    2013-10-01

    A prototype system for neutron detection with an ultra-fast digitizer and pulse identification techniques has been implemented on the DIII-D tokamak. The system consists of a cylindrical neutron fission chamber, a charge sensitive amplifier, and a GaGe Octopus 12-bit CompuScope digitizer card installed in a Linux computer. Digital pulse identification techniques have been successfully performed at maximum data acquisition rate of 50 MSPS with on-board memory of 2 GS. Compared to the traditional approach with fast nuclear electronics for pulse counting, this straightforward digital solution has many advantages, including reduced expense, improved accuracy, higher counting rate, and easier maintenance. The system also provides the capability of neutron-gamma pulse shape discrimination and pulse height analysis. Plans for the upgrade of the old DIII-D neutron counting system with these techniques will be presented. Work supported by the US Department of Energy under SC-G903402, and DE-FC02-04ER54698.

  9. Identification of disease-related spatial covariance patterns using neuroimaging data.

    PubMed

    Spetsieris, Phoebe; Ma, Yilong; Peng, Shichun; Ko, Ji Hyun; Dhawan, Vijay; Tang, Chris C; Eidelberg, David

    2013-01-01

    The scaled subprofile model (SSM)(1-4) is a multivariate PCA-based algorithm that identifies major sources of variation in patient and control group brain image data while rejecting lesser components (Figure 1). Applied directly to voxel-by-voxel covariance data of steady-state multimodality images, an entire group image set can be reduced to a few significant linearly independent covariance patterns and corresponding subject scores. Each pattern, termed a group invariant subprofile (GIS), is an orthogonal principal component that represents a spatially distributed network of functionally interrelated brain regions. Large global mean scalar effects that can obscure smaller network-specific contributions are removed by the inherent logarithmic conversion and mean centering of the data(2,5,6). Subjects express each of these patterns to a variable degree represented by a simple scalar score that can correlate with independent clinical or psychometric descriptors(7,8). Using logistic regression analysis of subject scores (i.e. pattern expression values), linear coefficients can be derived to combine multiple principal components into single disease-related spatial covariance patterns, i.e. composite networks with improved discrimination of patients from healthy control subjects(5,6). Cross-validation within the derivation set can be performed using bootstrap resampling techniques(9). Forward validation is easily confirmed by direct score evaluation of the derived patterns in prospective datasets(10). Once validated, disease-related patterns can be used to score individual patients with respect to a fixed reference sample, often the set of healthy subjects that was used (with the disease group) in the original pattern derivation(11). These standardized values can in turn be used to assist in differential diagnosis(12,13) and to assess disease progression and treatment effects at the network level(7,14-16). We present an example of the application of this methodology to

  10. Comparative study of optical-digital vs all-digital techniques in textural pattern recognition

    NASA Astrophysics Data System (ADS)

    Otoole, R. K.; Stark, H.

    1980-08-01

    The application of both optical-digital and all-digital techniques in textural pattern recognition is examined and a comparison of the two approaches is made. The optical-digital scheme makes use of an optical-digital computer to generate textural measurements based on the 2-D irradiance spectrum. The all-digital scheme produces measurements based on gray-tone spatial-dependence matrices. In both cases two feature extraction algorithms were employed: the Hotelling trace method and the Foley-Sammon discriminant vector analysis. Classification was accomplished using the k-nearest neighbor decision rule. The performance of these techniques was evaluated in an experiment involving the classification of four texture patterns. The results show that, for the textures chosen, both approaches give high classification accuracy with the optical-digital method performing somewhat better.