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Sample records for feature-based discriminative method

  1. Feature-based Detection and Discrimination at DuPont's Lake Success Business Park, Connecticut

    National Research Council Canada - National Science Library

    Keiswetter, Dean A

    2007-01-01

    The objective of this demonstration was to determine if laser-positioned, high-density EM61 data acquired in a moving survey mode could support feature-based discrimination decisions for a canopied...

  2. Gas Classification Using Combined Features Based on a Discriminant Analysis for an Electronic Nose

    Directory of Open Access Journals (Sweden)

    Sang-Il Choi

    2016-01-01

    Full Text Available This paper proposes a gas classification method for an electronic nose (e-nose system, for which combined features that have been configured through discriminant analysis are used. First, each global feature is extracted from the entire measurement section of the data samples, while the same process is applied to the local features of the section that corresponds to the stabilization, exposure, and purge stages. The discriminative information amounts in the individual features are then measured based on the discriminant analysis, and the combined features are subsequently composed by selecting the features that have a large amount of discriminative information. Regarding a variety of volatile organic compound data, the results of the experiment show that, in a noisy environment, the proposed method exhibits classification performance that is relatively excellent compared to the other feature types.

  3. A Two-Dimensional Solar Tracking Stationary Guidance Method Based on Feature-Based Time Series

    Directory of Open Access Journals (Sweden)

    Keke Zhang

    2018-01-01

    Full Text Available The amount of satellite energy acquired has a direct impact on operational capacities of the satellite. As for practical high functional density microsatellites, solar tracking guidance design of solar panels plays an extremely important role. Targeted at stationary tracking problems incurred in a new system that utilizes panels mounted in the two-dimensional turntable to acquire energies to the greatest extent, a two-dimensional solar tracking stationary guidance method based on feature-based time series was proposed under the constraint of limited satellite attitude coupling control capability. By analyzing solar vector variation characteristics within an orbit period and solar vector changes within the whole life cycle, such a method could be adopted to establish a two-dimensional solar tracking guidance model based on the feature-based time series to realize automatic switching of feature-based time series and stationary guidance under the circumstance of different β angles and the maximum angular velocity control, which was applicable to near-earth orbits of all orbital inclination. It was employed to design a two-dimensional solar tracking stationary guidance system, and a mathematical simulation for guidance performance was carried out in diverse conditions under the background of in-orbit application. The simulation results show that the solar tracking accuracy of two-dimensional stationary guidance reaches 10∘ and below under the integrated constraints, which meet engineering application requirements.

  4. A circular feature-based pose measurement method for metal part grasping

    International Nuclear Information System (INIS)

    Wu, Chenrui; He, Zaixing; Zhang, Shuyou; Zhao, Xinyue

    2017-01-01

    The grasping of circular metal parts such as bearings and flanges is a common task in industry. Limited by low texture and repeated features, the point-feature-based method is not applicable in pose measurement of these parts. In this paper, we propose a novel pose measurement method for grasping circular metal parts. This method is based on cone degradation and involves a monocular camera. To achieve higher measurement accuracy, a position-based visual servoing method is presented to continuously control an eye-in-hand, six-degrees-of-freedom robot arm to grasp the part. The uncertainty of the part’s coordinate frame during the control process is solved by defining a fixed virtual coordinate frame. Experimental results are provided to illustrate the effectiveness of the proposed method and the factors that affect measurement accuracy are analyzed. (paper)

  5. Examining Brain Morphometry Associated with Self-Esteem in Young Adults Using Multilevel-ROI-Features-Based Classification Method

    Directory of Open Access Journals (Sweden)

    Bo Peng

    2017-05-01

    Full Text Available Purpose: This study is to exam self-esteem related brain morphometry on brain magnetic resonance (MR images using multilevel-features-based classification method.Method: The multilevel region of interest (ROI features consist of two types of features: (i ROI features, which include gray matter volume, white matter volume, cerebrospinal fluid volume, cortical thickness, and cortical surface area, and (ii similarity features, which are based on similarity calculation of cortical thickness between ROIs. For each feature type, a hybrid feature selection method, comprising of filter-based and wrapper-based algorithms, is used to select the most discriminating features. ROI features and similarity features are integrated by using multi-kernel support vector machines (SVMs with appropriate weighting factor.Results: The classification performance is improved by using multilevel ROI features with an accuracy of 96.66%, a specificity of 96.62%, and a sensitivity of 95.67%. The most discriminating ROI features that are related to self-esteem spread over occipital lobe, frontal lobe, parietal lobe, limbic lobe, temporal lobe, and central region, mainly involving white matter and cortical thickness. The most discriminating similarity features are distributed in both the right and left hemisphere, including frontal lobe, occipital lobe, limbic lobe, parietal lobe, and central region, which conveys information of structural connections between different brain regions.Conclusion: By using ROI features and similarity features to exam self-esteem related brain morphometry, this paper provides a pilot evidence that self-esteem is linked to specific ROIs and structural connections between different brain regions.

  6. A line feature-based camera tracking method applicable to nuclear power plant environment

    International Nuclear Information System (INIS)

    Yan, Weida; Ishii, Hirotake; Shimoda, Hiroshi; Izumi, Masanori

    2014-01-01

    Augmented reality, which can support the maintenance and decommissioning work of an NPP to improve efficiency and reduce human error, is expected to be practically used in an NPP. AR has indispensable tracking technology that estimates the 3D position and orientation of users in real time, but because of the complication of the NPP environment, it is difficult for its practial use in the large space of an NPP. This study attempt to develop a tracking method for the practial use in an NPP. Marker tracking is a legacy tracking method, but the preparation work necessary for that method is onerous. Therefore, this study developed and evaluated a natural feature-based camera tracking method that demands less preparation and which is applicable in an NPP environment. This method registers natural features as landmarks. When tracking, the natural features existing in the NPP environment can be registered automatically as landmarks. It is therefore possible to expand the tracking area to cover a wide environment in theory. The evaluation result shows that the proposed tracking method has the possibility to support field work of some kinds in an NPP environment. It is possible to reduce the preparation work necessary for the marker tracking method. (author)

  7. Multiple-Features-Based Semisupervised Clustering DDoS Detection Method

    Directory of Open Access Journals (Sweden)

    Yonghao Gu

    2017-01-01

    Full Text Available DDoS attack stream from different agent host converged at victim host will become very large, which will lead to system halt or network congestion. Therefore, it is necessary to propose an effective method to detect the DDoS attack behavior from the massive data stream. In order to solve the problem that large numbers of labeled data are not provided in supervised learning method, and the relatively low detection accuracy and convergence speed of unsupervised k-means algorithm, this paper presents a semisupervised clustering detection method using multiple features. In this detection method, we firstly select three features according to the characteristics of DDoS attacks to form detection feature vector. Then, Multiple-Features-Based Constrained-K-Means (MF-CKM algorithm is proposed based on semisupervised clustering. Finally, using MIT Laboratory Scenario (DDoS 1.0 data set, we verify that the proposed method can improve the convergence speed and accuracy of the algorithm under the condition of using a small amount of labeled data sets.

  8. Stego Keys Performance on Feature Based Coding Method in Text Domain

    Directory of Open Access Journals (Sweden)

    Din Roshidi

    2017-01-01

    Full Text Available A main critical factor on embedding process in any text steganography method is a key used known as stego key. This factor will be influenced the success of the embedding process of text steganography method to hide a message from third party or any adversary. One of the important aspects on embedding process in text steganography method is the fitness performance of the stego key. Three parameters of the fitness performance of the stego key have been identified such as capacity ratio, embedded fitness ratio and saving space ratio. It is because a better as capacity ratio, embedded fitness ratio and saving space ratio offers of any stego key; a more message can be hidden. Therefore, main objective of this paper is to analyze three features coding based namely CALP, VERT and QUAD of stego keys in text steganography on their capacity ratio, embedded fitness ratio and saving space ratio. It is found that CALP method give a good effort performance compared to VERT and QUAD methods.

  9. Comparing writing style feature-based classification methods for estimating user reputations in social media.

    Science.gov (United States)

    Suh, Jong Hwan

    2016-01-01

    In recent years, the anonymous nature of the Internet has made it difficult to detect manipulated user reputations in social media, as well as to ensure the qualities of users and their posts. To deal with this, this study designs and examines an automatic approach that adopts writing style features to estimate user reputations in social media. Under varying ways of defining Good and Bad classes of user reputations based on the collected data, it evaluates the classification performance of the state-of-art methods: four writing style features, i.e. lexical, syntactic, structural, and content-specific, and eight classification techniques, i.e. four base learners-C4.5, Neural Network (NN), Support Vector Machine (SVM), and Naïve Bayes (NB)-and four Random Subspace (RS) ensemble methods based on the four base learners. When South Korea's Web forum, Daum Agora, was selected as a test bed, the experimental results show that the configuration of the full feature set containing content-specific features and RS-SVM combining RS and SVM gives the best accuracy for classification if the test bed poster reputations are segmented strictly into Good and Bad classes by portfolio approach. Pairwise t tests on accuracy confirm two expectations coming from the literature reviews: first, the feature set adding content-specific features outperform the others; second, ensemble learning methods are more viable than base learners. Moreover, among the four ways on defining the classes of user reputations, i.e. like, dislike, sum, and portfolio, the results show that the portfolio approach gives the highest accuracy.

  10. A multilevel-ROI-features-based machine learning method for detection of morphometric biomarkers in Parkinson's disease.

    Science.gov (United States)

    Peng, Bo; Wang, Suhong; Zhou, Zhiyong; Liu, Yan; Tong, Baotong; Zhang, Tao; Dai, Yakang

    2017-06-09

    Machine learning methods have been widely used in recent years for detection of neuroimaging biomarkers in regions of interest (ROIs) and assisting diagnosis of neurodegenerative diseases. The innovation of this study is to use multilevel-ROI-features-based machine learning method to detect sensitive morphometric biomarkers in Parkinson's disease (PD). Specifically, the low-level ROI features (gray matter volume, cortical thickness, etc.) and high-level correlative features (connectivity between ROIs) are integrated to construct the multilevel ROI features. Filter- and wrapper- based feature selection method and multi-kernel support vector machine (SVM) are used in the classification algorithm. T1-weighted brain magnetic resonance (MR) images of 69 PD patients and 103 normal controls from the Parkinson's Progression Markers Initiative (PPMI) dataset are included in the study. The machine learning method performs well in classification between PD patients and normal controls with an accuracy of 85.78%, a specificity of 87.79%, and a sensitivity of 87.64%. The most sensitive biomarkers between PD patients and normal controls are mainly distributed in frontal lobe, parental lobe, limbic lobe, temporal lobe, and central region. The classification performance of our method with multilevel ROI features is significantly improved comparing with other classification methods using single-level features. The proposed method shows promising identification ability for detecting morphometric biomarkers in PD, thus confirming the potentiality of our method in assisting diagnosis of the disease. Copyright © 2017 Elsevier B.V. All rights reserved.

  11. Line-feature-based calibration method of structured light plane parameters for robot hand-eye system

    Science.gov (United States)

    Qi, Yuhan; Jing, Fengshui; Tan, Min

    2013-03-01

    For monocular-structured light vision measurement, it is essential to calibrate the structured light plane parameters in addition to the camera intrinsic parameters. A line-feature-based calibration method of structured light plane parameters for a robot hand-eye system is proposed. Structured light stripes are selected as calibrating primitive elements, and the robot moves from one calibrating position to another with constraint in order that two misaligned stripe lines are generated. The images of stripe lines could then be captured by the camera fixed at the robot's end link. During calibration, the equations of two stripe lines in the camera coordinate system are calculated, and then the structured light plane could be determined. As the robot's motion may affect the effectiveness of calibration, so the robot's motion constraints are analyzed. A calibration experiment and two vision measurement experiments are implemented, and the results reveal that the calibration accuracy can meet the precision requirement of robot thick plate welding. Finally, analysis and discussion are provided to illustrate that the method has a high efficiency fit for industrial in-situ calibration.

  12. Improved initial guess with semi-subpixel level accuracy in digital image correlation by feature-based method

    Science.gov (United States)

    Zhang, Yunlu; Yan, Lei; Liou, Frank

    2018-05-01

    The quality initial guess of deformation parameters in digital image correlation (DIC) has a serious impact on convergence, robustness, and efficiency of the following subpixel level searching stage. In this work, an improved feature-based initial guess (FB-IG) scheme is presented to provide initial guess for points of interest (POIs) inside a large region. Oriented FAST and Rotated BRIEF (ORB) features are semi-uniformly extracted from the region of interest (ROI) and matched to provide initial deformation information. False matched pairs are eliminated by the novel feature guided Gaussian mixture model (FG-GMM) point set registration algorithm, and nonuniform deformation parameters of the versatile reproducing kernel Hilbert space (RKHS) function are calculated simultaneously. Validations on simulated images and real-world mini tensile test verify that this scheme can robustly and accurately compute initial guesses with semi-subpixel level accuracy in cases with small or large translation, deformation, or rotation.

  13. Functional discriminant method and neuronal net

    International Nuclear Information System (INIS)

    Minh-Quan Tran.

    1993-02-01

    The ZEUS detector at the ep storage ring HERA at DESY is equipped with a 3 level trigger system. This enormous effort is necessary to fight against the high proton beamgas background that was estimated to be at the level of 100 kHz. In this thesis two methods were investigated to calculate a trigger decision from a set of various trigger parameters. The Functional Discriminant Analysis evalutes a decision parameter that is optimized by means of a linear algebra technic. A method is shown how to determine the most important trigger parameters. A 'feed forward' neuralnetwork was analyzed in order to allow none lineare cuts in the n dimensinal configuration space spanned by the trigger parameters. The error back propagation method was used to teach the neural network. It is shown that both decision methods are able to abstract the important characteristics of event samples. As soon as they are tought they will seperate events from these classes even though they were not part of the training sample. (orig.) [de

  14. Discriminant forest classification method and system

    Science.gov (United States)

    Chen, Barry Y.; Hanley, William G.; Lemmond, Tracy D.; Hiller, Lawrence J.; Knapp, David A.; Mugge, Marshall J.

    2012-11-06

    A hybrid machine learning methodology and system for classification that combines classical random forest (RF) methodology with discriminant analysis (DA) techniques to provide enhanced classification capability. A DA technique which uses feature measurements of an object to predict its class membership, such as linear discriminant analysis (LDA) or Andersen-Bahadur linear discriminant technique (AB), is used to split the data at each node in each of its classification trees to train and grow the trees and the forest. When training is finished, a set of n DA-based decision trees of a discriminant forest is produced for use in predicting the classification of new samples of unknown class.

  15. Horse breed discrimination using machine learning methods

    Czech Academy of Sciences Publication Activity Database

    Burócziová, Monika; Riha, J.

    2009-01-01

    Roč. 50, č. 4 (2009), s. 375-377 ISSN 1234-1983 Institutional research plan: CEZ:AV0Z50450515 Keywords : Breed discrimination * Genetics diversity * Horse breeds Subject RIV: EG - Zoology Impact factor: 1.324, year: 2009

  16. A Method for Extracting Suspected Parotid Lesions in CT Images using Feature-based Segmentation and Active Contours based on Stationary Wavelet Transform

    Science.gov (United States)

    Wu, T. Y.; Lin, S. F.

    2013-10-01

    Automatic suspected lesion extraction is an important application in computer-aided diagnosis (CAD). In this paper, we propose a method to automatically extract the suspected parotid regions for clinical evaluation in head and neck CT images. The suspected lesion tissues in low contrast tissue regions can be localized with feature-based segmentation (FBS) based on local texture features, and can be delineated with accuracy by modified active contour models (ACM). At first, stationary wavelet transform (SWT) is introduced. The derived wavelet coefficients are applied to derive the local features for FBS, and to generate enhanced energy maps for ACM computation. Geometric shape features (GSFs) are proposed to analyze each soft tissue region segmented by FBS; the regions with higher similarity GSFs with the lesions are extracted and the information is also applied as the initial conditions for fine delineation computation. Consequently, the suspected lesions can be automatically localized and accurately delineated for aiding clinical diagnosis. The performance of the proposed method is evaluated by comparing with the results outlined by clinical experts. The experiments on 20 pathological CT data sets show that the true-positive (TP) rate on recognizing parotid lesions is about 94%, and the dimension accuracy of delineation results can also approach over 93%.

  17. A quantitative method for determining spatial discriminative capacity

    Directory of Open Access Journals (Sweden)

    Dennis Robert G

    2008-03-01

    Full Text Available Abstract Background The traditional two-point discrimination (TPD test, a widely used tactile spatial acuity measure, has been criticized as being imprecise because it is based on subjective criteria and involves a number of non-spatial cues. The results of a recent study showed that as two stimuli were delivered simultaneously, vibrotactile amplitude discrimination became worse when the two stimuli were positioned relatively close together and was significantly degraded when the probes were within a subject's two-point limen. The impairment of amplitude discrimination with decreasing inter-probe distance suggested that the metric of amplitude discrimination could possibly provide a means of objective and quantitative measurement of spatial discrimination capacity. Methods A two alternative forced-choice (2AFC tracking procedure was used to assess a subject's ability to discriminate the amplitude difference between two stimuli positioned at near-adjacent skin sites. Two 25 Hz flutter stimuli, identical except for a constant difference in amplitude, were delivered simultaneously to the hand dorsum. The stimuli were initially spaced 30 mm apart, and the inter-stimulus distance was modified on a trial-by-trial basis based on the subject's performance of discriminating the stimulus with higher intensity. The experiment was repeated via sequential, rather than simultaneous, delivery of the same vibrotactile stimuli. Results Results obtained from this study showed that the performance of the amplitude discrimination task was significantly degraded when the stimuli were delivered simultaneously and were near a subject's two-point limen. In contrast, subjects were able to correctly discriminate between the amplitudes of the two stimuli when they were sequentially delivered at all inter-probe distances (including those within the two-point limen, and improved when an adapting stimulus was delivered prior to simultaneously delivered stimuli. Conclusion

  18. The use of the discriminant analysis method for e π μ separation in BES

    International Nuclear Information System (INIS)

    Jiang Zhijin; Wang Taijie; Xie Yigang; Huang Tao

    1994-01-01

    We use the discriminant analysis method in multivariate statistical theory to handle the e π μ separation in BES, describing the principle of the discriminant analysis method, deriving the unstandardized discriminant functions (responsible for particle separation), giving the discriminant efficiency for e π μ and comparing the results from the discriminant analysis method with those obtained in a conventional way. ((orig.))

  19. Discrimination symbol applying method for sintered nuclear fuel product

    International Nuclear Information System (INIS)

    Ishizaki, Jin

    1998-01-01

    The present invention provides a symbol applying method for applying discrimination information such as an enrichment degree on the end face of a sintered nuclear product. Namely, discrimination symbols of information of powders are applied by a sintering aid to the end face of a molded member formed by molding nuclear fuel powders under pressure. Then, the molded product is sintered. The sintering aid comprises aluminum oxide, a mixture of aluminum oxide and silicon dioxide, aluminum hydride or aluminum stearate alone or in admixture. As an applying means of the sintering aid, discrimination symbols of information of powders are drawn by an isostearic acid on the end face of the molded product, and the sintering aid is sprayed thereto, or the sintering aid is applied directly, or the sintering aid is suspended in isostearic acid, and the suspension is applied with a brush. As a result, visible discrimination information can be applied to the sintered member easily. (N.H.)

  20. Neutron spectrum measurement using rise-time discrimination method

    International Nuclear Information System (INIS)

    Luo Zhiping; Suzuki, C.; Kosako, T.; Ma Jizeng

    2009-01-01

    PSD method can be used to measure the fast neutron spectrum in n/γ mixed field. A set of assemblies for measuring the pulse height distribution of neutrons is built up,based on a large volume NE213 liquid scintillator and standard NIM circuits,through the rise-time discrimination method. After that,the response matrix is calculated using Monte Carlo method. The energy calibration of the pulse height distribution is accomplished using 60 Co radioisotope. The neutron spectrum of the mono-energetic accelerator neutron source is achieved by unfolding process. Suggestions for further improvement of the system are presented at last. (authors)

  1. Statistical methods of discrimination and classification advances in theory and applications

    CERN Document Server

    Choi, Sung C

    1986-01-01

    Statistical Methods of Discrimination and Classification: Advances in Theory and Applications is a collection of papers that tackles the multivariate problems of discriminating and classifying subjects into exclusive population. The book presents 13 papers that cover that advancement in the statistical procedure of discriminating and classifying. The studies in the text primarily focus on various methods of discriminating and classifying variables, such as multiple discriminant analysis in the presence of mixed continuous and categorical data; choice of the smoothing parameter and efficiency o

  2. Discriminative power of Campylobacter phenotypic and genotypic typing methods.

    Science.gov (United States)

    Duarte, Alexandra; Seliwiorstow, Tomasz; Miller, William G; De Zutter, Lieven; Uyttendaele, Mieke; Dierick, Katelijne; Botteldoorn, Nadine

    2016-06-01

    The aim of this study was to compare different typing methods, individually and combined, for use in the monitoring of Campylobacter in food. Campylobacter jejuni (n=94) and Campylobacter coli (n=52) isolated from different broiler meat carcasses were characterized using multilocus sequence typing (MLST), flagellin gene A restriction fragment length polymorphism typing (flaA-RFLP), antimicrobial resistance profiling (AMRp), the presence/absence of 5 putative virulence genes; and, exclusively for C. jejuni, the determination of lipooligosaccharide (LOS) class. Discriminatory power was calculated by the Simpson's index of diversity (SID) and the congruence was measured by the adjusted Rand index and adjusted Wallace coefficient. MLST was individually the most discriminative typing method for both C. jejuni (SID=0.981) and C. coli (SID=0.957). The most discriminative combination with a SID of 0.992 for both C. jejuni and C. coli was obtained by combining MLST with flaA-RFLP. The combination of MLST with flaA-RFLP is an easy and feasible typing method for short-term monitoring of Campylobacter in broiler meat carcass. Copyright © 2016 Elsevier B.V. All rights reserved.

  3. Investigation on n/γ discrimination methods for liquid scintillator detector

    International Nuclear Information System (INIS)

    Li Kuinian; Li Yang; Zhang Mei; Zhang Zhongbing; Li Binkang; Zhang Xiaodong; Liu Jun; Zhang Xianpeng

    2014-01-01

    To obtain the n/γ discrimination ability of different digital pulse shape discrimination methods, four methods (rising time method, charge comparison method, pulse gradient analysis and frequency gradient analysis) in americium-beryllium mixed radiation fields were demonstrated. The signals from EJ-301 and BC501A scintillator detectors were digitized using oscilloscope. A comparison was taken among the four discrimination methods. The discrimination results of the four methods in liquid scintillator detectors show that the rising time method is the best and it provides a good choice in real-time n/γ discrimination system. (authors)

  4. Using discriminant analysis as a nucleation event classification method

    Directory of Open Access Journals (Sweden)

    S. Mikkonen

    2006-01-01

    Full Text Available More than three years of measurements of aerosol size-distribution and different gas and meteorological parameters made in Po Valley, Italy were analysed for this study to examine which of the meteorological and trace gas variables effect on the emergence of nucleation events. As the analysis method, we used discriminant analysis with non-parametric Epanechnikov kernel, included in non-parametric density estimation method. The best classification result in our data was reached with the combination of relative humidity, ozone concentration and a third degree polynomial of radiation. RH appeared to have a preventing effect on the new particle formation whereas the effects of O3 and radiation were more conductive. The concentration of SO2 and NO2 also appeared to have significant effect on the emergence of nucleation events but because of the great amount of missing observations, we had to exclude them from the final analysis.

  5. Review of research in feature based design

    NARCIS (Netherlands)

    Salomons, O.W.; van Houten, Frederikus J.A.M.; Kals, H.J.J.

    1993-01-01

    Research in feature-based design is reviewed. Feature-based design is regarded as a key factor towards CAD/CAPP integration from a process planning point of view. From a design point of view, feature-based design offers possibilities for supporting the design process better than current CAD systems

  6. A Fast and Robust Feature-Based Scan-Matching Method in 3D SLAM and the Effect of Sampling Strategies

    Directory of Open Access Journals (Sweden)

    Cihan Ulas

    2013-11-01

    Full Text Available Simultaneous localization and mapping (SLAM plays an important role in fully autonomous systems when a GNSS (global navigation satellite system is not available. Studies in both 2D indoor and 3D outdoor SLAM are based on the appearance of environments and utilize scan-matching methods to find rigid body transformation parameters between two consecutive scans. In this study, a fast and robust scan-matching method based on feature extraction is introduced. Since the method is based on the matching of certain geometric structures, like plane segments, the outliers and noise in the point cloud are considerably eliminated. Therefore, the proposed scan-matching algorithm is more robust than conventional methods. Besides, the registration time and the number of iterations are significantly reduced, since the number of matching points is efficiently decreased. As a scan-matching framework, an improved version of the normal distribution transform (NDT is used. The probability density functions (PDFs of the reference scan are generated as in the traditional NDT, and the feature extraction - based on stochastic plane detection - is applied to the only input scan. By using experimental dataset belongs to an outdoor environment like a university campus, we obtained satisfactory performance results. Moreover, the feature extraction part of the algorithm is considered as a special sampling strategy for scan-matching and compared to other sampling strategies, such as random sampling and grid-based sampling, the latter of which is first used in the NDT. Thus, this study also shows the effect of the subsampling on the performance of the NDT.

  7. Method and apparatus for sub-hysteresis discrimination

    Science.gov (United States)

    De Geronimo, Gianluigi

    2015-12-29

    Embodiments of comparator circuits are disclosed. A comparator circuit may include a differential input circuit, an output circuit, a positive feedback circuit operably coupled between the differential input circuit and the output circuit, and a hysteresis control circuit operably coupled with the positive feedback circuit. The hysteresis control circuit includes a switching device and a transistor. The comparator circuit provides sub-hysteresis discrimination and high speed discrimination.

  8. Research on n-γ discrimination method based on spectrum gradient analysis of signals

    International Nuclear Information System (INIS)

    Luo Xiaoliang; Liu Guofu; Yang Jun; Wang Yueke

    2013-01-01

    Having discovered that there are distinct differences between the spectrum gradient of the output neutron and γ-ray signal from liquid scintillator detectors, this paper presented a n-γ discrimination method called spectrum gradient analysis (SGA) based on frequency-domain features of the pulse signals. The basic principle and feasibility of SGA method were discussed and the validity of n-γ discrimination results of SGA was verified by the associated particle neutron flight experiment. The discrimination performance of SGA was evaluated under different conditions of sampling rates ranging from 5 G/s to 250 M/s. The results show that SGA method exhibits insensitivity to noise, strong anti-interference ability, stable discrimination performance and lower amount of calculation in contrast with time-domain n-γ discrimination methods. (authors)

  9. Phylogenetic comparative methods complement discriminant function analysis in ecomorphology.

    Science.gov (United States)

    Barr, W Andrew; Scott, Robert S

    2014-04-01

    In ecomorphology, Discriminant Function Analysis (DFA) has been used as evidence for the presence of functional links between morphometric variables and ecological categories. Here we conduct simulations of characters containing phylogenetic signal to explore the performance of DFA under a variety of conditions. Characters were simulated using a phylogeny of extant antelope species from known habitats. Characters were modeled with no biomechanical relationship to the habitat category; the only sources of variation were body mass, phylogenetic signal, or random "noise." DFA on the discriminability of habitat categories was performed using subsets of the simulated characters, and Phylogenetic Generalized Least Squares (PGLS) was performed for each character. Analyses were repeated with randomized habitat assignments. When simulated characters lacked phylogenetic signal and/or habitat assignments were random, ecomorphology. Copyright © 2013 Wiley Periodicals, Inc.

  10. Discrimination of Semi-Quantitative Models by Experiment Selection: Method Application in Population Biology

    NARCIS (Netherlands)

    Vatcheva, Ivayla; Bernard, Olivier; de Jong, Hidde; Gouze, Jean-Luc; Mars, Nicolaas; Nebel, B.

    2001-01-01

    Modeling an experimental system often results in a number of alternative models that are justified equally well by the experimental data. In order to discriminate between these models, additional experiments are needed. We present a method for the discrimination of models in the form of

  11. Feature-based RNN target recognition

    Science.gov (United States)

    Bakircioglu, Hakan; Gelenbe, Erol

    1998-09-01

    Detection and recognition of target signatures in sensory data obtained by synthetic aperture radar (SAR), forward- looking infrared, or laser radar, have received considerable attention in the literature. In this paper, we propose a feature based target classification methodology to detect and classify targets in cluttered SAR images, that makes use of selective signature data from sensory data, together with a neural network technique which uses a set of trained networks based on the Random Neural Network (RNN) model (Gelenbe 89, 90, 91, 93) which is trained to act as a matched filter. We propose and investigate radial features of target shapes that are invariant to rotation, translation, and scale, to characterize target and clutter signatures. These features are then used to train a set of learning RNNs which can be used to detect targets within clutter with high accuracy, and to classify the targets or man-made objects from natural clutter. Experimental data from SAR imagery is used to illustrate and validate the proposed method, and to calculate Receiver Operating Characteristics which illustrate the performance of the proposed algorithm.

  12. Pulse-shape discrimination in radioanalytical methods. Part I. Delayed fission neutron counting

    International Nuclear Information System (INIS)

    Posta, S.; Vacik, J.; Hnatowicz, V.; Cervena, J.

    1999-01-01

    In this study the principle of pulse shape discrimination (PSD) has been employed in delayed fission neutron counting (DNC) method. Effective elimination of unwanted gamma background signals in measured radiation spectra has been proved. (author)

  13. Wavelet transform and real-time learning method for myoelectric signal in motion discrimination

    International Nuclear Information System (INIS)

    Liu Haihua; Chen Xinhao; Chen Yaguang

    2005-01-01

    This paper discusses the applicability of the Wavelet transform for analyzing an EMG signal and discriminating motion classes. In many previous works, researchers have dealt with steady EMG and have proposed suitable analyzing methods for the EMG, for example FFT and STFT. Therefore, it is difficult for the previous approaches to discriminate motions from the EMG in the different phases of muscle activity, i.e., pre-activity, in activity, postactivity phases, as well as the period of motion transition from one to another. In this paper, we introduce the Wavelet transform using the Coiflet mother wavelet into our real-time EMG prosthetic hand controller for discriminating motions from steady and unsteady EMG. A preliminary experiment to discriminate three hand motions from four channel EMG in the initial pre-activity and in activity phase is carried out to show the effectiveness of the approach. However, future research efforts are necessary to discriminate more motions much precisely

  14. Neutron–gamma discrimination based on the support vector machine method

    International Nuclear Information System (INIS)

    Yu, Xunzhen; Zhu, Jingjun; Lin, ShinTed; Wang, Li; Xing, Haoyang; Zhang, Caixun; Xia, Yuxi; Liu, Shukui; Yue, Qian; Wei, Weiwei; Du, Qiang; Tang, Changjian

    2015-01-01

    In this study, the combination of the support vector machine (SVM) method with the moment analysis method (MAM) is proposed and utilized to perform neutron/gamma (n/γ) discrimination of the pulses from an organic liquid scintillator (OLS). Neutron and gamma events, which can be firmly separated on the scatter plot drawn by the charge comparison method (CCM), are detected to form the training data set and the test data set for the SVM, and the MAM is used to create the feature vectors for individual events in the data sets. Compared to the traditional methods, such as CCM, the proposed method can not only discriminate the neutron and gamma signals, even at lower energy levels, but also provide the corresponding classification accuracy for each event, which is useful in validating the discrimination. Meanwhile, the proposed method can also offer a predication of the classification for the under-energy-limit events

  15. Feature based omnidirectional sparse visual path following

    OpenAIRE

    Goedemé, Toon; Tuytelaars, Tinne; Van Gool, Luc; Vanacker, Gerolf; Nuttin, Marnix

    2005-01-01

    Goedemé T., Tuytelaars T., Van Gool L., Vanacker G., Nuttin M., ''Feature based omnidirectional sparse visual path following'', Proceedings IEEE/RSJ international conference on intelligent robots and systems - IROS2005, pp. 1003-1008, August 2-6, 2005, Edmonton, Alberta, Canada.

  16. Comparison of n-γ discrimination by zero-crossing and digital charge comparison methods

    International Nuclear Information System (INIS)

    Wolski, D.; Moszynski, M.; Ludziejewski, T.; Johnson, A.; Klamra, W.; Skeppstedt, Oe.

    1995-01-01

    A comparative study of the n-γ discrimination done by the digital charge comparison and zero-crossing methods was carried out for a 130 mm in diameter and 130 mm high BC501A liquid scintillator coupled to a 130 mm diameter XP4512B photomultiplier. The high quality of the tested detector was reflected in a photoelectron yield of 2300±100 phe/MeV and excellent n-γ discrimination properties with energy discrimination thresholds corresponding to very low neutron (or electron) energies. The superiority of the Z/C method was demonstrated for the n-γ discrimination method alone, as well as, for the simultaneous separation by the pulse shape discrimination and the time-of-flight methods down to about 30 keV recoil electron energy. The digital charge comparison method fails for a large dynamic range of energy and its separation is weakly improved by time-of-flight method for low energies. (orig.)

  17. Discrimination methods between neutron and gamma rays for boron loaded plastic scintillators

    CERN Document Server

    Normand, S; Haan, S; Louvel, M

    2002-01-01

    Boron loaded plastic scintillators exhibit interesting properties for neutron detection in nuclear waste management and especially in investigating the amount of fissile materials when enclosed in waste containers. Combining a high thermal neutron efficiency and a low mean neutron lifetime, they are suitable in neutron multiplicity counting. However, due to their high sensitivity to gamma rays, pulse shape discrimination methods need to be developed in order to optimize the passive neutron assay measurement. From the knowledge of their physical properties, it is possible to separate the three kinds of particles that have interacted in the boron loaded plastic scintillator (gamma, fast neutron and thermal neutron). For this purpose, we have developed and compared the two well known discrimination methods (zero crossing and charge comparison) applied for the first time to boron loaded plastic scintillator. The setup for the zero crossing discrimination method and the charge comparison methods is thoroughly expl...

  18. Discrimination of Rice with Different Pretreatment Methods by Using a Voltammetric Electronic Tongue

    Directory of Open Access Journals (Sweden)

    Li Wang

    2015-07-01

    Full Text Available In this study, an application of a voltammetric electronic tongue for discrimination and prediction of different varieties of rice was investigated. Different pretreatment methods were selected, which were subsequently used for the discrimination of different varieties of rice and prediction of unknown rice samples. To this aim, a voltammetric array of sensors based on metallic electrodes was used as the sensing part. The different samples were analyzed by cyclic voltammetry with two sample-pretreatment methods. Discriminant Factorial Analysis was used to visualize the different categories of rice samples; however, radial basis function (RBF artificial neural network with leave-one-out cross-validation method was employed for prediction modeling. The collected signal data were first compressed employing fast Fourier transform (FFT and then significant features were extracted from the voltammetric signals. The experimental results indicated that the sample solutions obtained by the non-crushed pretreatment method could efficiently meet the effect of discrimination and recognition. The satisfactory prediction results of voltammetric electronic tongue based on RBF artificial neural network were obtained with less than five-fold dilution of the sample solution. The main objective of this study was to develop primary research on the application of an electronic tongue system for the discrimination and prediction of solid foods and provide an objective assessment tool for the food industry.

  19. Identification of discriminant proteins through antibody profiling, methods and apparatus for identifying an individual

    Science.gov (United States)

    Thompson, Vicki S; Lacey, Jeffrey A; Gentillon, Cynthia A; Apel, William A

    2015-03-03

    A method for determining a plurality of proteins for discriminating and positively identifying an individual based from a biological sample. The method may include profiling a biological sample from a plurality of individuals against a protein array including a plurality of proteins. The protein array may include proteins attached to a support in a preselected pattern such that locations of the proteins are known. The biological sample may be contacted with the protein array such that a portion of antibodies in the biological sample reacts with and binds to the proteins forming immune complexes. A statistical analysis method, such as discriminant analysis, may be performed to determine discriminating proteins for distinguishing individuals. Proteins of interest may be used to form a protein array. Such a protein array may be used, for example, to compare a forensic sample from an unknown source with a sample from a known source.

  20. Identification of discriminant proteins through antibody profiling, methods and apparatus for identifying an individual

    Energy Technology Data Exchange (ETDEWEB)

    Apel, William A.; Thompson, Vicki S; Lacey, Jeffrey A.; Gentillon, Cynthia A.

    2016-08-09

    A method for determining a plurality of proteins for discriminating and positively identifying an individual based from a biological sample. The method may include profiling a biological sample from a plurality of individuals against a protein array including a plurality of proteins. The protein array may include proteins attached to a support in a preselected pattern such that locations of the proteins are known. The biological sample may be contacted with the protein array such that a portion of antibodies in the biological sample reacts with and binds to the proteins forming immune complexes. A statistical analysis method, such as discriminant analysis, may be performed to determine discriminating proteins for distinguishing individuals. Proteins of interest may be used to form a protein array. Such a protein array may be used, for example, to compare a forensic sample from an unknown source with a sample from a known source.

  1. Discriminating background from anthropogenic lead by isotopic methods

    International Nuclear Information System (INIS)

    Nelson, B.K.; O'Brien, H.E.

    1995-01-01

    The goal of this pilot project was to evaluate the practicality of using natural variations in the isotopic composition of lead to test for the presence of anthropogenic lead in soil, surface water and ground water. Complex chemical reactions in the environment may cause measured lead concentrations to be ambiguous indicators of anthropogenic lead component. The lead isotope tracer technique has the potential to identify both the presence and proportion of anthropogenic lead in the environment. The tested the lead isotope technique at Eielson Air Force Base, Alaska, on sources of suspected fuel contamination. Although the results are specific to this base, the general technique of using lead isotopes to trace the movement of anthropogenic lead is applicable to other CERCLA sites. The study had four objectives: (1) characterize the natural lead isotope composition of bedrock, stream sediment and soils; (2) characterize the isotopic composition of the contaminant lead derived from fuel; (3) evaluate the sensitivity of the isotopic method to distinguishing between anthropogenic and natural lead in soil and water samples and (4) evaluate the analytical feasibility and accuracy of the method at the Isotope Geochemistry Laboratory at the University of Washington

  2. A comparison of different discrimination parameters for the DFT-based PSD method in fast scintillators

    International Nuclear Information System (INIS)

    Liu, G.; Yang, J.; Luo, X.L.; Lin, C.B.; Peng, J.X.; Yang, Y.

    2013-01-01

    Although the discrete Fourier transform (DFT) based pulse shape discrimination (PSD) method, realized by transforming the digitized scintillation pulses into frequency coefficients by using DFT, has been proven to effectively discriminate neutrons and γ rays, its discrimination performance depends strongly on the selection of the discrimination parameter obtained by the combination of these frequency coefficients. In order to thoroughly understand and apply the DFT-based PSD in organic scintillation detectors, a comparison of three different discrimination parameters, i.e. the amplitude of zero-frequency component, the amplitude difference between the amplitude of zero-frequency component and the amplitude of base-frequency component, and the ratio of the amplitude of base-frequency component to the amplitude of zero-frequency component, is described in this paper. An experimental setup consisting of an Americium–Beryllium (Am–Be) source, a BC501A liquid scintillator detector, and a 5Gsample/s 8-bit oscilloscope was built to assess the performance of the DFT-based PSD with each of these discrimination parameters in terms of the figure-of-merit (based on the separation of the event distributions). The third technique, which uses the ratio of the amplitude of base-frequency component to the amplitude of zero-frequency component as the discrimination parameter, is observed to provide the best discrimination performance in this research. - Highlights: • The spectrum difference between neutron pulse and γ-ray pulse was investigated. • The DFT-based PSD with different parameter definitions was assessed. • The way of using the ratio of magnitude spectrum provides the best performance. • The performance differences were explained from noise suppression features

  3. A new digital method for high precision neutron-gamma discrimination with liquid scintillation detectors

    International Nuclear Information System (INIS)

    Nakhostin, M

    2013-01-01

    A new pulse-shape discrimination algorithm for neutron and gamma (n/γ) discrimination with liquid scintillation detectors has been developed, leading to a considerable improvement of n/γ separation quality. The method is based on triangular pulse shaping which offers a high sensitivity to the shape of input pulses, as well as, excellent noise filtering characteristics. A clear separation of neutrons and γ-rays down to a scintillation light yield of about 65 keVee (electron equivalent energy) with a dynamic range of 45:1 was achieved. The method can potentially operate at high counting rates and is well suited for real-time measurements.

  4. A Headset Method for Measuring the Visual Temporal Discrimination Threshold in Cervical Dystonia

    Directory of Open Access Journals (Sweden)

    Anna Molloy

    2014-07-01

    Full Text Available Background: The visual temporal discrimination threshold (TDT is the shortest time interval at which one can determine two stimuli to be asynchronous and meets criteria for a valid endophenotype in adult‐onset idiopathic focal dystonia, a poorly penetrant disorder. Temporal discrimination is assessed in the hospital laboratory; in unaffected relatives of multiplex adult‐onset dystonia patients distance from the hospital is a barrier to data acquisition. We devised a portable headset method for visual temporal discrimination determination and our aim was to validate this portable tool against the traditional laboratory‐based method in a group of patients and in a large cohort of healthy controls. Methods: Visual TDTs were examined in two groups 1 in 96 healthy control participants divided by age and gender, and 2 in 33 cervical dystonia patients, using two methods of data acquisition, the traditional table‐top laboratory‐based system, and the novel portable headset method. The order of assessment was randomized in the control group. The results obtained by each technique were compared. Results: Visual temporal discrimination in healthy control participants demonstrated similar age and gender effects by the headset method as found by the table‐top examination. There were no significant differences between visual TDTs obtained using the two methods, both for the control participants and for the cervical dystonia patients. Bland–Altman testing showed good concordance between the two methods in both patients and in controls.Discussion: The portable headset device is a reliable and accurate method for visual temporal discrimination testing for use outside the laboratory, and will facilitate increased TDT data collection outside of the hospital setting. This is of particular importance in multiplex families where data collection in all available members of the pedigree is important for exome sequencing studies.

  5. Effect of noise on the performance of Digital Charge Comparison method for n-γ discrimination

    International Nuclear Information System (INIS)

    Singh, Harleen; Mehra, Rohit

    2017-01-01

    The neutron-gamma discrimination from a mixed radiation field is of prime importance in the field of nuclear safeguards, nuclear fission, radiation therapy etc. The liquid scintillators are widely used for n-γ discrimination as the relative decay rate of neutron pulse is less as compared to γ - ray in these detectors.The most popular and simple technique for pulse shape discrimination (PSD) is the charge comparison (CC). Due to the availability of fast ADCs and FPGAs, the traditional analogue techniques can be implemented in digital domain by sampling the PMT pulses. The performance of a PSD method depends on various parameters like sampling rate, noise distortion in the pulses the duration of processing gate etc. In this paper, the effect of noise levels on the performance of CC method is investigated at optimized processing gate

  6. Calculation of neutron activation discriminating the chemical weapons underground using Monte Carlo methods

    International Nuclear Information System (INIS)

    Shen Chunxia; Qian Jianfu; Zhang Wenzhong

    2003-01-01

    This paper mainly calculate neutron activation discriminating the chemical weapons underground, and analyses the factors that soil influence discrimination, finally we conclude soil can not influence discrimination. (authors)

  7. Target discrimination method for SAR images based on semisupervised co-training

    Science.gov (United States)

    Wang, Yan; Du, Lan; Dai, Hui

    2018-01-01

    Synthetic aperture radar (SAR) target discrimination is usually performed in a supervised manner. However, supervised methods for SAR target discrimination may need lots of labeled training samples, whose acquirement is costly, time consuming, and sometimes impossible. This paper proposes an SAR target discrimination method based on semisupervised co-training, which utilizes a limited number of labeled samples and an abundant number of unlabeled samples. First, Lincoln features, widely used in SAR target discrimination, are extracted from the training samples and partitioned into two sets according to their physical meanings. Second, two support vector machine classifiers are iteratively co-trained with the extracted two feature sets based on the co-training algorithm. Finally, the trained classifiers are exploited to classify the test data. The experimental results on real SAR images data not only validate the effectiveness of the proposed method compared with the traditional supervised methods, but also demonstrate the superiority of co-training over self-training, which only uses one feature set.

  8. Indonesian palm civet coffee discrimination using UV-visible spectroscopy and several chemometrics methods

    International Nuclear Information System (INIS)

    Yulia, M; Suhandy, D

    2017-01-01

    Indonesian palm civet coffee or kopi luwak (Indonesian words for coffee and palm civet) is well known as the world’s priciest and rarest coffee. To protect the authenticity of luwak coffee and protect consumer from luwak coffee adulteration, it is very important to develop a simple and inexpensive method to discriminate between civet and non-civet coffee. The discrimination between civet and non-civet coffee in ground roasted (powder) samples is very challenging since it is very difficult to distinguish between the two by using conventional method. In this research, the use of UV-Visible spectra combined with two chemometric methods, SIMCA and PLS-DA, was evaluated to discriminate civet and non-civet ground coffee samples. The spectral data of civet and non-civet coffee were acquired using UV-Vis spectrometer (Genesys™ 10S UV-Vis, Thermo Scientific, USA). The result shows that using both supervised discrimination methods: SIMCA and PLS-DA, all samples were correctly classified into their corresponding classes with 100% rate for accuracy, sensitivity and specificity, respectively. (paper)

  9. Street Lighting Infrastructure Assessment Using Discriminant and GIS Method on Mount Merapi Evacuation Road

    Science.gov (United States)

    Izdihar, R. P.; Maryono, M.; Widjonarko, W.; Rahayu, S.

    2018-02-01

    This research aims to assess street lighting infrastructure in rural-urban of Mount Merapi Evacuation road. Three evacuation road/corridor; Mriyan-Boyolali, Wonodoyo-Boyolali and Samiran-Boyolali are selected as case study. By using discriminant this study examine 6 variables namely type of lamp, physical component, height, time, power and cons consumption. In addition this study also using GIS method to assessing geographical feature as of previous result. According to the discriminant analysis, the characteristic of street lighting could be distinguished as two characteristic, while from the GIS assessment, the study found three characteristic of geographical street lighting feature.

  10. Pb and Sr isotopic compositions of ancient pottery: a method to discriminate production sites

    International Nuclear Information System (INIS)

    Zhang Xun; Chen Jiangfeng; Ma Lin; He Jianfeng; Wang Changsui; Qiu Ping

    2004-01-01

    The discriminating of production sites of ancient pottery samples using multi-isotopic systematics was described. Previous work has proven that Pb isotopic ratios can be used for discriminating the production sites of ancient pottery under certain conditions. The present work suggests that although Nd isotopic ratios are not sensitive to the production sites of ancient pottery, Sr isotopic ratios are important for the purpose. Pb isotopic ratios are indistinguishable for the pottery excavated from the Jiahu relict, Wuyang, Henan Province and for famous Qin Terra-cotta Figures. But, the 87 Sr/ 86 Sr ratios for the former (about 0.715) are significantly lower than that of the latter (0.717-0.718). The authors concluded that a combined use of Pb and Sr isotopes would be a more powerful method for discriminating the production site of ancient pottery. (authors)

  11. Analyzing locomotion synthesis with feature-based motion graphs.

    Science.gov (United States)

    Mahmudi, Mentar; Kallmann, Marcelo

    2013-05-01

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

  12. Prediction Model of Collapse Risk Based on Information Entropy and Distance Discriminant Analysis Method

    Directory of Open Access Journals (Sweden)

    Hujun He

    2017-01-01

    Full Text Available The prediction and risk classification of collapse is an important issue in the process of highway construction in mountainous regions. Based on the principles of information entropy and Mahalanobis distance discriminant analysis, we have produced a collapse hazard prediction model. We used the entropy measure method to reduce the influence indexes of the collapse activity and extracted the nine main indexes affecting collapse activity as the discriminant factors of the distance discriminant analysis model (i.e., slope shape, aspect, gradient, and height, along with exposure of the structural face, stratum lithology, relationship between weakness face and free face, vegetation cover rate, and degree of rock weathering. We employ postearthquake collapse data in relation to construction of the Yingxiu-Wolong highway, Hanchuan County, China, as training samples for analysis. The results were analyzed using the back substitution estimation method, showing high accuracy and no errors, and were the same as the prediction result of uncertainty measure. Results show that the classification model based on information entropy and distance discriminant analysis achieves the purpose of index optimization and has excellent performance, high prediction accuracy, and a zero false-positive rate. The model can be used as a tool for future evaluation of collapse risk.

  13. Estimation of optimum time interval for neutron- γ discrimination by simplified digital charge collection method

    International Nuclear Information System (INIS)

    Singh, Harleen; Singh, Sarabjeet

    2014-01-01

    The discrimination of mixed radiation field is of prime importance due to its application in neutron detection which leads to radiation safety, nuclear material detection etc. The liquid scintillators are one of the most important radiation detectors because the relative decay rate of neutron pulse is slower as compared to gamma radiation in these detectors. There are techniques like zero crossing and charge comparison which are very popular and implemented using analogue electronics. In the recent years due to availability of fast ADC and FPGA, digital methods for discrimination of mixed field radiations have been investigated. Some of the digital time domain techniques developed are pulse gradient analysis (PGA), simplified digital charge collection method (SDCC), digital zero crossing method. The performance of these methods depends on the appropriate selection of gate time for which the pulse is processed. In this paper, the SDCC method is investigated for a neutron-gamma mixed field. The main focus of the study is to get the knowledge of optimum gate time which is very important in neutron gamma discrimination analysis in a mixed radiation field. The comparison with charge collection (CC) method is also investigated

  14. Feature-based tolerancing for intelligent inspection process definition

    International Nuclear Information System (INIS)

    Brown, C.W.

    1993-07-01

    This paper describes a feature-based tolerancing capability that complements a geometric solid model with an explicit representation of conventional and geometric tolerances. This capability is focused on supporting an intelligent inspection process definition system. The feature-based tolerance model's benefits include advancing complete product definition initiatives (e.g., STEP -- Standard for Exchange of Product model dam), suppling computer-integrated manufacturing applications (e.g., generative process planning and automated part programming) with product definition information, and assisting in the solution of measurement performance issues. A feature-based tolerance information model was developed based upon the notion of a feature's toleranceable aspects and describes an object-oriented scheme for representing and relating tolerance features, tolerances, and datum reference frames. For easy incorporation, the tolerance feature entities are interconnected with STEP solid model entities. This schema will explicitly represent the tolerance specification for mechanical products, support advanced dimensional measurement applications, and assist in tolerance-related methods divergence issues

  15. Detection-Discrimination Method for Multiple Repeater False Targets Based on Radar Polarization Echoes

    Directory of Open Access Journals (Sweden)

    Z. W. ZONG

    2014-04-01

    Full Text Available Multiple repeat false targets (RFTs, created by the digital radio frequency memory (DRFM system of jammer, are widely used in practical to effectively exhaust the limited tracking and discrimination resource of defence radar. In this paper, common characteristic of radar polarization echoes of multiple RFTs is used for target recognition. Based on the echoes from two receiving polarization channels, the instantaneous polarization radio (IPR is defined and its variance is derived by employing Taylor series expansion. A detection-discrimination method is designed based on probability grids. By using the data from microwave anechoic chamber, the detection threshold of the method is confirmed. Theoretical analysis and simulations indicate that the method is valid and feasible. Furthermore, the estimation performance of IPRs of RFTs due to the influence of signal noise ratio (SNR is also covered.

  16. Discriminant analysis method to determine the power of the boys 11-12 year

    Directory of Open Access Journals (Sweden)

    Mirosława Cieślicka

    2016-10-01

    Full Text Available Purpose: To determine the model of power in boys 11-12 years old. Material and methods: To achieve the objectives, the following methods: analysis of scientific literature, statistical methods for analysis of results. The study involved 35 boys 11 year (n = 35 and 32 boys 12 year (n = 32. Results: Analysis of the results shows that the statistical significance of differences in the test results of boys 11 and 12 years there has been research jump from the place of execution and the amount of squats (the amount of execution time (p <0.001, p <0. Conclusions: Structural factors discriminant function suggest that more attention is paid to training of speed and endurance, the more likely to increase the force to prepare the boys. The canonical discriminant function can  be used to assess and forecast the development of motor skills in boys.

  17. An automatic method to discriminate malignant masses from normal tissue in digital mammograms

    International Nuclear Information System (INIS)

    Brake, Guido M. te; Karssemeijer, Nico; Hendriks, Jan H.C.L.

    2000-01-01

    Specificity levels of automatic mass detection methods in mammography are generally rather low, because suspicious looking normal tissue is often hard to discriminate from real malignant masses. In this work a number of features were defined that are related to image characteristics that radiologists use to discriminate real lesions from normal tissue. An artificial neural network was used to map the computed features to a measure of suspiciousness for each region that was found suspicious by a mass detection method. Two data sets were used to test the method. The first set of 72 malignant cases (132 films) was a consecutive series taken from the Nijmegen screening programme, 208 normal films were added to improve the estimation of the specificity of the method. The second set was part of the new DDSM data set from the University of South Florida. A total of 193 cases (772 films) with 372 annotated malignancies was used. The measure of suspiciousness that was computed using the image characteristics was successful in discriminating tumours from false positive detections. Approximately 75% of all cancers were detected in at least one view at a specificity level of 0.1 false positive per image. (author)

  18. Feature-based Alignment of Volumetric Multi-modal Images

    Science.gov (United States)

    Toews, Matthew; Zöllei, Lilla; Wells, William M.

    2014-01-01

    This paper proposes a method for aligning image volumes acquired from different imaging modalities (e.g. MR, CT) based on 3D scale-invariant image features. A novel method for encoding invariant feature geometry and appearance is developed, based on the assumption of locally linear intensity relationships, providing a solution to poor repeatability of feature detection in different image modalities. The encoding method is incorporated into a probabilistic feature-based model for multi-modal image alignment. The model parameters are estimated via a group-wise alignment algorithm, that iteratively alternates between estimating a feature-based model from feature data, then realigning feature data to the model, converging to a stable alignment solution with few pre-processing or pre-alignment requirements. The resulting model can be used to align multi-modal image data with the benefits of invariant feature correspondence: globally optimal solutions, high efficiency and low memory usage. The method is tested on the difficult RIRE data set of CT, T1, T2, PD and MP-RAGE brain images of subjects exhibiting significant inter-subject variability due to pathology. PMID:24683955

  19. Feature-based automatic color calibration for networked camera system

    Science.gov (United States)

    Yamamoto, Shoji; Taki, Keisuke; Tsumura, Norimichi; Nakaguchi, Toshiya; Miyake, Yoichi

    2011-01-01

    In this paper, we have developed a feature-based automatic color calibration by using an area-based detection and adaptive nonlinear regression method. Simple color matching of chartless is achieved by using the characteristic of overlapping image area with each camera. Accurate detection of common object is achieved by the area-based detection that combines MSER with SIFT. Adaptive color calibration by using the color of detected object is calculated by nonlinear regression method. This method can indicate the contribution of object's color for color calibration, and automatic selection notification for user is performed by this function. Experimental result show that the accuracy of the calibration improves gradually. It is clear that this method can endure practical use of multi-camera color calibration if an enough sample is obtained.

  20. Discriminant method for the optimization of radionuclide activity in studies of nuclear medicine

    International Nuclear Information System (INIS)

    Perez Diaz, Marlen

    2003-01-01

    It is presented a method for the optimization of the radionuclidic activity to administer to mature patients in studies of Nuclear Medicine. The method is based in technical of discriminant analysis to build a function that discriminates groups with image quality differed on the base of physical parameters as they are the contrast image and the aleatory noise. The image quality is the dependent variable and it is selected by means of experts' evaluation and technical of clustering. The function is a lineal combination of a reduced group of variables physical-medical, able to discriminate the groups starting from a big group of variables measures. The method allows, also, to establish the relative weight of each discriminant variable selected . The behavior of the same ones is analyzed among studies carried out with different administered activity, with the objective of determining the minimum value of this that still allows good results in the image quality (Approach of activity optimization). It is validated the method by means of results comparison with the grateful Curved ROC in studies carried out with the Mannequins of Jaszczak (for planar studies) and of Insert Heart (for studies of SPECT). The optim activity value of the 99mTc, obtained with the application of the method, was coincident with the one obtained after the application of the method ROC to 6 expert observers as much in planar studies as in SPECT for two different cameras gamma. The method was applied later on in static, dynamic studies and of SPECT carried out with camera gamma to a mature population of 210 patient. The decisive variables of the quality of the image were obtained in the nuclear venticulography in rest, the bony gammagraphy, the nuclear renogram, the renal gammagraphy and the cerebral SPECT, as well as some activity values optimized for the equipment conditions and available radiopharmac in the country, allowing to establish a better commitment relationship between image quality

  1. A novel electroencephalographic analysis method discriminates alcohol effects from those of other sedative/hypnotics.

    Science.gov (United States)

    Steffensen, Scott C; Lee, Rong-Sheng; Henriksen, Steven J; Packer, Thomas L; Cook, Daniel R

    2002-04-15

    Here we describe a mathematical and statistical signal processing strategy termed event resolution imaging (ERI). Our principal objective was to determine if the acute intoxicating effects of ethanol on spontaneous EEG activity could be discriminated from those of other sedative/hypnotics. We employed ERI to combine and integrate standard analysis methods to learn multiple signal features of time-varying EEG signals. We recorded cortical EEG, electromyographic activity, and motor activity during intravenous administration of saline, ethanol (1.0 g/kg), chlordiazepoxide (10 mg/kg), pentobarbital (6 mg/kg), heroin (0.3 mg/kg), and methamphetamine (2 mg/kg) administered on separate days in six rats. A blind treatment of one of the drugs was readministered to validate the efficacy of ERI analysis. Significant changes in spontaneous EEG activity produced by all five drugs were detected by ERI analysis with a time resolution of 5-10 s. ERI analysis of spontaneous EEG activity also discriminated, with 90-95% accuracy, an ataxic dose of ethanol versus equivalent ataxic doses of chlordiazepoxide or pentobarbital, as well as the effects of saline, a reinforcing dose of heroin, or a locomotor activating dose of methamphetamine. ERI correctly matched the 'blind drug' as ethanol. These findings indicate that ERI analysis can detect the central nervous system effects of various psychoactive drugs and accurately discriminate the electrocortical effects of select sedative/hypnotics, with similar behavioral endpoints, but with dissimilar mechanisms of action.

  2. A Feature Selection Method Based on Fisher's Discriminant Ratio for Text Sentiment Classification

    Science.gov (United States)

    Wang, Suge; Li, Deyu; Wei, Yingjie; Li, Hongxia

    With the rapid growth of e-commerce, product reviews on the Web have become an important information source for customers' decision making when they intend to buy some product. As the reviews are often too many for customers to go through, how to automatically classify them into different sentiment orientation categories (i.e. positive/negative) has become a research problem. In this paper, based on Fisher's discriminant ratio, an effective feature selection method is proposed for product review text sentiment classification. In order to validate the validity of the proposed method, we compared it with other methods respectively based on information gain and mutual information while support vector machine is adopted as the classifier. In this paper, 6 subexperiments are conducted by combining different feature selection methods with 2 kinds of candidate feature sets. Under 1006 review documents of cars, the experimental results indicate that the Fisher's discriminant ratio based on word frequency estimation has the best performance with F value 83.3% while the candidate features are the words which appear in both positive and negative texts.

  3. Evaluation of hierarchical agglomerative cluster analysis methods for discrimination of primary biological aerosol

    Directory of Open Access Journals (Sweden)

    I. Crawford

    2015-11-01

    Full Text Available In this paper we present improved methods for discriminating and quantifying primary biological aerosol particles (PBAPs by applying hierarchical agglomerative cluster analysis to multi-parameter ultraviolet-light-induced fluorescence (UV-LIF spectrometer data. The methods employed in this study can be applied to data sets in excess of 1 × 106 points on a desktop computer, allowing for each fluorescent particle in a data set to be explicitly clustered. This reduces the potential for misattribution found in subsampling and comparative attribution methods used in previous approaches, improving our capacity to discriminate and quantify PBAP meta-classes. We evaluate the performance of several hierarchical agglomerative cluster analysis linkages and data normalisation methods using laboratory samples of known particle types and an ambient data set. Fluorescent and non-fluorescent polystyrene latex spheres were sampled with a Wideband Integrated Bioaerosol Spectrometer (WIBS-4 where the optical size, asymmetry factor and fluorescent measurements were used as inputs to the analysis package. It was found that the Ward linkage with z-score or range normalisation performed best, correctly attributing 98 and 98.1 % of the data points respectively. The best-performing methods were applied to the BEACHON-RoMBAS (Bio–hydro–atmosphere interactions of Energy, Aerosols, Carbon, H2O, Organics and Nitrogen–Rocky Mountain Biogenic Aerosol Study ambient data set, where it was found that the z-score and range normalisation methods yield similar results, with each method producing clusters representative of fungal spores and bacterial aerosol, consistent with previous results. The z-score result was compared to clusters generated with previous approaches (WIBS AnalysiS Program, WASP where we observe that the subsampling and comparative attribution method employed by WASP results in the overestimation of the fungal spore concentration by a factor of 1.5 and the

  4. Discrimination of several Indonesian specialty coffees using Fluorescence Spectroscopy combined with SIMCA method

    Science.gov (United States)

    Suhandy, D.; Yulia, M.

    2018-03-01

    Indonesia is one of the important producers of several specialty coffees, which have a particularly high economic value, including Civet coffee (‘kopi luwak’ in Indonesian language) and Peaberry coffee (‘kopi lanang’ in Indonesian language). The production of Civet and Peaberry coffee is very limited. In order to provide authentication of Civet and Peaberry coffee and protect consumers from adulteration, a robust and easy method for evaluating ground Civet and Peaberry coffee and detection of its adulteration is needed. In this study, we investigate the use of fluorescence spectroscopy combined with SIMCA (soft independent modelling of class analogies) method to discriminate three Indonesian specialty coffee: ground Peaberry, Civet and Pagar Alam coffee. Total 90 samples were used (30 samples for Civet, Peaberry and Pagar Alam coffee, respectively). All coffee samples were ground using a home-coffee-grinder. Since particle size in coffee powder has a significant influence on the spectra obtained, we sieved all coffee samples through a nest of U. S. standard sieves (mesh number of 40) on a Meinzer II sieve shaker for 10 minutes to obtain a particle size of 420 µm. The experiments were performed at room temperature (around 27-29°C). All samples were extracted with distilled water and then filtered. For each samples, 3 mL of extracted sample then was pipetted into 10 mm cuvettes for spectral data acquisition. The EEM (excitation-emission matrix) spectral data of coffee samples were acquired using JASCO FP-8300 Fluorescence Spectrometer. The principal component analysis (PCA) result shows that it is possible to discriminate types of coffee based on information from EEM (excitation-emission matrix) spectral data. Using SIMCA method, the discrimination model of Indonesian specialty coffee was successfully developed and resulted in high performance of discrimination with 100% of sensitivity and specificity for Peaberry, Civet and Pagar Alam coffee. This research

  5. Study on non-linear bistable dynamics model based EEG signal discrimination analysis method.

    Science.gov (United States)

    Ying, Xiaoguo; Lin, Han; Hui, Guohua

    2015-01-01

    Electroencephalogram (EEG) is the recording of electrical activity along the scalp. EEG measures voltage fluctuations generating from ionic current flows within the neurons of the brain. EEG signal is looked as one of the most important factors that will be focused in the next 20 years. In this paper, EEG signal discrimination based on non-linear bistable dynamical model was proposed. EEG signals were processed by non-linear bistable dynamical model, and features of EEG signals were characterized by coherence index. Experimental results showed that the proposed method could properly extract the features of different EEG signals.

  6. Deep Salient Feature Based Anti-Noise Transfer Network for Scene Classification of Remote Sensing Imagery

    Directory of Open Access Journals (Sweden)

    Xi Gong

    2018-03-01

    Full Text Available Remote sensing (RS scene classification is important for RS imagery semantic interpretation. Although tremendous strides have been made in RS scene classification, one of the remaining open challenges is recognizing RS scenes in low quality variance (e.g., various scales and noises. This paper proposes a deep salient feature based anti-noise transfer network (DSFATN method that effectively enhances and explores the high-level features for RS scene classification in different scales and noise conditions. In DSFATN, a novel discriminative deep salient feature (DSF is introduced by saliency-guided DSF extraction, which conducts a patch-based visual saliency (PBVS algorithm using “visual attention” mechanisms to guide pre-trained CNNs for producing the discriminative high-level features. Then, an anti-noise network is proposed to learn and enhance the robust and anti-noise structure information of RS scene by directly propagating the label information to fully-connected layers. A joint loss is used to minimize the anti-noise network by integrating anti-noise constraint and a softmax classification loss. The proposed network architecture can be easily trained with a limited amount of training data. The experiments conducted on three different scale RS scene datasets show that the DSFATN method has achieved excellent performance and great robustness in different scales and noise conditions. It obtains classification accuracy of 98.25%, 98.46%, and 98.80%, respectively, on the UC Merced Land Use Dataset (UCM, the Google image dataset of SIRI-WHU, and the SAT-6 dataset, advancing the state-of-the-art substantially.

  7. Campbell's MSV method the neutron-gamma discrimination in mixed field of nuclear reactor

    International Nuclear Information System (INIS)

    Stankovic, S. J.; Loncar, B.; Avramovic, I.; Osmokrovic, P.

    2003-10-01

    In this paper it is carried out the analysis some capabilities of Campbell's MSV (Mean Square Value) measuring chain on base the principles derived by Campbell's theorem. Nevertheless, measurements have performed with digitized MSV method and results have compared related to they attained with classic measuring chain, when the mean value of signal from detector output has measured. In our case, detector element was uncompensated ionization chamber for mixed n-gamma fields. Thermal neutron flux, absorbed dose rate, equivalent dose rate and exposure rate in surrounding the reactor vessel of system HERBE, at nuclear reactor RB in 'VINCA' Institute, are determined. The examination of discrimination for gamma relate to neutron component in signal of detector output is performed whereby experimental work and the calculation according to linear theoretical model. The dependencies of changes for variance and mean value output detector signal versus four-decade change of fission reactor power, in range from 10 mW to 22W, are obtained. The advantage of MSV method is confirmed and concluded that the order n-gamma discrimination in MSV signal processing is around fifty times larger than classical measuring method. (author)

  8. Pulse shape discrimination and classification methods for continuous depth of interaction encoding PET detectors

    International Nuclear Information System (INIS)

    Roncali, Emilie; Phipps, Jennifer E; Marcu, Laura; Cherry, Simon R

    2012-01-01

    In previous work we demonstrated the potential of positron emission tomography (PET) detectors with depth-of-interaction (DOI) encoding capability based on phosphor-coated crystals. A DOI resolution of 8 mm full-width at half-maximum was obtained for 20 mm long scintillator crystals using a delayed charge integration linear regression method (DCI-LR). Phosphor-coated crystals modify the pulse shape to allow continuous DOI information determination, but the relationship between pulse shape and DOI is complex. We are therefore interested in developing a sensitive and robust method to estimate the DOI. Here, linear discriminant analysis (LDA) was implemented to classify the events based on information extracted from the pulse shape. Pulses were acquired with 2×2×20 mm 3 phosphor-coated crystals at five irradiation depths and characterized by their DCI values or Laguerre coefficients. These coefficients were obtained by expanding the pulses on a Laguerre basis set and constituted a unique signature for each pulse. The DOI of individual events was predicted using LDA based on Laguerre coefficients (Laguerre-LDA) or DCI values (DCI-LDA) as discriminant features. Predicted DOIs were compared to true irradiation depths. Laguerre-LDA showed higher sensitivity and accuracy than DCI-LDA and DCI-LR and was also more robust to predict the DOI of pulses with higher statistical noise due to low light levels (interaction depths further from the photodetector face). This indicates that Laguerre-LDA may be more suitable to DOI estimation in smaller crystals where lower collected light levels are expected. This novel approach is promising for calculating DOI using pulse shape discrimination in single-ended readout depth-encoding PET detectors. (paper)

  9. Bag-of-features based medical image retrieval via multiple assignment and visual words weighting

    KAUST Repository

    Wang, Jingyan; Li, Yongping; Zhang, Ying; Wang, Chao; Xie, Honglan; Chen, Guoling; Gao, Xin

    2011-01-01

    Bag-of-features based approaches have become prominent for image retrieval and image classification tasks in the past decade. Such methods represent an image as a collection of local features, such as image patches and key points with scale invariant feature transform (SIFT) descriptors. To improve the bag-of-features methods, we first model the assignments of local descriptors as contribution functions, and then propose a novel multiple assignment strategy. Assuming the local features can be reconstructed by their neighboring visual words in a vocabulary, reconstruction weights can be solved by quadratic programming. The weights are then used to build contribution functions, resulting in a novel assignment method, called quadratic programming (QP) assignment. We further propose a novel visual word weighting method. The discriminative power of each visual word is analyzed by the sub-similarity function in the bin that corresponds to the visual word. Each sub-similarity function is then treated as a weak classifier. A strong classifier is learned by boosting methods that combine those weak classifiers. The weighting factors of the visual words are learned accordingly. We evaluate the proposed methods on medical image retrieval tasks. The methods are tested on three well-known data sets, i.e., the ImageCLEFmed data set, the 304 CT Set, and the basal-cell carcinoma image set. Experimental results demonstrate that the proposed QP assignment outperforms the traditional nearest neighbor assignment, the multiple assignment, and the soft assignment, whereas the proposed boosting based weighting strategy outperforms the state-of-the-art weighting methods, such as the term frequency weights and the term frequency-inverse document frequency weights. © 2011 IEEE.

  10. Bag-of-features based medical image retrieval via multiple assignment and visual words weighting

    KAUST Repository

    Wang, Jingyan

    2011-11-01

    Bag-of-features based approaches have become prominent for image retrieval and image classification tasks in the past decade. Such methods represent an image as a collection of local features, such as image patches and key points with scale invariant feature transform (SIFT) descriptors. To improve the bag-of-features methods, we first model the assignments of local descriptors as contribution functions, and then propose a novel multiple assignment strategy. Assuming the local features can be reconstructed by their neighboring visual words in a vocabulary, reconstruction weights can be solved by quadratic programming. The weights are then used to build contribution functions, resulting in a novel assignment method, called quadratic programming (QP) assignment. We further propose a novel visual word weighting method. The discriminative power of each visual word is analyzed by the sub-similarity function in the bin that corresponds to the visual word. Each sub-similarity function is then treated as a weak classifier. A strong classifier is learned by boosting methods that combine those weak classifiers. The weighting factors of the visual words are learned accordingly. We evaluate the proposed methods on medical image retrieval tasks. The methods are tested on three well-known data sets, i.e., the ImageCLEFmed data set, the 304 CT Set, and the basal-cell carcinoma image set. Experimental results demonstrate that the proposed QP assignment outperforms the traditional nearest neighbor assignment, the multiple assignment, and the soft assignment, whereas the proposed boosting based weighting strategy outperforms the state-of-the-art weighting methods, such as the term frequency weights and the term frequency-inverse document frequency weights. © 2011 IEEE.

  11. Improved neutron-gamma discrimination for a 3He neutron detector using subspace learning methods

    Science.gov (United States)

    Wang, C. L.; Funk, L. L.; Riedel, R. A.; Berry, K. D.

    2017-05-01

    3He gas based neutron Linear-Position-Sensitive Detectors (LPSDs) have been used for many neutron scattering instruments. Traditional Pulse-height Analysis (PHA) for Neutron-Gamma Discrimination (NGD) resulted in the neutron-gamma efficiency ratio (NGD ratio) on the order of 105-106. The NGD ratios of 3He detectors need to be improved for even better scientific results from neutron scattering. Digital Signal Processing (DSP) analyses of waveforms were proposed for obtaining better NGD ratios, based on features extracted from rise-time, pulse amplitude, charge integration, a simplified Wiener filter, and the cross-correlation between individual and template waveforms of neutron and gamma events. Fisher Linear Discriminant Analysis (FLDA) and three Multivariate Analyses (MVAs) of the features were performed. The NGD ratios are improved by about 102-103 times compared with the traditional PHA method. Our results indicate the NGD capabilities of 3He tube detectors can be significantly improved with subspace-learning based methods, which may result in a reduced data-collection time and better data quality for further data reduction.

  12. Kennard-Stone combined with least square support vector machine method for noncontact discriminating human blood species

    Science.gov (United States)

    Zhang, Linna; Li, Gang; Sun, Meixiu; Li, Hongxiao; Wang, Zhennan; Li, Yingxin; Lin, Ling

    2017-11-01

    Identifying whole bloods to be either human or nonhuman is an important responsibility for import-export ports and inspection and quarantine departments. Analytical methods and DNA testing methods are usually destructive. Previous studies demonstrated that visible diffuse reflectance spectroscopy method can realize noncontact human and nonhuman blood discrimination. An appropriate method for calibration set selection was very important for a robust quantitative model. In this paper, Random Selection (RS) method and Kennard-Stone (KS) method was applied in selecting samples for calibration set. Moreover, proper stoichiometry method can be greatly beneficial for improving the performance of classification model or quantification model. Partial Least Square Discrimination Analysis (PLSDA) method was commonly used in identification of blood species with spectroscopy methods. Least Square Support Vector Machine (LSSVM) was proved to be perfect for discrimination analysis. In this research, PLSDA method and LSSVM method was used for human blood discrimination. Compared with the results of PLSDA method, this method could enhance the performance of identified models. The overall results convinced that LSSVM method was more feasible for identifying human and animal blood species, and sufficiently demonstrated LSSVM method was a reliable and robust method for human blood identification, and can be more effective and accurate.

  13. A parallel spatiotemporal saliency and discriminative online learning method for visual target tracking in aerial videos.

    Science.gov (United States)

    Aghamohammadi, Amirhossein; Ang, Mei Choo; A Sundararajan, Elankovan; Weng, Ng Kok; Mogharrebi, Marzieh; Banihashem, Seyed Yashar

    2018-01-01

    Visual tracking in aerial videos is a challenging task in computer vision and remote sensing technologies due to appearance variation difficulties. Appearance variations are caused by camera and target motion, low resolution noisy images, scale changes, and pose variations. Various approaches have been proposed to deal with appearance variation difficulties in aerial videos, and amongst these methods, the spatiotemporal saliency detection approach reported promising results in the context of moving target detection. However, it is not accurate for moving target detection when visual tracking is performed under appearance variations. In this study, a visual tracking method is proposed based on spatiotemporal saliency and discriminative online learning methods to deal with appearance variations difficulties. Temporal saliency is used to represent moving target regions, and it was extracted based on the frame difference with Sauvola local adaptive thresholding algorithms. The spatial saliency is used to represent the target appearance details in candidate moving regions. SLIC superpixel segmentation, color, and moment features can be used to compute feature uniqueness and spatial compactness of saliency measurements to detect spatial saliency. It is a time consuming process, which prompted the development of a parallel algorithm to optimize and distribute the saliency detection processes that are loaded into the multi-processors. Spatiotemporal saliency is then obtained by combining the temporal and spatial saliencies to represent moving targets. Finally, a discriminative online learning algorithm was applied to generate a sample model based on spatiotemporal saliency. This sample model is then incrementally updated to detect the target in appearance variation conditions. Experiments conducted on the VIVID dataset demonstrated that the proposed visual tracking method is effective and is computationally efficient compared to state-of-the-art methods.

  14. A parallel spatiotemporal saliency and discriminative online learning method for visual target tracking in aerial videos

    Science.gov (United States)

    2018-01-01

    Visual tracking in aerial videos is a challenging task in computer vision and remote sensing technologies due to appearance variation difficulties. Appearance variations are caused by camera and target motion, low resolution noisy images, scale changes, and pose variations. Various approaches have been proposed to deal with appearance variation difficulties in aerial videos, and amongst these methods, the spatiotemporal saliency detection approach reported promising results in the context of moving target detection. However, it is not accurate for moving target detection when visual tracking is performed under appearance variations. In this study, a visual tracking method is proposed based on spatiotemporal saliency and discriminative online learning methods to deal with appearance variations difficulties. Temporal saliency is used to represent moving target regions, and it was extracted based on the frame difference with Sauvola local adaptive thresholding algorithms. The spatial saliency is used to represent the target appearance details in candidate moving regions. SLIC superpixel segmentation, color, and moment features can be used to compute feature uniqueness and spatial compactness of saliency measurements to detect spatial saliency. It is a time consuming process, which prompted the development of a parallel algorithm to optimize and distribute the saliency detection processes that are loaded into the multi-processors. Spatiotemporal saliency is then obtained by combining the temporal and spatial saliencies to represent moving targets. Finally, a discriminative online learning algorithm was applied to generate a sample model based on spatiotemporal saliency. This sample model is then incrementally updated to detect the target in appearance variation conditions. Experiments conducted on the VIVID dataset demonstrated that the proposed visual tracking method is effective and is computationally efficient compared to state-of-the-art methods. PMID:29438421

  15. Feature Based Control of Compact Disc Players

    DEFF Research Database (Denmark)

    Odgaard, Peter Fogh

    Two servo control loops are used to keep the Optical Pick-up Unit focused and radially on the information track of the Compact Disc. These control servos have problems handling surface faults on the Compact Disc. In this Ph.D thesis a method is proposed to improve the handling of these surface...

  16. Non-destructive Testing of Wood Defects Based on Discriminant Analysis Method

    Directory of Open Access Journals (Sweden)

    Wenshu LIN

    2015-09-01

    Full Text Available The defects of wood samples were tested by the technique of stress wave and ultrasonic technology, and the testing results were comparatively analyzed by using the Fisher discriminant analysis in the statistic software of SPSS. The differences of defect detection sensitivity and accuracy for stress wave and ultrasonic under different wood properties and defects were concluded. Therefore, in practical applications, according to different situations the corresponding wood non- destructive testing method should be used, or the two detection methods are applied at the same time in order to compensate for its shortcomings with each other to improve the ability to distinguish the timber defects. The results can provide a reference for further improvement of the reliability of timber defects detection.

  17. Feature-Based Nonlocal Polarimetric SAR Filtering

    Directory of Open Access Journals (Sweden)

    Xiaoli Xing

    2017-10-01

    Full Text Available Polarimetric synthetic aperture radar (PolSAR images are inherently contaminated by multiplicative speckle noise, which complicates the image interpretation and image analyses. To reduce the speckle effect, several adaptive speckle filters have been developed based on the weighted average of the similarity measures commonly depending on the model or probability distribution, which are often affected by the distribution parameters and modeling texture components. In this paper, a novel filtering method introduces the coefficient of variance ( CV and Pauli basis (PB to measure the similarity, and the two features are combined with the framework of the nonlocal mean filtering. The CV is used to describe the complexity of various scenes and distinguish the scene heterogeneity; moreover, the Pauli basis is able to express the polarimetric information in PolSAR image processing. This proposed filtering combines the CV and Pauli basis to improve the estimation accuracy of the similarity weights. Then, the similarity of the features is deduced according to the test statistic. Subsequently, the filtering is proceeded by using the nonlocal weighted estimation. The performance of the proposed filter is tested with the simulated images and real PolSAR images, which are acquired by AIRSAR system and ESAR system. The qualitative and quantitative experiments indicate the validity of the proposed method by comparing with the widely-used despeckling methods.

  18. A method for discrimination of noise and EMG signal regions recorded during rhythmic behaviors.

    Science.gov (United States)

    Ying, Rex; Wall, Christine E

    2016-12-08

    Analyses of muscular activity during rhythmic behaviors provide critical data for biomechanical studies. Electrical potentials measured from muscles using electromyography (EMG) require discrimination of noise regions as the first step in analysis. An experienced analyst can accurately identify the onset and offset of EMG but this process takes hours to analyze a short (10-15s) record of rhythmic EMG bursts. Existing computational techniques reduce this time but have limitations. These include a universal threshold for delimiting noise regions (i.e., a single signal value for identifying the EMG signal onset and offset), pre-processing using wide time intervals that dampen sensitivity for EMG signal characteristics, poor performance when a low frequency component (e.g., DC offset) is present, and high computational complexity leading to lack of time efficiency. We present a new statistical method and MATLAB script (EMG-Extractor) that includes an adaptive algorithm to discriminate noise regions from EMG that avoids these limitations and allows for multi-channel datasets to be processed. We evaluate the EMG-Extractor with EMG data on mammalian jaw-adductor muscles during mastication, a rhythmic behavior typified by low amplitude onsets/offsets and complex signal pattern. The EMG-Extractor consistently and accurately distinguishes noise from EMG in a manner similar to that of an experienced analyst. It outputs the raw EMG signal region in a form ready for further analysis. Copyright © 2016 Elsevier Ltd. All rights reserved.

  19. Spatial discrimination and visual discrimination

    DEFF Research Database (Denmark)

    Haagensen, Annika M. J.; Grand, Nanna; Klastrup, Signe

    2013-01-01

    Two methods investigating learning and memory in juvenile Gottingen minipigs were evaluated for potential use in preclinical toxicity testing. Twelve minipigs were tested using a spatial hole-board discrimination test including a learning phase and two memory phases. Five minipigs were tested...... in a visual discrimination test. The juvenile minipigs were able to learn the spatial hole-board discrimination test and showed improved working and reference memory during the learning phase. Performance in the memory phases was affected by the retention intervals, but the minipigs were able to remember...... the concept of the test in both memory phases. Working memory and reference memory were significantly improved in the last trials of the memory phases. In the visual discrimination test, the minipigs learned to discriminate between the three figures presented to them within 9-14 sessions. For the memory test...

  20. Neutron-Gamma Pulse Shape Discrimination With Ne-213 Liquid Scintillator By Using Digital Signal Processing Combined With Similarity Method

    International Nuclear Information System (INIS)

    Mardiyanto

    2008-01-01

    Neutron-Gamma Pulse Shape Discrimination with a NE-213 Liquid Scintillator by Using Digital Signal Processing Combined with Similarity Method. Measurement of mixed neutron-gamma radiation is difficult because a nuclear detector is usually sensitive to both radiations. A new attempt of neutron-gamma pulse shape discrimination for a NE-213 liquid scintillator is presented by using digital signal processing combined with an off-line similarity method. The output pulse shapes are digitized with a high speed digital oscilloscope. The n-γ discrimination is done by calculating the index of each pulse shape, which is determined by the similarity method, and then fusing it with its corresponding pulse height. Preliminary results demonstrate good separation of neutron and gamma-ray signals from a NE-213 scintillator with a simple digital system. The results were better than those with a conventional rise time method. Figure of Merit is used to determine the quality of discrimination. The figure of merit of the discrimination using digital signal processing combined with off-line similarity method are 1.9; 1.7; 1.1; 1.1; and 0.8; on the other hand by using conventional method the rise time are 0.9; 0.9; 0.9; 0.7; and 0.4 for the equivalent electron energy of 800; 278; 139; 69; and 30 keV. (author)

  1. Convolutional neural network features based change detection in satellite images

    Science.gov (United States)

    Mohammed El Amin, Arabi; Liu, Qingjie; Wang, Yunhong

    2016-07-01

    With the popular use of high resolution remote sensing (HRRS) satellite images, a huge research efforts have been placed on change detection (CD) problem. An effective feature selection method can significantly boost the final result. While hand-designed features have proven difficulties to design features that effectively capture high and mid-level representations, the recent developments in machine learning (Deep Learning) omit this problem by learning hierarchical representation in an unsupervised manner directly from data without human intervention. In this letter, we propose approaching the change detection problem from a feature learning perspective. A novel deep Convolutional Neural Networks (CNN) features based HR satellite images change detection method is proposed. The main guideline is to produce a change detection map directly from two images using a pretrained CNN. This method can omit the limited performance of hand-crafted features. Firstly, CNN features are extracted through different convolutional layers. Then, a concatenation step is evaluated after an normalization step, resulting in a unique higher dimensional feature map. Finally, a change map was computed using pixel-wise Euclidean distance. Our method has been validated on real bitemporal HRRS satellite images according to qualitative and quantitative analyses. The results obtained confirm the interest of the proposed method.

  2. The Neutron-Gamma Pulse Shape Discrimination Method for Neutron Flux Detection in the ITER

    International Nuclear Information System (INIS)

    Xu Xiufeng; Li Shiping; Cao Hongrui; Yin Zejie; Yuan Guoliang; Yang Qingwei

    2013-01-01

    The neutron flux monitor (NFM), as a significant diagnostic system in the International Thermonuclear Experimental Reactor (ITER), will play an important role in the readings of a series of key parameters in the fusion reaction process. As the core of the main electronic system of the NFM, the neutron-gamma pulse shape discrimination (n-γ PSD) can distinguish the neutron pulse from the gamma pulse and other disturbing pulses according to the thresholds of the rising time and the amplitude pre-installed on the board, the double timing point CFD method is used to get the rising time of the pulse. The n-γ PSD can provide an accurate neutron count. (magnetically confined plasma)

  3. A Comparative Study of Feature Selection Methods for the Discriminative Analysis of Temporal Lobe Epilepsy

    Directory of Open Access Journals (Sweden)

    Chunren Lai

    2017-12-01

    Full Text Available It is crucial to differentiate patients with temporal lobe epilepsy (TLE from the healthy population and determine abnormal brain regions in TLE. The cortical features and changes can reveal the unique anatomical patterns of brain regions from structural magnetic resonance (MR images. In this study, structural MR images from 41 patients with left TLE, 34 patients with right TLE, and 58 normal controls (NC were acquired, and four kinds of cortical measures, namely cortical thickness, cortical surface area, gray matter volume (GMV, and mean curvature, were explored for discriminative analysis. Three feature selection methods including the independent sample t-test filtering, the sparse-constrained dimensionality reduction model (SCDRM, and the support vector machine-recursive feature elimination (SVM-RFE were investigated to extract dominant features among the compared groups for classification using the support vector machine (SVM classifier. The results showed that the SVM-RFE achieved the highest performance (most classifications with more than 84% accuracy, followed by the SCDRM, and the t-test. Especially, the surface area and GMV exhibited prominent discriminative ability, and the performance of the SVM was improved significantly when the four cortical measures were combined. Additionally, the dominant regions with higher classification weights were mainly located in the temporal and the frontal lobe, including the entorhinal cortex, rostral middle frontal, parahippocampal cortex, superior frontal, insula, and cuneus. This study concluded that the cortical features provided effective information for the recognition of abnormal anatomical patterns and the proposed methods had the potential to improve the clinical diagnosis of TLE.

  4. Monitoring of facial stress during space flight: Optical computer recognition combining discriminative and generative methods

    Science.gov (United States)

    Dinges, David F.; Venkataraman, Sundara; McGlinchey, Eleanor L.; Metaxas, Dimitris N.

    2007-02-01

    Astronauts are required to perform mission-critical tasks at a high level of functional capability throughout spaceflight. Stressors can compromise their ability to do so, making early objective detection of neurobehavioral problems in spaceflight a priority. Computer optical approaches offer a completely unobtrusive way to detect distress during critical operations in space flight. A methodology was developed and a study completed to determine whether optical computer recognition algorithms could be used to discriminate facial expressions during stress induced by performance demands. Stress recognition from a facial image sequence is a subject that has not received much attention although it is an important problem for many applications beyond space flight (security, human-computer interaction, etc.). This paper proposes a comprehensive method to detect stress from facial image sequences by using a model-based tracker. The image sequences were captured as subjects underwent a battery of psychological tests under high- and low-stress conditions. A cue integration-based tracking system accurately captured the rigid and non-rigid parameters of different parts of the face (eyebrows, lips). The labeled sequences were used to train the recognition system, which consisted of generative (hidden Markov model) and discriminative (support vector machine) parts that yield results superior to using either approach individually. The current optical algorithm methods performed at a 68% accuracy rate in an experimental study of 60 healthy adults undergoing periods of high-stress versus low-stress performance demands. Accuracy and practical feasibility of the technique is being improved further with automatic multi-resolution selection for the discretization of the mask, and automated face detection and mask initialization algorithms.

  5. A Time-Walk Correction Method for PET Detectors Based on Leading Edge Discriminators.

    Science.gov (United States)

    Du, Junwei; Schmall, Jeffrey P; Judenhofer, Martin S; Di, Kun; Yang, Yongfeng; Cherry, Simon R

    2017-09-01

    The leading edge timing pick-off technique is the simplest timing extraction method for PET detectors. Due to the inherent time-walk of the leading edge technique, corrections should be made to improve timing resolution, especially for time-of-flight PET. Time-walk correction can be done by utilizing the relationship between the threshold crossing time and the event energy on an event by event basis. In this paper, a time-walk correction method is proposed and evaluated using timing information from two identical detectors both using leading edge discriminators. This differs from other techniques that use an external dedicated reference detector, such as a fast PMT-based detector using constant fraction techniques to pick-off timing information. In our proposed method, one detector was used as reference detector to correct the time-walk of the other detector. Time-walk in the reference detector was minimized by using events within a small energy window (508.5 - 513.5 keV). To validate this method, a coincidence detector pair was assembled using two SensL MicroFB SiPMs and two 2.5 mm × 2.5 mm × 20 mm polished LYSO crystals. Coincidence timing resolutions using different time pick-off techniques were obtained at a bias voltage of 27.5 V and a fixed temperature of 20 °C. The coincidence timing resolution without time-walk correction were 389.0 ± 12.0 ps (425 -650 keV energy window) and 670.2 ± 16.2 ps (250-750 keV energy window). The timing resolution with time-walk correction improved to 367.3 ± 0.5 ps (425 - 650 keV) and 413.7 ± 0.9 ps (250 - 750 keV). For comparison, timing resolutions were 442.8 ± 12.8 ps (425 - 650 keV) and 476.0 ± 13.0 ps (250 - 750 keV) using constant fraction techniques, and 367.3 ± 0.4 ps (425 - 650 keV) and 413.4 ± 0.9 ps (250 - 750 keV) using a reference detector based on the constant fraction technique. These results show that the proposed leading edge based time-walk correction method works well. Timing resolution obtained

  6. The use of principal component, discriminate and rough sets analysis methods of radiological data

    International Nuclear Information System (INIS)

    Seddeek, M.K.; Kozae, A.M.; Sharshar, T.; Badran, H.M.

    2006-01-01

    In this work, computational methods of finding clusters of multivariate data points were explored using principal component analysis (PCA), discriminate analysis (DA) and rough set analysis (RSA) methods. The variables were the concentrations of four natural isotopes and the texture characteristics of 100 sand samples from the coast of North Sinai, Egypt. Beach and dune sands are the two types of samples included. These methods were used to reduce the dimensionality of multivariate data and as classification and clustering methods. The results showed that the classification of sands in the environment of North Sinai is dependent upon the radioactivity contents of the naturally occurring radioactive materials and not upon the characteristics of the sand. The application of DA enables the creation of a classification rule for sand type and it revealed that samples with high negatively values of the first score have the highest contamination of black sand. PCA revealed that radioactivity concentrations alone can be considered to predict the classification of other samples. The results of RSA showed that only one of the concentrations of 238 U, 226 Ra and 232 Th with 40 K content, can characterize the clusters together with characteristics of the sand. Both PCA and RSA result in the following conclusion: 238 U, 226 Ra and 232 Th behave similarly. RSA revealed that one/two of them may not be considered without affecting the body of knowledge

  7. Theoretical vs. empirical discriminability: the application of ROC methods to eyewitness identification.

    Science.gov (United States)

    Wixted, John T; Mickes, Laura

    2018-01-01

    Receiver operating characteristic (ROC) analysis was introduced to the field of eyewitness identification 5 years ago. Since that time, it has been both influential and controversial, and the debate has raised an issue about measuring discriminability that is rarely considered. The issue concerns the distinction between empirical discriminability (measured by area under the ROC curve) vs. underlying/theoretical discriminability (measured by d' or variants of it). Under most circumstances, the two measures will agree about a difference between two conditions in terms of discriminability. However, it is possible for them to disagree, and that fact can lead to confusion about which condition actually yields higher discriminability. For example, if the two conditions have implications for real-world practice (e.g., a comparison of competing lineup formats), should a policymaker rely on the area-under-the-curve measure or the theory-based measure? Here, we illustrate the fact that a given empirical ROC yields as many underlying discriminability measures as there are theories that one is willing to take seriously. No matter which theory is correct, for practical purposes, the singular area-under-the-curve measure best identifies the diagnostically superior procedure. For that reason, area under the ROC curve informs policy in a way that underlying theoretical discriminability never can. At the same time, theoretical measures of discriminability are equally important, but for a different reason. Without an adequate theoretical understanding of the relevant task, the field will be in no position to enhance empirical discriminability.

  8. Study of n-γ discrimination by digital charge comparison method for a large volume liquid scintillator

    International Nuclear Information System (INIS)

    Moszynski, M.; Costa, G.J.; Guillaume, G.; Heusch, B.; Huck, A.; Ring, C.; Bizard, G.; Durand, D.; Peter, J.; Tamain, B.; El Masri, Y.; Hanappe, F.

    1992-01-01

    The study of the n-γ discrimination for a large 41 volume BC501A liquid scintillator coupled to a 130 mm diameter XP4512B photomultiplier was carried out by digital charge comparison method. A very good n-γ discrimination down to 100 keV of recoil electron energy was achieved. The measured relative intensity of the charge integrated at the slow component of the scintillation pulse and the photoelectron yield of the tested counter allow the factor of merit of the n-γ discrimination spectra to be calculated and to be compared with those measured experimentally. This shows that the main limitation of the n-γ discrimination is associated with the statistical fluctuation of the photoelectron number at the slow component. A serious effect of the distortion in the cable used to send the photomultiplier pulse to the electronics for the n-γ discrimination was studied. This suggests that the length of RG58 cable should be limited to about 40 m to preserve a high quality n-γ discrimination. (orig.)

  9. Feature-based attentional modulation increases with stimulus separation in divided-attention tasks.

    Science.gov (United States)

    Sally, Sharon L; Vidnyánsky, Zoltán; Papathomas, Thomas V

    2009-01-01

    Attention modifies our visual experience by selecting certain aspects of a scene for further processing. It is therefore important to understand factors that govern the deployment of selective attention over the visual field. Both location and feature-specific mechanisms of attention have been identified and their modulatory effects can interact at a neural level (Treue and Martinez-Trujillo, 1999). The effects of spatial parameters on feature-based attentional modulation were examined for the feature dimensions of orientation, motion and color using three divided-attention tasks. Subjects performed concurrent discriminations of two briefly presented targets (Gabor patches) to the left and right of a central fixation point at eccentricities of +/-2.5 degrees , 5 degrees , 10 degrees and 15 degrees in the horizontal plane. Gabors were size-scaled to maintain consistent single-task performance across eccentricities. For all feature dimensions, the data show a linear increase in the attentional effects with target separation. In a control experiment, Gabors were presented on an isoeccentric viewing arc at 10 degrees and 15 degrees at the closest spatial separation (+/-2.5 degrees ) of the main experiment. Under these conditions, the effects of feature-based attentional effects were largely eliminated. Our results are consistent with the hypothesis that feature-based attention prioritizes the processing of attended features. Feature-based attentional mechanisms may have helped direct the attentional focus to the appropriate target locations at greater separations, whereas similar assistance may not have been necessary at closer target spacings. The results of the present study specify conditions under which dual-task performance benefits from sharing similar target features and may therefore help elucidate the processes by which feature-based attention operates.

  10. Image Recommendation Algorithm Using Feature-Based Collaborative Filtering

    Science.gov (United States)

    Kim, Deok-Hwan

    As the multimedia contents market continues its rapid expansion, the amount of image contents used in mobile phone services, digital libraries, and catalog service is increasing remarkably. In spite of this rapid growth, users experience high levels of frustration when searching for the desired image. Even though new images are profitable to the service providers, traditional collaborative filtering methods cannot recommend them. To solve this problem, in this paper, we propose feature-based collaborative filtering (FBCF) method to reflect the user's most recent preference by representing his purchase sequence in the visual feature space. The proposed approach represents the images that have been purchased in the past as the feature clusters in the multi-dimensional feature space and then selects neighbors by using an inter-cluster distance function between their feature clusters. Various experiments using real image data demonstrate that the proposed approach provides a higher quality recommendation and better performance than do typical collaborative filtering and content-based filtering techniques.

  11. Perceived discrimination, humiliation, and mental health: a mixed-methods study among Haitian migrants in the Dominican Republic.

    Science.gov (United States)

    Keys, Hunter M; Kaiser, Bonnie N; Foster, Jennifer W; Burgos Minaya, Rosa Y; Kohrt, Brandon A

    2015-01-01

    Many Haitian migrants live and work as undocumented laborers in the Dominican Republic. This study examines the legacy of anti-Haitian discrimination in the Dominican Republic and association of discrimination with mental health among Haitian migrants. This study used mixed methods to generate hypotheses for associations between discrimination and mental health of Haitian migrants in the Dominican Republic. In-depth interviews were conducted with 21 Haitian and 18 Dominican community members and clinicians. One hundred and twenty-seven Haitian migrants participated in a pilot cross-sectional community survey. Instruments included culturally adapted Kreyòl versions of the Beck Depression Inventory (BDI) and Beck Anxiety Inventory (BAI) and a locally developed function impairment scale. Haitian migrants described humiliation (imilyasyon) as a reason for mental distress and barrier to health care. Dominicans reported that discrimination (discriminación) was not a current social problem and attributed negative social interactions to sociocultural, behavioral, and biological differences between Dominicans and Haitians. These qualitative findings were supported in the quantitative analyses. Perceived discrimination was significantly associated with depression severity and functional impairment. Perceived mistreatment by Dominicans was associated with a 6.6-point increase in BDI score (90% confidence interval [CI]: 3.29, 9.9). Knowing someone who was interrogated or deported was associated with a 3.4-point increase in BAI score (90% CI: 0.22, 6.64). Both qualitative and quantitative methods suggest that perceived discrimination and the experience of humiliation contribute to Haitian migrant mental ill-health and limit access to health care. Future research should evaluate these associations and identify intervention pathways for both improved treatment access and reduction of discrimination-related health risk factors.

  12. Iris features-based heart disease diagnosis by computer vision

    Science.gov (United States)

    Nguchu, Benedictor A.; Li, Li

    2017-07-01

    The study takes advantage of several new breakthroughs in computer vision technology to develop a new mid-irisbiomedical platform that processes iris image for early detection of heart-disease. Guaranteeing early detection of heart disease provides a possibility of having non-surgical treatment as suggested by biomedical researchers and associated institutions. However, our observation discovered that, a clinical practicable solution which could be both sensible and specific for early detection is still lacking. Due to this, the rate of majority vulnerable to death is highly increasing. The delayed diagnostic procedures, inefficiency, and complications of available methods are the other reasons for this catastrophe. Therefore, this research proposes the novel IFB (Iris Features Based) method for diagnosis of premature, and early stage heart disease. The method incorporates computer vision and iridology to obtain a robust, non-contact, nonradioactive, and cost-effective diagnostic tool. The method analyzes abnormal inherent weakness in tissues, change in color and patterns, of a specific region of iris that responds to impulses of heart organ as per Bernard Jensen-iris Chart. The changes in iris infer the presence of degenerative abnormalities in heart organ. These changes are precisely detected and analyzed by IFB method that includes, tensor-based-gradient(TBG), multi orientations gabor filters(GF), textural oriented features(TOF), and speed-up robust features(SURF). Kernel and Multi class oriented support vector machines classifiers are used for classifying normal and pathological iris features. Experimental results demonstrated that the proposed method, not only has better diagnostic performance, but also provides an insight for early detection of other diseases.

  13. Photoacoustic discrimination of vascular and pigmented lesions using classical and Bayesian methods

    Science.gov (United States)

    Swearingen, Jennifer A.; Holan, Scott H.; Feldman, Mary M.; Viator, John A.

    2010-01-01

    Discrimination of pigmented and vascular lesions in skin can be difficult due to factors such as size, subungual location, and the nature of lesions containing both melanin and vascularity. Misdiagnosis may lead to precancerous or cancerous lesions not receiving proper medical care. To aid in the rapid and accurate diagnosis of such pathologies, we develop a photoacoustic system to determine the nature of skin lesions in vivo. By irradiating skin with two laser wavelengths, 422 and 530 nm, we induce photoacoustic responses, and the relative response at these two wavelengths indicates whether the lesion is pigmented or vascular. This response is due to the distinct absorption spectrum of melanin and hemoglobin. In particular, pigmented lesions have ratios of photoacoustic amplitudes of approximately 1.4 to 1 at the two wavelengths, while vascular lesions have ratios of about 4.0 to 1. Furthermore, we consider two statistical methods for conducting classification of lesions: standard multivariate analysis classification techniques and a Bayesian-model-based approach. We study 15 human subjects with eight vascular and seven pigmented lesions. Using the classical method, we achieve a perfect classification rate, while the Bayesian approach has an error rate of 20%.

  14. Beyond discrimination: A comparison of calibration methods and clinical usefulness of predictive models of readmission risk.

    Science.gov (United States)

    Walsh, Colin G; Sharman, Kavya; Hripcsak, George

    2017-12-01

    Prior to implementing predictive models in novel settings, analyses of calibration and clinical usefulness remain as important as discrimination, but they are not frequently discussed. Calibration is a model's reflection of actual outcome prevalence in its predictions. Clinical usefulness refers to the utilities, costs, and harms of using a predictive model in practice. A decision analytic approach to calibrating and selecting an optimal intervention threshold may help maximize the impact of readmission risk and other preventive interventions. To select a pragmatic means of calibrating predictive models that requires a minimum amount of validation data and that performs well in practice. To evaluate the impact of miscalibration on utility and cost via clinical usefulness analyses. Observational, retrospective cohort study with electronic health record data from 120,000 inpatient admissions at an urban, academic center in Manhattan. The primary outcome was thirty-day readmission for three causes: all-cause, congestive heart failure, and chronic coronary atherosclerotic disease. Predictive modeling was performed via L1-regularized logistic regression. Calibration methods were compared including Platt Scaling, Logistic Calibration, and Prevalence Adjustment. Performance of predictive modeling and calibration was assessed via discrimination (c-statistic), calibration (Spiegelhalter Z-statistic, Root Mean Square Error [RMSE] of binned predictions, Sanders and Murphy Resolutions of the Brier Score, Calibration Slope and Intercept), and clinical usefulness (utility terms represented as costs). The amount of validation data necessary to apply each calibration algorithm was also assessed. C-statistics by diagnosis ranged from 0.7 for all-cause readmission to 0.86 (0.78-0.93) for congestive heart failure. Logistic Calibration and Platt Scaling performed best and this difference required analyzing multiple metrics of calibration simultaneously, in particular Calibration

  15. Prediction of Nepsilon-acetylation on internal lysines implemented in Bayesian Discriminant Method.

    Science.gov (United States)

    Li, Ao; Xue, Yu; Jin, Changjiang; Wang, Minghui; Yao, Xuebiao

    2006-12-01

    Protein acetylation is an important and reversible post-translational modification (PTM), and it governs a variety of cellular dynamics and plasticity. Experimental identification of acetylation sites is labor-intensive and often limited by the availability of reagents such as acetyl-specific antibodies and optimization of enzymatic reactions. Computational analyses may facilitate the identification of potential acetylation sites and provide insights into further experimentation. In this manuscript, we present a novel protein acetylation prediction program named PAIL, prediction of acetylation on internal lysines, implemented in a BDM (Bayesian Discriminant Method) algorithm. The accuracies of PAIL are 85.13%, 87.97%, and 89.21% at low, medium, and high thresholds, respectively. Both Jack-Knife validation and n-fold cross-validation have been performed to show that PAIL is accurate and robust. Taken together, we propose that PAIL is a novel predictor for identification of protein acetylation sites and may serve as an important tool to study the function of protein acetylation. PAIL has been implemented in PHP and is freely available on a web server at: http://bioinformatics.lcd-ustc.org/pail.

  16. Prediction of Nε-acetylation on internal lysines implemented in Bayesian Discriminant Method

    Science.gov (United States)

    Li, Ao; Xue, Yu; Jin, Changjiang; Wang, Minghui; Yao, Xuebiao

    2007-01-01

    Protein acetylation is an important and reversible post-translational modification (PTM), and it governs a variety of cellular dynamics and plasticity. Experimental identification of acetylation sites is labor-intensive and often limited by the availability reagents such as acetyl-specific antibodies and optimization of enzymatic reactions. Computational analyses may facilitate the identification of potential acetylation sites and provide insights into further experimentation. In this manuscript, we present a novel protein acetylation prediction program named PAIL, prediction of acetylation on internal lysines, implemented in a BDM (Bayesian Discriminant Method) algorithm. The accuracies of PAIL are 85.13%, 87.97% and 89.21% at low, medium and high thresholds, respectively. Both Jack-Knife validation and n-fold cross validation have been performed to show that PAIL is accurate and robust. Taken together, we propose that PAIL is a novel predictor for identification of protein acetylation sites and may serve as an important tool to study the function of protein acetylation. PAIL has been implemented in PHP and is freely available on a web server at: http://bioinformatics.lcd-ustc.org/pail. PMID:17045240

  17. [Outlier sample discriminating methods for building calibration model in melons quality detecting using NIR spectra].

    Science.gov (United States)

    Tian, Hai-Qing; Wang, Chun-Guang; Zhang, Hai-Jun; Yu, Zhi-Hong; Li, Jian-Kang

    2012-11-01

    Outlier samples strongly influence the precision of the calibration model in soluble solids content measurement of melons using NIR Spectra. According to the possible sources of outlier samples, three methods (predicted concentration residual test; Chauvenet test; leverage and studentized residual test) were used to discriminate these outliers respectively. Nine suspicious outliers were detected from calibration set which including 85 fruit samples. Considering the 9 suspicious outlier samples maybe contain some no-outlier samples, they were reclaimed to the model one by one to see whether they influence the model and prediction precision or not. In this way, 5 samples which were helpful to the model joined in calibration set again, and a new model was developed with the correlation coefficient (r) 0. 889 and root mean square errors for calibration (RMSEC) 0.6010 Brix. For 35 unknown samples, the root mean square errors prediction (RMSEP) was 0.854 degrees Brix. The performance of this model was more better than that developed with non outlier was eliminated from calibration set (r = 0.797, RMSEC= 0.849 degrees Brix, RMSEP = 1.19 degrees Brix), and more representative and stable with all 9 samples were eliminated from calibration set (r = 0.892, RMSEC = 0.605 degrees Brix, RMSEP = 0.862 degrees).

  18. Evaluation of sensory panels of consumers of specialty coffee beverages using the boosting method in discriminant analysis

    Directory of Open Access Journals (Sweden)

    Gilberto Rodrigues Liska

    2015-12-01

    Full Text Available Automatic classification methods have been widely used in numerous situations and the boosting method has become known for use of a classification algorithm, which considers a set of training data and, from that set, constructs a classifier with reweighted versions of the training set. Given this characteristic, the aim of this study is to assess a sensory experiment related to acceptance tests with specialty coffees, with reference to both trained and untrained consumer groups. For the consumer group, four sensory characteristics were evaluated, such as aroma, body, sweetness, and final score, attributed to four types of specialty coffees. In order to obtain a classification rule that discriminates trained and untrained tasters, we used the conventional Fisher’s Linear Discriminant Analysis (LDA and discriminant analysis via boosting algorithm (AdaBoost. The criteria used in the comparison of the two approaches were sensitivity, specificity, false positive rate, false negative rate, and accuracy of classification methods. Additionally, to evaluate the performance of the classifiers, the success rates and error rates were obtained by Monte Carlo simulation, considering 100 replicas of a random partition of 70% for the training set, and the remaining for the test set. It was concluded that the boosting method applied to discriminant analysis yielded a higher sensitivity rate in regard to the trained panel, at a value of 80.63% and, hence, reduction in the rate of false negatives, at 19.37%. Thus, the boosting method may be used as a means of improving the LDA classifier for discrimination of trained tasters.

  19. THE BOLOCAM GALACTIC PLANE SURVEY. VIII. A MID-INFRARED KINEMATIC DISTANCE DISCRIMINATION METHOD

    Energy Technology Data Exchange (ETDEWEB)

    Ellsworth-Bowers, Timothy P.; Glenn, Jason; Battersby, Cara; Ginsburg, Adam; Bally, John [CASA, University of Colorado, UCB 389, University of Colorado, Boulder, CO 80309 (United States); Rosolowsky, Erik [Department of Physics and Astronomy, University of British Columbia Okanagan, 3333 University Way, Kelowna, BC V1V 1V7 (Canada); Mairs, Steven [Department of Physics and Astronomy, University of Victoria, 3800 Finnerty Road, Victoria, BC V8P 1A1 (Canada); Evans, Neal J. II [Department of Astronomy, University of Texas, 1 University Station C1400, Austin, TX 78712 (United States); Shirley, Yancy L., E-mail: timothy.ellsworthbowers@colorado.edu [Steward Observatory, University of Arizona, 933 North Cherry Avenue, Tucson, AZ 85721 (United States)

    2013-06-10

    We present a new distance estimation method for dust-continuum-identified molecular cloud clumps. Recent (sub-)millimeter Galactic plane surveys have cataloged tens of thousands of these objects, plausible precursors to stellar clusters, but detailed study of their physical properties requires robust distance determinations. We derive Bayesian distance probability density functions (DPDFs) for 770 objects from the Bolocam Galactic Plane Survey in the Galactic longitude range 7. Degree-Sign 5 {<=} l {<=} 65 Degree-Sign . The DPDF formalism is based on kinematic distances, and uses any number of external data sets to place prior distance probabilities to resolve the kinematic distance ambiguity (KDA) for objects in the inner Galaxy. We present here priors related to the mid-infrared absorption of dust in dense molecular regions and the distribution of molecular gas in the Galactic disk. By assuming a numerical model of Galactic mid-infrared emission and simple radiative transfer, we match the morphology of (sub-)millimeter thermal dust emission with mid-infrared absorption to compute a prior DPDF for distance discrimination. Selecting objects first from (sub-)millimeter source catalogs avoids a bias towards the darkest infrared dark clouds (IRDCs) and extends the range of heliocentric distance probed by mid-infrared extinction and includes lower-contrast sources. We derive well-constrained KDA resolutions for 618 molecular cloud clumps, with approximately 15% placed at or beyond the tangent distance. Objects with mid-infrared contrast sufficient to be cataloged as IRDCs are generally placed at the near kinematic distance. Distance comparisons with Galactic Ring Survey KDA resolutions yield a 92% agreement. A face-on view of the Milky Way using resolved distances reveals sections of the Sagittarius and Scutum-Centaurus Arms. This KDA-resolution method for large catalogs of sources through the combination of (sub-)millimeter and mid-infrared observations of molecular

  20. Novel methods for the molecular discrimination of Fasciola spp. on the basis of nuclear protein-coding genes.

    Science.gov (United States)

    Shoriki, Takuya; Ichikawa-Seki, Madoka; Suganuma, Keisuke; Naito, Ikunori; Hayashi, Kei; Nakao, Minoru; Aita, Junya; Mohanta, Uday Kumar; Inoue, Noboru; Murakami, Kenji; Itagaki, Tadashi

    2016-06-01

    Fasciolosis is an economically important disease of livestock caused by Fasciola hepatica, Fasciola gigantica, and aspermic Fasciola flukes. The aspermic Fasciola flukes have been discriminated morphologically from the two other species by the absence of sperm in their seminal vesicles. To date, the molecular discrimination of F. hepatica and F. gigantica has relied on the nucleotide sequences of the internal transcribed spacer 1 (ITS1) region. However, ITS1 genotypes of aspermic Fasciola flukes cannot be clearly differentiated from those of F. hepatica and F. gigantica. Therefore, more precise and robust methods are required to discriminate Fasciola spp. In this study, we developed PCR restriction fragment length polymorphism and multiplex PCR methods to discriminate F. hepatica, F. gigantica, and aspermic Fasciola flukes on the basis of the nuclear protein-coding genes, phosphoenolpyruvate carboxykinase and DNA polymerase delta, which are single locus genes in most eukaryotes. All aspermic Fasciola flukes used in this study had mixed fragment pattern of F. hepatica and F. gigantica for both of these genes, suggesting that the flukes are descended through hybridization between the two species. These molecular methods will facilitate the identification of F. hepatica, F. gigantica, and aspermic Fasciola flukes, and will also prove useful in etiological studies of fasciolosis. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  1. Modification method to reduce the impact of blood vessel on noncontact discrimination of human blood based on ;M+N; theory

    Science.gov (United States)

    Zhang, Linna; Ding, Hongyan; Lin, Ling; Wang, Yimin; Guo, Xin

    2018-01-01

    Noncontact discriminating human blood is significantly crucial for import-export ports and inspection and quarantine departments. We had already demonstrated that visible diffuse reflectance spectroscopy combining PLS-DA method can successfully realize noncontact human blood discrimination. However, the circulated blood vessels may be produced with different materials. The use of various kinds of blood tubes may have a negative effect on the discrimination, based on ;M+N; theory (Li et al., 2016). In this research, we explored the impact of different material of blood vessels, such as glass tube and plastic tube, on the prediction ability of the discrimination model. Furthermore, we searched for the modification method to reduce the influence from the blood tubes. Our work indicated that generalized diffuse reflectance method can greatly improve the discrimination accuracy. This research can greatly facilitate the application of noncontact discrimination method based on visible and near-infrared diffuse reflectance spectroscopy.

  2. Adaptive Feature Based Control of Compact Disk Players

    DEFF Research Database (Denmark)

    Odgaard, Peter Fogh; Stoustrup, Jakob; Vidal, Enrique Sanchez

    2005-01-01

    Many have experienced the problem that their Compact Disc players have difficulties playing Compact Discs with surface faults like scratches and fingerprints. The cause of this is due to the two servo control loops used to keep the Optical Pick-up Unit focused and radially on the information track...... of the Compact Disc. The problem is to design servo controllers which are well suited for handling surface faults which disturb the position measurement and still react sufficiently against normal disturbances like mechanical shocks. In previous work of the same authors a feature based control scheme for CD......-players playing CDs with surface fault is derived and described. This feature based control scheme uses precomputed base to remove the surface fault influence from the position measurements. In this paper an adaptive version of the feature based control scheme is proposed and described. This adaptive scheme can...

  3. Feature-based Ontology Mapping from an Information Receivers’ Viewpoint

    DEFF Research Database (Denmark)

    Glückstad, Fumiko Kano; Mørup, Morten

    2012-01-01

    This paper compares four algorithms for computing feature-based similarities between concepts respectively possessing a distinctive set of features. The eventual purpose of comparing these feature-based similarity algorithms is to identify a candidate term in a Target Language (TL) that can...... optimally convey the original meaning of a culturally-specific Source Language (SL) concept to a TL audience by aligning two culturally-dependent domain-specific ontologies. The results indicate that the Bayesian Model of Generalization [1] performs best, not only for identifying candidate translation terms...

  4. A pulse-shape discrimination method for improving Gamma-ray spectrometry based on a new digital shaping filter

    Science.gov (United States)

    Qin, Zhang-jian; Chen, Chuan; Luo, Jun-song; Xie, Xing-hong; Ge, Liang-quan; Wu, Qi-fan

    2018-04-01

    It is a usual practice for improving spectrum quality by the mean of designing a good shaping filter to improve signal-noise ratio in development of nuclear spectroscopy. Another method is proposed in the paper based on discriminating pulse-shape and discarding the bad pulse whose shape is distorted as a result of abnormal noise, unusual ballistic deficit or bad pulse pile-up. An Exponentially Decaying Pulse (EDP) generated in nuclear particle detectors can be transformed into a Mexican Hat Wavelet Pulse (MHWP) and the derivation process of the transform is given. After the transform is performed, the baseline drift is removed in the new MHWP. Moreover, the MHWP-shape can be discriminated with the three parameters: the time difference between the two minima of the MHWP, and the two ratios which are from the amplitude of the two minima respectively divided by the amplitude of the maximum in the MHWP. A new type of nuclear spectroscopy was implemented based on the new digital shaping filter and the Gamma-ray spectra were acquired with a variety of pulse-shape discrimination levels. It had manifested that the energy resolution and the peak-Compton ratio were both improved after the pulse-shape discrimination method was used.

  5. Discrimination method of large log-likelihood study in differential diagnosis of pulmonary diffuse mild micro-nodule

    International Nuclear Information System (INIS)

    Chen Budong; Ma Daqing; He Wen; Tang Hongqu; Qian Linxue; Zhou Ronglin

    2001-01-01

    Objective: To analyze HRCT and thin-slice CT scan findings in 150 patients with pulmonary diffuse mild micro-nodule, and to find the features with the purpose of identifying random micro-nodule, peri-lymphatic micro-nodule, and centrilobular micro-nodule. Methods: The useful features i 150 patients with pulmonary diffuse mild micro-nodule were translated into scores by means of discrimination method of large log-likelihood to identify the micro-nodular category. Results: The accuracy of diagnosis was 94.0% for random micro-nodule, 76.0% for peri-lymphatic micro-nodule, and 90.0% for centrilobular micro-nodule. Conclusion: HRCT and thin-slice CT scans were helpful in differential diagnosis of pulmonary diffuse mild micro-nodule. The discrimination method of large log-likelihood was propitious to diagnosis and differential diagnosis

  6. Feature-based morphometry: discovering group-related anatomical patterns.

    Science.gov (United States)

    Toews, Matthew; Wells, William; Collins, D Louis; Arbel, Tal

    2010-02-01

    This paper presents feature-based morphometry (FBM), a new fully data-driven technique for discovering patterns of group-related anatomical structure in volumetric imagery. In contrast to most morphometry methods which assume one-to-one correspondence between subjects, FBM explicitly aims to identify distinctive anatomical patterns that may only be present in subsets of subjects, due to disease or anatomical variability. The image is modeled as a collage of generic, localized image features that need not be present in all subjects. Scale-space theory is applied to analyze image features at the characteristic scale of underlying anatomical structures, instead of at arbitrary scales such as global or voxel-level. A probabilistic model describes features in terms of their appearance, geometry, and relationship to subject groups, and is automatically learned from a set of subject images and group labels. Features resulting from learning correspond to group-related anatomical structures that can potentially be used as image biomarkers of disease or as a basis for computer-aided diagnosis. The relationship between features and groups is quantified by the likelihood of feature occurrence within a specific group vs. the rest of the population, and feature significance is quantified in terms of the false discovery rate. Experiments validate FBM clinically in the analysis of normal (NC) and Alzheimer's (AD) brain images using the freely available OASIS database. FBM automatically identifies known structural differences between NC and AD subjects in a fully data-driven fashion, and an equal error classification rate of 0.80 is achieved for subjects aged 60-80 years exhibiting mild AD (CDR=1). Copyright (c) 2009 Elsevier Inc. All rights reserved.

  7. Feature-based attentional modulation of orientation perception in somatosensation

    Directory of Open Access Journals (Sweden)

    Meike Annika Schweisfurth

    2014-07-01

    Full Text Available In a reaction time study of human tactile orientation detection the effects of spatial attention and feature-based attention were investigated. Subjects had to give speeded responses to target orientations (parallel and orthogonal to the finger axis in a random stream of oblique tactile distractor orientations presented to their index and ring fingers. Before each block of trials, subjects received a tactile cue at one finger. By manipulating the validity of this cue with respect to its location and orientation (feature, we provided an incentive to subjects to attend spatially to the cued location and only there to the cued orientation. Subjects showed quicker responses to parallel compared to orthogonal targets, pointing to an orientation anisotropy in sensory processing. Also, faster reaction times were observed in location-matched trials, i.e. when targets appeared on the cued finger, representing a perceptual benefit of spatial attention. Most importantly, reaction times were shorter to orientations matching the cue, both at the cued and at the uncued location, documenting a global enhancement of tactile sensation by feature-based attention. This is the first report of a perceptual benefit of feature-based attention outside the spatial focus of attention in somatosensory perception. The similarity to effects of feature-based attention in visual perception supports the notion of matching attentional mechanisms across sensory domains.

  8. An ancillary method in urine cytology: Nucleolar/nuclear volume ratio for discrimination between benign and malignant urothelial cells.

    Science.gov (United States)

    Tone, Kiyoshi; Kojima, Keiko; Hoshiai, Keita; Kumagai, Naoya; Kijima, Hiroshi; Kurose, Akira

    2016-06-01

    The essential of urine cytology for the diagnosis and the follow-up of urothelial neoplasia has been widely recognized. However, there are some cases in which a definitive diagnosis cannot be made due to difficulty in discriminating between benign and malignant. This study evaluated the practicality of nucleolar/nuclear volume ratio (%) for the discrimination. Using Papanicolaou-stained slides, 253 benign urothelial cells and 282 malignant urothelial cells were selected and divided into a benign urothelial cell and an urothelial carcinoma (UC) cell groups. Three suspicious cases and four cases in which discrimination between benign and malignant was difficult were prepared for verification test. Subject cells were decolorized and stained with 4',6-diamidino-2-phenylindole for detection of the nuclei and the nucleoli. Z-stack method was performed to analyze. When the cutoff point of 1.514% discriminating benign urothelial cells and UC cells from nucleolar/nuclear volume ratio (%) was utilized, the sensitivity was 56.0%, the specificity was 88.5%, the positive predictive value was 84.5%, and the negative predictive value was 64.4%. Nuclear and nucleolar volume, number of the nucleoli, and nucleolar/nuclear volume ratio (%) were significantly higher in the UC cell group than in the benign urothelial cell group (P benign and malignant urothelial cells, providing possible additional information in urine cytology. Diagn. Cytopathol. 2016;44:483-491. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  9. Fast-HPLC Fingerprinting to Discriminate Olive Oil from Other Edible Vegetable Oils by Multivariate Classification Methods.

    Science.gov (United States)

    Jiménez-Carvelo, Ana M; González-Casado, Antonio; Pérez-Castaño, Estefanía; Cuadros-Rodríguez, Luis

    2017-03-01

    A new analytical method for the differentiation of olive oil from other vegetable oils using reversed-phase LC and applying chemometric techniques was developed. A 3 cm short column was used to obtain the chromatographic fingerprint of the methyl-transesterified fraction of each vegetable oil. The chromatographic analysis took only 4 min. The multivariate classification methods used were k-nearest neighbors, partial least-squares (PLS) discriminant analysis, one-class PLS, support vector machine classification, and soft independent modeling of class analogies. The discrimination of olive oil from other vegetable edible oils was evaluated by several classification quality metrics. Several strategies for the classification of the olive oil were used: one input-class, two input-class, and pseudo two input-class.

  10. Analysis of the discriminative methods for diagnosis of benign and malignant solitary pulmonary nodules based on serum markers.

    Science.gov (United States)

    Wang, Wanping; Liu, Mingyue; Wang, Jing; Tian, Rui; Dong, Junqiang; Liu, Qi; Zhao, Xianping; Wang, Yuanfang

    2014-01-01

    Screening indexes of tumor serum markers for benign and malignant solitary pulmonary nodules (SPNs) were analyzed to find the optimum method for diagnosis. Enzyme-linked immunosorbent assays, an automatic immune analyzer and radioimmunoassay methods were used to examine the levels of 8 serum markers in 164 SPN patients, and the sensitivity for differential diagnosis of malignant or benign SPN was compared for detection using a single plasma marker or a combination of markers. The results for serological indicators that closely relate to benign and malignant SPNs were screened using the Fisher discriminant analysis and a non-conditional logistic regression analysis method, respectively. The results were then verified by the k-means clustering analysis method. The sensitivity when using a combination of serum markers to detect SPN was higher than that using a single marker. By Fisher discriminant analysis, cytokeratin 19 fragments (CYFRA21-1), carbohydrate antigen 125 (CA125), squamous cell carcinoma antigen (SCC) and breast cancer antigen (CA153), which relate to the benign and malignant SPNs, were screened. Through non-conditional logistic regression analysis, CYFRA21-1, SCC and CA153 were obtained. Using the k-means clustering analysis, the cophenetic correlation coefficient (0.940) obtained by the Fisher discriminant analysis was higher than that obtained with logistic regression analysis (0.875). This study indicated that the Fisher discriminant analysis functioned better in screening out serum markers to recognize the benign and malignant SPN. The combined detection of CYFRA21-1, CA125, SCC and CA153 is an effective way to distinguish benign and malignant SPN, and will find an important clinical application in the early diagnosis of SPN. © 2014 S. Karger GmbH, Freiburg.

  11. A method to reduce the suppression of relevant pulses in pulse weight discriminators

    International Nuclear Information System (INIS)

    Schwartz, P.

    1975-01-01

    The pulse height analyzer is used, for instance, with proportional counters. Pulses are broken down into amplitude ranges in accordance with their maximum amplitudes. In pulse height analyzers with real time analog-digital conversion only one deadtime is needed for the respective range selected. For this purpose, all discriminator thresholds of the amplitude stores connected parallel are actuated as an input pulse arrives. The leading edges of the discriminator signals set the amplitude range flip-flop. Only the flip-flop circuit of the maximum amplitude range reached remains set whilst all the others are erased. The trailing edge of the discriminator signals actuates the evaluation of the information stored by the flip-flop circuit selected. It triggers a pulse extender and resets the flip-flop selected. Therefore, only the amplitude range selected needs a deadtime. The pulse extender in addition reduces the processing time of the analyzer by the output pulse length. The characteristic used for the trailing edge is the backward count of the real time analog-digital converter. (DG/RF) [de

  12. Modeling multiple visual words assignment for bag-of-features based medical image retrieval

    KAUST Repository

    Wang, Jim Jing-Yan

    2012-01-01

    In this paper, we investigate the bag-of-features based medical image retrieval methods, which represent an image as a collection of local features, such as image patch and key points with SIFT descriptor. To improve the bag-of-features method, we first model the assignment of local descriptor as contribution functions, and then propose a new multiple assignment strategy. By assuming the local feature can be reconstructed by its neighboring visual words in vocabulary, we solve the reconstruction weights as a QP problem and then use the solved weights as contribution functions, which results in a new assignment method called the QP assignment. We carry our experiments on ImageCLEFmed datasets. Experiments\\' results show that our proposed method exceeds the performances of traditional solutions and works well for the bag-of-features based medical image retrieval tasks.

  13. Modeling multiple visual words assignment for bag-of-features based medical image retrieval

    KAUST Repository

    Wang, Jim Jing-Yan; Almasri, Islam

    2012-01-01

    In this paper, we investigate the bag-of-features based medical image retrieval methods, which represent an image as a collection of local features, such as image patch and key points with SIFT descriptor. To improve the bag-of-features method, we first model the assignment of local descriptor as contribution functions, and then propose a new multiple assignment strategy. By assuming the local feature can be reconstructed by its neighboring visual words in vocabulary, we solve the reconstruction weights as a QP problem and then use the solved weights as contribution functions, which results in a new assignment method called the QP assignment. We carry our experiments on ImageCLEFmed datasets. Experiments' results show that our proposed method exceeds the performances of traditional solutions and works well for the bag-of-features based medical image retrieval tasks.

  14. A rapid method to screen for cell-wall mutants using discriminant analysis of Fourier transform infrared spectra

    International Nuclear Information System (INIS)

    Chen LiMei; Carpita, N.C.; Reiter, W.D.; Wilson, R.H.; Jeffries, C.; McCann, M.C.

    1998-01-01

    We have developed a rapid method to screen large numbers of mutant plants for a broad range of cell wall phenotypes using Fourier transform infrared (FTIR) microspectroscopy of leaves. We established and validated a model that can discriminate between the leaves of wild-type and a previously defined set of cell-wall mutants of Arabidopsis. Exploratory principal component analysis indicated that mutants deficient in different cell-wall sugars can be distinguished from each other. Discrimination of cell-wall mutants from wild-type was independent of variability in starch content or additional unrelated mutations that might be present in a heavily mutagenised population. We then developed an analysis of FTIR spectra of leaves obtained from over 1000 mutagenised flax plants, and selected 59 plants whose spectral variation from wild-type was significantly out of the range of a wild-type population, determined by Mahalanobis distance. Cell wall sugars from the leaves of selected putative mutants were assayed by gas chromatography-mass spectrometry and 42 showed significant differences in neutral sugar composition. The FTIR spectra indicated that six of the remaining 17 plants have altered ester or protein content. We conclude that linear discriminant analysis of FTIR spectra is a robust method to identify a broad range of structural and architectural alterations in cell walls, appearing as a consequence of developmental regulation, environmental adaptation or genetic modification. (author)

  15. AUTOMATED FEATURE BASED TLS DATA REGISTRATION FOR 3D BUILDING MODELING

    OpenAIRE

    K. Kitamura; N. Kochi; S. Kaneko

    2012-01-01

    In this paper we present a novel method for the registration of point cloud data obtained using terrestrial laser scanner (TLS). The final goal of our investigation is the automated reconstruction of CAD drawings and the 3D modeling of objects surveyed by TLS. Because objects are scanned from multiple positions, individual point cloud need to be registered to the same coordinate system. We propose in this paper an automated feature based registration procedure. Our proposed method does not re...

  16. A comparison of two methods of pulse-shape discrimination for alpha-gamma separation with trans-stilbene

    International Nuclear Information System (INIS)

    Shani, G.; Cojocaru, M.

    1977-01-01

    A method for measurement of low level alpha particles in high level gamma background is investigated. Because of its pulse-shape-discrimination properties and being a solid scintillator, trans-stilbene seems to be the proper scintillator, for this purpose. The investigation was done by measuring the effect of different gamma background level (from very low to very high) on constant alpha count rate. Two different pulse-shape-discrimination systems were used and compared. The Ortec system measures the pulse fall time and supplies a corresponding pulse height and the Elscint system checks whether the pulse is what is expected to be the gamma pulse, or is a longer pulse. Both systems yielded good results and were found to be adequate for alpha-gamma separation with trans-stilbene. (Auth.)

  17. A real-time neutron-gamma discriminator based on the support vector machine method for the time-of-flight neutron spectrometer

    Science.gov (United States)

    Wei, ZHANG; Tongyu, WU; Bowen, ZHENG; Shiping, LI; Yipo, ZHANG; Zejie, YIN

    2018-04-01

    A new neutron-gamma discriminator based on the support vector machine (SVM) method is proposed to improve the performance of the time-of-flight neutron spectrometer. The neutron detector is an EJ-299-33 plastic scintillator with pulse-shape discrimination (PSD) property. The SVM algorithm is implemented in field programmable gate array (FPGA) to carry out the real-time sifting of neutrons in neutron-gamma mixed radiation fields. This study compares the ability of the pulse gradient analysis method and the SVM method. The results show that this SVM discriminator can provide a better discrimination accuracy of 99.1%. The accuracy and performance of the SVM discriminator based on FPGA have been evaluated in the experiments. It can get a figure of merit of 1.30.

  18. Feature-based handling of surface faults in compact disc players

    DEFF Research Database (Denmark)

    Odgaard, Peter Fogh; Stoustrup, Jakob; Andersen, Palle

    2006-01-01

    In this paper a novel method called feature-based control is presented. The method is designed to improve compact disc players’ handling of surface faults on the discs. The method is based on a fault-tolerant control scheme, which uses extracted features of the surface faults to remove those from...... the detector signals used for control during the occurrence of surface faults. The extracted features are coefficients of Karhunen–Loève approximations of the surface faults. The performance of the feature-based control scheme controlling compact disc players playing discs with surface faults has been...... validated experimentally. The proposed scheme reduces the control errors due to the surface faults, and in some cases where the standard fault handling scheme fails, our scheme keeps the CD-player playing....

  19. Collaborative Tracking of Image Features Based on Projective Invariance

    Science.gov (United States)

    Jiang, Jinwei

    -mode sensors for improving the flexibility and robustness of the system. From the experimental results during three field tests for the LASOIS system, we observed that most of the errors in the image processing algorithm are caused by the incorrect feature tracking. This dissertation addresses the feature tracking problem in image sequences acquired from cameras. Despite many alternatives to feature tracking problem, iterative least squares solution solving the optical flow equation has been the most popular approach used by many in the field. This dissertation attempts to leverage the former efforts to enhance feature tracking methods by introducing a view geometric constraint to the tracking problem, which provides collaboration among features. In contrast to alternative geometry based methods, the proposed approach provides an online solution to optical flow estimation in a collaborative fashion by exploiting Horn and Schunck flow estimation regularized by view geometric constraints. Proposed collaborative tracker estimates the motion of a feature based on the geometry of the scene and how the other features are moving. Alternative to this approach, a new closed form solution to tracking that combines the image appearance with the view geometry is also introduced. We particularly use invariants in the projective coordinates and conjecture that the traditional appearance solution can be significantly improved using view geometry. The geometric constraint is introduced by defining a new optical flow equation which exploits the scene geometry from a set drawn from tracked features. At the end of each tracking loop the quality of the tracked features is judged using both appearance similarity and geometric consistency. Our experiments demonstrate robust tracking performance even when the features are occluded or they undergo appearance changes due to projective deformation of the template. The proposed collaborative tracking method is also tested in the visual navigation

  20. The DosiMap, a new 2D scintillating dosimeter for IMRT quality assurance: Characterization of two Cerenkov discrimination methods

    International Nuclear Information System (INIS)

    Frelin, A-M.; Fontbonne, J-M.; Ban, G.; Colin, J.; Labalme, M.; Batalla, A.; Vela, A.; Boher, P.; Braud, M.; Leroux, T.

    2008-01-01

    New radiation therapy techniques such as IMRT present significant efficiency due to their highly conformal dose distributions. A consequence of the complexity of their dose distributions (high gradients, small irradiation fields, low dose distribution, ...) is the requirement for better precision quality assurance than in classical radiotherapy in order to compare the conformation of the delivered dose with the planned dose distribution and to guarantee the quality of the treatment. Currently this control is mostly performed by matrices of ionization chambers, diode detectors, dosimetric films, portal imaging, or dosimetric gels. Another approach is scintillation dosimetry, which has been developed in the last 15 years mainly through scintillating fiber devices. Despite having many advantages over other methods it is still at an experimental level for routine dosimetry because the Cerenkov radiation produced under irradiation represents an important stem effect. A new 2D water equivalent scintillating dosimeter, the DosiMap, and two different Cerenkov discrimination methods were developed with the collaboration of the Laboratoire de Physique Corpusculaire of Caen, the Comprehensive Cancer Center Francois Baclesse, and the ELDIM Co., in the frame of the MAESTRO European project. The DosiMap consists of a plastic scintillating sheet placed inside a transparent polystyrene phantom. The light distribution produced under irradiation is recorded by a CCD camera. Our first Cerenkov discrimination technique is subtractive. It uses a chessboard pattern placed in front of the scintillator, which provides a background signal containing only Cerenkov light. Our second discrimination technique is colorimetric. It performs a spectral analysis of the light signal, which allows the unfolding of the Cerenkov radiation and the scintillation. Tests were carried out with our DosiMap prototype and the performances of the two discrimination methods were assessed. The comparison of the

  1. The DosiMap, a new 2D scintillating dosimeter for IMRT quality assurance: characterization of two Cerenkov discrimination methods.

    Science.gov (United States)

    Frelin, A M; Fontbonne, J M; Ban, G; Colin, J; Labalme, M; Batalla, A; Vela, A; Boher, P; Braud, M; Leroux, T

    2008-05-01

    New radiation therapy techniques such as IMRT present significant efficiency due to their highly conformal dose distributions. A consequence of the complexity of their dose distributions (high gradients, small irradiation fields, low dose distribution, ...) is the requirement for better precision quality assurance than in classical radiotherapy in order to compare the conformation of the delivered dose with the planned dose distribution and to guarantee the quality of the treatment. Currently this control is mostly performed by matrices of ionization chambers, diode detectors, dosimetric films, portal imaging, or dosimetric gels. Another approach is scintillation dosimetry, which has been developed in the last 15 years mainly through scintillating fiber devices. Despite having many advantages over other methods it is still at an experimental level for routine dosimetry because the Cerenkov radiation produced under irradiation represents an important stem effect. A new 2D water equivalent scintillating dosimeter, the DosiMap, and two different Cerenkov discrimination methods were developed with the collaboration of the Laboratoire de Physique Corpusculaire of Caen, the Comprehensive Cancer Center François Baclesse, and the ELDIM Co., in the frame of the MAESTRO European project. The DosiMap consists of a plastic scintillating sheet placed inside a transparent polystyrene phantom. The light distribution produced under irradiation is recorded by a CCD camera. Our first Cerenkov discrimination technique is subtractive. It uses a chessboard pattern placed in front of the scintillator, which provides a background signal containing only Cerenkov light. Our second discrimination technique is colorimetric. It performs a spectral analysis of the light signal, which allows the unfolding of the Cerenkov radiation and the scintillation. Tests were carried out with our DosiMap prototype and the performances of the two discrimination methods were assessed. The comparison of the

  2. A New Method for Improving the Discrimination Power and Weights Dispersion in the Data Envelopment Analysis

    Directory of Open Access Journals (Sweden)

    S. Kordrostami

    2013-06-01

    Full Text Available The appropriate choice of input-output weights is necessary to have a successful DEA model. Generally, if the number of DMUs i.e., n, is less than number of inputs and outputs i.e., m+s, then many of DMUs are introduced as efficient then the discrimination between DMUs is not possible. Besides, DEA models are free to choose the best weights. For resolving the problems that are resulted from freedom of weights, some constraints are set on the input-output weights. Symmetric weight constraints are a kind of weight constrains. In this paper, we represent a new model based on a multi-criterion data envelopment analysis (MCDEA are developed to moderate the homogeneity of weights distribution by using symmetric weight constrains.Consequently, we show that the improvement of the dispersal of unrealistic input-output weights and the increasing discrimination power for our suggested models. Finally, as an application of the new model, we use this model to evaluate and ranking guilan selected hospitals.

  3. Structural Discrimination

    DEFF Research Database (Denmark)

    Thorsen, Mira Skadegård

    discrimination as two ways of articulating particular, opaque forms of racial discrimination that occur in everyday Danish (and other) contexts, and have therefore become normalized. I present and discuss discrimination as it surfaces in data from my empirical studies of discrimination in Danish contexts...

  4. Feature-based component model for design of embedded systems

    Science.gov (United States)

    Zha, Xuan Fang; Sriram, Ram D.

    2004-11-01

    An embedded system is a hybrid of hardware and software, which combines software's flexibility and hardware real-time performance. Embedded systems can be considered as assemblies of hardware and software components. An Open Embedded System Model (OESM) is currently being developed at NIST to provide a standard representation and exchange protocol for embedded systems and system-level design, simulation, and testing information. This paper proposes an approach to representing an embedded system feature-based model in OESM, i.e., Open Embedded System Feature Model (OESFM), addressing models of embedded system artifacts, embedded system components, embedded system features, and embedded system configuration/assembly. The approach provides an object-oriented UML (Unified Modeling Language) representation for the embedded system feature model and defines an extension to the NIST Core Product Model. The model provides a feature-based component framework allowing the designer to develop a virtual embedded system prototype through assembling virtual components. The framework not only provides a formal precise model of the embedded system prototype but also offers the possibility of designing variation of prototypes whose members are derived by changing certain virtual components with different features. A case study example is discussed to illustrate the embedded system model.

  5. Feature-Based and String-Based Models for Predicting RNA-Protein Interaction

    Directory of Open Access Journals (Sweden)

    Donald Adjeroh

    2018-03-01

    Full Text Available In this work, we study two approaches for the problem of RNA-Protein Interaction (RPI. In the first approach, we use a feature-based technique by combining extracted features from both sequences and secondary structures. The feature-based approach enhanced the prediction accuracy as it included much more available information about the RNA-protein pairs. In the second approach, we apply search algorithms and data structures to extract effective string patterns for prediction of RPI, using both sequence information (protein and RNA sequences, and structure information (protein and RNA secondary structures. This led to different string-based models for predicting interacting RNA-protein pairs. We show results that demonstrate the effectiveness of the proposed approaches, including comparative results against leading state-of-the-art methods.

  6. Feature-Based Classification of Amino Acid Substitutions outside Conserved Functional Protein Domains

    Directory of Open Access Journals (Sweden)

    Branislava Gemovic

    2013-01-01

    Full Text Available There are more than 500 amino acid substitutions in each human genome, and bioinformatics tools irreplaceably contribute to determination of their functional effects. We have developed feature-based algorithm for the detection of mutations outside conserved functional domains (CFDs and compared its classification efficacy with the most commonly used phylogeny-based tools, PolyPhen-2 and SIFT. The new algorithm is based on the informational spectrum method (ISM, a feature-based technique, and statistical analysis. Our dataset contained neutral polymorphisms and mutations associated with myeloid malignancies from epigenetic regulators ASXL1, DNMT3A, EZH2, and TET2. PolyPhen-2 and SIFT had significantly lower accuracies in predicting the effects of amino acid substitutions outside CFDs than expected, with especially low sensitivity. On the other hand, only ISM algorithm showed statistically significant classification of these sequences. It outperformed PolyPhen-2 and SIFT by 15% and 13%, respectively. These results suggest that feature-based methods, like ISM, are more suitable for the classification of amino acid substitutions outside CFDs than phylogeny-based tools.

  7. Radiation ray discrimination method using photo-stimulated luminescence fluorescent material

    International Nuclear Information System (INIS)

    Atsumi, Yoshihiro; Takebe, Masahiro; Abe, Ken.

    1996-01-01

    An IP (imaging plate) using PSL (photo-stimulated luminescence fluorescent material) is formed by coating a photo-stimulated luminescence fluorescent material on a thin plastic plate. A predetermined colorants is added to the PSL material. A colorant which absorbs a light having a wavelength of about 600nm is preferred. After irradiating various kinds of radiation rays to the IP, and then irradiating a white light thereto for a predetermined period of time, lights at several kinds of wavelength specific to several kinds of radiation rays to be measured are successively irradiated to the IP. The ratios between the luminance intensity of the fluorescent light emitted from the IP in this case and that emitted when a light of one specific wavelength is irradiated are successively calculated. The light of the specific wavelength preferably has a wavelength of 600nm. With such procedures, the kinds of the several radiation rays which are irradiated to the IP can be discriminated. (I.N.)

  8. Efficient Identification Using a Prime-Feature-Based Technique

    DEFF Research Database (Denmark)

    Hussain, Dil Muhammad Akbar; Haq, Shaiq A.; Valente, Andrea

    2011-01-01

    . Fingerprint identification system, implemented on PC/104 based real-time systems, can accurately identify the operator. Traditionally, the uniqueness of a fingerprint is determined by the overall pattern of ridges and valleys as well as the local ridge anomalies e.g., a ridge bifurcation or a ridge ending......, which are called minutiae points. Designing a reliable automatic fingerprint matching algorithm for minimal platform is quite challenging. In real-time systems, efficiency of the matching algorithm is of utmost importance. To achieve this goal, a prime-feature-based indexing algorithm is proposed......Identification of authorized train drivers through biometrics is a growing area of interest in locomotive radio remote control systems. The existing technique of password authentication is not very reliable and potentially unauthorized personnel may also operate the system on behalf of the operator...

  9. A Distributed Feature-based Environment for Collaborative Design

    Directory of Open Access Journals (Sweden)

    Wei-Dong Li

    2003-02-01

    Full Text Available This paper presents a client/server design environment based on 3D feature-based modelling and Java technologies to enable design information to be shared efficiently among members within a design team. In this environment, design tasks and clients are organised through working sessions generated and maintained by a collaborative server. The information from an individual design client during a design process is updated and broadcast to other clients in the same session through an event-driven and call-back mechanism. The downstream manufacturing analysis modules can be wrapped as agents and plugged into the open environment to support the design activities. At the server side, a feature-feature relationship is established and maintained to filter the varied information of a working part, so as to facilitate efficient information update during the design process.

  10. Reliability and Discriminative Ability of a New Method for Soccer Kicking Evaluation

    Science.gov (United States)

    Radman, Ivan; Wessner, Barbara; Bachl, Norbert; Ruzic, Lana; Hackl, Markus; Baca, Arnold; Markovic, Goran

    2016-01-01

    The study aimed to evaluate the test–retest reliability of a newly developed 356 Soccer Shooting Test (356-SST), and the discriminative ability of this test with respect to the soccer players' proficiency level and leg dominance. Sixty-six male soccer players, divided into three groups based on their proficiency level (amateur, n = 24; novice semi-professional, n = 18; and experienced semi-professional players, n = 24), performed 10 kicks following a two-step run up. Forty-eight of them repeated the test on a separate day. The following shooting variables were derived: ball velocity (BV; measured via radar gun), shooting accuracy (SA; average distance from the ball-entry point to the goal centre), and shooting quality (SQ; shooting accuracy divided by the time elapsed from hitting the ball to the point of entry). No systematic bias was evident in the selected shooting variables (SA: 1.98±0.65 vs. 2.00±0.63 m; BV: 24.6±2.3 vs. 24.5±1.9 m s-1; SQ: 2.92±1.0 vs. 2.93±1.0 m s-1; all p>0.05). The intra-class correlation coefficients were high (ICC = 0.70–0.88), and the coefficients of variation were low (CV = 5.3–5.4%). Finally, all three 356-SST variables identify, with adequate sensitivity, differences in soccer shooting ability with respect to the players' proficiency and leg dominance. The results suggest that the 356-SST is a reliable and sensitive test of specific shooting ability in men’s soccer. Future studies should test the validity of these findings in a fatigued state, as well as in other populations. PMID:26812247

  11. SPEECH EMOTION RECOGNITION USING MODIFIED QUADRATIC DISCRIMINATION FUNCTION

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    Quadratic Discrimination Function(QDF)is commonly used in speech emotion recognition,which proceeds on the premise that the input data is normal distribution.In this Paper,we propose a transformation to normalize the emotional features,then derivate a Modified QDF(MQDF) to speech emotion recognition.Features based on prosody and voice quality are extracted and Principal Component Analysis Neural Network (PCANN) is used to reduce dimension of the feature vectors.The results show that voice quality features are effective supplement for recognition.and the method in this paper could improve the recognition ratio effectively.

  12. High Resolution Melting Analysis Targeting hsp70 as a Fast and Efficient Method for the Discrimination of Leishmania Species.

    Science.gov (United States)

    Zampieri, Ricardo Andrade; Laranjeira-Silva, Maria Fernanda; Muxel, Sandra Marcia; Stocco de Lima, Ana Carolina; Shaw, Jeffrey Jon; Floeter-Winter, Lucile Maria

    2016-02-01

    Protozoan parasites of the genus Leishmania cause a large spectrum of clinical manifestations known as Leishmaniases. These diseases are increasingly important public health problems in many countries both within and outside endemic regions. Thus, an accurate differential diagnosis is extremely relevant for understanding epidemiological profiles and for the administration of the best therapeutic protocol. Exploring the High Resolution Melting (HRM) dissociation profiles of two amplicons using real time polymerase chain reaction (real-time PCR) targeting heat-shock protein 70 coding gene (hsp70) revealed differences that allowed the discrimination of genomic DNA samples of eight Leishmania species found in the Americas, including Leishmania (Leishmania) infantum chagasi, L. (L.) amazonensis, L. (L.) mexicana, L. (Viannia) lainsoni, L. (V.) braziliensis, L. (V.) guyanensis, L. (V.) naiffi and L. (V.) shawi, and three species found in Eurasia and Africa, including L. (L.) tropica, L. (L.) donovani and L. (L.) major. In addition, we tested DNA samples obtained from standard promastigote culture, naturally infected phlebotomines, experimentally infected mice and clinical human samples to validate the proposed protocol. HRM analysis of hsp70 amplicons is a fast and robust strategy that allowed for the detection and discrimination of all Leishmania species responsible for the Leishmaniases in Brazil and Eurasia/Africa with high sensitivity and accuracy. This method could detect less than one parasite per reaction, even in the presence of host DNA.

  13. High Resolution Melting Analysis Targeting hsp70 as a Fast and Efficient Method for the Discrimination of Leishmania Species.

    Directory of Open Access Journals (Sweden)

    Ricardo Andrade Zampieri

    2016-02-01

    Full Text Available Protozoan parasites of the genus Leishmania cause a large spectrum of clinical manifestations known as Leishmaniases. These diseases are increasingly important public health problems in many countries both within and outside endemic regions. Thus, an accurate differential diagnosis is extremely relevant for understanding epidemiological profiles and for the administration of the best therapeutic protocol.Exploring the High Resolution Melting (HRM dissociation profiles of two amplicons using real time polymerase chain reaction (real-time PCR targeting heat-shock protein 70 coding gene (hsp70 revealed differences that allowed the discrimination of genomic DNA samples of eight Leishmania species found in the Americas, including Leishmania (Leishmania infantum chagasi, L. (L. amazonensis, L. (L. mexicana, L. (Viannia lainsoni, L. (V. braziliensis, L. (V. guyanensis, L. (V. naiffi and L. (V. shawi, and three species found in Eurasia and Africa, including L. (L. tropica, L. (L. donovani and L. (L. major. In addition, we tested DNA samples obtained from standard promastigote culture, naturally infected phlebotomines, experimentally infected mice and clinical human samples to validate the proposed protocol.HRM analysis of hsp70 amplicons is a fast and robust strategy that allowed for the detection and discrimination of all Leishmania species responsible for the Leishmaniases in Brazil and Eurasia/Africa with high sensitivity and accuracy. This method could detect less than one parasite per reaction, even in the presence of host DNA.

  14. Photoacoustic discrimination of viable and thermally coagulated blood using a two-wavelength method for burn injury monitoring

    International Nuclear Information System (INIS)

    Talbert, Robert J; Holan, Scott H; Viator, John A

    2007-01-01

    Discriminating viable from thermally coagulated blood in a burn wound can be used to profile burn depth, thus aiding the removal of necrotic tissue. In this study, we used a two-wavelength photoacoustic imaging method to discriminate coagulated and non-coagulated blood in a dermal burn phantom. Differences in the optical absorption spectra of coagulated and non-coagulated blood produce different values of the ratio of peak photoacoustic amplitude at 543 and 633 nm. The absorption values obtained from spectroscopic measurements indicate that the ratio of photoacoustic pressure for 543 and 633 nm for non-coagulated blood was 15.7:1 and 1.6:1 for coagulated blood. Using planar blood layers, we found the photoacoustic ratios to be 13.5:1 and 1.6:1, respectively. Using the differences in the ratios of coagulated and non-coagulated blood, we propose a scheme using statistical classification analysis to identify the different blood samples. Based upon these distinctly different ratios, we identified the planar blood samples with an error rate of 0%. Using a burn phantom with cylindrical vessels containing coagulated and non-coagulated blood, we achieved an error rate of 11.4%. These results have shown that photoacoustic imaging could prove to be a valuable tool in the diagnosis of burns

  15. Optical Flow of Small Objects Using Wavelets, Bootstrap Methods, and Synthetic Discriminant Filters

    National Research Council Canada - National Science Library

    Hewer, Gary

    1997-01-01

    ...) targets in highly cluttered and noisy environments. In this paper; we present a novel wavelet detection algorithm which incorporates adaptive CFAR detection statistics using the bootstrap method...

  16. Three dimensional pattern recognition using feature-based indexing and rule-based search

    Science.gov (United States)

    Lee, Jae-Kyu

    In flexible automated manufacturing, robots can perform routine operations as well as recover from atypical events, provided that process-relevant information is available to the robot controller. Real time vision is among the most versatile sensing tools, yet the reliability of machine-based scene interpretation can be questionable. The effort described here is focused on the development of machine-based vision methods to support autonomous nuclear fuel manufacturing operations in hot cells. This thesis presents a method to efficiently recognize 3D objects from 2D images based on feature-based indexing. Object recognition is the identification of correspondences between parts of a current scene and stored views of known objects, using chains of segments or indexing vectors. To create indexed object models, characteristic model image features are extracted during preprocessing. Feature vectors representing model object contours are acquired from several points of view around each object and stored. Recognition is the process of matching stored views with features or patterns detected in a test scene. Two sets of algorithms were developed, one for preprocessing and indexed database creation, and one for pattern searching and matching during recognition. At recognition time, those indexing vectors with the highest match probability are retrieved from the model image database, using a nearest neighbor search algorithm. The nearest neighbor search predicts the best possible match candidates. Extended searches are guided by a search strategy that employs knowledge-base (KB) selection criteria. The knowledge-based system simplifies the recognition process and minimizes the number of iterations and memory usage. Novel contributions include the use of a feature-based indexing data structure together with a knowledge base. Both components improve the efficiency of the recognition process by improved structuring of the database of object features and reducing data base size

  17. Determination and discrimination of biodiesel fuels by gas chromatographic and chemometric methods

    Science.gov (United States)

    Milina, R.; Mustafa, Z.; Bojilov, D.; Dagnon, S.; Moskovkina, M.

    2016-03-01

    Pattern recognition method (PRM) was applied to gas chromatographic (GC) data for a fatty acid methyl esters (FAME) composition of commercial and laboratory synthesized biodiesel fuels from vegetable oils including sunflower, rapeseed, corn and palm oils. Two GC quantitative methods to calculate individual fames were compared: Area % and internal standard. The both methods were applied for analysis of two certified reference materials. The statistical processing of the obtained results demonstrates the accuracy and precision of the two methods and allows them to be compared. For further chemometric investigations of biodiesel fuels by their FAME-profiles any of those methods can be used. PRM results of FAME profiles of samples from different vegetable oils show a successful recognition of biodiesels according to the feedstock. The information obtained can be used for selection of feedstock to produce biodiesels with certain properties, for assessing their interchangeability, for fuel spillage and remedial actions in the environment.

  18. Determination and discrimination of biodiesel fuels by gas chromatographic and chemometric methods

    Directory of Open Access Journals (Sweden)

    Milina R.

    2016-03-01

    Full Text Available Pattern recognition method (PRM was applied to gas chromatographic (GC data for a fatty acid methyl esters (FAME composition of commercial and laboratory synthesized biodiesel fuels from vegetable oils including sunflower, rapeseed, corn and palm oils. Two GC quantitative methods to calculate individual fames were compared: Area % and internal standard. The both methods were applied for analysis of two certified reference materials. The statistical processing of the obtained results demonstrates the accuracy and precision of the two methods and allows them to be compared. For further chemometric investigations of biodiesel fuels by their FAME-profiles any of those methods can be used. PRM results of FAME profiles of samples from different vegetable oils show a successful recognition of biodiesels according to the feedstock. The information obtained can be used for selection of feedstock to produce biodiesels with certain properties, for assessing their interchangeability, for fuel spillage and remedial actions in the environment.

  19. Discriminative staining methods for the nervous system: luxol fast blue--periodic acid-Schiff--hematoxylin triple stain and subsidiary staining methods.

    Science.gov (United States)

    Goto, N

    1987-09-01

    This paper describes a new series of staining methods which can discriminatively demonstrate every structure of the nervous system, including axons and capillaries, in animal and human materials. Methods described in this paper consist of one primary stain, luxol fast blue-periodic acid Schiff-hematoxylin (LPH) and six different subsidiary staining methods. The LPH triple stain can precisely differentiate the following structures: neurons (Nissl bodies, cytoplasm, nuclear membrane and nucleolus), various kinds of nuclei (glia, ependyma, endothelium, leucocyte, connective tissue, etc.), myelin sheaths, neuronal processes (axons and dendrites), reacted glial cell bodies (protoplasmic astrocytes, foamy cells, etc.), blood vessels (arteries, veins and capillaries), meninges, intervening connective tissue, erythrocytes, lipofuscin granules, amyloid bodies, and others. Subsidiary staining methods are also described briefly. Applications are discussed in the context of staining technology and neuromorphological research.

  20. Gender-based discrimination and unprotected receptive anal intercourse among transgender women in Brazil: A mixed methods study.

    Science.gov (United States)

    Magno, Laio; Dourado, Inês; Silva, Luís Augusto V da; Brignol, Sandra; Amorim, Leila; MacCarthy, Sarah

    2018-01-01

    Discrimination related to gender identity may directly influence vulnerability to HIV through increased exposure to unprotected receptive anal intercourse (URAI). Little is known about the relationship between gender-based discrimination (GBD) and URAI with stable partners among transgender women. This mixed-methods research began with a cross-sectional survey conducted between 2014 and 2016 with transgender women in Salvador, the capital city in one of the poorest regions in Brazil. Respondent-driven sampling was used to recruit the study population. GBD was defined through Latent Class Analysis. Additionally, 19 semi-structured interviews with participants were transcribed and analyzed through thematic content analysis. URAI with stable partners was commonly reported (37.3%). GDB was positively associated with URAI among stable partners (OR = 6.47; IC 95%: 1.67-25.02). The analysis of the interviews illustrated how GBD impacted transgender women in diverse ways. Experiences with GBD perpetrated by the family often initiated a trajectory of economic vulnerability that led many to engage in survival sex work. The constant experience with GBD contributed to participants feeling an immense sense of trust with their stable partners, ultimately diminished their desire to use condoms. Further, the high frequency of GBD contributed to poor mental health overall, though some participants said engagement in transgender advocacy efforts provided a vital source of resilience and support. Our mixed-method study capitalizes upon the strengths of diverse data sets to produce a holistic understanding of GBD and URAI with stable partners. Furthermore, by confirming the association between greater GBD and URAI, we have demonstrated how GBD can impact condom negotiation in diverse relationships.

  1. Differential discriminator

    International Nuclear Information System (INIS)

    Dukhanov, V.I.; Mazurov, I.B.

    1981-01-01

    A principal flowsheet of a differential discriminator intended for operation in a spectrometric circuit with statistical time distribution of pulses is described. The differential discriminator includes four integrated discriminators and a channel of piled-up signal rejection. The presence of the rejection channel enables the discriminator to operate effectively at loads of 14x10 3 pulse/s. The temperature instability of the discrimination thresholds equals 250 μV/ 0 C. The discrimination level changes within 0.1-5 V, the level shift constitutes 0.5% for the filling ratio of 1:10. The rejection coefficient is not less than 90%. Alpha spectrum of the 228 Th source is presented to evaluate the discriminator operation with the rejector. The rejector provides 50 ns time resolution

  2. Automatic feature-based grouping during multiple object tracking.

    Science.gov (United States)

    Erlikhman, Gennady; Keane, Brian P; Mettler, Everett; Horowitz, Todd S; Kellman, Philip J

    2013-12-01

    Contour interpolation automatically binds targets with distractors to impair multiple object tracking (Keane, Mettler, Tsoi, & Kellman, 2011). Is interpolation special in this regard or can other features produce the same effect? To address this question, we examined the influence of eight features on tracking: color, contrast polarity, orientation, size, shape, depth, interpolation, and a combination (shape, color, size). In each case, subjects tracked 4 of 8 objects that began as undifferentiated shapes, changed features as motion began (to enable grouping), and returned to their undifferentiated states before halting. We found that intertarget grouping improved performance for all feature types except orientation and interpolation (Experiment 1 and Experiment 2). Most importantly, target-distractor grouping impaired performance for color, size, shape, combination, and interpolation. The impairments were, at times, large (>15% decrement in accuracy) and occurred relative to a homogeneous condition in which all objects had the same features at each moment of a trial (Experiment 2), and relative to a "diversity" condition in which targets and distractors had different features at each moment (Experiment 3). We conclude that feature-based grouping occurs for a variety of features besides interpolation, even when irrelevant to task instructions and contrary to the task demands, suggesting that interpolation is not unique in promoting automatic grouping in tracking tasks. Our results also imply that various kinds of features are encoded automatically and in parallel during tracking.

  3. 3-D FEATURE-BASED MATCHING BY RSTG APPROACH

    Directory of Open Access Journals (Sweden)

    J.-J. Jaw

    2012-07-01

    Full Text Available 3-D feature matching is the essential kernel in a fully automated feature-based LiDAR point cloud registration. After feasible procedures of feature acquisition, connecting corresponding features in different data frames is imperative to be solved. The objective addressed in this paper is developing an approach coined RSTG to retrieve corresponding counterparts of unsorted multiple 3-D features extracted from sets of LiDAR point clouds. RSTG stands for the four major processes, "Rotation alignment"; "Scale estimation"; "Translation alignment" and "Geometric check," strategically formulated towards finding out matching solution with high efficiency and leading to accomplishing the 3-D similarity transformation among all sets. The workable types of features to RSTG comprise points, lines, planes and clustered point groups. Each type of features can be employed exclusively or combined with others, if sufficiently supplied, throughout the matching scheme. The paper gives a detailed description of the matching methodology and discusses on the matching effects based on the statistical assessment which revealed that the RSTG approach reached an average matching rate of success up to 93% with around 6.6% of statistical type 1 error. Notably, statistical type 2 error, the critical indicator of matching reliability, was kept 0% throughout all the experiments.

  4. Validation of Underwater Sensor Package Using Feature Based SLAM

    Directory of Open Access Journals (Sweden)

    Christopher Cain

    2016-03-01

    Full Text Available Robotic vehicles working in new, unexplored environments must be able to locate themselves in the environment while constructing a picture of the objects in the environment that could act as obstacles that would prevent the vehicles from completing their desired tasks. In enclosed environments, underwater range sensors based off of acoustics suffer performance issues due to reflections. Additionally, their relatively high cost make them less than ideal for usage on low cost vehicles designed to be used underwater. In this paper we propose a sensor package composed of a downward facing camera, which is used to perform feature tracking based visual odometry, and a custom vision-based two dimensional rangefinder that can be used on low cost underwater unmanned vehicles. In order to examine the performance of this sensor package in a SLAM framework, experimental tests are performed using an unmanned ground vehicle and two feature based SLAM algorithms, the extended Kalman filter based approach and the Rao-Blackwellized, particle filter based approach, to validate the sensor package.

  5. Pupil size reflects the focus of feature-based attention.

    Science.gov (United States)

    Binda, Paola; Pereverzeva, Maria; Murray, Scott O

    2014-12-15

    We measured pupil size in adult human subjects while they selectively attended to one of two surfaces, bright and dark, defined by coherently moving dots. The two surfaces were presented at the same location; therefore, subjects could select the cued surface only on the basis of its features. With no luminance change in the stimulus, we find that pupil size was smaller when the bright surface was attended and larger when the dark surface was attended: an effect of feature-based (or surface-based) attention. With the same surfaces at nonoverlapping locations, we find a similar effect of spatial attention. The pupil size modulation cannot be accounted for by differences in eye position and by other variables known to affect pupil size such as task difficulty, accommodation, or the mere anticipation (imagery) of bright/dark stimuli. We conclude that pupil size reflects not just luminance or cognitive state, but the interaction between the two: it reflects which luminance level in the visual scene is relevant for the task at hand. Copyright © 2014 the American Physiological Society.

  6. Validation of Underwater Sensor Package Using Feature Based SLAM

    Science.gov (United States)

    Cain, Christopher; Leonessa, Alexander

    2016-01-01

    Robotic vehicles working in new, unexplored environments must be able to locate themselves in the environment while constructing a picture of the objects in the environment that could act as obstacles that would prevent the vehicles from completing their desired tasks. In enclosed environments, underwater range sensors based off of acoustics suffer performance issues due to reflections. Additionally, their relatively high cost make them less than ideal for usage on low cost vehicles designed to be used underwater. In this paper we propose a sensor package composed of a downward facing camera, which is used to perform feature tracking based visual odometry, and a custom vision-based two dimensional rangefinder that can be used on low cost underwater unmanned vehicles. In order to examine the performance of this sensor package in a SLAM framework, experimental tests are performed using an unmanned ground vehicle and two feature based SLAM algorithms, the extended Kalman filter based approach and the Rao-Blackwellized, particle filter based approach, to validate the sensor package. PMID:26999142

  7. Electronic methods for discriminating scintillation shapes; Methodes electroniques de discrimination des formes des impulsions issues de scintillateurs; Ehlektronnye metody diskriminatsii form stsintillyatsii; Metodos electronicos de discriminacion de forma de impulsos de centelleo

    Energy Technology Data Exchange (ETDEWEB)

    Forte, M; Konsta, A; Maranzana, C [European Atomic Energy Community, CCR, ISPRA (Italy)

    1962-04-15

    As reported previously, the scintillation pulse shape, which is characteristic of the excitating particle type (electron, proton, alpha, etc.), can be converted into a pulse-height independent parameter. This displays, by means of a multichannel analyser, the composition of a mixed particle beam which excites the scintillator. This method was successful with several scintillators, both of the organic and the inorganic type. Details are given of the electronic techniques used for converting the pulse shapes. For the simpler case of discrimination between only two classes of pulses (e.g. neutron-gamma discrimination) the use of passive networks has also been considered possible for further improvements and simplifications. A few networks were tried, the main results being that, in the presence of gamma background, the discrimination of recoil protons in liquid scintillators was extended to small pulses of a few decades of photoelectrons and the discrimination of neutron-capture fragments in boronloaded liquids was obtained. Some of these networks operated with pulses of the same polarity, from two of the last dynode, or even with the output from a single electrode. This may be useful when it is convenient to use the anode independently, e. g. for operating fast time circuits. (author) [French] On sait que la forme des impulsions delivrees par un detecteur a scintillations, qui est fonction du type de particule excitatrice (electron, proton, particule alpha, etc.), peut etre convertie en un parametre d'amplitude d'impulsion independant. Cette propriete permet de determiner, a l'aide d'un selecteur multicanaux, la composition d'un faisceau de particules mixte qui frappe le scintillateur. Cette methode a ete utilisee avec succes dans le cas de plusieurs scintillateurs, tant organiques qu'inorganiques. Les auteurs donnent des precisions sur les procedes electroniques employes pour convertir la forme de l'impulsion. Dans le cas le plus simple, celui ou la discrimination

  8. Coherent versus incoherent resonant emission: an experimental method for easy discrimination and measurement

    Science.gov (United States)

    Ceccherini, S.; Colocci, M.; Gurioli, M.; Bogani, F.

    1998-11-01

    The distinction between the coherent and the incoherent component of the radiation emitted from resonantly excited material systems is difficult experimentally, particularly when ultra-short optical pulses are used for excitation. We propose an experimental procedure allowing an easy measurement of the two components. The method is completely general and applicable to any kind of physical system; its feasibility is demonstrated on the resonant emission from excitons in a semiconductor quantum well.

  9. Discrimination and delusional ideation

    NARCIS (Netherlands)

    Janssen, I.C.M.; Hanssen, M.S.S.; Bak, M.L.F.J.; Bijl, R.V.; Graaf, R. de; Vollebergh, W.A.M.; McKenzie, K.; Os, J. van

    2003-01-01

    Background In the UK and The Netherlands, people with high rates of psychosis are chronically exposed to discrimination. Aims To test whether perceived discrimination is associated longitudinally with onset of psychosis. Method A 3-year prospective study of cohorts with no history of psychosis and

  10. Basis material decomposition method for material discrimination with a new spectrometric X-ray imaging detector

    Science.gov (United States)

    Brambilla, A.; Gorecki, A.; Potop, A.; Paulus, C.; Verger, L.

    2017-08-01

    Energy sensitive photon counting X-ray detectors provide energy dependent information which can be exploited for material identification. The attenuation of an X-ray beam as a function of energy depends on the effective atomic number Zeff and the density. However, the measured attenuation is degraded by the imperfections of the detector response such as charge sharing or pile-up. These imperfections lead to non-linearities that limit the benefits of energy resolved imaging. This work aims to implement a basis material decomposition method which overcomes these problems. Basis material decomposition is based on the fact that the attenuation of any material or complex object can be accurately reproduced by a combination of equivalent thicknesses of basis materials. Our method is based on a calibration phase to learn the response of the detector for different combinations of thicknesses of the basis materials. The decomposition algorithm finds the thicknesses of basis material whose spectrum is closest to the measurement, using a maximum likelihood criterion assuming a Poisson law distribution of photon counts for each energy bin. The method was used with a ME100 linear array spectrometric X-ray imager to decompose different plastic materials on a Polyethylene and Polyvinyl Chloride base. The resulting equivalent thicknesses were used to estimate the effective atomic number Zeff. The results are in good agreement with the theoretical Zeff, regardless of the plastic sample thickness. The linear behaviour of the equivalent lengths makes it possible to process overlapped materials. Moreover, the method was tested with a 3 materials base by adding gadolinium, whose K-edge is not taken into account by the other two materials. The proposed method has the advantage that it can be used with any number of energy channels, taking full advantage of the high energy resolution of the ME100 detector. Although in principle two channels are sufficient, experimental measurements show

  11. Characteristic Chromatogram: A Method of Discriminate and Quantitative Analysis for Quality Evaluation of Uncaria Stem with Hooks.

    Science.gov (United States)

    Hou, Jinjun; Feng, Ruihong; Zhang, Yibei; Pan, Huiqin; Yao, Shuai; Han, Sumei; Feng, Zijin; Cai, Luying; Wu, Wanying; Guo, De-An

    2018-04-01

    It remains a challenge to establish new monographs for herbal drugs derived from multiple botanical sources. Specifically, the difficulty involves discriminating and quantifying these herbs with components whose levels vary markedly among different samples. Using Uncaria stem with hooks as an example, a characteristic chromatogram was proposed to discriminate its five botanical origins and to quantify its characteristic components in the chromatogram. The characteristic chromatogram with respect to the components of Uncaria stem with hooks with the five botanical origins was established using 0.02% diethylamine and acetonitrile as the mobile phase. The total analysis time was 50 min and the detection wavelength was 245 nm. Using the same chromatogram parameters, the single standard to determine multicomponents method was validated to simultaneously quantify nine indole alkaloids, including vincosamide, 3 α -dihydrocadambine, isocorynoxeine, corynoxeine, isorhynchophylline, rhynchophylline, hirsuteine, hirsutine, and geissoschizine methyl ether. The results showed that only the Uncaria stem with hooks from Uncaria rhynchophylla , the most widely used in the herbal market, showed the presence of these nine alkaloids. The conversion factors were 1.27, 2.32, 0.98, 1.04, 1.00, 1.02, 1.26, 1.33, and 1.25, respectively. The limits of quantitation were lower than 700 ng/mL. The total contents of 31 batches of Uncaria stem with hooks were in the range of 0.1 - 0.6%, except for Uncaria hirsuta Havil and Uncaria sinensis (Oliv.) Havil. The results also showed that the total content of indole alkaloids tended to decrease with an increase in the hook diameter. This showed that the characteristic chromatogram is practical for controlling the quality of traditional Chinese medicines with multiple botanical origins. Georg Thieme Verlag KG Stuttgart · New York.

  12. Feature-Based Statistical Analysis of Combustion Simulation Data

    Energy Technology Data Exchange (ETDEWEB)

    Bennett, J; Krishnamoorthy, V; Liu, S; Grout, R; Hawkes, E; Chen, J; Pascucci, V; Bremer, P T

    2011-11-18

    We present a new framework for feature-based statistical analysis of large-scale scientific data and demonstrate its effectiveness by analyzing features from Direct Numerical Simulations (DNS) of turbulent combustion. Turbulent flows are ubiquitous and account for transport and mixing processes in combustion, astrophysics, fusion, and climate modeling among other disciplines. They are also characterized by coherent structure or organized motion, i.e. nonlocal entities whose geometrical features can directly impact molecular mixing and reactive processes. While traditional multi-point statistics provide correlative information, they lack nonlocal structural information, and hence, fail to provide mechanistic causality information between organized fluid motion and mixing and reactive processes. Hence, it is of great interest to capture and track flow features and their statistics together with their correlation with relevant scalar quantities, e.g. temperature or species concentrations. In our approach we encode the set of all possible flow features by pre-computing merge trees augmented with attributes, such as statistical moments of various scalar fields, e.g. temperature, as well as length-scales computed via spectral analysis. The computation is performed in an efficient streaming manner in a pre-processing step and results in a collection of meta-data that is orders of magnitude smaller than the original simulation data. This meta-data is sufficient to support a fully flexible and interactive analysis of the features, allowing for arbitrary thresholds, providing per-feature statistics, and creating various global diagnostics such as Cumulative Density Functions (CDFs), histograms, or time-series. We combine the analysis with a rendering of the features in a linked-view browser that enables scientists to interactively explore, visualize, and analyze the equivalent of one terabyte of simulation data. We highlight the utility of this new framework for combustion

  13. New theory of discriminant analysis after R. Fisher advanced research by the feature selection method for microarray data

    CERN Document Server

    Shinmura, Shuichi

    2016-01-01

    This is the first book to compare eight LDFs by different types of datasets, such as Fisher’s iris data, medical data with collinearities, Swiss banknote data that is a linearly separable data (LSD), student pass/fail determination using student attributes, 18 pass/fail determinations using exam scores, Japanese automobile data, and six microarray datasets (the datasets) that are LSD. We developed the 100-fold cross-validation for the small sample method (Method 1) instead of the LOO method. We proposed a simple model selection procedure to choose the best model having minimum M2 and Revised IP-OLDF based on MNM criterion was found to be better than other M2s in the above datasets. We compared two statistical LDFs and six MP-based LDFs. Those were Fisher’s LDF, logistic regression, three SVMs, Revised IP-OLDF, and another two OLDFs. Only a hard-margin SVM (H-SVM) and Revised IP-OLDF could discriminate LSD theoretically (Problem 2). We solved the defect of the generalized inverse matrices (Problem 3). For ...

  14. Discrimination of Breast Tumors in Ultrasonic Images by Classifier Ensemble Trained with AdaBoost

    Science.gov (United States)

    Takemura, Atsushi; Shimizu, Akinobu; Hamamoto, Kazuhiko

    In this paper, we propose a novel method for acurate automated discrimination of breast tumors (carcinoma, fibroadenoma, and cyst). We defined 199 features related to diagnositic observations noticed when a doctor judges breast tumors, such as internal echo, shape, and boundary echo. These features included novel features based on a parameter of log-compressed K distribution, which reflect physical characteristics of ultrasonic B-mode imaging. Furthermore, we propose a discrimination method of breast tumors by using an ensemble classifier based on the multi-class AdaBoost algorithm with effective features selection. Verification by analyzing 200 carcinomas, 30 fibroadenomas and 30 cycts showed the usefulness of the newly defined features and the effectiveness of the discrimination by using an ensemble classifier trained by AdaBoost.

  15. 3D-2D Deformable Image Registration Using Feature-Based Nonuniform Meshes.

    Science.gov (United States)

    Zhong, Zichun; Guo, Xiaohu; Cai, Yiqi; Yang, Yin; Wang, Jing; Jia, Xun; Mao, Weihua

    2016-01-01

    By using prior information of planning CT images and feature-based nonuniform meshes, this paper demonstrates that volumetric images can be efficiently registered with a very small portion of 2D projection images of a Cone-Beam Computed Tomography (CBCT) scan. After a density field is computed based on the extracted feature edges from planning CT images, nonuniform tetrahedral meshes will be automatically generated to better characterize the image features according to the density field; that is, finer meshes are generated for features. The displacement vector fields (DVFs) are specified at the mesh vertices to drive the deformation of original CT images. Digitally reconstructed radiographs (DRRs) of the deformed anatomy are generated and compared with corresponding 2D projections. DVFs are optimized to minimize the objective function including differences between DRRs and projections and the regularity. To further accelerate the above 3D-2D registration, a procedure to obtain good initial deformations by deforming the volume surface to match 2D body boundary on projections has been developed. This complete method is evaluated quantitatively by using several digital phantoms and data from head and neck cancer patients. The feature-based nonuniform meshing method leads to better results than either uniform orthogonal grid or uniform tetrahedral meshes.

  16. 3D-2D Deformable Image Registration Using Feature-Based Nonuniform Meshes

    Directory of Open Access Journals (Sweden)

    Zichun Zhong

    2016-01-01

    Full Text Available By using prior information of planning CT images and feature-based nonuniform meshes, this paper demonstrates that volumetric images can be efficiently registered with a very small portion of 2D projection images of a Cone-Beam Computed Tomography (CBCT scan. After a density field is computed based on the extracted feature edges from planning CT images, nonuniform tetrahedral meshes will be automatically generated to better characterize the image features according to the density field; that is, finer meshes are generated for features. The displacement vector fields (DVFs are specified at the mesh vertices to drive the deformation of original CT images. Digitally reconstructed radiographs (DRRs of the deformed anatomy are generated and compared with corresponding 2D projections. DVFs are optimized to minimize the objective function including differences between DRRs and projections and the regularity. To further accelerate the above 3D-2D registration, a procedure to obtain good initial deformations by deforming the volume surface to match 2D body boundary on projections has been developed. This complete method is evaluated quantitatively by using several digital phantoms and data from head and neck cancer patients. The feature-based nonuniform meshing method leads to better results than either uniform orthogonal grid or uniform tetrahedral meshes.

  17. Prospective Validation of 18F-FDG Brain PET Discriminant Analysis Methods in the Diagnosis of Amyotrophic Lateral Sclerosis.

    Science.gov (United States)

    Van Weehaeghe, Donatienne; Ceccarini, Jenny; Delva, Aline; Robberecht, Wim; Van Damme, Philip; Van Laere, Koen

    2016-08-01

    An objective biomarker for early identification and accurate differential diagnosis of amyotrophic lateral sclerosis (ALS) is lacking. (18)F-FDG PET brain imaging with advanced statistical analysis may provide a tool to facilitate this. The objective of this work was to validate volume-of-interest (VOI) and voxel-based (using a support vector machine [SVM] approach) (18)F-FDG PET analysis methods to differentiate ALS from controls in an independent prospective large cohort, using a priori-derived classifiers. Furthermore, the prognostic value of (18)F-FDG PET was evaluated. A prospective cohort of patients with a suspected diagnosis of a motor neuron disorder (n = 119; mean age ± SD, 61 ± 12 y; 81 men and 38 women) was recruited. One hundred five patients were diagnosed with ALS (mean age ± SD, 61.0 ± 12 y; 74 men and 31 women) (group 2), 10 patients with primary lateral sclerosis (mean age ± SD, 55.5 ± 12 y; 3 men and 7 women), and 4 patients with progressive muscular atrophy (mean age ± SD, 59.2 ± 5 y; 4 men). The mean disease duration of all patients was 15.0 ± 13.4 mo at diagnosis, with PET conducted 15.2 ± 13.3 mo after the first symptoms. Data were compared with a previously gathered dataset of 20 screened healthy subjects (mean age ± SD, 62.4 ± 6.4 y; 12 men and 8 women) and 70 ALS patients (mean age ± SD, 62.2 ± 12.5 y; 44 men and 26 women) (group 1). Data were spatially normalized and analyzed on a VOI basis (statistical software (using the Hammers atlas) and voxel basis using statistical parametric mapping. Discriminant analysis and SVM were used to classify new cases based on the classifiers derived from group 1. Compared with controls, ALS patients showed a nearly identical pattern of hypo- and hypermetabolism in groups 1 and 2. VOI-based discriminant analysis resulted in an 88.8% accuracy in predicting the new ALS cases. For the SVM approach, this accuracy was 100%. Brain metabolism between ALS and primary lateral sclerosis patients was

  18. Molecular discrimination of Echinococcus granulosus and Echinococcus multilocularis by sequencing and a new PCR-RFLP method with the potential use for other Echinococcus species.

    Science.gov (United States)

    Şakalar, Çağrı; Kuk, Salih; Erensoy, Ahmet; Dağli, Adile Ferda; Özercan, İbrahim Hanifi; Çetınkaya, Ülfet; Yazar, Süleyman

    2014-01-01

    To develop a novel polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) protocol using a new genomic marker sequence and a novel set of restriction enzymes in order to detect and discriminate 2 Echinococcus species, E. granulosus and E. multilocularis, found in formalin-fixed paraffin-embedded (FFPE) human tissues. DNA was isolated from 11 FFPE human tissue samples positive for cystic echinococcosis or alveolar echinococcosis. A mitochondrial genomic marker region was amplified and sequenced using a novel primer pair and a new PCR-RFLP protocol was developed for the detection and discrimination of E. granulosus and E. multilocularis using a set of restriction enzymes including AccI, MboI, MboII, and TsoI. The selected marker region was amplified using DNA isolated from FFPE human tissue samples positive for cystic echinococcosis or alveolar echinococcosis and the discrimination of E. granulosus and E. multilocularis was accomplished by use of the novel PCR-RFLP method. In this PCR-RFLP protocol, use of any single restriction enzyme is enough for the discrimination of E. granulosus and E. multilocularis. The PCR-RFLP protocol can be potentially used for the discrimination of 5 other Echinococcus species: E. oligarthus, E. shiquicus, E. ortleppi, E. canadensis, and E. vogeli.

  19. Contour Propagation Using Feature-Based Deformable Registration for Lung Cancer

    Directory of Open Access Journals (Sweden)

    Yuhan Yang

    2013-01-01

    Full Text Available Accurate target delineation of CT image is a critical step in radiotherapy treatment planning. This paper describes a novel strategy for automatic contour propagation, based on deformable registration, for CT images of lung cancer. The proposed strategy starts with a manual-delineated contour in one slice of a 3D CT image. By means of feature-based deformable registration, the initial contour in other slices of the image can be propagated automatically, and then refined by active contour approach. Three algorithms are employed in the strategy: the Speeded-Up Robust Features (SURF, Thin-Plate Spline (TPS, and an adapted active contour (Snake, used to refine and modify the initial contours. Five pulmonary cancer cases with about 400 slices and 1000 contours have been used to verify the proposed strategy. Experiments demonstrate that the proposed strategy can improve the segmentation performance in the pulmonary CT images. Jaccard similarity (JS mean is about 0.88 and the maximum of Hausdorff distance (HD is about 90%. In addition, delineation time has been considerably reduced. The proposed feature-based deformable registration method in the automatic contour propagation improves the delineation efficiency significantly.

  20. Application of the discriminant analysis method to the recognition of jets and the nature of partons in the e+e- hadrons reactions

    International Nuclear Information System (INIS)

    Mjahed, M.

    1987-06-01

    In e + e - annihilation process, the jets are produced by the fragmentation of various partons: the six flavours of quarks (u, d, s, c and the hypothetic top quark) and from the gluon. They form, according to the processus of production (e + e - →, qantiq, qantiqg, qantiqgg, qantiqqantiq) 2, 3, 4... jet events. Those jets are characterized by cinematical variables: sphericity, thrust, aplanarity, transverse momentum, charge, the fastest particle or the direction of jets. The identification of the variety of events or jets, by chosen variables taken one by one is not generally sufficient. The discriminant analysis method we used allows correlation of the greatest set of variables and the finding of the axis or the discriminant function, by which the classes of events or jets are discriminated. With the application of the method to the e + e - → hadrons reactions we can: - identify quark top events - determine the number of jets in u, d, s, c or b events - distinguish between quark jets and gluon jets -recognize the flavours of quark jets. The analysis is done at high energy (LEP) and based on a Monte-Carlo simulation with the Lund code, and for the first two points a simulation with constraint coming from the apparatus of detector ALEPH. The discriminant functions give an excellent separation of the different processes and can be used for real data (LEP...) The method can be used to other reactions: pantip, ep [fr

  1. Mass discrimination

    Energy Technology Data Exchange (ETDEWEB)

    Broeckman, A. [Rijksuniversiteit Utrecht (Netherlands)

    1978-12-15

    In thermal ionization mass spectrometry the phenomenon of mass discrimination has led to the use of a correction factor for isotope ratio-measurements. The correction factor is defined as the measured ratio divided by the true or accepted value of this ratio. In fact this factor corrects for systematic errors of the whole procedure; however mass discrimination is often associated just with the mass spectrometer.

  2. Serum prolactin revisited: parametric reference intervals and cross platform evaluation of polyethylene glycol precipitation-based methods for discrimination between hyperprolactinemia and macroprolactinemia.

    Science.gov (United States)

    Overgaard, Martin; Pedersen, Susanne Møller

    2017-10-26

    Hyperprolactinemia diagnosis and treatment is often compromised by the presence of biologically inactive and clinically irrelevant higher-molecular-weight complexes of prolactin, macroprolactin. The objective of this study was to evaluate the performance of two macroprolactin screening regimes across commonly used automated immunoassay platforms. Parametric total and monomeric gender-specific reference intervals were determined for six immunoassay methods using female (n=96) and male sera (n=127) from healthy donors. The reference intervals were validated using 27 hyperprolactinemic and macroprolactinemic sera, whose presence of monomeric and macroforms of prolactin were determined using gel filtration chromatography (GFC). Normative data for six prolactin assays included the range of values (2.5th-97.5th percentiles). Validation sera (hyperprolactinemic and macroprolactinemic; n=27) showed higher discordant classification [mean=2.8; 95% confidence interval (CI) 1.2-4.4] for the monomer reference interval method compared to the post-polyethylene glycol (PEG) recovery cutoff method (mean=1.8; 95% CI 0.8-2.8). The two monomer/macroprolactin discrimination methods did not differ significantly (p=0.089). Among macroprolactinemic sera evaluated by both discrimination methods, the Cobas and Architect/Kryptor prolactin assays showed the lowest and the highest number of misclassifications, respectively. Current automated immunoassays for prolactin testing require macroprolactin screening methods based on PEG precipitation in order to discriminate truly from falsely elevated serum prolactin. While the recovery cutoff and monomeric reference interval macroprolactin screening methods demonstrate similar discriminative ability, the latter method also provides the clinician with an easy interpretable monomeric prolactin concentration along with a monomeric reference interval.

  3. How discriminating are discriminative instruments?

    Science.gov (United States)

    Hankins, Matthew

    2008-05-27

    The McMaster framework introduced by Kirshner & Guyatt is the dominant paradigm for the development of measures of health status and health-related quality of life (HRQL). The framework defines the functions of such instruments as evaluative, predictive or discriminative. Evaluative instruments are required to be sensitive to change (responsiveness), but there is no corresponding index of the degree to which discriminative instruments are sensitive to cross-sectional differences. This paper argues that indices of validity and reliability are not sufficient to demonstrate that a discriminative instrument performs its function of discriminating between individuals, and that the McMaster framework would be augmented by the addition of a separate index of discrimination. The coefficient proposed by Ferguson (Delta) is easily adapted to HRQL instruments and is a direct, non-parametric index of the degree to which an instrument distinguishes between individuals. While Delta should prove useful in the development and evaluation of discriminative instruments, further research is required to elucidate the relationship between the measurement properties of discrimination, reliability and responsiveness.

  4. How discriminating are discriminative instruments?

    Directory of Open Access Journals (Sweden)

    Hankins Matthew

    2008-05-01

    Full Text Available Abstract The McMaster framework introduced by Kirshner & Guyatt is the dominant paradigm for the development of measures of health status and health-related quality of life (HRQL. The framework defines the functions of such instruments as evaluative, predictive or discriminative. Evaluative instruments are required to be sensitive to change (responsiveness, but there is no corresponding index of the degree to which discriminative instruments are sensitive to cross-sectional differences. This paper argues that indices of validity and reliability are not sufficient to demonstrate that a discriminative instrument performs its function of discriminating between individuals, and that the McMaster framework would be augmented by the addition of a separate index of discrimination. The coefficient proposed by Ferguson (Delta is easily adapted to HRQL instruments and is a direct, non-parametric index of the degree to which an instrument distinguishes between individuals. While Delta should prove useful in the development and evaluation of discriminative instruments, further research is required to elucidate the relationship between the measurement properties of discrimination, reliability and responsiveness.

  5. A Novel Method for the Discrimination of Semen Arecae and Its Processed Products by Using Computer Vision, Electronic Nose, and Electronic Tongue

    Directory of Open Access Journals (Sweden)

    Min Xu

    2015-01-01

    Full Text Available Areca nut, commonly known locally as Semen Arecae (SA in China, has been used as an important Chinese herbal medicine for thousands of years. The raw SA (RAW is commonly processed by stir-baking to yellow (SBY, stir-baking to dark brown (SBD, and stir-baking to carbon dark (SBC for different clinical uses. In our present investigation, intelligent sensory technologies consisting of computer vision (CV, electronic nose (E-nose, and electronic tongue (E-tongue were employed in order to develop a novel and accurate method for discrimination of SA and its processed products. Firstly, the color parameters and electronic sensory responses of E-nose and E-tongue of the samples were determined, respectively. Then, indicative components including 5-hydroxymethyl furfural (5-HMF and arecoline (ARE were determined by HPLC. Finally, principal component analysis (PCA and discriminant factor analysis (DFA were performed. The results demonstrated that these three instruments can effectively discriminate SA and its processed products. 5-HMF and ARE can reflect the stir-baking degree of SA. Interestingly, the two components showed close correlations to the color parameters and sensory responses of E-nose and E-tongue. In conclusion, this novel method based on CV, E-nose, and E-tongue can be successfully used to discriminate SA and its processed products.

  6. Low power constant fraction discriminator

    International Nuclear Information System (INIS)

    Krishnan, Shanti; Raut, S.M.; Mukhopadhyay, P.K.

    2001-01-01

    This paper describes the design of a low power ultrafast constant fraction discriminator, which significantly reduces the power consumption. A conventional fast discriminator consumes about 1250 MW of power whereas this low power version consumes about 440 MW. In a multi detector system, where the number of discriminators is very large, reduction of power is of utmost importance. This low power discriminator is being designed for GRACE (Gamma Ray Atmospheric Cerenkov Experiments) telescope where 1000 channels of discriminators are required. A novel method of decreasing power consumption has been described. (author)

  7. Signal Detection Methods and Discriminant Analysis Applied to Categorization of Newspaper and Government Documents: A Preliminary Study.

    Science.gov (United States)

    Ng, Kwong Bor; Rieh, Soo Young; Kantor, Paul

    2000-01-01

    Discussion of natural language processing focuses on experiments using linear discriminant analysis to distinguish "Wall Street Journal" texts from "Federal Register" tests using information about the frequency of occurrence of word boundaries, sentence boundaries, and punctuation marks. Displays and interprets results in terms…

  8. FEATURES BASED ON NEIGHBORHOOD PIXELS DENSITY - A STUDY AND COMPARISON

    Directory of Open Access Journals (Sweden)

    Satish Kumar

    2016-02-01

    Full Text Available In optical character recognition applications, the feature extraction method(s used to recognize document images play an important role. The features are the properties of the pattern that can be statistical, structural and/or transforms or series expansion. The structural features are difficult to compute particularly from hand-printed images. The structure of the strokes present inside the hand-printed images can be estimated using statistical means. In this paper three features have been purposed, those are based on the distribution of B/W pixels on the neighborhood of a pixel in an image. We name these features as Spiral Neighbor Density, Layer Pixel Density and Ray Density. The recognition performance of these features has been compared with two more features Neighborhood Pixels Weight and Total Distances in Four Directions already studied in our work. We have used more than 20000 Devanagari handwritten character images for conducting experiments. The experiments are conducted with two classifiers i.e. PNN and k-NN.

  9. The Speed of Feature-Based Attention: Attentional Advantage Is Slow, but Selection Is Fast

    Science.gov (United States)

    Huang, Liqiang

    2010-01-01

    When paying attention to a feature (e.g., red), no attentional advantage is gained in perceiving items with this feature in very brief displays. Therefore, feature-based attention seems to be slow. In previous feature-based attention studies, attention has often been measured as the difference in performance in a secondary task. In our recent work…

  10. Selecting protein families for environmental features based on manifold regularization.

    Science.gov (United States)

    Jiang, Xingpeng; Xu, Weiwei; Park, E K; Li, Guangrong

    2014-06-01

    Recently, statistics and machine learning have been developed to identify functional or taxonomic features of environmental features or physiological status. Important proteins (or other functional and taxonomic entities) to environmental features can be potentially used as biosensors. A major challenge is how the distribution of protein and gene functions embodies the adaption of microbial communities across environments and host habitats. In this paper, we propose a novel regularization method for linear regression to adapt the challenge. The approach is inspired by local linear embedding (LLE) and we call it a manifold-constrained regularization for linear regression (McRe). The novel regularization procedure also has potential to be used in solving other linear systems. We demonstrate the efficiency and the performance of the approach in both simulation and real data.

  11. Molecular discrimination of Echinococcus granulosus and Echinococcus multilocularis by sequencing and a new PCR-RFLP method with the potential use for other Echinococcus species

    OpenAIRE

    ŞAKALAR, Çağrı; KUK, Salih; ERENSOY, Ahmet; DAĞLI, Adile Ferda; ÖZERCAN, İbrahim Hanifi

    2015-01-01

    To develop a novel polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) protocol using a new genomic marker sequence and a novel set of restriction enzymes in order to detect and discriminate 2 Echinococcus species, E. granulosus and E. multilocularis, found in formalin-fixed paraffin-embedded (FFPE) human tissues. Materials and methods: DNA was isolated from 11 FFPE human tissue samples positive for cystic echinococcosis or alveolar echinococcosis. A mitochondrial...

  12. A rapid, simple method for the genetic discrimination of intact Arabidopsis thaliana mutant seeds using metabolic profiling by direct analysis in real-time mass spectrometry

    Directory of Open Access Journals (Sweden)

    Jang Young

    2011-06-01

    Full Text Available Abstract Background Efficient high throughput screening systems of useful mutants are prerequisite for study of plant functional genomics and lots of application fields. Advance in such screening tools, thanks to the development of analytic instruments. Direct analysis in real-time (DART-mass spectrometry (MS by ionization of complex materials at atmospheric pressure is a rapid, simple, high-resolution analytical technique. Here we describe a rapid, simple method for the genetic discrimination of intact Arabidopsis thaliana mutant seeds using metabolic profiling by DART-MS. Results To determine whether this DART-MS combined by multivariate analysis can perform genetic discrimination based on global metabolic profiling, intact Arabidopsis thaliana mutant seeds were subjected to DART-MS without any sample preparation. Partial least squares-discriminant analysis (PLS-DA of DART-MS spectral data from intact seeds classified 14 different lines of seeds into two distinct groups: Columbia (Col-0 and Landsberg erecta (Ler ecotype backgrounds. A hierarchical dendrogram based on partial least squares-discriminant analysis (PLS-DA subdivided the Col-0 ecotype into two groups: mutant lines harboring defects in the phenylpropanoid biosynthetic pathway and mutants without these defects. These results indicated that metabolic profiling with DART-MS could discriminate intact Arabidopsis seeds at least ecotype level and metabolic pathway level within same ecotype. Conclusion The described DART-MS combined by multivariate analysis allows for rapid screening and metabolic characterization of lots of Arabidopsis mutant seeds without complex metabolic preparation steps. Moreover, potential novel metabolic markers can be detected and used to clarify the genetic relationship between Arabidopsis cultivars. Furthermore this technique can be applied to predict the novel gene function of metabolic mutants regardless of morphological phenotypes.

  13. Topological Embedding Feature Based Resource Allocation in Network Virtualization

    Directory of Open Access Journals (Sweden)

    Hongyan Cui

    2014-01-01

    Full Text Available Virtualization provides a powerful way to run multiple virtual networks on a shared substrate network, which needs accurate and efficient mathematical models. Virtual network embedding is a challenge in network virtualization. In this paper, considering the degree of convergence when mapping a virtual network onto substrate network, we propose a new embedding algorithm based on topology mapping convergence-degree. Convergence-degree means the adjacent degree of virtual network’s nodes when they are mapped onto a substrate network. The contributions of our method are as below. Firstly, we map virtual nodes onto the substrate nodes with the maximum convergence-degree. The simulation results show that our proposed algorithm largely enhances the network utilization efficiency and decreases the complexity of the embedding problem. Secondly, we define the load balance rate to reflect the load balance of substrate links. The simulation results show our proposed algorithm achieves better load balance. Finally, based on the feature of star topology, we further improve our embedding algorithm and make it suitable for application in the star topology. The test result shows it gets better performance than previous works.

  14. Spectral features based tea garden extraction from digital orthophoto maps

    Science.gov (United States)

    Jamil, Akhtar; Bayram, Bulent; Kucuk, Turgay; Zafer Seker, Dursun

    2018-05-01

    The advancements in the photogrammetry and remote sensing technologies has made it possible to extract useful tangible information from data which plays a pivotal role in various application such as management and monitoring of forests and agricultural lands etc. This study aimed to evaluate the effectiveness of spectral signatures for extraction of tea gardens from 1 : 5000 scaled digital orthophoto maps obtained from Rize city in Turkey. First, the normalized difference vegetation index (NDVI) was derived from the input images to suppress the non-vegetation areas. NDVI values less than zero were discarded and the output images was normalized in the range 0-255. Individual pixels were then mapped into meaningful objects using global region growing technique. The resulting image was filtered and smoothed to reduce the impact of noise. Furthermore, geometrical constraints were applied to remove small objects (less than 500 pixels) followed by morphological opening operator to enhance the results. These objects served as building blocks for further image analysis. Finally, for the classification stage, a range of spectral values were empirically calculated for each band and applied on candidate objects to extract tea gardens. For accuracy assessment, we employed an area based similarity metric by overlapping obtained tea garden boundaries with the manually digitized tea garden boundaries created by experts of photogrammetry. The overall accuracy of the proposed method scored 89 % for tea gardens from 10 sample orthophoto maps. We concluded that exploiting the spectral signatures using object based analysis is an effective technique for extraction of dominant tree species from digital orthophoto maps.

  15. Origin Discrimination of Osmanthus fragrans var. thunbergii Flowers using GC-MS and UPLC-PDA Combined with Multivariable Analysis Methods.

    Science.gov (United States)

    Zhou, Fei; Zhao, Yajing; Peng, Jiyu; Jiang, Yirong; Li, Maiquan; Jiang, Yuan; Lu, Baiyi

    2017-07-01

    Osmanthus fragrans flowers are used as folk medicine and additives for teas, beverages and foods. The metabolites of O. fragrans flowers from different geographical origins were inconsistent in some extent. Chromatography and mass spectrometry combined with multivariable analysis methods provides an approach for discriminating the origin of O. fragrans flowers. To discriminate the Osmanthus fragrans var. thunbergii flowers from different origins with the identified metabolites. GC-MS and UPLC-PDA were conducted to analyse the metabolites in O. fragrans var. thunbergii flowers (in total 150 samples). Principal component analysis (PCA), soft independent modelling of class analogy analysis (SIMCA) and random forest (RF) analysis were applied to group the GC-MS and UPLC-PDA data. GC-MS identified 32 compounds common to all samples while UPLC-PDA/QTOF-MS identified 16 common compounds. PCA of the UPLC-PDA data generated a better clustering than PCA of the GC-MS data. Ten metabolites (six from GC-MS and four from UPLC-PDA) were selected as effective compounds for discrimination by PCA loadings. SIMCA and RF analysis were used to build classification models, and the RF model, based on the four effective compounds (caffeic acid derivative, acteoside, ligustroside and compound 15), yielded better results with the classification rate of 100% in the calibration set and 97.8% in the prediction set. GC-MS and UPLC-PDA combined with multivariable analysis methods can discriminate the origin of Osmanthus fragrans var. thunbergii flowers. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

  16. Morphological evaluation of common bean diversity in Bosnia and Herzegovina using the discriminant analysis of principal components (DAPC multivariate method

    Directory of Open Access Journals (Sweden)

    Grahić Jasmin

    2013-01-01

    Full Text Available In order to analyze morphological characteristics of locally cultivated common bean landraces from Bosnia and Herzegovina (B&H, thirteen quantitative and qualitative traits of 40 P. vulgaris accessions, collected from four geographical regions (Northwest B&H, Northeast B&H, Central B&H and Sarajevo and maintained at the Gene bank of the Faculty of Agriculture and Food Sciences in Sarajevo, were examined. Principal component analysis (PCA showed that the proportion of variance retained in the first two principal components was 54.35%. The first principal component had high contributing factor loadings from seed width, seed height and seed weight, whilst the second principal component had high contributing factor loadings from the analyzed traits seed per pod and pod length. PCA plot, based on the first two principal components, displayed a high level of variability among the analyzed material. The discriminant analysis of principal components (DAPC created 3 discriminant functions (DF, whereby the first two discriminant functions accounted for 90.4% of the variance retained. Based on the retained DFs, DAPC provided group membership probabilities which showed that 70% of the accessions examined were correctly classified between the geographically defined groups. Based on the taxonomic distance, 40 common bean accessions analyzed in this study formed two major clusters, whereas two accessions Acc304 and Acc307 didn’t group in any of those. Acc360 and Acc362, as well as Acc324 and Acc371 displayed a high level of similarity and are probably the same landrace. The present diversity of Bosnia and Herzegovina’s common been landraces could be useful in future breeding programs.

  17. A discrimination task used as a novel method of testing decision-making behavior following traumatic brain injury.

    Science.gov (United States)

    Martens, Kris M; Vonder Haar, Cole; Hutsell, Blake A; Hoane, Michael R

    2012-10-10

    Traumatic brain injury (TBI) results in a multitude of deficits following injury. Some of the most pervasive in humans are the changes that affect frontally-mediated cognitive functioning, such as decision making. The assessment of decision-making behavior in rodents has been extensively tested in the field of the experimental analysis of behavior. However, due to the narrow therapeutic window following TBI, time-intensive operant paradigms are rarely incorporated into the battery of tests traditionally used, the majority of which assess motor and sensory functioning. The cognitive measures that are used are frequently limited to memory and do not account for changes in decision-making behavior. The purpose of the present study was to develop a simplified discrimination task that can assess deficits in decision-making behavior in rodents. For the task, rats were required to dig in cocoa-scented sand (versus unscented sand) for a reinforcer. Rats were given 12 sessions per day until a criterion level of 80% accuracy for 3 days straight was reached. Once the criterion was achieved, cortical contusion injuries were induced (frontal, parietal, or sham). Following a recovery period, the rats were re-tested on cocoa versus unscented sand. Upon reaching criterion, a reversal discrimination was evaluated in which the reinforcer was placed in unscented sand. Finally, a novel scent discrimination (basil versus coffee with basil reinforced), and a reversal (coffee) were evaluated. The results indicated that the Dig task is a simple experimental preparation that can be used to assess deficits in decision-making behavior following TBI.

  18. Logistic discriminant parametric mapping: a novel method for the pixel-based differential diagnosis of Parkinson's disease

    International Nuclear Information System (INIS)

    Acton, P.D.; Mozley, P.D.; Kung, H.F.; Pennsylvania Univ., Philadelphia, PA

    1999-01-01

    Positron emission tomography (PET) and single-photon emission tomography (SPET) imaging of the dopaminergic system is a powerful tool for distinguishing groups of patients with neurodegenerative disorders, such as Parkinson's disease (PD). However, the differential diagnosis of individual subjects presenting early in the progress of the disease is much more difficult, particularly using region-of-interest analysis where small localized differences between subjects are diluted. In this paper we present a novel pixel-based technique using logistic discriminant analysis to distinguish between a group of PD patients and age-matched healthy controls. Simulated images of an anthropomorphic head phantom were used to test the sensitivity of the technique to striatal lesions of known size. The methodology was applied to real clinical SPET images of binding of technetium-99m labelled TRODAT-1 to dopamine transporters in PD patients (n=42) and age-matched controls (n=23). The discriminant model was trained on a subset (n=17) of patients for whom the diagnosis was unequivocal. Logistic discriminant parametric maps were obtained for all subjects, showing the probability distribution of pixels classified as being consistent with PD. The probability maps were corrected for correlated multiple comparisons assuming an isotropic Gaussian point spread function. Simulated lesion sizes measured by logistic discriminant parametric mapping (LDPM) gave strong correlations with the known data (r 2 =0.985, P<0.001). LDPM correctly classified all PD patients (sensitivity 100%) and only misclassified one control (specificity 95%). All patients who had equivocal clinical symptoms associated with early onset PD (n=4) were correctly assigned to the patient group. Statistical parametric mapping (SPM) had a sensitivity of only 24% on the same patient group. LDPM is a powerful pixel-based tool for the differential diagnosis of patients with PD and healthy controls. The diagnosis of disease even

  19. Learning discriminant face descriptor.

    Science.gov (United States)

    Lei, Zhen; Pietikäinen, Matti; Li, Stan Z

    2014-02-01

    Local feature descriptor is an important module for face recognition and those like Gabor and local binary patterns (LBP) have proven effective face descriptors. Traditionally, the form of such local descriptors is predefined in a handcrafted way. In this paper, we propose a method to learn a discriminant face descriptor (DFD) in a data-driven way. The idea is to learn the most discriminant local features that minimize the difference of the features between images of the same person and maximize that between images from different people. In particular, we propose to enhance the discriminative ability of face representation in three aspects. First, the discriminant image filters are learned. Second, the optimal neighborhood sampling strategy is soft determined. Third, the dominant patterns are statistically constructed. Discriminative learning is incorporated to extract effective and robust features. We further apply the proposed method to the heterogeneous (cross-modality) face recognition problem and learn DFD in a coupled way (coupled DFD or C-DFD) to reduce the gap between features of heterogeneous face images to improve the performance of this challenging problem. Extensive experiments on FERET, CAS-PEAL-R1, LFW, and HFB face databases validate the effectiveness of the proposed DFD learning on both homogeneous and heterogeneous face recognition problems. The DFD improves POEM and LQP by about 4.5 percent on LFW database and the C-DFD enhances the heterogeneous face recognition performance of LBP by over 25 percent.

  20. Enhancing the discrimination accuracy between metastases, gliomas and meningiomas on brain MRI by volumetric textural features and ensemble pattern recognition methods.

    Science.gov (United States)

    Georgiadis, Pantelis; Cavouras, Dionisis; Kalatzis, Ioannis; Glotsos, Dimitris; Athanasiadis, Emmanouil; Kostopoulos, Spiros; Sifaki, Koralia; Malamas, Menelaos; Nikiforidis, George; Solomou, Ekaterini

    2009-01-01

    Three-dimensional (3D) texture analysis of volumetric brain magnetic resonance (MR) images has been identified as an important indicator for discriminating among different brain pathologies. The purpose of this study was to evaluate the efficiency of 3D textural features using a pattern recognition system in the task of discriminating benign, malignant and metastatic brain tissues on T1 postcontrast MR imaging (MRI) series. The dataset consisted of 67 brain MRI series obtained from patients with verified and untreated intracranial tumors. The pattern recognition system was designed as an ensemble classification scheme employing a support vector machine classifier, specially modified in order to integrate the least squares features transformation logic in its kernel function. The latter, in conjunction with using 3D textural features, enabled boosting up the performance of the system in discriminating metastatic, malignant and benign brain tumors with 77.14%, 89.19% and 93.33% accuracy, respectively. The method was evaluated using an external cross-validation process; thus, results might be considered indicative of the generalization performance of the system to "unseen" cases. The proposed system might be used as an assisting tool for brain tumor characterization on volumetric MRI series.

  1. The discrimination of d-tartrate positive and d-tartrate negative S. enterica subsp. enterica serovar Paratyphi B isolated in Malaysia by phenotypic and genotypic methods.

    Science.gov (United States)

    Ahmad, Norazah; Hoon, Shirley Tang Gee; Ghani, Mohamed Kamel Abd; Tee, Koh Yin

    2012-06-01

    Serotyping is not sufficient to differentiate between Salmonella species that cause paratyphoid fever from the strains that cause milder gastroenteritis as these organisms share the same serotype Salmonella Paratyphi B (S. Paratyphi B). Strains causing paratyphoid fever do not ferment d-tartrate and this key feature was used in this study to determine the prevalence of these strains among the collection of S. Paratyphi B strains isolated from patients in Malaysia. A total of 105 isolates of S. Paratyphi B were discriminated into d-tartrate positive (dT+) and d-tartrate negative (dT) variants by two lead acetate test protocols and multiplex PCR. The lead acetate test protocol 1 differed from protocol 2 by a lower inoculum size and different incubation conditions while the multiplex PCR utilized 2 sets of primers targeting the ATG start codon of the gene STM3356. Lead acetate protocol 1 discriminated 97.1% of the isolates as S. Paratyphi B dT+ and 2.9% as dT while test protocol 2 discriminated all the isolates as S. Paratyphi B dT+. The multiplex PCR test identified all 105 isolates as S. Paratyphi B dT+ strains. The concordance of the lead acetate test relative to that of multiplex PCR was 97.7% and 100% for protocol 1 and 2 respectively. This study showed that S. Paratyphi B dT+ is a common causative agent of gastroenteritis in Malaysia while paratyphoid fever appears to be relatively uncommon. Multiplex PCR was shown to be a simpler, more rapid and reliable method to discriminate S. Paratyphi B than the phenotypic lead acetate test.

  2. A Study on the Method to Discriminate Between the Internal and External Radioactive Contamination Using Whole Body Counter

    International Nuclear Information System (INIS)

    Kong, T. Y.; Kim, H. G.; Yang, H. Y.; Kang, D. W.; Lim, S. N.; Kim, H. J.; Jin, H. H.; Lee, S. G.; Park, S. C.

    2006-01-01

    Whole Body Counter (WBC) is used to identify and measure the radioactivity in the body of human beings in a nuclear power plants (NPPs). In domestic NPPs, it is prescribed that all workers should take a whole body counting after radiation works if the possibilities of radioactive contamination exist or the radioactivity is detected by a portal monitoring. It is, however, found that the external skin contamination is occasionally estimated as the internal radioactive contamination. In this case, the worker assumed to be detected is recommended to take showers for the decontamination of skin and take a whole body counting again. Although the detected radioactivity is reduced remarkably after several decontaminations, confirmed as the external skin contamination, it is determined finally as an internal exposure if the radioactivity is still detected in the body of worker. The amount of detected radioactivity can be much higher than that of the expected for this mistaken contamination since the radioisotopes attached to skin come to be close to the detectors of WBC. Finally, this makes the misjudgment of the external skin contamination as well as the excessively conservative estimation of radioactive contamination. In this study, several experiments were carried out to discriminate between the internal and external radioactive contamination using the humanoid phantom and WBC. Preliminary experimental results indicated that the use of front and backside counts could be applied to the discrimination of the external skin contamination and the difference of detected radioactivities between front and backside counts was less than about factor 2 for the internal contamination

  3. Wavelet Types Comparison for Extracting Iris Feature Based on Energy Compaction

    Science.gov (United States)

    Rizal Isnanto, R.

    2015-06-01

    Human iris has a very unique pattern which is possible to be used as a biometric recognition. To identify texture in an image, texture analysis method can be used. One of method is wavelet that extract the image feature based on energy. Wavelet transforms used are Haar, Daubechies, Coiflets, Symlets, and Biorthogonal. In the research, iris recognition based on five mentioned wavelets was done and then comparison analysis was conducted for which some conclusions taken. Some steps have to be done in the research. First, the iris image is segmented from eye image then enhanced with histogram equalization. The features obtained is energy value. The next step is recognition using normalized Euclidean distance. Comparison analysis is done based on recognition rate percentage with two samples stored in database for reference images. After finding the recognition rate, some tests are conducted using Energy Compaction for all five types of wavelets above. As the result, the highest recognition rate is achieved using Haar, whereas for coefficients cutting for C(i) < 0.1, Haar wavelet has a highest percentage, therefore the retention rate or significan coefficient retained for Haaris lower than other wavelet types (db5, coif3, sym4, and bior2.4)

  4. In silico and experimental evaluation of DNA-based detection methods for the ability to discriminate almond from other Prunus spp.

    Science.gov (United States)

    Brežná, Barbara; Šmíd, Jiří; Costa, Joana; Radvanszky, Jan; Mafra, Isabel; Kuchta, Tomáš

    2015-04-01

    Ten published DNA-based analytical methods aiming at detecting material of almond (Prunus dulcis) were in silico evaluated for potential cross-reactivity with other stone fruits (Prunus spp.), including peach, apricot, plum, cherry, sour cherry and Sargent cherry. For most assays, the analysis of nucleotide databases suggested none or insufficient discrimination of at least some stone fruits. On the other hand, the assay targeting non-specific lipid transfer protein (Röder et al., 2011, Anal Chim Acta 685:74-83) was sufficiently discriminative, judging from nucleotide alignments. Empirical evaluation was performed for three of the published methods, one modification of a commercial kit (SureFood allergen almond) and one attempted novel method targeting thaumatin-like protein gene. Samples of leaves and kernels were used in the experiments. The empirical results were favourable for the method from Röder et al. (2011) and a modification of SureFood allergen almond kit, both showing cross-reactivity <10(-3) compared to the model almond. Copyright © 2014 Elsevier Ltd. All rights reserved.

  5. Rainfall induced landslide susceptibility mapping using weight-of-evidence, linear and quadratic discriminant and logistic model tree method

    Science.gov (United States)

    Hong, H.; Zhu, A. X.

    2017-12-01

    Climate change is a common phenomenon and it is very serious all over the world. The intensification of rainfall extremes with climate change is of key importance to society and then it may induce a large impact through landslides. This paper presents GIS-based new ensemble data mining techniques that weight-of-evidence, logistic model tree, linear and quadratic discriminant for landslide spatial modelling. This research was applied in Anfu County, which is a landslide-prone area in Jiangxi Province, China. According to a literature review and research the study area, we select the landslide influencing factor and their maps were digitized in a GIS environment. These landslide influencing factors are the altitude, plan curvature, profile curvature, slope degree, slope aspect, topographic wetness index (TWI), Stream Power Index (SPI), Topographic Wetness Index (SPI), distance to faults, distance to rivers, distance to roads, soil, lithology, normalized difference vegetation index and land use. According to historical information of individual landslide events, interpretation of the aerial photographs, and field surveys supported by the government of Jiangxi Meteorological Bureau of China, 367 landslides were identified in the study area. The landslide locations were divided into two subsets, namely, training and validating (70/30), based on a random selection scheme. In this research, Pearson's correlation was used for the evaluation of the relationship between the landslides and influencing factors. In the next step, three data mining techniques combined with the weight-of-evidence, logistic model tree, linear and quadratic discriminant, were used for the landslide spatial modelling and its zonation. Finally, the landslide susceptibility maps produced by the mentioned models were evaluated by the ROC curve. The results showed that the area under the curve (AUC) of all of the models was > 0.80. At the same time, the highest AUC value was for the linear and quadratic

  6. Discriminative Shape Alignment

    DEFF Research Database (Denmark)

    Loog, M.; de Bruijne, M.

    2009-01-01

    , not taking into account that eventually the shapes are to be assigned to two or more different classes. This work introduces a discriminative variation to well-known Procrustes alignment and demonstrates its benefit over this classical method in shape classification tasks. The focus is on two...

  7. Airborne particulate discriminator

    Science.gov (United States)

    Creek, Kathryn Louise [San Diego, CA; Castro, Alonso [Santa Fe, NM; Gray, Perry Clayton [Los Alamos, NM

    2009-08-11

    A method and apparatus for rapid and accurate detection and discrimination of biological, radiological, and chemical particles in air. A suspect aerosol of the target particulates is treated with a taggant aerosol of ultrafine particulates. Coagulation of the taggant and target particles causes a change in fluorescent properties of the cloud, providing an indication of the presence of the target.

  8. Disturbance by optimal discrimination

    Science.gov (United States)

    Kawakubo, Ryûitirô; Koike, Tatsuhiko

    2018-03-01

    We discuss the disturbance by measurements which unambiguously discriminate between given candidate states. We prove that such an optimal measurement necessarily changes distinguishable states indistinguishable when the inconclusive outcome is obtained. The result was previously shown by Chefles [Phys. Lett. A 239, 339 (1998), 10.1016/S0375-9601(98)00064-4] under restrictions on the class of quantum measurements and on the definition of optimality. Our theorems remove these restrictions and are also applicable to infinitely many candidate states. Combining with our previous results, one can obtain concrete mathematical conditions for the resulting states. The method may have a wide variety of applications in contexts other than state discrimination.

  9. Optical beam classification using deep learning: a comparison with rule- and feature-based classification

    Science.gov (United States)

    Alom, Md. Zahangir; Awwal, Abdul A. S.; Lowe-Webb, Roger; Taha, Tarek M.

    2017-08-01

    Vector Machine (SVM). The experimental results show around 96% classification accuracy using CNN; the CNN approach also provides comparable recognition results compared to the present feature-based off-normal detection. The feature-based solution was developed to capture the expertise of a human expert in classifying the images. The misclassified results are further studied to explain the differences and discover any discrepancies or inconsistencies in current classification.

  10. Discrimination of Inrush from Fault Currents in Power Transformers Based on Equivalent Instantaneous Inductance Technique Coupled with Finite Element Method

    Directory of Open Access Journals (Sweden)

    M. Jamali

    2011-09-01

    Full Text Available The phenomenon of magnetizing inrush is a transient condition, which occurs primarily when a transformer is energized. The magnitude of inrush current may be as high as ten times or more times of transformer rated current that causes malfunction of protection system. So, for safe running of a transformer, it is necessary to distinguish inrush current from fault currents. In this paper, an equivalent instantaneous inductance (EII technique is used to discriminate inrush current from fault currents. For this purpose, a three-phase power transformer has been simulated in Maxwell software that is based on finite elements. This three-phase power transformer has been used to simulate different conditions. Then, the results have been used as inputs in MATLAB program to implement the equivalent instantaneous inductance technique. The results show that in the case of inrush current, the equivalent instantaneous inductance has a drastic variation, while it is almost constant in the cases of fault conditions.

  11. Application of the A/E pulse shape discrimination method to first Ge-76 enriched BEGe detectors operated in GERDA

    Energy Technology Data Exchange (ETDEWEB)

    Lazzaro, Andrea; Agostini, Matteo; Budjas, Dusan; Schoenert, Stefan [Physik-Department E15, Technische Universitaet Muenchen (Germany); Collaboration: GERDA-Collaboration

    2013-07-01

    In 2013 the Gerda experiment will be upgraded to its second phase with more than double of the current {sup 76}Ge mass. The additional diodes are custom made Broad Energy Germanium (BEGe) detectors. This design has been chosen to enhance the pulse shape discrimination (PSD) capability, with respect to the Phase I coaxial detectors. The goal of Phase II is to improve by one order of magnitude the current background index; the PSD will bring a major contribution to this result. Since summer 2012 the first set of five enriched BEGe detectors are operated in Gerda Phase I. This offers us the possibility to test the PSD performances and the signal analysis in an environment as close as possible to the Gerda Phase II configuration. In this talk I present the A/E analysis, the calibration of the cut parameters and the results in terms of background reduction for the data taken with these enriched BEGe.

  12. Moving-window bis-correlation coefficients method for visible and near-infrared spectral discriminant analysis with applications

    Directory of Open Access Journals (Sweden)

    Lijun Yao

    2018-03-01

    Full Text Available The moving-window bis-correlation coefficients (MW-BiCC was proposed and employed for the discriminant analysis of transgenic sugarcane leaves and β-thalassemia with visible and near-infrared (Vis–NIR spectroscopy. The well-performed moving-window principal component analysis linear discriminant analysis (MW-PCA–LDA was also conducted for comparison. A total of 306 transgenic (positive and 150 nontransgenic (negative leave samples of sugarcane were collected and divided to calibration, prediction, and validation. The diffuse reflection spectra were corrected using Savitzky–Golay (SG smoothing with first-order derivative (d=1, third-degree polynomial (p=3 and 25 smoothing points (m=25. The selected waveband was 736–1054nm with MW-BiCC, and the positive and negative validation recognition rates (V_REC+, V_REC− were 100%, 98.0%, which achieved the same effect as MW-PCA–LDA. Another example, the 93 β-thalassemia (positive and 148 nonthalassemia (negative of human hemolytic samples were collected. The transmission spectra were corrected using SG smoothing with d=1, p=3 and m=53. Using MW-BiCC, many best wavebands were selected (e.g., 1116–1146, 1794–1848 and 2284–2342nm. The V_REC+ and V_REC− were both 100%, which achieved the same effect as MW-PCA–LDA. Importantly, the BiCC only required calculating correlation coefficients between the spectrum of prediction sample and the average spectra of two types of calibration samples. Thus, BiCC was very simple in algorithm, and expected to obtain more applications. The results first confirmed the feasibility of distinguishing β-thalassemia and normal control samples by NIR spectroscopy, and provided a promising simple tool for large population thalassemia screening.

  13. A new method of discriminating different types of post-Archean ophiolitic basalts and their tectonic significance using Th-Nb and Ce-Dy-Yb systematics

    Directory of Open Access Journals (Sweden)

    Emilio Saccani

    2015-07-01

    -derived components (nascent forearc sub-settings characterized by MTBs and depleted-MORBs. Two additional discrimination diagrams are proposed: (1 a Dy-Yb diagram is used for discriminating boninite and IAT basalts; (2 a Ce/Yb-Dy/Yb diagram is used for discriminating G-MORBs and normal MORBs. The proposed method may effectively assist in recovering the tectonic affinity of ancient ophiolites, which is fundamental for establishing the geodynamic evolution of ancient oceanic and continental domains, as well as orogenic belts.

  14. A Feature-Based Structural Measure: An Image Similarity Measure for Face Recognition

    Directory of Open Access Journals (Sweden)

    Noor Abdalrazak Shnain

    2017-08-01

    Full Text Available Facial recognition is one of the most challenging and interesting problems within the field of computer vision and pattern recognition. During the last few years, it has gained special attention due to its importance in relation to current issues such as security, surveillance systems and forensics analysis. Despite this high level of attention to facial recognition, the success is still limited by certain conditions; there is no method which gives reliable results in all situations. In this paper, we propose an efficient similarity index that resolves the shortcomings of the existing measures of feature and structural similarity. This measure, called the Feature-Based Structural Measure (FSM, combines the best features of the well-known SSIM (structural similarity index measure and FSIM (feature similarity index measure approaches, striking a balance between performance for similar and dissimilar images of human faces. In addition to the statistical structural properties provided by SSIM, edge detection is incorporated in FSM as a distinctive structural feature. Its performance is tested for a wide range of PSNR (peak signal-to-noise ratio, using ORL (Olivetti Research Laboratory, now AT&T Laboratory Cambridge and FEI (Faculty of Industrial Engineering, São Bernardo do Campo, São Paulo, Brazil databases. The proposed measure is tested under conditions of Gaussian noise; simulation results show that the proposed FSM outperforms the well-known SSIM and FSIM approaches in its efficiency of similarity detection and recognition of human faces.

  15. Feature based Weld-Deposition for Additive Manufacturing of Complex Shapes

    Science.gov (United States)

    Panchagnula, Jayaprakash Sharma; Simhambhatla, Suryakumar

    2018-06-01

    Fabricating functional metal parts using Additive Manufacturing (AM) is a leading trend. However, realizing overhanging features has been a challenge due to the lack of support mechanism for metals. Powder-bed fusion techniques like, Selective Laser Sintering (SLS) employ easily-breakable-scaffolds made of the same material to realize the overhangs. However, the same approach is not extendible to deposition processes like laser or arc based direct energy deposition processes. Although it is possible to realize small overhangs by exploiting the inherent overhanging capability of the process or by blinding some small features like holes, the same cannot be extended for more complex geometries. The current work presents a novel approach for realizing complex overhanging features without the need of support structures. This is possible by using higher order kinematics and suitably aligning the overhang with the deposition direction. Feature based non-uniform slicing and non-uniform area-filling are some vital concepts required in realizing the same and are briefly discussed here. This method can be used to fabricate and/or repair fully dense and functional components for various engineering applications. Although this approach has been implemented for weld-deposition based system, the same can be extended to any other direct energy deposition processes also.

  16. Identification of input variables for feature based artificial neural networks-saccade detection in EOG recordings.

    Science.gov (United States)

    Tigges, P; Kathmann, N; Engel, R R

    1997-07-01

    Though artificial neural networks (ANN) are excellent tools for pattern recognition problems when signal to noise ratio is low, the identification of decision relevant features for ANN input data is still a crucial issue. The experience of the ANN designer and the existing knowledge and understanding of the problem seem to be the only links for a specific construction. In the present study a backpropagation ANN based on modified raw data inputs showed encouraging results. Investigating the specific influences of prototypical input patterns on a specially designed ANN led to a new sparse and efficient input data presentation. This data coding obtained by a semiautomatic procedure combining existing expert knowledge and the internal representation structures of the raw data based ANN yielded a list of feature vectors, each representing the relevant information for saccade identification. The feature based ANN produced a reduction of the error rate of nearly 40% compared with the raw data ANN. An overall correct classification of 92% of so far unknown data was realized. The proposed method of extracting internal ANN knowledge for the production of a better input data representation is not restricted to EOG recordings, and could be used in various fields of signal analysis.

  17. Rapid discrimination between buffalo and cow milk and detection of adulteration of buffalo milk with cow milk using synchronous fluorescence spectroscopy in combination with multivariate methods.

    Science.gov (United States)

    Durakli Velioglu, Serap; Ercioglu, Elif; Boyaci, Ismail Hakki

    2017-05-01

    This research paper describes the potential of synchronous fluorescence (SF) spectroscopy for authentication of buffalo milk, a favourable raw material in the production of some premium dairy products. Buffalo milk is subjected to fraudulent activities like many other high priced foodstuffs. The current methods widely used for the detection of adulteration of buffalo milk have various disadvantages making them unattractive for routine analysis. Thus, the aim of the present study was to assess the potential of SF spectroscopy in combination with multivariate methods for rapid discrimination between buffalo and cow milk and detection of the adulteration of buffalo milk with cow milk. SF spectra of cow and buffalo milk samples were recorded between 400-550 nm excitation range with Δλ of 10-100 nm, in steps of 10 nm. The data obtained for ∆λ = 10 nm were utilised to classify the samples using principal component analysis (PCA), and detect the adulteration level of buffalo milk with cow milk using partial least square (PLS) methods. Successful discrimination of samples and detection of adulteration of buffalo milk with limit of detection value (LOD) of 6% are achieved with the models having root mean square error of calibration (RMSEC) and the root mean square error of cross-validation (RMSECV) and root mean square error of prediction (RMSEP) values of 2, 7, and 4%, respectively. The results reveal the potential of SF spectroscopy for rapid authentication of buffalo milk.

  18. Computer-aided assessment of breast density: comparison of supervised deep learning and feature-based statistical learning

    Science.gov (United States)

    Li, Songfeng; Wei, Jun; Chan, Heang-Ping; Helvie, Mark A.; Roubidoux, Marilyn A.; Lu, Yao; Zhou, Chuan; Hadjiiski, Lubomir M.; Samala, Ravi K.

    2018-01-01

    Breast density is one of the most significant factors that is associated with cancer risk. In this study, our purpose was to develop a supervised deep learning approach for automated estimation of percentage density (PD) on digital mammograms (DMs). The input ‘for processing’ DMs was first log-transformed, enhanced by a multi-resolution preprocessing scheme, and subsampled to a pixel size of 800 µm  ×  800 µm from 100 µm  ×  100 µm. A deep convolutional neural network (DCNN) was trained to estimate a probability map of breast density (PMD) by using a domain adaptation resampling method. The PD was estimated as the ratio of the dense area to the breast area based on the PMD. The DCNN approach was compared to a feature-based statistical learning approach. Gray level, texture and morphological features were extracted and a least absolute shrinkage and selection operator was used to combine the features into a feature-based PMD. With approval of the Institutional Review Board, we retrospectively collected a training set of 478 DMs and an independent test set of 183 DMs from patient files in our institution. Two experienced mammography quality standards act radiologists interactively segmented PD as the reference standard. Ten-fold cross-validation was used for model selection and evaluation with the training set. With cross-validation, DCNN obtained a Dice’s coefficient (DC) of 0.79  ±  0.13 and Pearson’s correlation (r) of 0.97, whereas feature-based learning obtained DC  =  0.72  ±  0.18 and r  =  0.85. For the independent test set, DCNN achieved DC  =  0.76  ±  0.09 and r  =  0.94, while feature-based learning achieved DC  =  0.62  ±  0.21 and r  =  0.75. Our DCNN approach was significantly better and more robust than the feature-based learning approach for automated PD estimation on DMs, demonstrating its potential use for automated density reporting as

  19. Computer-aided assessment of breast density: comparison of supervised deep learning and feature-based statistical learning.

    Science.gov (United States)

    Li, Songfeng; Wei, Jun; Chan, Heang-Ping; Helvie, Mark A; Roubidoux, Marilyn A; Lu, Yao; Zhou, Chuan; Hadjiiski, Lubomir M; Samala, Ravi K

    2018-01-09

    Breast density is one of the most significant factors that is associated with cancer risk. In this study, our purpose was to develop a supervised deep learning approach for automated estimation of percentage density (PD) on digital mammograms (DMs). The input 'for processing' DMs was first log-transformed, enhanced by a multi-resolution preprocessing scheme, and subsampled to a pixel size of 800 µm  ×  800 µm from 100 µm  ×  100 µm. A deep convolutional neural network (DCNN) was trained to estimate a probability map of breast density (PMD) by using a domain adaptation resampling method. The PD was estimated as the ratio of the dense area to the breast area based on the PMD. The DCNN approach was compared to a feature-based statistical learning approach. Gray level, texture and morphological features were extracted and a least absolute shrinkage and selection operator was used to combine the features into a feature-based PMD. With approval of the Institutional Review Board, we retrospectively collected a training set of 478 DMs and an independent test set of 183 DMs from patient files in our institution. Two experienced mammography quality standards act radiologists interactively segmented PD as the reference standard. Ten-fold cross-validation was used for model selection and evaluation with the training set. With cross-validation, DCNN obtained a Dice's coefficient (DC) of 0.79  ±  0.13 and Pearson's correlation (r) of 0.97, whereas feature-based learning obtained DC  =  0.72  ±  0.18 and r  =  0.85. For the independent test set, DCNN achieved DC  =  0.76  ±  0.09 and r  =  0.94, while feature-based learning achieved DC  =  0.62  ±  0.21 and r  =  0.75. Our DCNN approach was significantly better and more robust than the feature-based learning approach for automated PD estimation on DMs, demonstrating its potential use for automated density reporting as well as

  20. A dielectrophoretic method of discrimination between normal oral epithelium, and oral and oropharyngeal cancer in a clinical setting.

    Science.gov (United States)

    Graham, K A; Mulhall, H J; Labeed, F H; Lewis, M P; Hoettges, K F; Kalavrezos, N; McCaul, J; Liew, C; Porter, S; Fedele, S; Hughes, M P

    2015-08-07

    Despite the accessibility of the oral cavity to clinical examination, delays in diagnosis of oral and oropharyngeal carcinoma (OOPC) are observed in a large majority of patients, with negative impact on prognosis. Diagnostic aids might help detection and improve early diagnosis, but there remains little robust evidence supporting the use of any particular diagnostic technology at the moment. The aim of the present feasibility first-in-human study was to evaluate the preliminary diagnostic validity of a novel technology platform based on dielectrophoresis (DEP). DEP does not require labeling with antibodies or stains and it is an ideal tool for rapid analysis of cell properties. Cells from OOPC/dysplasia tissue and healthy oral mucosa were collected from 57 study participants via minimally-invasive brush biopsies and tested with a prototype DEP platform using median membrane midpoint frequency as main analysis parameter. Results indicate that the current DEP platform can discriminate between brush biopsy samples from cancerous and healthy oral tissue with a diagnostic sensitivity of 81.6% and a specificity of 81.0%. The present ex vivo results support the potential application of DEP testing for identification of OOPC. This result indicates that DEP has the potential to be developed into a low-cost, rapid platform as an assistive tool for the early identification of oral cancer in primary care; given the rapid, minimally-invasive and non-expensive nature of the test, dielectric characterization represents a promising platform for cost-effective early cancer detection.

  1. Comparison of pathways associated with hepatitis B- and C-infected hepatocellular carcinoma using pathway-based class discrimination method.

    Science.gov (United States)

    Lee, Sun Young; Song, Kwang Hoon; Koo, Imhoi; Lee, Kee-Ho; Suh, Kyung-Suk; Kim, Bu-Yeo

    2012-06-01

    Molecular signatures causing hepatocellular carcinoma (HCC) from chronic infection of hepatitis B virus (HBV) or hepatitis C virus (HCV) are not clearly known. Using microarray datasets composed of HCV-positive HCC or HBV-positive HCC, pathways that could discriminate tumor tissue from adjacent non-tumor liver tissue were selected by implementing nearest shrunken centroid algorithm. Cancer-related signaling pathways and lipid metabolism-related pathways were predominantly enriched in HCV-positive HCC, whereas functionally diverse pathways including immune-related pathways, cell cycle pathways, and RNA metabolism pathways were mainly enriched in HBV-positive HCC. In addition to differentially involved pathways, signaling pathways such as TGF-β, MAPK, and p53 pathways were commonly significant in both HCCs, suggesting the presence of common hepatocarcinogenesis process. The pathway clustering also verified segregation of pathways into the functional subgroups in both HCCs. This study indicates the functional distinction and similarity on the pathways implicated in the development of HCV- and/or HBV-positive HCC. Copyright © 2012 Elsevier Inc. All rights reserved.

  2. Efficiency of PCR-based methods in discriminating Bifidobacterium longum ssp. longum and Bifidobacterium longum ssp. infantis strains of human origin.

    Science.gov (United States)

    Srůtková, Dagmar; Spanova, Alena; Spano, Miroslav; Dráb, Vladimír; Schwarzer, Martin; Kozaková, Hana; Rittich, Bohuslav

    2011-10-01

    Bifidobacterium longum is considered to play an important role in health maintenance of the human gastrointestinal tract. Probiotic properties of bifidobacterial isolates are strictly strain-dependent and reliable methods for the identification and discrimination of this species at both subspecies and strain levels are thus required. Differentiation between B. longum ssp. longum and B. longum ssp. infantis is difficult due to high genomic similarities. In this study, four molecular-biological methods (species- and subspecies-specific PCRs, random amplified polymorphic DNA (RAPD) method using 5 primers, repetitive sequence-based (rep)-PCR with BOXA1R and (GTG)(5) primers and amplified ribosomal DNA restriction analysis (ARDRA)) and biochemical analysis, were compared for the classification of 30 B. longum strains (28 isolates and 2 collection strains) on subspecies level. Strains originally isolated from the faeces of breast-fed healthy infants (25) and healthy adults (3) showed a high degree of genetic homogeneity by PCR with subspecies-specific primers and rep-PCR. When analysed by RAPD, the strains formed many separate clusters without any potential for subspecies discrimination. These methods together with arabionose/melezitose fermentation analysis clearly differentiated only the collection strains into B. longum ssp. longum and B. longum ssp. infantis at the subspecies level. On the other hand, ARDRA analysis differentiated the strains into the B. longum/infantis subspecies using the cleavage analysis of genus-specific amplicon with just one enzyme, Sau3AI. According to our results the majority of the strains belong to the B. longum ssp. infantis (75%). Therefore we suggest ARDRA using Sau3AI restriction enzyme as the first method of choice for distinguishing between B. longum ssp. longum and B. longum ssp. infantis. Copyright © 2011 Elsevier B.V. All rights reserved.

  3. Comparison of hand-craft feature based SVM and CNN based deep learning framework for automatic polyp classification.

    Science.gov (United States)

    Younghak Shin; Balasingham, Ilangko

    2017-07-01

    Colonoscopy is a standard method for screening polyps by highly trained physicians. Miss-detected polyps in colonoscopy are potential risk factor for colorectal cancer. In this study, we investigate an automatic polyp classification framework. We aim to compare two different approaches named hand-craft feature method and convolutional neural network (CNN) based deep learning method. Combined shape and color features are used for hand craft feature extraction and support vector machine (SVM) method is adopted for classification. For CNN approach, three convolution and pooling based deep learning framework is used for classification purpose. The proposed framework is evaluated using three public polyp databases. From the experimental results, we have shown that the CNN based deep learning framework shows better classification performance than the hand-craft feature based methods. It achieves over 90% of classification accuracy, sensitivity, specificity and precision.

  4. More than a filter: Feature-based attention regulates the distribution of visual working memory resources.

    Science.gov (United States)

    Dube, Blaire; Emrich, Stephen M; Al-Aidroos, Naseem

    2017-10-01

    Across 2 experiments we revisited the filter account of how feature-based attention regulates visual working memory (VWM). Originally drawing from discrete-capacity ("slot") models, the filter account proposes that attention operates like the "bouncer in the brain," preventing distracting information from being encoded so that VWM resources are reserved for relevant information. Given recent challenges to the assumptions of discrete-capacity models, we investigated whether feature-based attention plays a broader role in regulating memory. Both experiments used partial report tasks in which participants memorized the colors of circle and square stimuli, and we provided a feature-based goal by manipulating the likelihood that 1 shape would be probed over the other across a range of probabilities. By decomposing participants' responses using mixture and variable-precision models, we estimated the contributions of guesses, nontarget responses, and imprecise memory representations to their errors. Consistent with the filter account, participants were less likely to guess when the probed memory item matched the feature-based goal. Interestingly, this effect varied with goal strength, even across high probabilities where goal-matching information should always be prioritized, demonstrating strategic control over filter strength. Beyond this effect of attention on which stimuli were encoded, we also observed effects on how they were encoded: Estimates of both memory precision and nontarget errors varied continuously with feature-based attention. The results offer support for an extension to the filter account, where feature-based attention dynamically regulates the distribution of resources within working memory so that the most relevant items are encoded with the greatest precision. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  5. An example of multidimensional analysis: Discriminant analysis

    International Nuclear Information System (INIS)

    Lutz, P.

    1990-01-01

    Among the approaches on the data multi-dimensional analysis, lectures on the discriminant analysis including theoretical and practical aspects are presented. The discrimination problem, the analysis steps and the discrimination categories are stressed. Examples on the descriptive historical analysis, the discrimination for decision making, the demonstration and separation of the top quark are given. In the linear discriminant analysis the following subjects are discussed: Huyghens theorem, projection, discriminant variable, geometrical interpretation, case for g=2, classification method, separation of the top events. Criteria allowing the obtention of relevant results are included [fr

  6. Two-step calibration method for multi-algorithm score-based face recognition systems by minimizing discrimination loss

    NARCIS (Netherlands)

    Susyanto, N.; Veldhuis, R.N.J.; Spreeuwers, L.J.; Klaassen, C.A.J.; Fierrez, J.; Li, S.Z.; Ross, A.; Veldhuis, R.; Alonso-Fernandez, F.; Bigun, J.

    2016-01-01

    We propose a new method for combining multi-algorithm score-based face recognition systems, which we call the two-step calibration method. Typically, algorithms for face recognition systems produce dependent scores. The two-step method is based on parametric copulas to handle this dependence. Its

  7. Feature-Based Methods for Landmine Detection with Ground Penetrating Radar

    Science.gov (United States)

    2012-09-27

    computer networks, Pattern Recognition Letters 24 (12) (2003) 1795–1803. [79] J-C. de Borda, Memoire sur les elections au scrutin, Histoire de l’AcadTmie...élections au scrutin,” Histoire de l’Académie Royale des Sciences, Paris, 1781. 3. Condorcet, M.J.A.N. de Caritat, Marquis de, Essai sur l’application de

  8. SU-E-J-237: Image Feature Based DRR and Portal Image Registration

    Energy Technology Data Exchange (ETDEWEB)

    Wang, X; Chang, J [NY Weill Cornell Medical Ctr, NY (United States)

    2014-06-01

    Purpose: Two-dimensional (2D) matching of the kV X-ray and digitally reconstructed radiography (DRR) images is an important setup technique for image-guided radiotherapy (IGRT). In our clinics, mutual information based methods are used for this purpose on commercial linear accelerators, but with often needs for manual corrections. This work proved the feasibility that feature based image transform can be used to register kV and DRR images. Methods: The scale invariant feature transform (SIFT) method was implemented to detect the matching image details (or key points) between the kV and DRR images. These key points represent high image intensity gradients, and thus the scale invariant features. Due to the poor image contrast from our kV image, direct application of the SIFT method yielded many detection errors. To assist the finding of key points, the center coordinates of the kV and DRR images were read from the DICOM header, and the two groups of key points with similar relative positions to their corresponding centers were paired up. Using these points, a rigid transform (with scaling, horizontal and vertical shifts) was estimated. We also artificially introduced vertical and horizontal shifts to test the accuracy of our registration method on anterior-posterior (AP) and lateral pelvic images. Results: The results provided a satisfactory overlay of the transformed kV onto the DRR image. The introduced vs. detected shifts were fit into a linear regression. In the AP image experiments, linear regression analysis showed a slope of 1.15 and 0.98 with an R2 of 0.89 and 0.99 for the horizontal and vertical shifts, respectively. The results are 1.2 and 1.3 with R2 of 0.72 and 0.82 for the lateral image shifts. Conclusion: This work provided an alternative technique for kV to DRR alignment. Further improvements in the estimation accuracy and image contrast tolerance are underway.

  9. Fighting discrimination.

    Science.gov (United States)

    Wientjens, Wim; Cairns, Douglas

    2012-10-01

    In the fight against discrimination, the IDF launched the first ever International Charter of Rights and Responsibilities of People with Diabetes in 2011: a balance between rights and duties to optimize health and quality of life, to enable as normal a life as possible and to reduce/eliminate the barriers which deny realization of full potential as members of society. It is extremely frustrating to suffer blanket bans and many examples exist, including insurance, driving licenses, getting a job, keeping a job and family affairs. In this article, an example is given of how pilots with insulin treated diabetes are allowed to fly by taking the responsibility of using special blood glucose monitoring protocols. At this time the systems in the countries allowing flying for pilots with insulin treated diabetes are applauded, particularly the USA for private flying, and Canada for commercial flying. Encouraging developments may be underway in the UK for commercial flying and, if this materializes, could be used as an example for other aviation authorities to help adopt similar protocols. However, new restrictions implemented by the new European Aviation Authority take existing privileges away for National Private Pilot Licence holders with insulin treated diabetes in the UK. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

  10. Rapid characterization of chemical markers for discrimination of Moutan Cortex and its processed products by direct injection-based mass spectrometry profiling and metabolomic method.

    Science.gov (United States)

    Li, Chao-Ran; Li, Meng-Ning; Yang, Hua; Li, Ping; Gao, Wen

    2018-06-01

    Processing of herbal medicines is a characteristic pharmaceutical technique in Traditional Chinese Medicine, which can reduce toxicity and side effect, improve the flavor and efficacy, and even change the pharmacological action entirely. It is significant and crucial to perform a method to find chemical markers for differentiating herbal medicines in different processed degrees. The aim of this study was to perform a rapid and reasonable method to discriminate Moutan Cortex and its processed products, and to reveal the characteristics of chemical components depend on chemical markers. Thirty batches of Moutan Cortex and its processed products, including 11 batches of Raw Moutan Cortex (RMC), 9 batches of Moutan Cortex Tostus (MCT) and 10 batches of Moutan Cortex Carbonisatus (MCC), were directly injected in electrospray ionization quadrupole time-of-flight mass spectrometry (ESI-QTOF MS) for rapid analysis in positive and negative mode. Without chromatographic separation, each run was completed within 3 min. The raw MS data were automatically extracted by background deduction and molecular feature (MF) extraction algorithm. In negative mode, a total of 452 MFs were obtained and then pretreated by data filtration and differential analysis. After that, the filtered 85 MFs were treated by principal component analysis (PCA) to reduce the dimensions. Subsequently, a partial least squares discrimination analysis (PLS-DA) model was constructed for differentiation and chemical markers detection of Moutan Cortex in different processed degrees. The positive mode data were treated as same as those in negative mode. RMC, MCT and MCC were successfully classified. Moreover, 14 and 3 chemical markers from negative and positive mode respectively, were screened by the combination of their relative peak areas and the parameter variable importance in the projection (VIP) values in PLS-DA model. The content changes of these chemical markers were employed in order to illustrate

  11. Feature-based attention and conflict monitoring in criminal offenders: interactive relations of psychopathy with anxiety and externalizing.

    Science.gov (United States)

    Zeier, Joshua D; Newman, Joseph P

    2013-08-01

    As predicted by the response modulation model, psychopathic offenders are insensitive to potentially important inhibitory information when it is peripheral to their primary focus of attention. To date, the clearest tests of this hypothesis have manipulated spatial attention to cue the location of goal-relevant versus inhibitory information. However, the theory predicts a more general abnormality in selective attention. In the current study, male prisoners performed a conflict-monitoring task, which included a feature-based manipulation (i.e., color) that biased selective attention toward goal-relevant stimuli and away from inhibitory distracters on some trials but not others. Paralleling results for spatial cuing, feature-based cuing resulted in less distracter interference, particularly for participants with primary psychopathy (i.e., low anxiety). This study also investigated the moderating effect of externalizing on psychopathy. Participants high in psychopathy but low in externalizing performed similarly to primary psychopathic individuals. These results demonstrate that the abnormal selective attention associated with primary psychopathy is not limited to spatial attention but, instead, applies to diverse methods for establishing attentional focus. Furthermore, they demonstrate a novel method of investigating psychopathic subtypes using continuous analyses. PsycINFO Database Record (c) 2013 APA, all rights reserved.

  12. The Use of a Parametric Feature Based CAD System to Teach Introductory Engineering Graphics.

    Science.gov (United States)

    Howell, Steven K.

    1995-01-01

    Describes the use of a parametric-feature-based computer-aided design (CAD) System, AutoCAD Designer, in teaching concepts of three dimensional geometrical modeling and design. Allows engineering graphics to go beyond the role of documentation and communication and allows an engineer to actually build a virtual prototype of a design idea and…

  13. Feature-based attention in early vision for the modulation of figure–ground segregation

    Directory of Open Access Journals (Sweden)

    Nobuhiko eWagatsuma

    2013-03-01

    Full Text Available We investigated psychophysically whether feature-based attention modulates the perception of figure–ground (F–G segregation and, based on the results, we investigated computationally the neural mechanisms underlying attention modulation. In the psychophysical experiments, the attention of participants was drawn to a specific motion direction and they were then asked to judge the side of figure in an ambiguous figure with surfaces consisting of distinct motion directions. The results of these experiments showed that the surface consisting of the attended direction of motion was more frequently observed as figure, with a degree comparable to that of spatial attention (Wagatsuma, Shimizu, and Sakai, 2008. These experiments also showed that perception was dependent on the distribution of feature contrast, specifically the motion direction differences. These results led us to hypothesize that feature-based attention functions in a framework similar to that of spatial attention. We proposed a V1–V2 model in which feature-based attention modulates the contrast of low-level feature in V1, and this modulation of contrast changes directly the surround modulation of border-ownership-selective cells in V2; thus, perception of F–G is biased. The model exhibited good agreement with human perception in the magnitude of attention modulation and its invariance among stimuli. These results indicate that early-level features that are modified by feature-based attention alter subsequent processing along afferent pathway, and that such modification could even change the perception of object.

  14. Feature-Based Attention in Early Vision for the Modulation of Figure–Ground Segregation

    Science.gov (United States)

    Wagatsuma, Nobuhiko; Oki, Megumi; Sakai, Ko

    2013-01-01

    We investigated psychophysically whether feature-based attention modulates the perception of figure–ground (F–G) segregation and, based on the results, we investigated computationally the neural mechanisms underlying attention modulation. In the psychophysical experiments, the attention of participants was drawn to a specific motion direction and they were then asked to judge the side of figure in an ambiguous figure with surfaces consisting of distinct motion directions. The results of these experiments showed that the surface consisting of the attended direction of motion was more frequently observed as figure, with a degree comparable to that of spatial attention (Wagatsuma et al., 2008). These experiments also showed that perception was dependent on the distribution of feature contrast, specifically the motion direction differences. These results led us to hypothesize that feature-based attention functions in a framework similar to that of spatial attention. We proposed a V1–V2 model in which feature-based attention modulates the contrast of low-level feature in V1, and this modulation of contrast changes directly the surround modulation of border-ownership-selective cells in V2; thus, perception of F–G is biased. The model exhibited good agreement with human perception in the magnitude of attention modulation and its invariance among stimuli. These results indicate that early-level features that are modified by feature-based attention alter subsequent processing along afferent pathway, and that such modification could even change the perception of object. PMID:23515841

  15. Feature-based attention in early vision for the modulation of figure-ground segregation.

    Science.gov (United States)

    Wagatsuma, Nobuhiko; Oki, Megumi; Sakai, Ko

    2013-01-01

    We investigated psychophysically whether feature-based attention modulates the perception of figure-ground (F-G) segregation and, based on the results, we investigated computationally the neural mechanisms underlying attention modulation. In the psychophysical experiments, the attention of participants was drawn to a specific motion direction and they were then asked to judge the side of figure in an ambiguous figure with surfaces consisting of distinct motion directions. The results of these experiments showed that the surface consisting of the attended direction of motion was more frequently observed as figure, with a degree comparable to that of spatial attention (Wagatsuma et al., 2008). These experiments also showed that perception was dependent on the distribution of feature contrast, specifically the motion direction differences. These results led us to hypothesize that feature-based attention functions in a framework similar to that of spatial attention. We proposed a V1-V2 model in which feature-based attention modulates the contrast of low-level feature in V1, and this modulation of contrast changes directly the surround modulation of border-ownership-selective cells in V2; thus, perception of F-G is biased. The model exhibited good agreement with human perception in the magnitude of attention modulation and its invariance among stimuli. These results indicate that early-level features that are modified by feature-based attention alter subsequent processing along afferent pathway, and that such modification could even change the perception of object.

  16. Feature-Based versus Category-Based Induction with Uncertain Categories

    Science.gov (United States)

    Griffiths, Oren; Hayes, Brett K.; Newell, Ben R.

    2012-01-01

    Previous research has suggested that when feature inferences have to be made about an instance whose category membership is uncertain, feature-based inductive reasoning is used to the exclusion of category-based induction. These results contrast with the observation that people can and do use category-based induction when category membership is…

  17. Automatic brain MR image denoising based on texture feature-based artificial neural networks.

    Science.gov (United States)

    Chang, Yu-Ning; Chang, Herng-Hua

    2015-01-01

    Noise is one of the main sources of quality deterioration not only for visual inspection but also in computerized processing in brain magnetic resonance (MR) image analysis such as tissue classification, segmentation and registration. Accordingly, noise removal in brain MR images is important for a wide variety of subsequent processing applications. However, most existing denoising algorithms require laborious tuning of parameters that are often sensitive to specific image features and textures. Automation of these parameters through artificial intelligence techniques will be highly beneficial. In the present study, an artificial neural network associated with image texture feature analysis is proposed to establish a predictable parameter model and automate the denoising procedure. In the proposed approach, a total of 83 image attributes were extracted based on four categories: 1) Basic image statistics. 2) Gray-level co-occurrence matrix (GLCM). 3) Gray-level run-length matrix (GLRLM) and 4) Tamura texture features. To obtain the ranking of discrimination in these texture features, a paired-samples t-test was applied to each individual image feature computed in every image. Subsequently, the sequential forward selection (SFS) method was used to select the best texture features according to the ranking of discrimination. The selected optimal features were further incorporated into a back propagation neural network to establish a predictable parameter model. A wide variety of MR images with various scenarios were adopted to evaluate the performance of the proposed framework. Experimental results indicated that this new automation system accurately predicted the bilateral filtering parameters and effectively removed the noise in a number of MR images. Comparing to the manually tuned filtering process, our approach not only produced better denoised results but also saved significant processing time.

  18. A method for recognition of coexisting environmental sound sources based on the Fisher’s linear discriminant classifier

    DEFF Research Database (Denmark)

    Creixell Mediante, Ester; Haddad, Karim; Song, Wookeun

    2015-01-01

    A method for sound recognition of coexisting environmental noise sources by applying pattern recognition techniques is developed. The investigated technique could benefit several areas of application, such as noise impact assessment, acoustic pollution mitigation and soundscape characterization...

  19. Discrimination and Anti-discrimination in Denmark

    DEFF Research Database (Denmark)

    Olsen, Tore Vincents

    The purpose of this report is to describe and analyse Danish anti-discrimination legislation and the debate about discrimination in Denmark in order to identify present and future legal challenges. The main focus is the implementation of the EU anti-discrimination directives in Danish law...

  20. Methods for discriminating gas-liquid two phase flow patterns based on gray neural networks and SVM

    International Nuclear Information System (INIS)

    Li Jingjing; Zhou Tao; Duan Jun; Zhang Lei

    2013-01-01

    Background: The flow patterns of two phase flow will directly influence the heat transfer and mass transfer of the flow. Purpose: By wavelet analysis of the pressure drop experimental data, the wavelet coefficients of different frequency can be obtained. Methods: Get the wavelet energy and then train them in the model of BP neural network to distinguish the flow patterns. Introduced the implant gray neural networks model and use it for the two phase flow for the first time. At the same time, set up the method of training the pressure data and wavelet energy data in the support vector machine. Results: Through treatment of the gray layer, the result of the neural network is more accuracy. It can obviously reduce the effect of data marginalization. The accuracy of the pressure drop Lib-SVM method is 95.2%. Conclusions: The results show that these three methods can make a distinction among the different flow patterns and the Lib-SVM method gets the best result, then the gray neural networks, and at last the BP neural networks. (authors)

  1. Discrimination of Medicine Radix Astragali from Different Geographic Origins Using Multiple Spectroscopies Combined with Data Fusion Methods

    Science.gov (United States)

    Wang, Hai-Yan; Song, Chao; Sha, Min; Liu, Jun; Li, Li-Ping; Zhang, Zheng-Yong

    2018-05-01

    Raman spectra and ultraviolet-visible absorption spectra of four different geographic origins of Radix Astragali were collected. These data were analyzed using kernel principal component analysis combined with sparse representation classification. The results showed that the recognition rate reached 70.44% using Raman spectra for data input and 90.34% using ultraviolet-visible absorption spectra for data input. A new fusion method based on Raman combined with ultraviolet-visible data was investigated and the recognition rate was increased to 96.43%. The experimental results suggested that the proposed data fusion method effectively improved the utilization rate of the original data.

  2. Racial/Ethnic Workplace Discrimination

    Science.gov (United States)

    Chavez, Laura J.; Ornelas, India J.; Lyles, Courtney R.; Williams, Emily C.

    2014-01-01

    Background Experiences of discrimination are associated with tobacco and alcohol use, and work is a common setting where individuals experience racial/ethnic discrimination. Few studies have evaluated the association between workplace discrimination and these behaviors, and none have described associations across race/ethnicity. Purpose To examine the association between workplace discrimination and tobacco and alcohol use in a large, multistate sample of U.S. adult respondents to the Behavioral Risk Factor Surveillance System survey Reactions to Race Module (2004–2010). Methods Multivariable logistic regression analyses evaluated cross-sectional associations between self-reported workplace discrimination and tobacco (current and daily smoking) and alcohol use (any and heavy use, and binge drinking) among all participants and stratified by race/ethnicity, adjusting for relevant covariates. Data were analyzed in 2013. Results Among respondents, 70,080 completed the workplace discrimination measure. Discrimination was more common among black non-Hispanic (21%), Hispanic (12%), and other race respondents (11%) than white non-Hispanics (4%) (pdiscrimination was associated with current smoking (risk ratio [RR]=1.32, 95% CI=1.19, 1.47), daily smoking (RR=1.41, 95% CI=1.24, 1.61), and heavy drinking (RR=1.11, 95% CI=1.01, 1.22), but not binge or any drinking. Among Hispanics, workplace discrimination was associated with increased heavy and binge drinking, but not any alcohol use or smoking. Workplace discrimination among black non-Hispanics and white Non-Hispanics was associated with increased current and daily smoking, but not alcohol outcomes. Conclusions Workplace discrimination is common, associated with smoking and alcohol use, and merits further policy attention given the impact of these behaviors on morbidity and mortality. PMID:25441232

  3. The determination of biurea: A novel method to discriminate between nitrofurazone and azodicarbonamide use in food products

    International Nuclear Information System (INIS)

    Mulder, P.P.J.; Beumer, B.; Rhijn, J.A. van

    2007-01-01

    Recently doubts have arisen on the usefulness of semicarbazide as marker residue for the illegal use of the antibiotic nitrofurazone (NFZ) in aquaculture and poultry production. Most notably azodicarbonamide (ADC) has been implicated as an alternative source of semicarbazide. ADC is used in some countries as a dough conditioner at concentrations up to 45 mg kg -1 . The use of ADC-treated flour or dough in coated or breaded food products may generate false non-compliant results in the analytical method for nitrofurazone metabolites, which is currently in use. During the dough preparation process ADC is largely reduced to biurea, which can be considered as an appropriate marker residue of ADC. Thus far no methods have been published for the determination of biurea in food commodities. Due to its polar nature it is very difficult to generate sufficient retention on conventional C 18 HPLC columns. With a TSK amide HILIC type column good retention was obtained. A straightforward extraction-dilution protocol was developed. Using a mixture of dimethyl formamide and water biurea was nearly quantitatively extracted from a variety of fresh, coated and processed products. Mass spectrometric detection was performed with positive electrospray ionisation. The sensitivity and selectivity of the mass spectrometer for biurea was very good, allowing detection at concentrations as low as 10 μg kg -1 . However, in some extracts severe ion suppression effects was observed. To overcome the implications of ion suppression on the quantitative performance of the method an isotopically-labelled biurea internal standard was synthesized and incorporated in the method. The method developed can be used effectively in nitrofurazone analysis to eliminate the risk of false non-compliant results due to the presence of azodicarbonamide-treated components in the food product

  4. Magnesium interference and different efficiencies of diastereoisomeric cluster formation in phenylalanine enantiomeric discrimination by the kinetic method

    Czech Academy of Sciences Publication Activity Database

    Ranc, V.; Havlíček, Vladimír; Bednář, P.; Lemr, Karel

    2009-01-01

    Roč. 280, 1-3 (2009), s. 213-217 ISSN 1387-3806 R&D Projects: GA MŠk LC07017; GA ČR GA203/07/0765 Grant - others:XE(XE) EC: MKTD-CT-2004-014407 Institutional research plan: CEZ:AV0Z50200510 Keywords : enantiomeric dicrimination * kinetic method * mass spectrometry Subject RIV: CB - Analytical Chemistry, Separation Impact factor: 2.117, year: 2009

  5. Innovations in individual feature history management - The significance of feature-based temporal model

    Science.gov (United States)

    Choi, J.; Seong, J.C.; Kim, B.; Usery, E.L.

    2008-01-01

    A feature relies on three dimensions (space, theme, and time) for its representation. Even though spatiotemporal models have been proposed, they have principally focused on the spatial changes of a feature. In this paper, a feature-based temporal model is proposed to represent the changes of both space and theme independently. The proposed model modifies the ISO's temporal schema and adds new explicit temporal relationship structure that stores temporal topological relationship with the ISO's temporal primitives of a feature in order to keep track feature history. The explicit temporal relationship can enhance query performance on feature history by removing topological comparison during query process. Further, a prototype system has been developed to test a proposed feature-based temporal model by querying land parcel history in Athens, Georgia. The result of temporal query on individual feature history shows the efficiency of the explicit temporal relationship structure. ?? Springer Science+Business Media, LLC 2007.

  6. Feature-based and object-based attention orientation during short-term memory maintenance.

    Science.gov (United States)

    Ku, Yixuan

    2015-12-01

    Top-down attention biases the short-term memory (STM) processing at multiple stages. Orienting attention during the maintenance period of STM by a retrospective cue (retro-cue) strengthens the representation of the cued item and improves the subsequent STM performance. In a recent article, Backer et al. (Backer KC, Binns MA, Alain C. J Neurosci 35: 1307-1318, 2015) extended these findings from the visual to the auditory domain and combined electroencephalography to dissociate neural mechanisms underlying feature-based and object-based attention orientation. Both event-related potentials and neural oscillations explained the behavioral benefits of retro-cues and favored the theory that feature-based and object-based attention orientation were independent. Copyright © 2015 the American Physiological Society.

  7. A discriminative method for family-based protein remote homology detection that combines inductive logic programming and propositional models.

    Science.gov (United States)

    Bernardes, Juliana S; Carbone, Alessandra; Zaverucha, Gerson

    2011-03-23

    Remote homology detection is a hard computational problem. Most approaches have trained computational models by using either full protein sequences or multiple sequence alignments (MSA), including all positions. However, when we deal with proteins in the "twilight zone" we can observe that only some segments of sequences (motifs) are conserved. We introduce a novel logical representation that allows us to represent physico-chemical properties of sequences, conserved amino acid positions and conserved physico-chemical positions in the MSA. From this, Inductive Logic Programming (ILP) finds the most frequent patterns (motifs) and uses them to train propositional models, such as decision trees and support vector machines (SVM). We use the SCOP database to perform our experiments by evaluating protein recognition within the same superfamily. Our results show that our methodology when using SVM performs significantly better than some of the state of the art methods, and comparable to other. However, our method provides a comprehensible set of logical rules that can help to understand what determines a protein function. The strategy of selecting only the most frequent patterns is effective for the remote homology detection. This is possible through a suitable first-order logical representation of homologous properties, and through a set of frequent patterns, found by an ILP system, that summarizes essential features of protein functions.

  8. A novel and discriminative method of in vitro disintegration time for preparation and optimization of taste-masked orally disintegrating tablets of carbinoxamine maleate.

    Science.gov (United States)

    Liu, Yali; Li, Peng; Qian, Rong; Sun, Tianyu; Fang, Fangzhi; Wang, Zonghua; Ke, Xue; Xu, Bohui

    2018-08-01

    The primary objective of this study was to mask bitter taste and decrease the disintegration time of carbinoxamine maleate (CAM) orally disintegrating tablets (ODTs). In order to screen the prescription of ODTs, a novel modified in vitro disintegration method (MIVDM) was developed to measure the in vitro disintegration time. In this method, different concentrations of ethanol served as disintegration medium in order to delay the in vitro water absorption and disintegration process of tablets. The MIVDM demonstrated good in vitro and in vivo correlation and proved more precise and discriminative than other reported methods. In this research, ion exchange resins (IERs) were used to mask bitter taste for improving mouthfeel. The drug-resin ratio and reaction temperature were investigated to obtain the optimum carbinoxamine resin complexes (CRCs). The characterization of CRCs revealed an amorphous state. ODTs were prepared by direct compression. Superdisintegrants and diluents of ODTs were screened first. Further optimization was carried out by using Box-Behnken design. The effect of (X 1 ) mannitol/microcrystalline cellulose ratio, (X 2 ) the amount of low-substituted hydroxypropylcellulose and (X 3 ) the hardness was investigated for achieving the lowest (Y) in vitro disintegration time. Technological characterization, wetting time, water absorption ratio, and roughness degree were evaluated. The CRCs and ODTs proved successful taste-masking efficiency. The end product improved patients' compliance. The developed MIVDM was practical for commercial use.

  9. Experimental Method of Temperature and Strain Discrimination in Polymer Composite Material by Embedded Fiber-Optic Sensors Based on Femtosecond-Inscribed FBGs

    Directory of Open Access Journals (Sweden)

    Victor V. Shishkin

    2016-01-01

    Full Text Available Experimental method of temperature and strain discrimination with fiber Bragg gratings (FBGs sensors embedded in carbon fiber-reinforced plastic is proposed. The method is based on two-fiber technique, when two FBGs inscribed in different fibers with different sensitivities to strain and/or temperature are placed close to each other and act as a single sensing element. The nonlinear polynomial approximation of Bragg wavelength shift as a function of temperature and strain is presented for this method. The FBGs were inscribed with femtosecond laser by point-by-point inscription technique through polymer cladding of the fiber. The comparison of linear and nonlinear approximation accuracies for array of embedded sensors is performed. It is shown that the use of nonlinear approximation gives 1.5–2 times better accuracy. The obtained accuracies of temperature and strain measurements are 2.6–3.8°C and 50–83 με in temperature and strain range of 30–120°C and 0–400 με, respectively.

  10. Discrimination of edible oils and fats by combination of multivariate pattern recognition and FT-IR spectroscopy: A comparative study between different modeling methods

    Science.gov (United States)

    Javidnia, Katayoun; Parish, Maryam; Karimi, Sadegh; Hemmateenejad, Bahram

    2013-03-01

    By using FT-IR spectroscopy, many researchers from different disciplines enrich the experimental complexity of their research for obtaining more precise information. Moreover chemometrics techniques have boosted the use of IR instruments. In the present study we aimed to emphasize on the power of FT-IR spectroscopy for discrimination between different oil samples (especially fat from vegetable oils). Also our data were used to compare the performance of different classification methods. FT-IR transmittance spectra of oil samples (Corn, Colona, Sunflower, Soya, Olive, and Butter) were measured in the wave-number interval of 450-4000 cm-1. Classification analysis was performed utilizing PLS-DA, interval PLS-DA, extended canonical variate analysis (ECVA) and interval ECVA methods. The effect of data preprocessing by extended multiplicative signal correction was investigated. Whilst all employed method could distinguish butter from vegetable oils, iECVA resulted in the best performances for calibration and external test set with 100% sensitivity and specificity.

  11. Extracting intrinsic functional networks with feature-based group independent component analysis.

    Science.gov (United States)

    Calhoun, Vince D; Allen, Elena

    2013-04-01

    There is increasing use of functional imaging data to understand the macro-connectome of the human brain. Of particular interest is the structure and function of intrinsic networks (regions exhibiting temporally coherent activity both at rest and while a task is being performed), which account for a significant portion of the variance in functional MRI data. While networks are typically estimated based on the temporal similarity between regions (based on temporal correlation, clustering methods, or independent component analysis [ICA]), some recent work has suggested that these intrinsic networks can be extracted from the inter-subject covariation among highly distilled features, such as amplitude maps reflecting regions modulated by a task or even coordinates extracted from large meta analytic studies. In this paper our goal was to explicitly compare the networks obtained from a first-level ICA (ICA on the spatio-temporal functional magnetic resonance imaging (fMRI) data) to those from a second-level ICA (i.e., ICA on computed features rather than on the first-level fMRI data). Convergent results from simulations, task-fMRI data, and rest-fMRI data show that the second-level analysis is slightly noisier than the first-level analysis but yields strikingly similar patterns of intrinsic networks (spatial correlations as high as 0.85 for task data and 0.65 for rest data, well above the empirical null) and also preserves the relationship of these networks with other variables such as age (for example, default mode network regions tended to show decreased low frequency power for first-level analyses and decreased loading parameters for second-level analyses). In addition, the best-estimated second-level results are those which are the most strongly reflected in the input feature. In summary, the use of feature-based ICA appears to be a valid tool for extracting intrinsic networks. We believe it will become a useful and important approach in the study of the macro

  12. Quality Evaluation in Wireless Imaging Using Feature-Based Objective Metrics

    OpenAIRE

    Engelke, Ulrich; Zepernick, Hans-Jürgen

    2007-01-01

    This paper addresses the evaluation of image quality in the context of wireless systems using feature-based objective metrics. The considered metrics comprise of a weighted combination of feature values that are used to quantify the extend by which the related artifacts are present in a processed image. In view of imaging applications in mobile radio and wireless communication systems, reduced-reference objective quality metrics are investigated for quantifying user-perceived quality. The exa...

  13. Feature-Based Attention in Early Vision for the Modulation of Figure?Ground Segregation

    OpenAIRE

    Wagatsuma, Nobuhiko; Oki, Megumi; Sakai, Ko

    2013-01-01

    We investigated psychophysically whether feature-based attention modulates the perception of figure–ground (F–G) segregation and, based on the results, we investigated computationally the neural mechanisms underlying attention modulation. In the psychophysical experiments, the attention of participants was drawn to a specific motion direction and they were then asked to judge the side of figure in an ambiguous figure with surfaces consisting of distinct motion directions. The results of these...

  14. Feature-based attention in early vision for the modulation of figure–ground segregation

    OpenAIRE

    Nobuhiko eWagatsuma; Nobuhiko eWagatsuma; Megumi eOki; Ko eSakai

    2013-01-01

    We investigated psychophysically whether feature-based attention modulates the perception of figure–ground (F–G) segregation and, based on the results, we investigated computationally the neural mechanisms underlying attention modulation. In the psychophysical experiments, the attention of participants was drawn to a specific motion direction and they were then asked to judge the side of figure in an ambiguous figure with surfaces consisting of distinct motion directions. The results of these...

  15. A product feature-based user-centric product search model

    OpenAIRE

    Ben Jabeur, Lamjed; Soulier, Laure; Tamine, Lynda; Mousset, Paul

    2016-01-01

    During the online shopping process, users would search for interesting products and quickly access those that fit with their needs among a long tail of similar or closely related products. Our contribution addresses head queries that are frequently submitted on e-commerce Web sites. Head queries usually target featured products with several variations, accessories, and complementary products. We present in this paper a product feature-based user-centric model for product search involving in a...

  16. Shape based automated detection of pulmonary nodules with surface feature based false positive reduction

    International Nuclear Information System (INIS)

    Nomura, Y.; Itoh, H.; Masutani, Y.; Ohtomo, K.; Maeda, E.; Yoshikawa, T.; Hayashi, N.

    2007-01-01

    We proposed a shape based automated detection of pulmonary nodules with surface feature based false positive (FP) reduction. In the proposed system, the FP existing in internal of vessel bifurcation is removed using extracted surface of vessels and nodules. From the validation with 16 chest CT scans, we find that the proposed CAD system achieves 18.7 FPs/scan at 90% sensitivity, and 7.8 FPs/scan at 80% sensitivity. (orig.)

  17. Validation of a new background discrimination method for the TACTIC TeV γ-ray telescope with Markarian 421 data

    International Nuclear Information System (INIS)

    Sharma, Mradul; Nayak, J.; Koul, M.K.; Bose, S.; Mitra, Abhas; Dhar, V.K.; Tickoo, A.K.; Koul, R.

    2015-01-01

    This paper describes the validation of a new background discrimination method based on Random Forest technique by re-analysing the Markarian 421 (Mrk 421) observations performed by the TACTIC (TeV Atmospheric Cherenkov Telescope with Imaging Camera) γ-ray telescope. The Random Forest technique is a flexible multivariate method which combines Bagging and Random Split Selection to construct a large collection of decision trees and then combines them to construct a common classifier. Markarian 421 in a high state was observed by TACTIC during December 07, 2005–April 30, 2006 for 202 h. Previous analysis of this data led to a detection of flaring activity from the source at Energy >1TeV. Within this data set, a spell of 97 h revealed strong detection of a γ-ray signal with daily flux of >1 Crab unit on several days. Here we re-analyze this spell as well as the data from the entire observation period with the Random Forest method. Application of this method led to an improvement in the signal detection strength by ∼26% along with a ∼18% increase in detected γ rays compared to the conventional Dynamic Supercuts method. The resultant differential spectrum obtained is represented by a power law with an exponential cut off Γ=−2.51±0.10 and E 0 =4.71±2.20TeV. Such a spectrum is consistent with previously reported results and justifies the use of Random Forest method for analyzing data from atmospheric Cherenkov telescopes

  18. Validation of a new background discrimination method for the TACTIC TeV γ-ray telescope with Markarian 421 data

    Energy Technology Data Exchange (ETDEWEB)

    Sharma, Mradul, E-mail: mradul@barc.gov.in [Astrophysical Sciences Division, Bhabha Atomic Research Centre, Mumbai (India); Nayak, J. [The Bayesian and Interdisciplinary Research Unit, Indian Statistical Institute, Kolkata (India); Koul, M.K. [Astrophysical Sciences Division, Bhabha Atomic Research Centre, Mumbai (India); Bose, S. [The Bayesian and Interdisciplinary Research Unit, Indian Statistical Institute, Kolkata (India); Mitra, Abhas; Dhar, V.K.; Tickoo, A.K.; Koul, R. [Astrophysical Sciences Division, Bhabha Atomic Research Centre, Mumbai (India)

    2015-01-11

    This paper describes the validation of a new background discrimination method based on Random Forest technique by re-analysing the Markarian 421 (Mrk 421) observations performed by the TACTIC (TeV Atmospheric Cherenkov Telescope with Imaging Camera) γ-ray telescope. The Random Forest technique is a flexible multivariate method which combines Bagging and Random Split Selection to construct a large collection of decision trees and then combines them to construct a common classifier. Markarian 421 in a high state was observed by TACTIC during December 07, 2005–April 30, 2006 for 202 h. Previous analysis of this data led to a detection of flaring activity from the source at Energy >1TeV. Within this data set, a spell of 97 h revealed strong detection of a γ-ray signal with daily flux of >1 Crab unit on several days. Here we re-analyze this spell as well as the data from the entire observation period with the Random Forest method. Application of this method led to an improvement in the signal detection strength by ∼26% along with a ∼18% increase in detected γ rays compared to the conventional Dynamic Supercuts method. The resultant differential spectrum obtained is represented by a power law with an exponential cut off Γ=−2.51±0.10 and E{sub 0}=4.71±2.20TeV. Such a spectrum is consistent with previously reported results and justifies the use of Random Forest method for analyzing data from atmospheric Cherenkov telescopes.

  19. Similar effects of feature-based attention on motion perception and pursuit eye movements at different levels of awareness

    OpenAIRE

    Spering, Miriam; Carrasco, Marisa

    2012-01-01

    Feature-based attention enhances visual processing and improves perception, even for visual features that we are not aware of. Does feature-based attention also modulate motor behavior in response to visual information that does or does not reach awareness? Here we compare the effect of feature-based attention on motion perception and smooth pursuit eye movements in response to moving dichoptic plaids–stimuli composed of two orthogonally-drifting gratings, presented separately to each eye–in ...

  20. The fate of task-irrelevant visual motion: perceptual load versus feature-based attention.

    Science.gov (United States)

    Taya, Shuichiro; Adams, Wendy J; Graf, Erich W; Lavie, Nilli

    2009-11-18

    We tested contrasting predictions derived from perceptual load theory and from recent feature-based selection accounts. Observers viewed moving, colored stimuli and performed low or high load tasks associated with one stimulus feature, either color or motion. The resultant motion aftereffect (MAE) was used to evaluate attentional allocation. We found that task-irrelevant visual features received less attention than co-localized task-relevant features of the same objects. Moreover, when color and motion features were co-localized yet perceived to belong to two distinct surfaces, feature-based selection was further increased at the expense of object-based co-selection. Load theory predicts that the MAE for task-irrelevant motion would be reduced with a higher load color task. However, this was not seen for co-localized features; perceptual load only modulated the MAE for task-irrelevant motion when this was spatially separated from the attended color location. Our results suggest that perceptual load effects are mediated by spatial selection and do not generalize to the feature domain. Feature-based selection operates to suppress processing of task-irrelevant, co-localized features, irrespective of perceptual load.

  1. Different cortical mechanisms for spatial vs. feature-based attentional selection in visual working memory

    Directory of Open Access Journals (Sweden)

    Anna Heuer

    2016-08-01

    Full Text Available The limited capacity of visual working memory necessitates attentional mechanisms that selectively update and maintain only the most task-relevant content. Psychophysical experiments have shown that the retroactive selection of memory content can be based on visual properties such as location or shape, but the neural basis for such differential selection is unknown. For example, it is not known if there are different cortical modules specialized for spatial versus feature-based mnemonic attention, in the same way that has been demonstrated for attention to perceptual input. Here, we used transcranial magnetic stimulation (TMS to identify areas in human parietal and occipital cortex involved in the selection of objects from memory based on cues to their location (spatial information or their shape (featural information. We found that TMS over the supramarginal gyrus (SMG selectively facilitated spatial selection, whereas TMS over the lateral occipital cortex selectively enhanced feature-based selection for remembered objects in the contralateral visual field. Thus, different cortical regions are responsible for spatial vs. feature-based selection of working memory representations. Since the same regions are involved in attention to external events, these new findings indicate overlapping mechanisms for attentional control over perceptual input and mnemonic representations.

  2. Pulse duration discriminator

    International Nuclear Information System (INIS)

    Kosakovskij, L.F.

    1980-01-01

    Basic circuits of a discriminator for discrimination of pulses with the duration greater than the preset one, and of a multifunctional discriminator allowing to discriminate pulses with the duration greater (tsub(p)>tsub(s)) and lesser (tsub(p) tsub(s) and with the duration tsub(p) [ru

  3. A feature-based approach to modeling protein-DNA interactions.

    Directory of Open Access Journals (Sweden)

    Eilon Sharon

    Full Text Available Transcription factor (TF binding to its DNA target site is a fundamental regulatory interaction. The most common model used to represent TF binding specificities is a position specific scoring matrix (PSSM, which assumes independence between binding positions. However, in many cases, this simplifying assumption does not hold. Here, we present feature motif models (FMMs, a novel probabilistic method for modeling TF-DNA interactions, based on log-linear models. Our approach uses sequence features to represent TF binding specificities, where each feature may span multiple positions. We develop the mathematical formulation of our model and devise an algorithm for learning its structural features from binding site data. We also developed a discriminative motif finder, which discovers de novo FMMs that are enriched in target sets of sequences compared to background sets. We evaluate our approach on synthetic data and on the widely used TF chromatin immunoprecipitation (ChIP dataset of Harbison et al. We then apply our algorithm to high-throughput TF ChIP data from mouse and human, reveal sequence features that are present in the binding specificities of mouse and human TFs, and show that FMMs explain TF binding significantly better than PSSMs. Our FMM learning and motif finder software are available at http://genie.weizmann.ac.il/.

  4. A method to discriminate between closely related bovine major histocompatibility complex class I alleles by combining established PCR-SSP assays with RFLPs.

    Science.gov (United States)

    Svitek, N; Nzau, B; Steinaa, L; Nene, V

    2015-04-01

    We have developed a polymerase chain reaction-sequence-specific primers-restriction fragment length polymorphism (PCR-SSP-RFLP) method to rapidly differentiate between the A18 and A18 variant (v) BoLA haplotypes and between A14 and A15/A15v BoLA haplotypes in Holstein/Friesian cattle. We used published SSP to PCR amplify BoLA alleles expressed in animals of known haplotype and exposed the amplicons to the restriction enzyme PvuII that was predicted to cut at a unique site in the middle of BoLA-6*01302 (A18v) and BoLA-1*00901 (A15) but not in BoLA-6*01301 (A18) or BoLA-1*02301 (A14) alleles. Whereas the method does not discriminate between the A15 and A15v haplotypes, as the BoLA-1*00902 allele associated with A15v also contains a PvuII site, we are interested in cattle of A18 and A14 haplotype for vaccine related studies. Our results also indicated that the BoLA-6*01302 (A18v) allele is much more abundant than BoLA-6*01301 (A18) in the cattle that we sampled. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  5. Discrimination of chromosome by autoradiography

    International Nuclear Information System (INIS)

    Masubuchi, Masanori

    1975-01-01

    This paper describes discrimination of chromosome by autoradiography. In this method, the difference in DNA synthetic phase between each chromosome was used as a standard, and the used chromosome was in metaphase, as morphological characteristics were markedly in this phase. Cell cycle and autoradiography with 3 H-thymidine were also examined. In order to discriminate chromosome by autoradiography, it was effective to utilize the labelled pattern in late DNA synthetic phase, where asynchronous replication of chromosome appeared most obviously. DNA synthesis in chromosome was examined in each DNA synthetic phase by culturing the chromosome after the treatment with 3 H-thymidine and altering the time to prepare chromosome specimen. Discrimination of chromosome in plants and animals by autoradiography was also mentioned. It was noticed as a structural and functional discrimination of chromosome to observe amino acid uptake into chromosome protein and to utilize the difference in labelled pattern between the sites of chromosome. (K. Serizawa)

  6. Multipurpose discriminator with accurate time coupling

    International Nuclear Information System (INIS)

    Baldin, B.Yu.; Krumshtejn, Z.V.; Ronzhin, A.I.

    1977-01-01

    The principle diagram of a multipurpose discriminator is described, designed on the basis of a wide-band differential amplifier. The discriminator has three independent channels: the timing channel, the lower level discriminator and the control channel. The timing channel and the lower level discriminator are connected to a coincidence circuit. Three methods of timing are used: a single threshold, a double threshold with timing on the pulse front, and a constant fraction timing. The lower level discriminator is a wide-band amplifier with an adjustable threshold. The investigation of compensation characteristics of the discriminator has shown that the time shift of the discriminator output in the constant fraction timing regime does not exceed +-75 ns for the input signal range of 1:85. The time resolution was found to be 20 ns in the 20% energy range near the photo-peak maximum of 60 Co γ source

  7. Towards automated discrimination of lipids versus peptides from full scan mass spectra

    Directory of Open Access Journals (Sweden)

    Piotr Dittwald

    2014-09-01

    Full Text Available Although physicochemical fractionation techniques play a crucial role in the analysis of complex mixtures, they are not necessarily the best solution to separate specific molecular classes, such as lipids and peptides. Any physical fractionation step such as, for example, those based on liquid chromatography, will introduce its own variation and noise. In this paper we investigate to what extent the high sensitivity and resolution of contemporary mass spectrometers offers viable opportunities for computational separation of signals in full scan spectra. We introduce an automatic method that can discriminate peptide from lipid peaks in full scan mass spectra, based on their isotopic properties. We systematically evaluate which features maximally contribute to a peptide versus lipid classification. The selected features are subsequently used to build a random forest classifier that enables almost perfect separation between lipid and peptide signals without requiring ion fragmentation and classical tandem MS-based identification approaches. The classifier is trained on in silico data, but is also capable of discriminating signals in real world experiments. We evaluate the influence of typical data inaccuracies of common classes of mass spectrometry instruments on the optimal set of discriminant features. Finally, the method is successfully extended towards the classification of individual lipid classes from full scan mass spectral features, based on input data defined by the Lipid Maps Consortium.

  8. Discriminant analysis of plasma fusion data

    International Nuclear Information System (INIS)

    Kardaun, O.J.W.F.; Kardaun, J.W.P.F.; Itoh, S.; Itoh, K.

    1992-06-01

    Several discriminant analysis methods has been applied and compared to predict the type of ELM's in H-mode discharges: (a) quadratic discriminant analysis (linear discriminant analysis being a special case), (b) discrimination by non-parametric (kernel-) density estimates, and (c) discrimination by a product multinomial model on a discretised scale. Practical evaluation was performed using SAS in the first two cases, and INDEP, a standard FORTRAN program, initially developed for medical applications, in the last case. We give here a flavour of the approach and its results. In summary, discriminant analysis can be used as a useful descriptive method of specifying regions where particular types of plasma discharges can be produced. Parametric methods have the advantage of a rather compact mathematical formulation . Pertinent graphical representations are useful to make the theory and the results more palatable to the experimental physicists. (J.P.N.)

  9. Predicting Bank Financial Failures Using Discriminant Analysis And Support Vector Machines Methods A Comparative Analysis In Commercial Banks In Sudan 2006-2014

    Directory of Open Access Journals (Sweden)

    Mohammed A. SirElkhatim

    2017-04-01

    Full Text Available Bank failures threaten the economic system as a whole. Therefore predicting bank financial failures is crucial to prevent andor lessen its negative effects on the economic system. Financial crises affecting both emerging markets and advanced countries over the centuries have severe economic consequences but they can be hard to prevent and predict identifying financial crises causes remains both science and art said Stijn Claessens assistant director of the International Monetary Fund. While it would be better to mitigate risks financial crises will recur often in waves and better crisis management is therefore important. Analyses of recurrent causes suggest that to prevent crises governments should consider reforms in many underlying areas. That includes developing prudent fiscal and monetary policies better regulating the financial sector including reducing the problem of too-big-to-fail banks and developing effective macro-prudential policies. Despite new regulations and better supervision crises are likely to recur in part because they can reflect deeper problems related to income inequality the political economy and common human behavior. As such improvements in crisis management are also needed. This is originally a classification problem to categorize banks as healthy or non-healthy ones. This study aims to apply Discriminant analysis and Support Vector Machines methods to the bank failure prediction problem in a Sudanese case and to present a comprehensive computational comparison of the classification performances of the techniques tested. Eleven financial and non-financial ratios with six feature groups including capital adequacy asset quality Earning and liquidity CAMELS are selected as predictor variables in the study. Credit risk also been evaluated using logistic analysis to study the effect of Islamic finance modes sectors and payment types used by Sudanese banks with regard to their possibilities of failure. Experimental results

  10. Key Ingredients-Target Groups, Methods and Messages, and Evaluation-of Local-Level, Public Interventions to Counter Stigma and Discrimination: A Lived Experience Informed Selective Narrative Literature Review.

    Science.gov (United States)

    Ashton, Laura J; Gordon, Sarah E; Reeves, Racheal A

    2018-04-01

    A proliferation of recent literature provides substantial direction as to the key ingredients-target groups, messages and methods, and evaluation-of local-level, public interventions to counter stigma and discrimination. This paper provides a selective narrative review of that literature from the perspective or standpoint of anti-stigma experts with lived experience of mental distress, the key findings of which have been synthesised and presented in diagrammatic overviews (infographics). These are intended to guide providers in planning, delivering and evaluating lived experience-directed local-level, public interventions to counter stigma and discrimination in accord with current best practice.

  11. An object-oriented feature-based design system face-based detection of feature interactions

    International Nuclear Information System (INIS)

    Ariffin Abdul Razak

    1999-01-01

    This paper presents an object-oriented, feature-based design system which supports the integration of design and manufacture by ensuring that part descriptions fully account for any feature interactions. Manufacturing information is extracted from the feature descriptions in the form of volumes and Tool Access Directions, TADs. When features interact, both volumes and TADs are updated. This methodology has been demonstrated by developing a prototype system in which ACIS attributes are used to record feature information within the data structure of the solid model. The system implemented in the C++ programming language and embedded in a menu-driven X-windows user interface to the ACIS 3D Toolkit. (author)

  12. Tissue Feature-Based and Segmented Deformable Image Registration for Improved Modeling of Shear Movement of Lungs

    International Nuclear Information System (INIS)

    Xie Yaoqin; Chao Ming; Xing Lei

    2009-01-01

    Purpose: To report a tissue feature-based image registration strategy with explicit inclusion of the differential motions of thoracic structures. Methods and Materials: The proposed technique started with auto-identification of a number of corresponding points with distinct tissue features. The tissue feature points were found by using the scale-invariant feature transform method. The control point pairs were then sorted into different 'colors' according to the organs in which they resided and used to model the involved organs individually. A thin-plate spline method was used to register a structure characterized by the control points with a given 'color.' The proposed technique was applied to study a digital phantom case and 3 lung and 3 liver cancer patients. Results: For the phantom case, a comparison with the conventional thin-plate spline method showed that the registration accuracy was markedly improved when the differential motions of the lung and chest wall were taken into account. On average, the registration error and standard deviation of the 15 points against the known ground truth were reduced from 3.0 to 0.5 mm and from 1.5 to 0.2 mm, respectively, when the new method was used. A similar level of improvement was achieved for the clinical cases. Conclusion: The results of our study have shown that the segmented deformable approach provides a natural and logical solution to model the discontinuous organ motions and greatly improves the accuracy and robustness of deformable registration.

  13. Optical implementation of a feature-based neural network with application to automatic target recognition

    Science.gov (United States)

    Chao, Tien-Hsin; Stoner, William W.

    1993-01-01

    An optical neural network based on the neocognitron paradigm is introduced. A novel aspect of the architecture design is shift-invariant multichannel Fourier optical correlation within each processing layer. Multilayer processing is achieved by feeding back the ouput of the feature correlator interatively to the input spatial light modulator and by updating the Fourier filters. By training the neural net with characteristic features extracted from the target images, successful pattern recognition with intraclass fault tolerance and interclass discrimination is achieved. A detailed system description is provided. Experimental demonstrations of a two-layer neural network for space-object discrimination is also presented.

  14. Automatic target recognition using a feature-based optical neural network

    Science.gov (United States)

    Chao, Tien-Hsin

    1992-01-01

    An optical neural network based upon the Neocognitron paradigm (K. Fukushima et al. 1983) is introduced. A novel aspect of the architectural design is shift-invariant multichannel Fourier optical correlation within each processing layer. Multilayer processing is achieved by iteratively feeding back the output of the feature correlator to the input spatial light modulator and updating the Fourier filters. By training the neural net with characteristic features extracted from the target images, successful pattern recognition with intra-class fault tolerance and inter-class discrimination is achieved. A detailed system description is provided. Experimental demonstration of a two-layer neural network for space objects discrimination is also presented.

  15. Feature-Based Visual Short-Term Memory Is Widely Distributed and Hierarchically Organized.

    Science.gov (United States)

    Dotson, Nicholas M; Hoffman, Steven J; Goodell, Baldwin; Gray, Charles M

    2018-06-15

    Feature-based visual short-term memory is known to engage both sensory and association cortices. However, the extent of the participating circuit and the neural mechanisms underlying memory maintenance is still a matter of vigorous debate. To address these questions, we recorded neuronal activity from 42 cortical areas in monkeys performing a feature-based visual short-term memory task and an interleaved fixation task. We find that task-dependent differences in firing rates are widely distributed throughout the cortex, while stimulus-specific changes in firing rates are more restricted and hierarchically organized. We also show that microsaccades during the memory delay encode the stimuli held in memory and that units modulated by microsaccades are more likely to exhibit stimulus specificity, suggesting that eye movements contribute to visual short-term memory processes. These results support a framework in which most cortical areas, within a modality, contribute to mnemonic representations at timescales that increase along the cortical hierarchy. Copyright © 2018 Elsevier Inc. All rights reserved.

  16. Additivity of Feature-based and Symmetry-based Grouping Effects in Multiple Object Tracking

    Directory of Open Access Journals (Sweden)

    Chundi eWang

    2016-05-01

    Full Text Available Multiple object tracking (MOT is an attentional process wherein people track several moving targets among several distractors. Symmetry, an important indicator of regularity, is a general spatial pattern observed in natural and artificial scenes. According to the laws of perceptual organization proposed by Gestalt psychologists, regularity is a principle of perceptual grouping, such as similarity and closure. A great deal of research reported that feature-based similarity grouping (e.g., grouping based on color, size, or shape among targets in MOT tasks can improve tracking performance. However, no additive feature-based grouping effects have been reported where the tracking objects had two or more features. Additive effect refers to a greater grouping effect produced by grouping based on multiple cues instead of one cue. Can spatial symmetry produce a similar grouping effect similar to that of feature similarity in MOT tasks? Are the grouping effects based on symmetry and feature similarity additive? This study includes four experiments to address these questions. The results of Experiments 1 and 2 demonstrated the automatic symmetry-based grouping effects. More importantly, an additive grouping effect of symmetry and feature similarity was observed in Experiments 3 and 4. Our findings indicate that symmetry can produce an enhanced grouping effect in MOT and facilitate the grouping effect based on color or shape similarity. The where and what pathways might have played an important role in the additive grouping effect.

  17. Neural Determinants of Task Performance during Feature-Based Attention in Human Cortex

    Science.gov (United States)

    Gong, Mengyuan

    2018-01-01

    Abstract Studies of feature-based attention have associated activity in a dorsal frontoparietal network with putative attentional priority signals. Yet, how this neural activity mediates attentional selection and whether it guides behavior are fundamental questions that require investigation. We reasoned that endogenous fluctuations in the quality of attentional priority should influence task performance. Human subjects detected a speed increment while viewing clockwise (CW) or counterclockwise (CCW) motion (baseline task) or while attending to either direction amid distracters (attention task). In an fMRI experiment, direction-specific neural pattern similarity between the baseline task and the attention task revealed a higher level of similarity for correct than incorrect trials in frontoparietal regions. Using transcranial magnetic stimulation (TMS), we disrupted posterior parietal cortex (PPC) and found a selective deficit in the attention task, but not in the baseline task, demonstrating the necessity of this cortical area during feature-based attention. These results reveal that frontoparietal areas maintain attentional priority that facilitates successful behavioral selection. PMID:29497703

  18. Handling conditional discrimination

    NARCIS (Netherlands)

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

    2011-01-01

    Historical data used for supervised learning may contain discrimination. We study how to train classifiers on such data, so that they are discrimination free with respect to a given sensitive attribute, e.g., gender. Existing techniques that deal with this problem aim at removing all discrimination

  19. The Badness of Discrimination

    DEFF Research Database (Denmark)

    Lippert-Rasmussen, Kasper

    2006-01-01

    . In this paper I address these issues. First, I offer a taxonomy of discrimination. I then argue that discrimination is bad, when it is, because it harms people. Finally, I criticize a rival, disrespect-based account according to which discrimination is bad regardless of whether it causes harm....

  20. Orthogonal sparse linear discriminant analysis

    Science.gov (United States)

    Liu, Zhonghua; Liu, Gang; Pu, Jiexin; Wang, Xiaohong; Wang, Haijun

    2018-03-01

    Linear discriminant analysis (LDA) is a linear feature extraction approach, and it has received much attention. On the basis of LDA, researchers have done a lot of research work on it, and many variant versions of LDA were proposed. However, the inherent problem of LDA cannot be solved very well by the variant methods. The major disadvantages of the classical LDA are as follows. First, it is sensitive to outliers and noises. Second, only the global discriminant structure is preserved, while the local discriminant information is ignored. In this paper, we present a new orthogonal sparse linear discriminant analysis (OSLDA) algorithm. The k nearest neighbour graph is first constructed to preserve the locality discriminant information of sample points. Then, L2,1-norm constraint on the projection matrix is used to act as loss function, which can make the proposed method robust to outliers in data points. Extensive experiments have been performed on several standard public image databases, and the experiment results demonstrate the performance of the proposed OSLDA algorithm.

  1. LLNL's Regional Seismic Discrimination Research

    International Nuclear Information System (INIS)

    Hanley, W; Mayeda, K; Myers, S; Pasyanos, M; Rodgers, A; Sicherman, A; Walter, W

    1999-01-01

    As part of the Department of Energy's research and development effort to improve the monitoring capability of the planned Comprehensive Nuclear-Test-Ban Treaty international monitoring system, Lawrence Livermore Laboratory (LLNL) is testing and calibrating regional seismic discrimination algorithms in the Middle East, North Africa and Western Former Soviet Union. The calibration process consists of a number of steps: (1) populating the database with independently identified regional events; (2) developing regional boundaries and pre-identifying severe regional phase blockage zones; (3) measuring and calibrating coda based magnitude scales; (4a) measuring regional amplitudes and making magnitude and distance amplitude corrections (MDAC); (4b) applying the DOE modified kriging methodology to MDAC results using the regionalized background model; (5) determining the thresholds of detectability of regional phases as a function of phase type and frequency; (6) evaluating regional phase discriminant performance both singly and in combination; (7) combining steps 1-6 to create a calibrated discrimination surface for each stations; (8) assessing progress and iterating. We have now developed this calibration procedure to the point where it is fairly straightforward to apply earthquake-explosion discrimination in regions with ample empirical data. Several of the steps outlined above are discussed in greater detail in other DOE papers in this volume or in recent publications. Here we emphasize the results of the above process: station correction surfaces and their improvement to discrimination results compared with simpler calibration methods. Some of the outstanding discrimination research issues involve cases in which there is little or no empirical data. For example in many cases there is no regional nuclear explosion data at IMS stations or nearby surrogates. We have taken two approaches to this problem, first finding and using mining explosion data when available, and

  2. Pulse-width discriminators

    International Nuclear Information System (INIS)

    Budyashov, Yu.G.; Grebenyuk, V.M.; Zinov, V.G.

    1978-01-01

    A pulse duration discriminator is described which is intended for processing signals from multilayer scintillators. The basic elements of the scintillator are: an input gate, a current generator, an integrating capacitor, a Schmidt trigger and an anticoincidence circuit. The basic circuit of the discriminator and its time diagrams explaining its operating are given. The discriminator is based on microcircuits. Pulse duration discrimination threshold changes continuously from 20 to 100 ns, while its amplitude threshold changes within 20 to 100 mV. The temperature instability of discrimination thresholds (both in pulse width and in amplitude) is better than 0.1 per cent/deg C

  3. LABOR DISCRIMINATION IN BULGARIA

    Directory of Open Access Journals (Sweden)

    Vyara Slavyanska

    2017-03-01

    Full Text Available Labor discrimination is a phenomenon with very serious social and economic consequences, which has increased actuality and importance in Bulgaria nowadays. Because of the high price of discrimination, building effective anti-discrimination legislation occupies a special place in the policy of the European Union. Despite the European directives, the presence of anti-discrimination legislation and the broadly declared anti-discrimination inclinations in our country, these are absolutely not enough for providing environment of equality, with a climate of respect and tolerance to the differences. It turns out that certain groups are definitely victims of labor discrimination. In this connection the present article consecutively identifies these groups, as well as the reasons for their discrimination, underlining the necessity and benefits of the integration of the different.

  4. An Efficient Multimodal 2D + 3D Feature-based Approach to Automatic Facial Expression Recognition

    KAUST Repository

    Li, Huibin

    2015-07-29

    We present a fully automatic multimodal 2D + 3D feature-based facial expression recognition approach and demonstrate its performance on the BU-3DFE database. Our approach combines multi-order gradient-based local texture and shape descriptors in order to achieve efficiency and robustness. First, a large set of fiducial facial landmarks of 2D face images along with their 3D face scans are localized using a novel algorithm namely incremental Parallel Cascade of Linear Regression (iPar-CLR). Then, a novel Histogram of Second Order Gradients (HSOG) based local image descriptor in conjunction with the widely used first-order gradient based SIFT descriptor are used to describe the local texture around each 2D landmark. Similarly, the local geometry around each 3D landmark is described by two novel local shape descriptors constructed using the first-order and the second-order surface differential geometry quantities, i.e., Histogram of mesh Gradients (meshHOG) and Histogram of mesh Shape index (curvature quantization, meshHOS). Finally, the Support Vector Machine (SVM) based recognition results of all 2D and 3D descriptors are fused at both feature-level and score-level to further improve the accuracy. Comprehensive experimental results demonstrate that there exist impressive complementary characteristics between the 2D and 3D descriptors. We use the BU-3DFE benchmark to compare our approach to the state-of-the-art ones. Our multimodal feature-based approach outperforms the others by achieving an average recognition accuracy of 86.32%. Moreover, a good generalization ability is shown on the Bosphorus database.

  5. An Efficient Multimodal 2D + 3D Feature-based Approach to Automatic Facial Expression Recognition

    KAUST Repository

    Li, Huibin; Ding, Huaxiong; Huang, Di; Wang, Yunhong; Zhao, Xi; Morvan, Jean-Marie; Chen, Liming

    2015-01-01

    We present a fully automatic multimodal 2D + 3D feature-based facial expression recognition approach and demonstrate its performance on the BU-3DFE database. Our approach combines multi-order gradient-based local texture and shape descriptors in order to achieve efficiency and robustness. First, a large set of fiducial facial landmarks of 2D face images along with their 3D face scans are localized using a novel algorithm namely incremental Parallel Cascade of Linear Regression (iPar-CLR). Then, a novel Histogram of Second Order Gradients (HSOG) based local image descriptor in conjunction with the widely used first-order gradient based SIFT descriptor are used to describe the local texture around each 2D landmark. Similarly, the local geometry around each 3D landmark is described by two novel local shape descriptors constructed using the first-order and the second-order surface differential geometry quantities, i.e., Histogram of mesh Gradients (meshHOG) and Histogram of mesh Shape index (curvature quantization, meshHOS). Finally, the Support Vector Machine (SVM) based recognition results of all 2D and 3D descriptors are fused at both feature-level and score-level to further improve the accuracy. Comprehensive experimental results demonstrate that there exist impressive complementary characteristics between the 2D and 3D descriptors. We use the BU-3DFE benchmark to compare our approach to the state-of-the-art ones. Our multimodal feature-based approach outperforms the others by achieving an average recognition accuracy of 86.32%. Moreover, a good generalization ability is shown on the Bosphorus database.

  6. Optimal state discrimination using particle statistics

    International Nuclear Information System (INIS)

    Bose, S.; Ekert, A.; Omar, Y.; Paunkovic, N.; Vedral, V.

    2003-01-01

    We present an application of particle statistics to the problem of optimal ambiguous discrimination of quantum states. The states to be discriminated are encoded in the internal degrees of freedom of identical particles, and we use the bunching and antibunching of the external degrees of freedom to discriminate between various internal states. We show that we can achieve the optimal single-shot discrimination probability using only the effects of particle statistics. We discuss interesting applications of our method to detecting entanglement and purifying mixed states. Our scheme can easily be implemented with the current technology

  7. Genetic Discrimination: A Legal Or Biological Issue?

    Directory of Open Access Journals (Sweden)

    Bárbara Augusta de Paula Araujo Myssior

    2016-12-01

    Full Text Available This essay debates the technological evolution that, from the decoding of the human genome has opened up many scientific benefits, and yet brings up a new kind of segregation: genetic discrimination. Based on the right to privacy, as well as the concept of genetic identity, as well as data protection and information, worked up the genetic discrimination. Therefore, documentary research and critical analysis of scientific papers were taken, using up of the inductive reasoning method. As a result, elucidate how such discrimination affects individuals, it is possible to conclude that regardless of the type of discrimination, all should be restrained by law.

  8. Discriminative learning for speech recognition

    CERN Document Server

    He, Xiadong

    2008-01-01

    In this book, we introduce the background and mainstream methods of probabilistic modeling and discriminative parameter optimization for speech recognition. The specific models treated in depth include the widely used exponential-family distributions and the hidden Markov model. A detailed study is presented on unifying the common objective functions for discriminative learning in speech recognition, namely maximum mutual information (MMI), minimum classification error, and minimum phone/word error. The unification is presented, with rigorous mathematical analysis, in a common rational-functio

  9. Three-dimensional measurement of small inner surface profiles using feature-based 3-D panoramic registration

    Science.gov (United States)

    Gong, Yuanzheng; Seibel, Eric J.

    2017-01-01

    Rapid development in the performance of sophisticated optical components, digital image sensors, and computer abilities along with decreasing costs has enabled three-dimensional (3-D) optical measurement to replace more traditional methods in manufacturing and quality control. The advantages of 3-D optical measurement, such as noncontact, high accuracy, rapid operation, and the ability for automation, are extremely valuable for inline manufacturing. However, most of the current optical approaches are eligible for exterior instead of internal surfaces of machined parts. A 3-D optical measurement approach is proposed based on machine vision for the 3-D profile measurement of tiny complex internal surfaces, such as internally threaded holes. To capture the full topographic extent (peak to valley) of threads, a side-view commercial rigid scope is used to collect images at known camera positions and orientations. A 3-D point cloud is generated with multiview stereo vision using linear motion of the test piece, which is repeated by a rotation to form additional point clouds. Registration of these point clouds into a complete reconstruction uses a proposed automated feature-based 3-D registration algorithm. The resulting 3-D reconstruction is compared with x-ray computed tomography to validate the feasibility of our proposed method for future robotically driven industrial 3-D inspection.

  10. Fast Rotation-Free Feature-Based Image Registration Using Improved N-SIFT and GMM-Based Parallel Optimization.

    Science.gov (United States)

    Yu, Dongdong; Yang, Feng; Yang, Caiyun; Leng, Chengcai; Cao, Jian; Wang, Yining; Tian, Jie

    2016-08-01

    Image registration is a key problem in a variety of applications, such as computer vision, medical image processing, pattern recognition, etc., while the application of registration is limited by time consumption and the accuracy in the case of large pose differences. Aimed at these two kinds of problems, we propose a fast rotation-free feature-based rigid registration method based on our proposed accelerated-NSIFT and GMM registration-based parallel optimization (PO-GMMREG). Our method is accelerated by using the GPU/CUDA programming and preserving only the location information without constructing the descriptor of each interest point, while its robustness to missing correspondences and outliers is improved by converting the interest point matching to Gaussian mixture model alignment. The accuracy in the case of large pose differences is settled by our proposed PO-GMMREG algorithm by constructing a set of initial transformations. Experimental results demonstrate that our proposed algorithm can fast rigidly register 3-D medical images and is reliable for aligning 3-D scans even when they exhibit a poor initialization.

  11. Multiple computer-based methods of measuring joint space width can discriminate between treatment arms in the COBRA trial -- Update of an ongoing OMERACT project.

    Science.gov (United States)

    Sharp, John T; Angwin, Jane; Boers, Maarten; Duryea, Jeff; Finckh, Axel; Hall, James R; Kauffman, Joost A; Landewé, Robert; Langs, Georg; Lukas, Cédric; Moens, H J Bernelot; Peloschek, Philipp; Strand, C Vibeke; van der Heijde, Désirée

    2009-08-01

    Previously reported data on 5 computer-based programs for measurement of joint space width focusing on discriminating ability and reproducibility are updated, showing new data. Four of 5 different programs for measuring joint space width were more discriminating than observer scoring for change in narrowing in the 12 months interval. Three of 4 programs were more discriminating than observer scoring for the 0-18 month interval. The program that failed to discriminate in the 0-12 month interval was not the same program that failed in the 0-18 month interval. The committee agreed at an interim meeting in November 2007 that an important goal for computer-based measurement programs is a 90% success rate in making measurements of joint pairs in followup studies. This means that the same joint must be measured in images of both timepoints in order to assess change over time in serial radiographs. None of the programs met this 90% threshold, but 3 programs achieved 85%-90% success rate. Intraclass correlation coefficients for assessing change in joint space width in individual joints were 0.98 or 0.99 for 4 programs. The smallest detectable change was < 0.2 mm for 4 of the 5 programs, representing 29%-36% of the change within the 99th percentile of measurements.

  12. Discriminative Transfer Learning for General Image Restoration

    KAUST Repository

    Xiao, Lei

    2018-04-30

    Recently, several discriminative learning approaches have been proposed for effective image restoration, achieving convincing trade-off between image quality and computational efficiency. However, these methods require separate training for each restoration task (e.g., denoising, deblurring, demosaicing) and problem condition (e.g., noise level of input images). This makes it time-consuming and difficult to encompass all tasks and conditions during training. In this paper, we propose a discriminative transfer learning method that incorporates formal proximal optimization and discriminative learning for general image restoration. The method requires a single-pass discriminative training and allows for reuse across various problems and conditions while achieving an efficiency comparable to previous discriminative approaches. Furthermore, after being trained, our model can be easily transferred to new likelihood terms to solve untrained tasks, or be combined with existing priors to further improve image restoration quality.

  13. Discriminative Transfer Learning for General Image Restoration

    KAUST Repository

    Xiao, Lei; Heide, Felix; Heidrich, Wolfgang; Schö lkopf, Bernhard; Hirsch, Michael

    2018-01-01

    Recently, several discriminative learning approaches have been proposed for effective image restoration, achieving convincing trade-off between image quality and computational efficiency. However, these methods require separate training for each restoration task (e.g., denoising, deblurring, demosaicing) and problem condition (e.g., noise level of input images). This makes it time-consuming and difficult to encompass all tasks and conditions during training. In this paper, we propose a discriminative transfer learning method that incorporates formal proximal optimization and discriminative learning for general image restoration. The method requires a single-pass discriminative training and allows for reuse across various problems and conditions while achieving an efficiency comparable to previous discriminative approaches. Furthermore, after being trained, our model can be easily transferred to new likelihood terms to solve untrained tasks, or be combined with existing priors to further improve image restoration quality.

  14. Data mining methods in the prediction of Dementia: A real-data comparison of the accuracy, sensitivity and specificity of linear discriminant analysis, logistic regression, neural networks, support vector machines, classification trees and random forests

    Directory of Open Access Journals (Sweden)

    Santana Isabel

    2011-08-01

    Full Text Available Abstract Background Dementia and cognitive impairment associated with aging are a major medical and social concern. Neuropsychological testing is a key element in the diagnostic procedures of Mild Cognitive Impairment (MCI, but has presently a limited value in the prediction of progression to dementia. We advance the hypothesis that newer statistical classification methods derived from data mining and machine learning methods like Neural Networks, Support Vector Machines and Random Forests can improve accuracy, sensitivity and specificity of predictions obtained from neuropsychological testing. Seven non parametric classifiers derived from data mining methods (Multilayer Perceptrons Neural Networks, Radial Basis Function Neural Networks, Support Vector Machines, CART, CHAID and QUEST Classification Trees and Random Forests were compared to three traditional classifiers (Linear Discriminant Analysis, Quadratic Discriminant Analysis and Logistic Regression in terms of overall classification accuracy, specificity, sensitivity, Area under the ROC curve and Press'Q. Model predictors were 10 neuropsychological tests currently used in the diagnosis of dementia. Statistical distributions of classification parameters obtained from a 5-fold cross-validation were compared using the Friedman's nonparametric test. Results Press' Q test showed that all classifiers performed better than chance alone (p Conclusions When taking into account sensitivity, specificity and overall classification accuracy Random Forests and Linear Discriminant analysis rank first among all the classifiers tested in prediction of dementia using several neuropsychological tests. These methods may be used to improve accuracy, sensitivity and specificity of Dementia predictions from neuropsychological testing.

  15. Digital pulse shape discrimination

    International Nuclear Information System (INIS)

    Miller, L. F.; Preston, J.; Pozzi, S.; Flaska, M.; Neal, J.

    2007-01-01

    Pulse-shape discrimination (PSD) has been utilised for about 40 years as a method to obtain estimates for dose in mixed neutron and photon fields. Digitizers that operate close to GHz are currently available at a reasonable cost, and they can be used to directly sample signals from photomultiplier tubes. This permits one to perform digital PSD rather than the traditional, and well-established, analogous techniques. One issue that complicates PSD for neutrons in mixed fields is that the light output characteristics of typical scintillators available for PSD, such as BC501A, vary as a function of energy deposited in the detector. This behaviour is more easily accommodated with digital processing of signals than with analogous signal processing. Results illustrate the effectiveness of digital PSD. (authors)

  16. Introduction to multivariate discrimination

    Science.gov (United States)

    Kégl, Balázs

    2013-07-01

    Multivariate discrimination or classification is one of the best-studied problem in machine learning, with a plethora of well-tested and well-performing algorithms. There are also several good general textbooks [1-9] on the subject written to an average engineering, computer science, or statistics graduate student; most of them are also accessible for an average physics student with some background on computer science and statistics. Hence, instead of writing a generic introduction, we concentrate here on relating the subject to a practitioner experimental physicist. After a short introduction on the basic setup (Section 1) we delve into the practical issues of complexity regularization, model selection, and hyperparameter optimization (Section 2), since it is this step that makes high-complexity non-parametric fitting so different from low-dimensional parametric fitting. To emphasize that this issue is not restricted to classification, we illustrate the concept on a low-dimensional but non-parametric regression example (Section 2.1). Section 3 describes the common algorithmic-statistical formal framework that unifies the main families of multivariate classification algorithms. We explain here the large-margin principle that partly explains why these algorithms work. Section 4 is devoted to the description of the three main (families of) classification algorithms, neural networks, the support vector machine, and AdaBoost. We do not go into the algorithmic details; the goal is to give an overview on the form of the functions these methods learn and on the objective functions they optimize. Besides their technical description, we also make an attempt to put these algorithm into a socio-historical context. We then briefly describe some rather heterogeneous applications to illustrate the pattern recognition pipeline and to show how widespread the use of these methods is (Section 5). We conclude the chapter with three essentially open research problems that are either

  17. Introduction to multivariate discrimination

    International Nuclear Information System (INIS)

    Kegl, B.

    2013-01-01

    Multivariate discrimination or classification is one of the best-studied problem in machine learning, with a plethora of well-tested and well-performing algorithms. There are also several good general textbooks [1-9] on the subject written to an average engineering, computer science, or statistics graduate student; most of them are also accessible for an average physics student with some background on computer science and statistics. Hence, instead of writing a generic introduction, we concentrate here on relating the subject to a practitioner experimental physicist. After a short introduction on the basic setup (Section 1) we delve into the practical issues of complexity regularization, model selection, and hyper-parameter optimization (Section 2), since it is this step that makes high-complexity non-parametric fitting so different from low-dimensional parametric fitting. To emphasize that this issue is not restricted to classification, we illustrate the concept on a low-dimensional but non-parametric regression example (Section 2.1). Section 3 describes the common algorithmic-statistical formal framework that unifies the main families of multivariate classification algorithms. We explain here the large-margin principle that partly explains why these algorithms work. Section 4 is devoted to the description of the three main (families of) classification algorithms, neural networks, the support vector machine, and AdaBoost. We do not go into the algorithmic details; the goal is to give an overview on the form of the functions these methods learn and on the objective functions they optimize. Besides their technical description, we also make an attempt to put these algorithm into a socio-historical context. We then briefly describe some rather heterogeneous applications to illustrate the pattern recognition pipeline and to show how widespread the use of these methods is (Section 5). We conclude the chapter with three essentially open research problems that are either

  18. From Discrimination to Internalized Mental Illness Stigma: The Mediating Roles of Anticipated Discrimination and Anticipated Stigma

    Science.gov (United States)

    Quinn, Diane M.; Williams, Michelle K.; Weisz, Bradley M.

    2015-01-01

    Objective Internalizing mental illness stigma is related to poorer well-being, but less is known about the factors that predict levels of internalized stigma. This study explored how experiences of discrimination relate to greater anticipation of discrimination and devaluation in the future, and how anticipation of stigma, in turn predicts greater stigma internalization. Method Participants were 105 adults with mental illness who self-reported their experiences of discrimination based on their mental illness, their anticipation of discrimination and social devaluation from others in the future, and their level of internalized stigma. Participants were approached in several locations and completed surveys on laptop computers. Results Correlational analyses indicated that more experiences of discrimination due to one’s mental illness were related to increased anticipated discrimination in the future, increased anticipated social stigma from others, and greater internalized stigma. Multiple serial mediator analyses showed that the effect of experiences of discrimination on internalized stigma was fully mediated by increased anticipated discrimination and anticipated stigma. Conclusion and Implications for Practice Experiences of discrimination over the lifetime may influence not only how much future discrimination people with mental illness are concerned with but also how much they internalize negative feelings about the self. Mental health professionals may need to address concerns with future discrimination and devaluation in order to decrease internalized stigma. PMID:25844910

  19. Quantum-state discrimination

    International Nuclear Information System (INIS)

    Roa, Luis; Retamal, Juan Carlos; Saavedra, Carlos

    2002-01-01

    A proposal for a physical implementation of a quantum-state discrimination protocol using an ion in a linear trap is studied, where two nonorthogonal quantum states are codified using two electronic states of the ion. In addition, a protocol is given for discriminating superpositions of nonorthogonal entangled states between ions inside widely separated optical cavities. The discrimination protocol is extended to the case of N linearly independent nonorthogonal quantum states lying in a space of 2N-1 dimensions

  20. Socially-Tolerable Discrimination

    OpenAIRE

    Amegashie, J. Atsu

    2008-01-01

    History is replete with overt discrimination on the basis of race, gender, age, citizenship, ethnicity, marital status, academic performance, health status, volume of market transactions, religion, sexual orientation, etc. However, these forms of discrimination are not equally tolerable. For example, discrimination based on immutable or prohibitively unalterable characteristics such as race, gender, or ethnicity is much less acceptable. Why? I develop a simple rent-seeking model of conflict w...

  1. Binocular contrast discrimination needs monocular multiplicative noise

    Science.gov (United States)

    Ding, Jian; Levi, Dennis M.

    2016-01-01

    The effects of signal and noise on contrast discrimination are difficult to separate because of a singularity in the signal-detection-theory model of two-alternative forced-choice contrast discrimination (Katkov, Tsodyks, & Sagi, 2006). In this article, we show that it is possible to eliminate the singularity by combining that model with a binocular combination model to fit monocular, dichoptic, and binocular contrast discrimination. We performed three experiments using identical stimuli to measure the perceived phase, perceived contrast, and contrast discrimination of a cyclopean sine wave. In the absence of a fixation point, we found a binocular advantage in contrast discrimination both at low contrasts (discrimination mechanisms: a nonlinear contrast transducer and multiplicative noise (MN). A binocular combination model (the DSKL model; Ding, Klein, & Levi, 2013b) was first fitted to both the perceived-phase and the perceived-contrast data sets, then combined with either the nonlinear contrast transducer or the MN mechanism to fit the contrast-discrimination data. We found that the best model combined the DSKL model with early MN. Model simulations showed that, after going through interocular suppression, the uncorrelated noise in the two eyes became anticorrelated, resulting in less binocular noise and therefore a binocular advantage in the discrimination task. Combining a nonlinear contrast transducer or MN with a binocular combination model (DSKL) provides a powerful method for evaluating the two putative contrast-discrimination mechanisms. PMID:26982370

  2. A Featured-Based Strategy for Stereovision Matching in Sensors with Fish-Eye Lenses for Forest Environments

    Science.gov (United States)

    Herrera, Pedro Javier; Pajares, Gonzalo; Guijarro, Maria; Ruz, José J.; Cruz, Jesús M.; Montes, Fernando

    2009-01-01

    This paper describes a novel feature-based stereovision matching process based on a pair of omnidirectional images in forest stands acquired with a stereovision sensor equipped with fish-eye lenses. The stereo analysis problem consists of the following steps: image acquisition, camera modelling, feature extraction, image matching and depth determination. Once the depths of significant points on the trees are obtained, the growing stock volume can be estimated by considering the geometrical camera modelling, which is the final goal. The key steps are feature extraction and image matching. This paper is devoted solely to these two steps. At a first stage a segmentation process extracts the trunks, which are the regions used as features, where each feature is identified through a set of attributes of properties useful for matching. In the second step the features are matched based on the application of the following four well known matching constraints, epipolar, similarity, ordering and uniqueness. The combination of the segmentation and matching processes for this specific kind of sensors make the main contribution of the paper. The method is tested with satisfactory results and compared against the human expert criterion. PMID:22303134

  3. Credit scoring analysis using kernel discriminant

    Science.gov (United States)

    Widiharih, T.; Mukid, M. A.; Mustafid

    2018-05-01

    Credit scoring model is an important tool for reducing the risk of wrong decisions when granting credit facilities to applicants. This paper investigate the performance of kernel discriminant model in assessing customer credit risk. Kernel discriminant analysis is a non- parametric method which means that it does not require any assumptions about the probability distribution of the input. The main ingredient is a kernel that allows an efficient computation of Fisher discriminant. We use several kernel such as normal, epanechnikov, biweight, and triweight. The models accuracy was compared each other using data from a financial institution in Indonesia. The results show that kernel discriminant can be an alternative method that can be used to determine who is eligible for a credit loan. In the data we use, it shows that a normal kernel is relevant to be selected for credit scoring using kernel discriminant model. Sensitivity and specificity reach to 0.5556 and 0.5488 respectively.

  4. A self-affine multi-fractal wave turbulence discrimination method using data from single point fast response sensors in a nocturnal atmospheric boundary layer

    OpenAIRE

    Kamada, Ray; Decaria, Alex Joseph

    1992-01-01

    We present DA, a self-affine, multi-fractal which may become the first routine wave/turbulence discriminant for time series data. Using nocturnal atmospheric data, we show the advantages of D A over self-similar fractals and standard turbulence measures such as FFTs, Richardson number, Brunt-Vaisala frequency, buoyancy length scale, variances, turbulent kinetic energy, and phase averaging. DA also shows promise in resolving "wave-break" events. Since it uses local basis functions, DA may be...

  5. The Effects of Feature-Based Priming and Visual Working Memory on Oculomotor Capture

    Science.gov (United States)

    Silvis, Jeroen D.; Belopolsky, Artem V.; Murris, Jozua W. I.; Donk, Mieke

    2015-01-01

    Recently, it has been demonstrated that objects held in working memory can influence rapid oculomotor selection. This has been taken as evidence that perceptual salience can be modified by active working memory representations. The goal of the present study was to examine whether these results could also be caused by feature-based priming. In two experiments, participants were asked to saccade to a target line segment of a certain orientation that was presented together with a to-be-ignored distractor. Both objects were given a task-irrelevant color that varied per trial. In a secondary task, a color had to be memorized, and that color could either match the color of the target, match the color of the distractor, or it did not match the color of any of the objects in the search task. The memory task was completed either after the search task (Experiment 1), or before it (Experiment 2). The results showed that in both experiments the memorized color biased oculomotor selection. Eye movements were more frequently drawn towards objects that matched the memorized color, irrespective of whether the memory task was completed after (Experiment 1) or before (Experiment 2) the search task. This bias was particularly prevalent in short-latency saccades. The results show that early oculomotor selection performance is not only affected by properties that are actively maintained in working memory but also by those previously memorized. Both working memory and feature priming can cause early biases in oculomotor selection. PMID:26566137

  6. The Effects of Feature-Based Priming and Visual Working Memory on Oculomotor Capture.

    Science.gov (United States)

    Silvis, Jeroen D; Belopolsky, Artem V; Murris, Jozua W I; Donk, Mieke

    2015-01-01

    Recently, it has been demonstrated that objects held in working memory can influence rapid oculomotor selection. This has been taken as evidence that perceptual salience can be modified by active working memory representations. The goal of the present study was to examine whether these results could also be caused by feature-based priming. In two experiments, participants were asked to saccade to a target line segment of a certain orientation that was presented together with a to-be-ignored distractor. Both objects were given a task-irrelevant color that varied per trial. In a secondary task, a color had to be memorized, and that color could either match the color of the target, match the color of the distractor, or it did not match the color of any of the objects in the search task. The memory task was completed either after the search task (Experiment 1), or before it (Experiment 2). The results showed that in both experiments the memorized color biased oculomotor selection. Eye movements were more frequently drawn towards objects that matched the memorized color, irrespective of whether the memory task was completed after (Experiment 1) or before (Experiment 2) the search task. This bias was particularly prevalent in short-latency saccades. The results show that early oculomotor selection performance is not only affected by properties that are actively maintained in working memory but also by those previously memorized. Both working memory and feature priming can cause early biases in oculomotor selection.

  7. Testing coordinate measuring arms with a geometric feature-based gauge: in situ field trials

    Science.gov (United States)

    Cuesta, E.; Alvarez, B. J.; Patiño, H.; Telenti, A.; Barreiro, J.

    2016-05-01

    This work describes in detail the definition of a procedure for calibrating and evaluating coordinate measuring arms (AACMMs or CMAs). CMAs are portable coordinate measuring machines that have been widely accepted in industry despite their sensitivity to the skill and experience of the operator in charge of the inspection task. The procedure proposed here is based on the use of a dimensional gauge that incorporates multiple geometric features, specifically designed for evaluating the measuring technique when CMAs are used, at company facilities (workshops or laboratories) and by the usual operators who handle these devices in their daily work. After establishing the procedure and manufacturing the feature-based gauge, the research project was complemented with diverse in situ field tests performed with the collaboration of companies that use these devices in their inspection tasks. Some of the results are presented here, not only comparing different operators but also comparing different companies. The knowledge extracted from these experiments has allowed the procedure to be validated, the defects of the methodologies currently used for in situ inspections to be detected, and substantial improvements for increasing the reliability of these portable instruments to be proposed.

  8. Feature-Based Analysis of Plasma-Based Particle Acceleration Data

    Energy Technology Data Exchange (ETDEWEB)

    Rubel, Oliver [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Geddes, Cameron G. R. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Chen, Min [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Cormier-Michel, Estelle [Tech-X Corp., Boulder, CO (United States); Bethel, E. Wes [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2014-02-01

    Plasma-based particle accelerators can produce and sustain thousands of times stronger acceleration fields than conventional particle accelerators, providing a potential solution to the problem of the growing size and cost of conventional particle accelerators. To facilitate scientific knowledge discovery from the ever growing collections of accelerator simulation data generated by accelerator physicists to investigate next-generation plasma-based particle accelerator designs, we describe a novel approach for automatic detection and classification of particle beams and beam substructures due to temporal differences in the acceleration process, here called acceleration features. The automatic feature detection in combination with a novel visualization tool for fast, intuitive, query-based exploration of acceleration features enables an effective top-down data exploration process, starting from a high-level, feature-based view down to the level of individual particles. We describe the application of our analysis in practice to analyze simulations of single pulse and dual and triple colliding pulse accelerator designs, and to study the formation and evolution of particle beams, to compare substructures of a beam and to investigate transverse particle loss.

  9. Feature-based US to CT registration of the aortic root

    Science.gov (United States)

    Lang, Pencilla; Chen, Elvis C. S.; Guiraudon, Gerard M.; Jones, Doug L.; Bainbridge, Daniel; Chu, Michael W.; Drangova, Maria; Hata, Noby; Jain, Ameet; Peters, Terry M.

    2011-03-01

    A feature-based registration was developed to align biplane and tracked ultrasound images of the aortic root with a preoperative CT volume. In transcatheter aortic valve replacement, a prosthetic valve is inserted into the aortic annulus via a catheter. Poor anatomical visualization of the aortic root region can result in incorrect positioning, leading to significant morbidity and mortality. Registration of pre-operative CT to transesophageal ultrasound and fluoroscopy images is a major step towards providing augmented image guidance for this procedure. The proposed registration approach uses an iterative closest point algorithm to register a surface mesh generated from CT to 3D US points reconstructed from a single biplane US acquisition, or multiple tracked US images. The use of a single simultaneous acquisition biplane image eliminates reconstruction error introduced by cardiac gating and TEE probe tracking, creating potential for real-time intra-operative registration. A simple initialization procedure is used to minimize changes to operating room workflow. The algorithm is tested on images acquired from excised porcine hearts. Results demonstrate a clinically acceptable accuracy of 2.6mm and 5mm for tracked US to CT and biplane US to CT registration respectively.

  10. The Effects of Feature-Based Priming and Visual Working Memory on Oculomotor Capture.

    Directory of Open Access Journals (Sweden)

    Jeroen D Silvis

    Full Text Available Recently, it has been demonstrated that objects held in working memory can influence rapid oculomotor selection. This has been taken as evidence that perceptual salience can be modified by active working memory representations. The goal of the present study was to examine whether these results could also be caused by feature-based priming. In two experiments, participants were asked to saccade to a target line segment of a certain orientation that was presented together with a to-be-ignored distractor. Both objects were given a task-irrelevant color that varied per trial. In a secondary task, a color had to be memorized, and that color could either match the color of the target, match the color of the distractor, or it did not match the color of any of the objects in the search task. The memory task was completed either after the search task (Experiment 1, or before it (Experiment 2. The results showed that in both experiments the memorized color biased oculomotor selection. Eye movements were more frequently drawn towards objects that matched the memorized color, irrespective of whether the memory task was completed after (Experiment 1 or before (Experiment 2 the search task. This bias was particularly prevalent in short-latency saccades. The results show that early oculomotor selection performance is not only affected by properties that are actively maintained in working memory but also by those previously memorized. Both working memory and feature priming can cause early biases in oculomotor selection.

  11. Testing coordinate measuring arms with a geometric feature-based gauge: in situ field trials

    International Nuclear Information System (INIS)

    Cuesta, E; Alvarez, B J; Patiño, H; Telenti, A; Barreiro, J

    2016-01-01

    This work describes in detail the definition of a procedure for calibrating and evaluating coordinate measuring arms (AACMMs or CMAs). CMAs are portable coordinate measuring machines that have been widely accepted in industry despite their sensitivity to the skill and experience of the operator in charge of the inspection task. The procedure proposed here is based on the use of a dimensional gauge that incorporates multiple geometric features, specifically designed for evaluating the measuring technique when CMAs are used, at company facilities (workshops or laboratories) and by the usual operators who handle these devices in their daily work. After establishing the procedure and manufacturing the feature-based gauge, the research project was complemented with diverse in situ field tests performed with the collaboration of companies that use these devices in their inspection tasks. Some of the results are presented here, not only comparing different operators but also comparing different companies. The knowledge extracted from these experiments has allowed the procedure to be validated, the defects of the methodologies currently used for in situ inspections to be detected, and substantial improvements for increasing the reliability of these portable instruments to be proposed. (paper)

  12. Feature-based attention: it is all bottom-up priming.

    Science.gov (United States)

    Theeuwes, Jan

    2013-10-19

    Feature-based attention (FBA) enhances the representation of image characteristics throughout the visual field, a mechanism that is particularly useful when searching for a specific stimulus feature. Even though most theories of visual search implicitly or explicitly assume that FBA is under top-down control, we argue that the role of top-down processing in FBA may be limited. Our review of the literature indicates that all behavioural and neuro-imaging studies investigating FBA suffer from the shortcoming that they cannot rule out an effect of priming. The mere attending to a feature enhances the mandatory processing of that feature across the visual field, an effect that is likely to occur in an automatic, bottom-up way. Studies that have investigated the feasibility of FBA by means of cueing paradigms suggest that the role of top-down processing in FBA is limited (e.g. prepare for red). Instead, the actual processing of the stimulus is needed to cause the mandatory tuning of responses throughout the visual field. We conclude that it is likely that all FBA effects reported previously are the result of bottom-up priming.

  13. INTERSECTIONAL DISCRIMINATION AGAINST CHILDREN

    DEFF Research Database (Denmark)

    Ravnbøl, Camilla Ida

    This paper adds a perspective to existing research on child protection by engaging in a debate on intersectional discrimination and its relationship to child protection. The paper has a twofold objective, (1) to further establish intersectionality as a concept to address discrimination against...... children, and (2) to illustrate the importance of addressing intersectionality within rights-based programmes of child protection....

  14. Discrimination and delusional ideation.

    Science.gov (United States)

    Janssen, I; Hanssen, M; Bak, M; Bijl, R V; de Graaf, R; Vollebergh, W; McKenzie, K; van Os, J

    2003-01-01

    In the UK and The Netherlands, people with high rates of psychosis are chronically exposed to discrimination. To test whether perceived discrimination is associated longitudinally with onset of psychosis. A 3-year prospective study of cohorts with no history of psychosis and differential rates of reported discrimination on the basis of age, gender, disability, appearance, skin colour or ethnicity and sexual orientation was conducted in the Dutch general population (n=4076). The main outcome was onset of psychotic symptoms (delusions and hallucinations). The rate of delusional ideation was 0.5% (n=19) in those who did not report discrimination, 0.9% (n=4) in those who reported discrimination in one domain, and 2.7% (n=3) in those who reported discrimination in more than one domain (exact P=0.027). This association remained after adjustment for possible confounders. No association was found between baseline discrimination and onset of hallucinatory experiences. Perceived discrimination may induce delusional ideation and thus contribute to the high observed rates of psychotic disorder in exposed minority populations.

  15. Flash-Type Discrimination

    Science.gov (United States)

    Koshak, William J.

    2010-01-01

    This viewgraph presentation describes the significant progress made in the flash-type discrimination algorithm development. The contents include: 1) Highlights of Progress for GLM-R3 Flash-Type discrimination Algorithm Development; 2) Maximum Group Area (MGA) Data; 3) Retrieval Errors from Simulations; and 4) Preliminary Global-scale Retrieval.

  16. Discrimination against Black Students

    Science.gov (United States)

    Aloud, Ashwaq; Alsulayyim, Maryam

    2016-01-01

    Discrimination is a structured way of abusing people based on racial differences, hence barring them from accessing wealth, political participation and engagement in many spheres of human life. Racism and discrimination are inherently rooted in institutions in the society, the problem has spread across many social segments of the society including…

  17. Digital voltage discriminator

    International Nuclear Information System (INIS)

    Zhou Zhicheng

    1992-01-01

    A digital voltage discriminator is described, which is synthesized by digital comparator and ADC. The threshold is program controllable with high stability. Digital region of confusion is approximately equal to 1.5 LSB. This discriminator has a single channel analyzer function model with channel width of 1.5 LSB

  18. Introduction to integral discriminants

    International Nuclear Information System (INIS)

    Morozov, A.; Shakirov, Sh.

    2009-01-01

    The simplest partition function, associated with homogeneous symmetric forms S of degree r in n variables, is integral discriminant J n|r (S) = ∫e -S(x 1 ,...,x n ) dx 1 ...dx n . Actually, S-dependence remains the same if e -S in the integrand is substituted by arbitrary function f(S), i.e. integral discriminant is a characteristic of the form S itself, and not of the averaging procedure. The aim of the present paper is to calculate J n|r in a number of non-Gaussian cases. Using Ward identities - linear differential equations, satisfied by integral discriminants - we calculate J 2|3 ,J 2|4 ,J 2|5 and J 3|3 . In all these examples, integral discriminant appears to be a generalized hypergeometric function. It depends on several SL(n) invariants of S, with essential singularities controlled by the ordinary algebraic discriminant of S.

  19. Decision theory for discrimination-aware classification

    KAUST Repository

    Kamiran, Faisal; Karim, Asim A.; Zhang, Xiangliang

    2012-01-01

    Social discrimination (e.g., against females) arising from data mining techniques is a growing concern worldwide. In recent years, several methods have been proposed for making classifiers learned over discriminatory data discriminationaware

  20. Contextual Advantage for State Discrimination

    Science.gov (United States)

    Schmid, David; Spekkens, Robert W.

    2018-02-01

    Finding quantitative aspects of quantum phenomena which cannot be explained by any classical model has foundational importance for understanding the boundary between classical and quantum theory. It also has practical significance for identifying information processing tasks for which those phenomena provide a quantum advantage. Using the framework of generalized noncontextuality as our notion of classicality, we find one such nonclassical feature within the phenomenology of quantum minimum-error state discrimination. Namely, we identify quantitative limits on the success probability for minimum-error state discrimination in any experiment described by a noncontextual ontological model. These constraints constitute noncontextuality inequalities that are violated by quantum theory, and this violation implies a quantum advantage for state discrimination relative to noncontextual models. Furthermore, our noncontextuality inequalities are robust to noise and are operationally formulated, so that any experimental violation of the inequalities is a witness of contextuality, independently of the validity of quantum theory. Along the way, we introduce new methods for analyzing noncontextuality scenarios and demonstrate a tight connection between our minimum-error state discrimination scenario and a Bell scenario.

  1. Contextual Advantage for State Discrimination

    Directory of Open Access Journals (Sweden)

    David Schmid

    2018-02-01

    Full Text Available Finding quantitative aspects of quantum phenomena which cannot be explained by any classical model has foundational importance for understanding the boundary between classical and quantum theory. It also has practical significance for identifying information processing tasks for which those phenomena provide a quantum advantage. Using the framework of generalized noncontextuality as our notion of classicality, we find one such nonclassical feature within the phenomenology of quantum minimum-error state discrimination. Namely, we identify quantitative limits on the success probability for minimum-error state discrimination in any experiment described by a noncontextual ontological model. These constraints constitute noncontextuality inequalities that are violated by quantum theory, and this violation implies a quantum advantage for state discrimination relative to noncontextual models. Furthermore, our noncontextuality inequalities are robust to noise and are operationally formulated, so that any experimental violation of the inequalities is a witness of contextuality, independently of the validity of quantum theory. Along the way, we introduce new methods for analyzing noncontextuality scenarios and demonstrate a tight connection between our minimum-error state discrimination scenario and a Bell scenario.

  2. Tracking subtle stereotypes of children with trisomy 21: from facial-feature-based to implicit stereotyping.

    Directory of Open Access Journals (Sweden)

    Claire Enea-Drapeau

    Full Text Available BACKGROUND: Stigmatization is one of the greatest obstacles to the successful integration of people with Trisomy 21 (T21 or Down syndrome, the most frequent genetic disorder associated with intellectual disability. Research on attitudes and stereotypes toward these people still focuses on explicit measures subjected to social-desirability biases, and neglects how variability in facial stigmata influences attitudes and stereotyping. METHODOLOGY/PRINCIPAL FINDINGS: The participants were 165 adults including 55 young adult students, 55 non-student adults, and 55 professional caregivers working with intellectually disabled persons. They were faced with implicit association tests (IAT, a well-known technique whereby response latency is used to capture the relative strength with which some groups of people--here photographed faces of typically developing children and children with T21--are automatically (without conscious awareness associated with positive versus negative attributes in memory. Each participant also rated the same photographed faces (consciously accessible evaluations. We provide the first evidence that the positive bias typically found in explicit judgments of children with T21 is smaller for those whose facial features are highly characteristic of this disorder, compared to their counterparts with less distinctive features and to typically developing children. We also show that this bias can coexist with negative evaluations at the implicit level (with large effect sizes, even among professional caregivers. CONCLUSION: These findings support recent models of feature-based stereotyping, and more importantly show how crucial it is to go beyond explicit evaluations to estimate the true extent of stigmatization of intellectually disabled people.

  3. PROSPER: an integrated feature-based tool for predicting protease substrate cleavage sites.

    Directory of Open Access Journals (Sweden)

    Jiangning Song

    Full Text Available The ability to catalytically cleave protein substrates after synthesis is fundamental for all forms of life. Accordingly, site-specific proteolysis is one of the most important post-translational modifications. The key to understanding the physiological role of a protease is to identify its natural substrate(s. Knowledge of the substrate specificity of a protease can dramatically improve our ability to predict its target protein substrates, but this information must be utilized in an effective manner in order to efficiently identify protein substrates by in silico approaches. To address this problem, we present PROSPER, an integrated feature-based server for in silico identification of protease substrates and their cleavage sites for twenty-four different proteases. PROSPER utilizes established specificity information for these proteases (derived from the MEROPS database with a machine learning approach to predict protease cleavage sites by using different, but complementary sequence and structure characteristics. Features used by PROSPER include local amino acid sequence profile, predicted secondary structure, solvent accessibility and predicted native disorder. Thus, for proteases with known amino acid specificity, PROSPER provides a convenient, pre-prepared tool for use in identifying protein substrates for the enzymes. Systematic prediction analysis for the twenty-four proteases thus far included in the database revealed that the features we have included in the tool strongly improve performance in terms of cleavage site prediction, as evidenced by their contribution to performance improvement in terms of identifying known cleavage sites in substrates for these enzymes. In comparison with two state-of-the-art prediction tools, PoPS and SitePrediction, PROSPER achieves greater accuracy and coverage. To our knowledge, PROSPER is the first comprehensive server capable of predicting cleavage sites of multiple proteases within a single substrate

  4. Tissue feature-based intra-fractional motion tracking for stereoscopic x-ray image guided radiotherapy

    Science.gov (United States)

    Xie, Yaoqin; Xing, Lei; Gu, Jia; Liu, Wu

    2013-06-01

    Real-time knowledge of tumor position during radiation therapy is essential to overcome the adverse effect of intra-fractional organ motion. The goal of this work is to develop a tumor tracking strategy by effectively utilizing the inherent image features of stereoscopic x-ray images acquired during dose delivery. In stereoscopic x-ray image guided radiation delivery, two orthogonal x-ray images are acquired either simultaneously or sequentially. The essence of markerless tumor tracking is the reliable identification of inherent points with distinct tissue features on each projection image and their association between two images. The identification of the feature points on a planar x-ray image is realized by searching for points with high intensity gradient. The feature points are associated by using the scale invariance features transform descriptor. The performance of the proposed technique is evaluated by using images of a motion phantom and four archived clinical cases acquired using either a CyberKnife equipped with a stereoscopic x-ray imaging system, or a LINAC equipped with an onboard kV imager and an electronic portal imaging device. In the phantom study, the results obtained using the proposed method agree with the measurements to within 2 mm in all three directions. In the clinical study, the mean error is 0.48 ± 0.46 mm for four patient data with 144 sequential images. In this work, a tissue feature-based tracking method for stereoscopic x-ray image guided radiation therapy is developed. The technique avoids the invasive procedure of fiducial implantation and may greatly facilitate the clinical workflow.

  5. Tissue feature-based intra-fractional motion tracking for stereoscopic x-ray image guided radiotherapy

    International Nuclear Information System (INIS)

    Xie Yaoqin; Gu Jia; Xing Lei; Liu Wu

    2013-01-01

    Real-time knowledge of tumor position during radiation therapy is essential to overcome the adverse effect of intra-fractional organ motion. The goal of this work is to develop a tumor tracking strategy by effectively utilizing the inherent image features of stereoscopic x-ray images acquired during dose delivery. In stereoscopic x-ray image guided radiation delivery, two orthogonal x-ray images are acquired either simultaneously or sequentially. The essence of markerless tumor tracking is the reliable identification of inherent points with distinct tissue features on each projection image and their association between two images. The identification of the feature points on a planar x-ray image is realized by searching for points with high intensity gradient. The feature points are associated by using the scale invariance features transform descriptor. The performance of the proposed technique is evaluated by using images of a motion phantom and four archived clinical cases acquired using either a CyberKnife equipped with a stereoscopic x-ray imaging system, or a LINAC equipped with an onboard kV imager and an electronic portal imaging device. In the phantom study, the results obtained using the proposed method agree with the measurements to within 2 mm in all three directions. In the clinical study, the mean error is 0.48 ± 0.46 mm for four patient data with 144 sequential images. In this work, a tissue feature-based tracking method for stereoscopic x-ray image guided radiation therapy is developed. The technique avoids the invasive procedure of fiducial implantation and may greatly facilitate the clinical workflow. (paper)

  6. General description of discriminating quantum operations

    International Nuclear Information System (INIS)

    Zhang Ke-Jia; Gao Fei; Qin Su-Juan; Wen Qiao-Yan; Zhu Ping; Guo Fen-Zhuo

    2011-01-01

    The discrimination of quantum operations plays a key role in quantum information and computation. Unlike discriminating quantum states, it has some special properties which can be carried out in practice. In this paper, we provide a general description of discriminating quantum operations. Concretely speaking, we describe the distinguishability between quantum operations using a measure called operator fidelity. It is shown that, employing the theory of operator fidelity, we can not only verify some previous results to discriminate unitary operations, but also exhibit a more general discrimination condition. We further apply our results to analysing the security of some quantum cryptographic protocols and discuss the realization of our method using well-developed quantum algorithms. (general)

  7. Decision theory for discrimination-aware classification

    KAUST Repository

    Kamiran, Faisal

    2012-12-01

    Social discrimination (e.g., against females) arising from data mining techniques is a growing concern worldwide. In recent years, several methods have been proposed for making classifiers learned over discriminatory data discriminationaware. However, these methods suffer from two major shortcomings: (1) They require either modifying the discriminatory data or tweaking a specific classification algorithm and (2) They are not flexible w.r.t. discrimination control and multiple sensitive attribute handling. In this paper, we present two solutions for discrimination-aware classification that neither require data modification nor classifier tweaking. Our first and second solutions exploit, respectively, the reject option of probabilistic classifier(s) and the disagreement region of general classifier ensembles to reduce discrimination. We relate both solutions with decision theory for better understanding of the process. Our experiments using real-world datasets demonstrate that our solutions outperform existing state-ofthe-art methods, especially at low discrimination which is a significant advantage. The superior performance coupled with flexible control over discrimination and easy applicability to multiple sensitive attributes makes our solutions an important step forward in practical discrimination-aware classification. © 2012 IEEE.

  8. Rapid and novel discrimination and quantification of oleanolic and ursolic acids in complex plant extracts using two-dimensional nuclear magnetic resonance spectroscopy-Comparison with HPLC methods

    International Nuclear Information System (INIS)

    Kontogianni, Vassiliki G.; Exarchou, Vassiliki; Troganis, Anastassios; Gerothanassis, Ioannis P.

    2009-01-01

    A novel strategy for NMR analysis of mixtures of oleanolic and ursolic acids that occur in natural products is described. These important phytochemicals have similar structure and their discrimination and quantification is rather difficult. We report herein the combined use of proton-carbon heteronuclear single-quantum coherence ( 1 H- 13 C HSQC) and proton-carbon heteronuclear multiple-bond correlation ( 1 H- 13 C HMBC) NMR spectroscopy, in the identification and quantitation of oleanolic acid (OA) and ursolic acid (UA)in plant extracts of the Lamiaceae and Oleaceae family. The combination of 1 H- 13 C HSQC and 1 H- 13 C HMBC techniques allows the connection of the proton and carbon-13 spins across the molecular backbone resulting in the identification and, thus, discrimination of oleanolic and ursolic acid without resorting to physicochemical separation of the components. The quantitative results provided by 2D 1 H- 13 C HSQC NMR data were obtained within a short period of time (∼14 min) and are in excellent agreement with those obtained by HPLC, which support the efficiency of the suggested methodology

  9. Discrimination Method of the Volatiles from Fresh Mushrooms by an Electronic Nose Using a Trapping System and Statistical Standardization to Reduce Sensor Value Variation

    Directory of Open Access Journals (Sweden)

    Kouki Fujioka

    2013-11-01

    Full Text Available Electronic noses have the benefit of obtaining smell information in a simple and objective manner, therefore, many applications have been developed for broad analysis areas such as food, drinks, cosmetics, medicine, and agriculture. However, measurement values from electronic noses have a tendency to vary under humidity or alcohol exposure conditions, since several types of sensors in the devices are affected by such variables. Consequently, we show three techniques for reducing the variation of sensor values: (1 using a trapping system to reduce the infering components; (2 performing statistical standardization (calculation of z-score; and (3 selecting suitable sensors. With these techniques, we discriminated the volatiles of four types of fresh mushrooms: golden needle (Flammulina velutipes, white mushroom (Agaricus bisporus, shiitake (Lentinus edodes, and eryngii (Pleurotus eryngii among six fresh mushrooms (hen of the woods (Grifola frondosa, shimeji (Hypsizygus marmoreus plus the above mushrooms. Additionally, we succeeded in discrimination of white mushroom, only comparing with artificial mushroom flavors, such as champignon flavor and truffle flavor. In conclusion, our techniques will expand the options to reduce variations in sensor values.

  10. Set discrimination of quantum states

    International Nuclear Information System (INIS)

    Zhang Shengyu; Ying Mingsheng

    2002-01-01

    We introduce a notion of set discrimination, which is an interesting extension of quantum state discrimination. A state is secretly chosen from a number of quantum states, which are partitioned into some disjoint sets. A set discrimination is required to identify which set the given state belongs to. Several essential problems are addressed in this paper, including the condition of perfect set discrimination, unambiguous set discrimination, and in the latter case, the efficiency of the discrimination. This generalizes some important results on quantum state discrimination in the literature. A combination of state and set discrimination and the efficiency are also studied

  11. Hierarchical Discriminant Analysis

    Directory of Open Access Journals (Sweden)

    Di Lu

    2018-01-01

    Full Text Available The Internet of Things (IoT generates lots of high-dimensional sensor intelligent data. The processing of high-dimensional data (e.g., data visualization and data classification is very difficult, so it requires excellent subspace learning algorithms to learn a latent subspace to preserve the intrinsic structure of the high-dimensional data, and abandon the least useful information in the subsequent processing. In this context, many subspace learning algorithms have been presented. However, in the process of transforming the high-dimensional data into the low-dimensional space, the huge difference between the sum of inter-class distance and the sum of intra-class distance for distinct data may cause a bias problem. That means that the impact of intra-class distance is overwhelmed. To address this problem, we propose a novel algorithm called Hierarchical Discriminant Analysis (HDA. It minimizes the sum of intra-class distance first, and then maximizes the sum of inter-class distance. This proposed method balances the bias from the inter-class and that from the intra-class to achieve better performance. Extensive experiments are conducted on several benchmark face datasets. The results reveal that HDA obtains better performance than other dimensionality reduction algorithms.

  12. The effect of feature-based attention on flanker interference processing: An fMRI-constrained source analysis.

    Science.gov (United States)

    Siemann, Julia; Herrmann, Manfred; Galashan, Daniela

    2018-01-25

    The present study examined whether feature-based cueing affects early or late stages of flanker conflict processing using EEG and fMRI. Feature cues either directed participants' attention to the upcoming colour of the target or were neutral. Validity-specific modulations during interference processing were investigated using the N200 event-related potential (ERP) component and BOLD signal differences. Additionally, both data sets were integrated using an fMRI-constrained source analysis. Finally, the results were compared with a previous study in which spatial instead of feature-based cueing was applied to an otherwise identical flanker task. Feature-based and spatial attention recruited a common fronto-parietal network during conflict processing. Irrespective of attention type (feature-based; spatial), this network responded to focussed attention (valid cueing) as well as context updating (invalid cueing), hinting at domain-general mechanisms. However, spatially and non-spatially directed attention also demonstrated domain-specific activation patterns for conflict processing that were observable in distinct EEG and fMRI data patterns as well as in the respective source analyses. Conflict-specific activity in visual brain regions was comparable between both attention types. We assume that the distinction between spatially and non-spatially directed attention types primarily applies to temporal differences (domain-specific dynamics) between signals originating in the same brain regions (domain-general localization).

  13. Neuronal discrimination capacity

    International Nuclear Information System (INIS)

    Deng Yingchun; Williams, Peter; Feng Jianfeng; Liu Feng

    2003-01-01

    We explore neuronal mechanisms of discriminating between masked signals. It is found that when the correlation between input signals is zero, the output signals are separable if and only if input signals are separable. With positively (negatively) correlated signals, the output signals are separable (mixed) even when input signals are mixed (separable). Exact values of discrimination capacity are obtained for two most interesting cases: the exactly balanced inhibitory and excitatory input case and the uncorrelated input case. Interestingly, the discrimination capacity obtained in these cases is independent of model parameters, input distribution and is universal. Our results also suggest a functional role of inhibitory inputs and correlated inputs or, more generally, the large variability of efferent spike trains observed in in vivo experiments: the larger the variability of efferent spike trains, the easier it is to discriminate between masked input signals

  14. Neuronal discrimination capacity

    Energy Technology Data Exchange (ETDEWEB)

    Deng Yingchun [Department of Mathematics, Hunan Normal University 410081, Changsha (China); COGS, University of Sussex at Brighton, BN1 9QH (United Kingdom); Williams, Peter; Feng Jianfeng [COGS, University of Sussex at Brighton, BN1 9QH (United Kingdom); Liu Feng [COGS, University of Sussex at Brighton, BN1 9QH (United Kingdom); Physics Department, Nanjing University (China)

    2003-12-19

    We explore neuronal mechanisms of discriminating between masked signals. It is found that when the correlation between input signals is zero, the output signals are separable if and only if input signals are separable. With positively (negatively) correlated signals, the output signals are separable (mixed) even when input signals are mixed (separable). Exact values of discrimination capacity are obtained for two most interesting cases: the exactly balanced inhibitory and excitatory input case and the uncorrelated input case. Interestingly, the discrimination capacity obtained in these cases is independent of model parameters, input distribution and is universal. Our results also suggest a functional role of inhibitory inputs and correlated inputs or, more generally, the large variability of efferent spike trains observed in in vivo experiments: the larger the variability of efferent spike trains, the easier it is to discriminate between masked input signals.

  15. Discriminative analysis of Parkinson's disease based on whole-brain functional connectivity.

    Directory of Open Access Journals (Sweden)

    Yongbin Chen

    Full Text Available Recently, there has been an increasing emphasis on applications of pattern recognition and neuroimaging techniques in the effective and accurate diagnosis of psychiatric or neurological disorders. In the present study, we investigated the whole-brain resting-state functional connectivity patterns of Parkinson's disease (PD, which are expected to provide additional information for the clinical diagnosis and treatment of this disease. First, we computed the functional connectivity between each pair of 116 regions of interest derived from a prior atlas. The most discriminative features based on Kendall tau correlation coefficient were then selected. A support vector machine classifier was employed to classify 21 PD patients with 26 demographically matched healthy controls. This method achieved a classification accuracy of 93.62% using leave-one-out cross-validation, with a sensitivity of 90.47% and a specificity of 96.15%. The majority of the most discriminative functional connections were located within or across the default mode, cingulo-opercular and frontal-parietal networks and the cerebellum. These disease-related resting-state network alterations might play important roles in the pathophysiology of this disease. Our results suggest that analyses of whole-brain resting-state functional connectivity patterns have the potential to improve the clinical diagnosis and treatment evaluation of PD.

  16. Hybrid generative-discriminative approach to age-invariant face recognition

    Science.gov (United States)

    Sajid, Muhammad; Shafique, Tamoor

    2018-03-01

    Age-invariant face recognition is still a challenging research problem due to the complex aging process involving types of facial tissues, skin, fat, muscles, and bones. Most of the related studies that have addressed the aging problem are focused on generative representation (aging simulation) or discriminative representation (feature-based approaches). Designing an appropriate hybrid approach taking into account both the generative and discriminative representations for age-invariant face recognition remains an open problem. We perform a hybrid matching to achieve robustness to aging variations. This approach automatically segments the eyes, nose-bridge, and mouth regions, which are relatively less sensitive to aging variations compared with the rest of the facial regions that are age-sensitive. The aging variations of age-sensitive facial parts are compensated using a demographic-aware generative model based on a bridged denoising autoencoder. The age-insensitive facial parts are represented by pixel average vector-based local binary patterns. Deep convolutional neural networks are used to extract relative features of age-sensitive and age-insensitive facial parts. Finally, the feature vectors of age-sensitive and age-insensitive facial parts are fused to achieve the recognition results. Extensive experimental results on morphological face database II (MORPH II), face and gesture recognition network (FG-NET), and Verification Subset of cross-age celebrity dataset (CACD-VS) demonstrate the effectiveness of the proposed method for age-invariant face recognition well.

  17. Discrimination in Textbooks

    OpenAIRE

    大津, 尚志

    1996-01-01

    In this paper, I deal with the issues which concern discriminations in textbooks.In America, they have paid special attentions to these problems since 1960's. They made guidelines for textbooks to check various kinds of discriminative descriptions and tried to make textbooks to meet these standards. In this respects I would examine the present states about textbooks in America and would compare them to the Japanese ones. That would be useful, I believe, when we consider these issues in Japan.

  18. The extraction of motion-onset VEP BCI features based on deep learning and compressed sensing.

    Science.gov (United States)

    Ma, Teng; Li, Hui; Yang, Hao; Lv, Xulin; Li, Peiyang; Liu, Tiejun; Yao, Dezhong; Xu, Peng

    2017-01-01

    Motion-onset visual evoked potentials (mVEP) can provide a softer stimulus with reduced fatigue, and it has potential applications for brain computer interface(BCI)systems. However, the mVEP waveform is seriously masked in the strong background EEG activities, and an effective approach is needed to extract the corresponding mVEP features to perform task recognition for BCI control. In the current study, we combine deep learning with compressed sensing to mine discriminative mVEP information to improve the mVEP BCI performance. The deep learning and compressed sensing approach can generate the multi-modality features which can effectively improve the BCI performance with approximately 3.5% accuracy incensement over all 11 subjects and is more effective for those subjects with relatively poor performance when using the conventional features. Compared with the conventional amplitude-based mVEP feature extraction approach, the deep learning and compressed sensing approach has a higher classification accuracy and is more effective for subjects with relatively poor performance. According to the results, the deep learning and compressed sensing approach is more effective for extracting the mVEP feature to construct the corresponding BCI system, and the proposed feature extraction framework is easy to extend to other types of BCIs, such as motor imagery (MI), steady-state visual evoked potential (SSVEP)and P300. Copyright © 2016 Elsevier B.V. All rights reserved.

  19. Development of a data-processing method based on Bayesian k-means clustering to discriminate aneugens and clastogens in a high-content micronucleus assay.

    Science.gov (United States)

    Huang, Z H; Li, N; Rao, K F; Liu, C T; Huang, Y; Ma, M; Wang, Z J

    2018-03-01

    Genotoxicants can be identified as aneugens and clastogens through a micronucleus (MN) assay. The current high-content screening-based MN assays usually discriminate an aneugen from a clastogen based on only one parameter, such as the MN size, intensity, or morphology, which yields low accuracies (70-84%) because each of these parameters may contribute to the results. Therefore, the development of an algorithm that can synthesize high-dimensionality data to attain comparative results is important. To improve the automation and accuracy of detection using the current parameter-based mode of action (MoA), the MN MoA signatures of 20 chemicals were systematically recruited in this study to develop an algorithm. The results of the algorithm showed very good agreement (93.58%) between the prediction and reality, indicating that the proposed algorithm is a validated analytical platform for the rapid and objective acquisition of genotoxic MoA messages.

  20. A discrimination problem from seismology

    International Nuclear Information System (INIS)

    Elvers, E.

    1975-12-01

    Seismic discrimination between earthquakes and underground nuclear explosions is studied, utilizing magnitudes of two kinds from several seismic stations. A model is given first, where the mean values of the magnitudes are linear fuctions of a parameter describing event size. It is shown how the model parameters can be estimated after a minor restriction on their space. When the discrimination rule is derived from the model, a few different approaches are considered, and they are shown to coincide. It is found reasonabel to use a discriminant, which is linear in the magnitudes, and explicit formulas are obtained. The power of the method is expressed by a measure of separation between the alternatives, which also shows the importance of the individual magnitudes. Missing data is a frequent problem in practice, and the case is treated where there is a detection threshold for one of the magnitudes. The classicfication probabilities are computed when applying the rule to the available magnitudes, and they depend on the event size. The method is not optimal, and it is shown that it can be improved by using the technique of identification by negative evidence, i.e. by utilizing the threshold as upper bound for a missing magnitude. The model is one of general use, and the results thus have a wider applicability. (author)

  1. Gender discrimination in exam grading?

    DEFF Research Database (Denmark)

    Rangvid, Beatrice Schindler

    2018-01-01

    Girls, on average, obtain higher test scores in school than boys, and recent research suggests that part of this difference may be due to discrimination against boys in grading. This bias is consequential if admission to subsequent education programs is based on exam scores. This study assesses t...... tendencies are in accordance with statistical discrimination as a mechanism for grading bias in essay writing and with gender-stereotyped beliefs of math being a male domain....... are scored twice (blind and non-blind). Both strategies use difference-in-differences methods. Although imprecisely estimated, the point estimates indicate a blind grading advantage for boys in essay writing of approximately 5-8% SD, corresponding to 9-15% of the gender gap in essay exam grades. The effect...

  2. Rapid Discrimination for Traditional Complex Herbal Medicines from Different Parts, Collection Time, and Origins Using High-Performance Liquid Chromatography and Near-Infrared Spectral Fingerprints with Aid of Pattern Recognition Methods

    Directory of Open Access Journals (Sweden)

    Haiyan Fu

    2015-01-01

    Full Text Available As an effective method, the fingerprint technique, which emphasized the whole compositions of samples, has already been used in various fields, especially in identifying and assessing the quality of herbal medicines. High-performance liquid chromatography (HPLC and near-infrared (NIR, with their unique characteristics of reliability, versatility, precision, and simple measurement, played an important role among all the fingerprint techniques. In this paper, a supervised pattern recognition method based on PLSDA algorithm by HPLC and NIR has been established to identify the information of Hibiscus mutabilis L. and Berberidis radix, two common kinds of herbal medicines. By comparing component analysis (PCA, linear discriminant analysis (LDA, and particularly partial least squares discriminant analysis (PLSDA with different fingerprint preprocessing of NIR spectra variables, PLSDA model showed perfect functions on the analysis of samples as well as chromatograms. Most important, this pattern recognition method by HPLC and NIR can be used to identify different collection parts, collection time, and different origins or various species belonging to the same genera of herbal medicines which proved to be a promising approach for the identification of complex information of herbal medicines.

  3. A Trivial Linear Discriminant Function

    Directory of Open Access Journals (Sweden)

    Shuichi Shinmura

    2015-11-01

    Full Text Available In this paper, we focus on the new model selection procedure of the discriminant analysis. Combining re-sampling technique with k-fold cross validation, we develop a k-fold cross validation for small sample method. By this breakthrough, we obtain the mean error rate in the validation samples (M2 and the 95\\% confidence interval (CI of discriminant coefficient. Moreover, we propose the model  selection  procedure  in  which  the model having a minimum M2 was  chosen  to  the  best  model.  We  apply  this  new  method and procedure to the pass/ fail determination of  exam  scores.  In  this  case,  we  fix  the constant =1 for seven linear discriminant  functions  (LDFs  and  several  good  results  were obtained as follows: 1 M2 of Fisher's LDF are over 4.6\\% worse than Revised IP-OLDF. 2 A soft-margin  SVM  for  penalty c=1  (SVM1  is  worse  than  another  mathematical  programming (MP based LDFs and logistic regression . 3 The 95\\% CI of the best discriminant coefficients was obtained. Seven LDFs except for Fisher's LDF are almost the same as a trivial LDF for the linear separable model. Furthermore, if we choose the median of the coefficient of seven LDFs except for Fisher's LDF,  those are almost the same as the trivial LDF for the linear separable model.

  4. Genetic Discrimination: A Legal Or Biological Issue?

    OpenAIRE

    Myssior, Bárbara Augusta de Paula Araujo; Silva, Luís Eduardo Gomes

    2016-01-01

    This essay debates the technological evolution that, from the decoding of the human genome has opened up many scientific benefits, and yet brings up a new kind of segregation: genetic discrimination. Based on the right to privacy, as well as the concept of genetic identity, as well as data protection and information, worked up the genetic discrimination. Therefore, documentary research and critical analysis of scientific papers were taken, using up of the inductive reasoning method. As a resu...

  5. Earthquake—explosion discrimination using genetic algorithm-based boosting approach

    Science.gov (United States)

    Orlic, Niksa; Loncaric, Sven

    2010-02-01

    An important and challenging problem in seismic data processing is to discriminate between natural seismic events such as earthquakes and artificial seismic events such as explosions. Many automatic techniques for seismogram classification have been proposed in the literature. Most of these methods have a similar approach to seismogram classification: a predefined set of features based on ad-hoc feature selection criteria is extracted from the seismogram waveform or spectral data and these features are used for signal classification. In this paper we propose a novel approach for seismogram classification. A specially formulated genetic algorithm has been employed to automatically search for a near-optimal seismogram feature set, instead of using ad-hoc feature selection criteria. A boosting method is added to the genetic algorithm when searching for multiple features in order to improve classification performance. A learning set of seismogram data is used by the genetic algorithm to discover a near-optimal feature set. The feature set identified by the genetic algorithm is then used for seismogram classification. The described method is developed to classify seismograms in two groups, whereas a brief overview of method extension for multiple group classification is given. For method verification, a learning set consisting of 40 local earthquake seismograms and 40 explosion seismograms was used. The method was validated on seismogram set consisting of 60 local earthquake seismograms and 60 explosion seismograms, with correct classification of 85%.

  6. Origin discrimination and quality evaluation of Gastrodiae rhizoma ...

    African Journals Online (AJOL)

    quality control and origin discrimination of Gastrodiae rhizoma. Methods: Twelve .... Similarity. Evaluation. System for. Chromatographic Fingerprint of Traditional. Chinese Medicine ..... chromatography with tandem quadrupole time-of-flight.

  7. The 95% confidence intervals of error rates and discriminant coefficients

    Directory of Open Access Journals (Sweden)

    Shuichi Shinmura

    2015-02-01

    Full Text Available Fisher proposed a linear discriminant function (Fisher’s LDF. From 1971, we analysed electrocardiogram (ECG data in order to develop the diagnostic logic between normal and abnormal symptoms by Fisher’s LDF and a quadratic discriminant function (QDF. Our four years research was inferior to the decision tree logic developed by the medical doctor. After this experience, we discriminated many data and found four problems of the discriminant analysis. A revised Optimal LDF by Integer Programming (Revised IP-OLDF based on the minimum number of misclassification (minimum NM criterion resolves three problems entirely [13, 18]. In this research, we discuss fourth problem of the discriminant analysis. There are no standard errors (SEs of the error rate and discriminant coefficient. We propose a k-fold crossvalidation method. This method offers a model selection technique and a 95% confidence intervals (C.I. of error rates and discriminant coefficients.

  8. An image-processing method to detect sub-optical features based on understanding noise in intensity measurements.

    Science.gov (United States)

    Bhatia, Tripta

    2018-02-01

    Accurate quantitative analysis of image data requires that we distinguish between fluorescence intensity (true signal) and the noise inherent to its measurements to the extent possible. We image multilamellar membrane tubes and beads that grow from defects in the fluid lamellar phase of the lipid 1,2-dioleoyl-sn-glycero-3-phosphocholine dissolved in water and water-glycerol mixtures by using fluorescence confocal polarizing microscope. We quantify image noise and determine the noise statistics. Understanding the nature of image noise also helps in optimizing image processing to detect sub-optical features, which would otherwise remain hidden. We use an image-processing technique "optimum smoothening" to improve the signal-to-noise ratio of features of interest without smearing their structural details. A high SNR renders desired positional accuracy with which it is possible to resolve features of interest with width below optical resolution. Using optimum smoothening, the smallest and the largest core diameter detected is of width [Formula: see text] and [Formula: see text] nm, respectively, discussed in this paper. The image-processing and analysis techniques and the noise modeling discussed in this paper can be used for detailed morphological analysis of features down to sub-optical length scales that are obtained by any kind of fluorescence intensity imaging in the raster mode.

  9. Face-based recognition techniques: proposals for the metrological characterization of global and feature-based approaches

    Science.gov (United States)

    Betta, G.; Capriglione, D.; Crenna, F.; Rossi, G. B.; Gasparetto, M.; Zappa, E.; Liguori, C.; Paolillo, A.

    2011-12-01

    Security systems based on face recognition through video surveillance systems deserve great interest. Their use is important in several areas including airport security, identification of individuals and access control to critical areas. These systems are based either on the measurement of details of a human face or on a global approach whereby faces are considered as a whole. The recognition is then performed by comparing the measured parameters with reference values stored in a database. The result of this comparison is not deterministic because measurement results are affected by uncertainty due to random variations and/or to systematic effects. In these circumstances the recognition of a face is subject to the risk of a faulty decision. Therefore, a proper metrological characterization is needed to improve the performance of such systems. Suitable methods are proposed for a quantitative metrological characterization of face measurement systems, on which recognition procedures are based. The proposed methods are applied to three different algorithms based either on linear discrimination, on eigenface analysis, or on feature detection.

  10. Face-based recognition techniques: proposals for the metrological characterization of global and feature-based approaches

    International Nuclear Information System (INIS)

    Betta, G; Capriglione, D; Crenna, F; Rossi, G B; Gasparetto, M; Zappa, E; Liguori, C; Paolillo, A

    2011-01-01

    Security systems based on face recognition through video surveillance systems deserve great interest. Their use is important in several areas including airport security, identification of individuals and access control to critical areas. These systems are based either on the measurement of details of a human face or on a global approach whereby faces are considered as a whole. The recognition is then performed by comparing the measured parameters with reference values stored in a database. The result of this comparison is not deterministic because measurement results are affected by uncertainty due to random variations and/or to systematic effects. In these circumstances the recognition of a face is subject to the risk of a faulty decision. Therefore, a proper metrological characterization is needed to improve the performance of such systems. Suitable methods are proposed for a quantitative metrological characterization of face measurement systems, on which recognition procedures are based. The proposed methods are applied to three different algorithms based either on linear discrimination, on eigenface analysis, or on feature detection

  11. A rapid NMR-based method for discrimination of strain-specific cell wall teichoic acid structures reveals a third backbone type in Lactobacillus plantarum.

    Science.gov (United States)

    Tomita, Satoru; Tanaka, Naoto; Okada, Sanae

    2017-03-01

    The lactic acid bacterium Lactobacillus plantarum is capable of producing strain-specific structures of cell wall teichoic acid (WTA), an anionic polysaccharide found in the Gram-positive bacterial cell wall. In this study, we established a rapid, NMR-based procedure to discriminate WTA structures in this species, and applied it to 94 strains of L. plantarum. Six previously reported glycerol- and ribitol-containing WTA subtypes were successfully identified from 78 strains, suggesting that these were the dominant structures. However, the level of structural variety differed markedly among bacterial sources, possibly reflecting differences in strain-level microbial diversity. WTAs from eight strains were not identified based on NMR spectra and were classified into three groups. Structural analysis of a partial degradation product of an unidentified WTA produced by strain TUA 1496L revealed that the WTA was 1-O-β-d-glucosylglycerol. Two-dimensional NMR analysis of the polymer structure showed phosphodiester bonds between C-3 and C-6 of the glycerol and glucose residues, suggesting a polymer structure of 3,6΄-linked poly(1-O-β-d-glucosyl-sn-glycerol phosphate). This is the third WTA backbone structure in L. plantarum, following 3,6΄-linked poly(1-O-α-d-glucosyl-sn-glycerol phosphate) and 1,5-linked poly(ribitol phosphate). © FEMS 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  12. Multi-Feature Based Multiple Landmine Detection Using Ground Penetration Radar

    Directory of Open Access Journals (Sweden)

    S. Park

    2014-06-01

    Full Text Available This paper presents a novel method for detection of multiple landmines using a ground penetrating radar (GPR. Conventional algorithms mainly focus on detection of a single landmine, which cannot linearly extend to the multiple landmine case. The proposed algorithm is composed of four steps; estimation of the number of multiple objects buried in the ground, isolation of each object, feature extraction and detection of landmines. The number of objects in the GPR signal is estimated by using the energy projection method. Then signals for the objects are extracted by using the symmetry filtering method. Each signal is then processed for features, which are given as input to the support vector machine (SVM for landmine detection. Three landmines buried in various ground conditions are considered for the test of the proposed method. They demonstrate that the proposed method can successfully detect multiple landmines.

  13. Similar effects of feature-based attention on motion perception and pursuit eye movements at different levels of awareness.

    Science.gov (United States)

    Spering, Miriam; Carrasco, Marisa

    2012-05-30

    Feature-based attention enhances visual processing and improves perception, even for visual features that we are not aware of. Does feature-based attention also modulate motor behavior in response to visual information that does or does not reach awareness? Here we compare the effect of feature-based attention on motion perception and smooth-pursuit eye movements in response to moving dichoptic plaids--stimuli composed of two orthogonally drifting gratings, presented separately to each eye--in human observers. Monocular adaptation to one grating before the presentation of both gratings renders the adapted grating perceptually weaker than the unadapted grating and decreases the level of awareness. Feature-based attention was directed to either the adapted or the unadapted grating's motion direction or to both (neutral condition). We show that observers were better at detecting a speed change in the attended than the unattended motion direction, indicating that they had successfully attended to one grating. Speed change detection was also better when the change occurred in the unadapted than the adapted grating, indicating that the adapted grating was perceptually weaker. In neutral conditions, perception and pursuit in response to plaid motion were dissociated: While perception followed one grating's motion direction almost exclusively (component motion), the eyes tracked the average of both gratings (pattern motion). In attention conditions, perception and pursuit were shifted toward the attended component. These results suggest that attention affects perception and pursuit similarly even though only the former reflects awareness. The eyes can track an attended feature even if observers do not perceive it.

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

    Science.gov (United States)

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

    2016-04-01

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

  15. Joint learning and weighting of visual vocabulary for bag-of-feature based tissue classification

    KAUST Repository

    Wang, Jim Jing-Yan; Bensmail, Halima; Gao, Xin

    2013-01-01

    their power in this field. Two important issues of bag-of-feature strategy for tissue classification are investigated in this paper: the visual vocabulary learning and weighting, which are always considered independently in traditional methods by neglecting

  16. Simultaneous Channel and Feature Selection of Fused EEG Features Based on Sparse Group Lasso

    Directory of Open Access Journals (Sweden)

    Jin-Jia Wang

    2015-01-01

    Full Text Available Feature extraction and classification of EEG signals are core parts of brain computer interfaces (BCIs. Due to the high dimension of the EEG feature vector, an effective feature selection algorithm has become an integral part of research studies. In this paper, we present a new method based on a wrapped Sparse Group Lasso for channel and feature selection of fused EEG signals. The high-dimensional fused features are firstly obtained, which include the power spectrum, time-domain statistics, AR model, and the wavelet coefficient features extracted from the preprocessed EEG signals. The wrapped channel and feature selection method is then applied, which uses the logistical regression model with Sparse Group Lasso penalized function. The model is fitted on the training data, and parameter estimation is obtained by modified blockwise coordinate descent and coordinate gradient descent method. The best parameters and feature subset are selected by using a 10-fold cross-validation. Finally, the test data is classified using the trained model. Compared with existing channel and feature selection methods, results show that the proposed method is more suitable, more stable, and faster for high-dimensional feature fusion. It can simultaneously achieve channel and feature selection with a lower error rate. The test accuracy on the data used from international BCI Competition IV reached 84.72%.

  17. Discrimination in Employment

    Science.gov (United States)

    Abzug, Bella

    1975-01-01

    This testimony, before a public hearing of the New York City Commission on Human Rights in May 1974, expressly focuses on discrimination in employment, asserting that this has had the most direct effect on minorities and women in the country; while legal protections have grown stronger, they have not been used effectively. (Author/JM)

  18. Discrimination? - Exhibition of posters

    OpenAIRE

    Jakimovska, Jana

    2017-01-01

    Participation in the exhibition with the students form the Art Academy. The exhibition consisted of 15 posters tackling the subjects of hate speech and discrimination. The exhibition happened thanks to the invitation of the Faculty of Law at UGD, and it was a part of a larger event of launching books on the aforementioned subjects.

  19. Discrimination Learning in Children

    Science.gov (United States)

    Ochocki, Thomas E.; And Others

    1975-01-01

    Examined the learning performance of 192 fourth-, fifth-, and sixth-grade children on either a two or four choice simultaneous color discrimination task. Compared the use of verbal reinforcement and/or punishment, under conditions of either complete or incomplete instructions. (Author/SDH)

  20. Education and Gender Discrimination

    Science.gov (United States)

    Sumi, V. S.

    2012-01-01

    This paper discusses the status of women education in present education system and some measures to overcome the lags existing. Discrimination against girls and women in the developing world is a devastating reality. It results in millions of individual tragedies, which add up to lost potential for entire countries. Gender bias in education is an…

  1. Feature-based characterisation of signature topography in laser powder bed fusion of metals

    Science.gov (United States)

    Senin, Nicola; Thompson, Adam; Leach, Richard

    2018-04-01

    The use of state-of-the-art areal topography measurement instrumentation allows for a high level of detail in the acquisition of topographic information at micrometric scales. The 3D geometric models of surface topography obtained from measured data create new opportunities for the investigation of manufacturing processes through characterisation of the surfaces of manufactured parts. Conventional methods for quantitative assessment of topography usually only involve the computation of texture parameters, summary indicators of topography-related characteristics that are computed over the investigated area. However, further useful information may be obtained through characterisation of signature topographic formations, as more direct indicators of manufacturing process behaviour and performance. In this work, laser powder bed fusion of metals is considered. An original algorithmic method is proposed to isolate relevant topographic formations and to quantify their dimensional and geometric properties, using areal topography data acquired by state-of-the-art areal topography measurement instrumentation.

  2. Scoring relevancy of features based on combinatorial analysis of Lasso with application to lymphoma diagnosis

    Directory of Open Access Journals (Sweden)

    Zare Habil

    2013-01-01

    Full Text Available Abstract One challenge in applying bioinformatic tools to clinical or biological data is high number of features that might be provided to the learning algorithm without any prior knowledge on which ones should be used. In such applications, the number of features can drastically exceed the number of training instances which is often limited by the number of available samples for the study. The Lasso is one of many regularization methods that have been developed to prevent overfitting and improve prediction performance in high-dimensional settings. In this paper, we propose a novel algorithm for feature selection based on the Lasso and our hypothesis is that defining a scoring scheme that measures the "quality" of each feature can provide a more robust feature selection method. Our approach is to generate several samples from the training data by bootstrapping, determine the best relevance-ordering of the features for each sample, and finally combine these relevance-orderings to select highly relevant features. In addition to the theoretical analysis of our feature scoring scheme, we provided empirical evaluations on six real datasets from different fields to confirm the superiority of our method in exploratory data analysis and prediction performance. For example, we applied FeaLect, our feature scoring algorithm, to a lymphoma dataset, and according to a human expert, our method led to selecting more meaningful features than those commonly used in the clinics. This case study built a basis for discovering interesting new criteria for lymphoma diagnosis. Furthermore, to facilitate the use of our algorithm in other applications, the source code that implements our algorithm was released as FeaLect, a documented R package in CRAN.

  3. Feature-based plan adaptation for fast treatment planning in scanned ion beam therapy

    International Nuclear Information System (INIS)

    Chen Wenjing; Gemmel, Alexander; Rietzel, Eike

    2013-01-01

    We propose a plan adaptation method for fast treatment plan generation in scanned ion beam therapy. Analysis of optimized treatment plans with carbon ions indicates that the particle number modulation of consecutive rasterspots in depth shows little variation throughout target volumes with convex shape. Thus, we extract a depth-modulation curve (DMC) from existing reference plans and adapt it for creation of new plans in similar treatment situations. The proposed method is tested with seven CT serials of prostate patients and three digital phantom datasets generated with the MATLAB code. Plans are generated with a treatment planning software developed by GSI using single-field uniform dose optimization for all the CT datasets to serve as reference plans and ‘gold standard’. The adapted plans are generated based on the DMC derived from the reference plans of the same patient (intra-patient), different patient (inter-patient) and phantoms (phantom-patient). They are compared with the reference plans and a re-positioning strategy. Generally, in 1 min on a standard PC, either a physical plan or a biological plan can be generated with the adaptive method provided that the new target contour is available. In all the cases, the V95 values of the adapted plans can achieve 97% for either physical or biological plans. V107 is always 0 indicating no overdosage, and target dose homogeneity is above 0.98 in all cases. The dose received by the organs at risk is comparable to the optimized plans. The plan adaptation method has the potential for on-line adaptation to deal with inter-fractional motion, as well as fast off-line treatment planning, with either the prescribed physical dose or the RBE-weighted dose. (paper)

  4. A statistical-textural-features based approach for classification of solid drugs using surface microscopic images.

    Science.gov (United States)

    Tahir, Fahima; Fahiem, Muhammad Abuzar

    2014-01-01

    The quality of pharmaceutical products plays an important role in pharmaceutical industry as well as in our lives. Usage of defective tablets can be harmful for patients. In this research we proposed a nondestructive method to identify defective and nondefective tablets using their surface morphology. Three different environmental factors temperature, humidity and moisture are analyzed to evaluate the performance of the proposed method. Multiple textural features are extracted from the surface of the defective and nondefective tablets. These textural features are gray level cooccurrence matrix, run length matrix, histogram, autoregressive model and HAAR wavelet. Total textural features extracted from images are 281. We performed an analysis on all those 281, top 15, and top 2 features. Top 15 features are extracted using three different feature reduction techniques: chi-square, gain ratio and relief-F. In this research we have used three different classifiers: support vector machine, K-nearest neighbors and naïve Bayes to calculate the accuracies against proposed method using two experiments, that is, leave-one-out cross-validation technique and train test models. We tested each classifier against all selected features and then performed the comparison of their results. The experimental work resulted in that in most of the cases SVM performed better than the other two classifiers.

  5. A feature-based approach to modeling protein-protein interaction hot spots.

    Science.gov (United States)

    Cho, Kyu-il; Kim, Dongsup; Lee, Doheon

    2009-05-01

    Identifying features that effectively represent the energetic contribution of an individual interface residue to the interactions between proteins remains problematic. Here, we present several new features and show that they are more effective than conventional features. By combining the proposed features with conventional features, we develop a predictive model for interaction hot spots. Initially, 54 multifaceted features, composed of different levels of information including structure, sequence and molecular interaction information, are quantified. Then, to identify the best subset of features for predicting hot spots, feature selection is performed using a decision tree. Based on the selected features, a predictive model for hot spots is created using support vector machine (SVM) and tested on an independent test set. Our model shows better overall predictive accuracy than previous methods such as the alanine scanning methods Robetta and FOLDEF, and the knowledge-based method KFC. Subsequent analysis yields several findings about hot spots. As expected, hot spots have a larger relative surface area burial and are more hydrophobic than other residues. Unexpectedly, however, residue conservation displays a rather complicated tendency depending on the types of protein complexes, indicating that this feature is not good for identifying hot spots. Of the selected features, the weighted atomic packing density, relative surface area burial and weighted hydrophobicity are the top 3, with the weighted atomic packing density proving to be the most effective feature for predicting hot spots. Notably, we find that hot spots are closely related to pi-related interactions, especially pi . . . pi interactions.

  6. Joint learning and weighting of visual vocabulary for bag-of-feature based tissue classification

    KAUST Repository

    Wang, Jim Jing-Yan

    2013-12-01

    Automated classification of tissue types of Region of Interest (ROI) in medical images has been an important application in Computer-Aided Diagnosis (CAD). Recently, bag-of-feature methods which treat each ROI as a set of local features have shown their power in this field. Two important issues of bag-of-feature strategy for tissue classification are investigated in this paper: the visual vocabulary learning and weighting, which are always considered independently in traditional methods by neglecting the inner relationship between the visual words and their weights. To overcome this problem, we develop a novel algorithm, Joint-ViVo, which learns the vocabulary and visual word weights jointly. A unified objective function based on large margin is defined for learning of both visual vocabulary and visual word weights, and optimized alternately in the iterative algorithm. We test our algorithm on three tissue classification tasks: classifying breast tissue density in mammograms, classifying lung tissue in High-Resolution Computed Tomography (HRCT) images, and identifying brain tissue type in Magnetic Resonance Imaging (MRI). The results show that Joint-ViVo outperforms the state-of-art methods on tissue classification problems. © 2013 Elsevier Ltd.

  7. Protein single-model quality assessment by feature-based probability density functions.

    Science.gov (United States)

    Cao, Renzhi; Cheng, Jianlin

    2016-04-04

    Protein quality assessment (QA) has played an important role in protein structure prediction. We developed a novel single-model quality assessment method-Qprob. Qprob calculates the absolute error for each protein feature value against the true quality scores (i.e. GDT-TS scores) of protein structural models, and uses them to estimate its probability density distribution for quality assessment. Qprob has been blindly tested on the 11th Critical Assessment of Techniques for Protein Structure Prediction (CASP11) as MULTICOM-NOVEL server. The official CASP result shows that Qprob ranks as one of the top single-model QA methods. In addition, Qprob makes contributions to our protein tertiary structure predictor MULTICOM, which is officially ranked 3rd out of 143 predictors. The good performance shows that Qprob is good at assessing the quality of models of hard targets. These results demonstrate that this new probability density distribution based method is effective for protein single-model quality assessment and is useful for protein structure prediction. The webserver of Qprob is available at: http://calla.rnet.missouri.edu/qprob/. The software is now freely available in the web server of Qprob.

  8. Examining Workplace Discrimination in a Discrimination-Free Environment

    OpenAIRE

    Braxton, Shawn Lamont

    2010-01-01

    Examining Workplace Discrimination in a Discrimination-Free Environment Shawn L. Braxton Abstract The purpose of this study is to explore how racial and gender discrimination is reproduced in concrete workplace settings even when anti-discrimination policies are present, and to understand the various reactions utilized by those who commonly experience it. I have selected a particular medical center, henceforth referred to by a pseudonym, â The Bliley Medical Centerâ as my case ...

  9. Neutron-gamma discrimination in mixed field by pulse shape discriminator

    International Nuclear Information System (INIS)

    Sharghi Ido, A.; Shahriari, M.; Etaati, G. R.

    2009-01-01

    In this study, a pulse shape discriminator, incorporating zero-crossing method has been developed. The separate measurements with 241 Am-Be and 252 Cf sources undertaken by BC501A liquid have shown that the purposed and the common-used pulse shape discriminator's are in good agreement. The improved characteristics of the presented pulse shape discriminator are FOM=1.36 at a threshold of 60 ke Vee and 1.5μsec dead time which allows the count rates up to 50 k Hz

  10. Discrimination of Xihulongjing tea grade using an electronic tongue ...

    African Journals Online (AJOL)

    Five grades of Xihulongjing tea (grade: AAA, AA, A, B and C, from the same region and processed with the same processing method) were discriminated using -Astree II electronic tongue (e-tongue) coupled with pattern recognition methods including principal component analysis (PCA), canonical discriminant analysis ...

  11. A feature-based approach to modeling protein–protein interaction hot spots

    Science.gov (United States)

    Cho, Kyu-il; Kim, Dongsup; Lee, Doheon

    2009-01-01

    Identifying features that effectively represent the energetic contribution of an individual interface residue to the interactions between proteins remains problematic. Here, we present several new features and show that they are more effective than conventional features. By combining the proposed features with conventional features, we develop a predictive model for interaction hot spots. Initially, 54 multifaceted features, composed of different levels of information including structure, sequence and molecular interaction information, are quantified. Then, to identify the best subset of features for predicting hot spots, feature selection is performed using a decision tree. Based on the selected features, a predictive model for hot spots is created using support vector machine (SVM) and tested on an independent test set. Our model shows better overall predictive accuracy than previous methods such as the alanine scanning methods Robetta and FOLDEF, and the knowledge-based method KFC. Subsequent analysis yields several findings about hot spots. As expected, hot spots have a larger relative surface area burial and are more hydrophobic than other residues. Unexpectedly, however, residue conservation displays a rather complicated tendency depending on the types of protein complexes, indicating that this feature is not good for identifying hot spots. Of the selected features, the weighted atomic packing density, relative surface area burial and weighted hydrophobicity are the top 3, with the weighted atomic packing density proving to be the most effective feature for predicting hot spots. Notably, we find that hot spots are closely related to π–related interactions, especially π · · · π interactions. PMID:19273533

  12. Discrimination of solvent from protein regions in native Fouriers as a means of evaluating heavy-atom solutions in the MIR and MAD methods

    International Nuclear Information System (INIS)

    Terwilliger, Thomas C.; Berendzen, Joel

    1999-01-01

    The presence of distinct regions of high and low density variation in electron-density maps is found to be a good indicator of the correctness of a heavy-atom solution in the MIR and MAD methods. An automated examination of the native Fourier is tested as a means of evaluation of a heavy-atom solution in MAD and MIR methods for macromolecular crystallography. It is found that the presence of distinct regions of high and low density variation in electron-density maps is a good indicator of the correctness of a heavy-atom solution in the MIR and MAD methods. The method can be used to evaluate heavy-atom solutions during MAD and MIR structure solutions and to determine the handedness of the structure if anomalous data have been measured

  13. Feature-Based Retinal Image Registration Using D-Saddle Feature

    Directory of Open Access Journals (Sweden)

    Roziana Ramli

    2017-01-01

    Full Text Available Retinal image registration is important to assist diagnosis and monitor retinal diseases, such as diabetic retinopathy and glaucoma. However, registering retinal images for various registration applications requires the detection and distribution of feature points on the low-quality region that consists of vessels of varying contrast and sizes. A recent feature detector known as Saddle detects feature points on vessels that are poorly distributed and densely positioned on strong contrast vessels. Therefore, we propose a multiresolution difference of Gaussian pyramid with Saddle detector (D-Saddle to detect feature points on the low-quality region that consists of vessels with varying contrast and sizes. D-Saddle is tested on Fundus Image Registration (FIRE Dataset that consists of 134 retinal image pairs. Experimental results show that D-Saddle successfully registered 43% of retinal image pairs with average registration accuracy of 2.329 pixels while a lower success rate is observed in other four state-of-the-art retinal image registration methods GDB-ICP (28%, Harris-PIIFD (4%, H-M (16%, and Saddle (16%. Furthermore, the registration accuracy of D-Saddle has the weakest correlation (Spearman with the intensity uniformity metric among all methods. Finally, the paired t-test shows that D-Saddle significantly improved the overall registration accuracy of the original Saddle.

  14. Digital position sensitive discrimination for 2-dimensional scintillation detectors

    International Nuclear Information System (INIS)

    Engels, R.; Reinartz, R.; Reinhart, P.

    1996-01-01

    The energy sensitivity of a two-dimensional scintillation gamma detector based on position sensitive photomultipliers has been minimized by a digital differential discrimination unit. Since the photomultiplier gain is position-dependent by 50%, a discrimination unit has been developed where digital upper and lower discrimination levels are set due to the position-dependent photomultiplier gain obtained from calibration measurements. Depending on the spatial resolution there can be up to 65.536 position-sensitive discriminator levels defining energy windows. By this method, narrow discriminator windows can be used for reducing the low and high energy quanta without effecting the sensitivity of the detector. The new discrimination method, its performance and test measurements with gamma rays will be described. Furthermore experimental results are presented

  15. Fault-tolerant feature-based estimation of space debris rotational motion during active removal missions

    Science.gov (United States)

    Biondi, Gabriele; Mauro, Stefano; Pastorelli, Stefano; Sorli, Massimo

    2018-05-01

    One of the key functionalities required by an Active Debris Removal mission is the assessment of the target kinematics and inertial properties. Passive sensors, such as stereo cameras, are often included in the onboard instrumentation of a chaser spacecraft for capturing sequential photographs and for tracking features of the target surface. A plenty of methods, based on Kalman filtering, are available for the estimation of the target's state from feature positions; however, to guarantee the filter convergence, they typically require continuity of measurements and the capability of tracking a fixed set of pre-defined features of the object. These requirements clash with the actual tracking conditions: failures in feature detection often occur and the assumption of having some a-priori knowledge about the shape of the target could be restrictive in certain cases. The aim of the presented work is to propose a fault-tolerant alternative method for estimating the angular velocity and the relative magnitudes of the principal moments of inertia of the target. Raw data regarding the positions of the tracked features are processed to evaluate corrupted values of a 3-dimentional parameter which entirely describes the finite screw motion of the debris and which primarily is invariant on the particular set of considered features of the object. Missing values of the parameter are completely restored exploiting the typical periodicity of the rotational motion of an uncontrolled satellite: compressed sensing techniques, typically adopted for recovering images or for prognostic applications, are herein used in a completely original fashion for retrieving a kinematic signal that appears sparse in the frequency domain. Due to its invariance about the features, no assumptions are needed about the target's shape and continuity of the tracking. The obtained signal is useful for the indirect evaluation of an attitude signal that feeds an unscented Kalman filter for the estimation of

  16. Quadrilateral mesh fitting that preserves sharp features based on multi-normals for Laplacian energy

    Directory of Open Access Journals (Sweden)

    Yusuke Imai

    2014-04-01

    Full Text Available Because the cost of performance testing using actual products is expensive, manufacturers use lower-cost computer-aided design simulations for this function. In this paper, we propose using hexahedral meshes, which are more accurate than tetrahedral meshes, for finite element analysis. We propose automatic hexahedral mesh generation with sharp features to precisely represent the corresponding features of a target shape. Our hexahedral mesh is generated using a voxel-based algorithm. In our previous works, we fit the surface of the voxels to the target surface using Laplacian energy minimization. We used normal vectors in the fitting to preserve sharp features. However, this method could not represent concave sharp features precisely. In this proposal, we improve our previous Laplacian energy minimization by adding a term that depends on multi-normal vectors instead of using normal vectors. Furthermore, we accentuate a convex/concave surface subset to represent concave sharp features.

  17. Toward Meaningful Manufacturing Variation Data in Design - Feature Based Description of Variation in Manufacturing Processes

    DEFF Research Database (Denmark)

    Eifler, Tobias; Boorla, Srinivasa Murthy; Howard, Thomas J.

    2016-01-01

    The need to mitigate the effects of manufacturing variation already in design is nowadays commonly acknowledged and has led to a wide use of predictive modeling techniques, tolerancing approaches, etc. in industry. The trustworthiness of corresponding variation analyses is, however, not ensured...... by the availability of sophisticated methods and tools alone, but does evidently also depend on the accuracy of the input information used. As existing approaches for the description of manufacturing variation focus however, almost exclusively, on monitoring and controlling production processes, there is frequently...... a lack of objective variation data in design. As a result, variation analyses and tolerancing activities rely on numerous assumptions made to fill the gaps of missing or incomplete data. To overcome this hidden subjectivity, a schema for a consistent and standardised description of manufacturing...

  18. Patient feature based dosimetric Pareto front prediction in esophageal cancer radiotherapy.

    Science.gov (United States)

    Wang, Jiazhou; Jin, Xiance; Zhao, Kuaike; Peng, Jiayuan; Xie, Jiang; Chen, Junchao; Zhang, Zhen; Studenski, Matthew; Hu, Weigang

    2015-02-01

    To investigate the feasibility of the dosimetric Pareto front (PF) prediction based on patient's anatomic and dosimetric parameters for esophageal cancer patients. Eighty esophagus patients in the authors' institution were enrolled in this study. A total of 2928 intensity-modulated radiotherapy plans were obtained and used to generate PF for each patient. On average, each patient had 36.6 plans. The anatomic and dosimetric features were extracted from these plans. The mean lung dose (MLD), mean heart dose (MHD), spinal cord max dose, and PTV homogeneity index were recorded for each plan. Principal component analysis was used to extract overlap volume histogram (OVH) features between PTV and other organs at risk. The full dataset was separated into two parts; a training dataset and a validation dataset. The prediction outcomes were the MHD and MLD. The spearman's rank correlation coefficient was used to evaluate the correlation between the anatomical features and dosimetric features. The stepwise multiple regression method was used to fit the PF. The cross validation method was used to evaluate the model. With 1000 repetitions, the mean prediction error of the MHD was 469 cGy. The most correlated factor was the first principal components of the OVH between heart and PTV and the overlap between heart and PTV in Z-axis. The mean prediction error of the MLD was 284 cGy. The most correlated factors were the first principal components of the OVH between heart and PTV and the overlap between lung and PTV in Z-axis. It is feasible to use patients' anatomic and dosimetric features to generate a predicted Pareto front. Additional samples and further studies are required improve the prediction model.

  19. Fast timing discriminator

    International Nuclear Information System (INIS)

    Lo, C.C.

    1977-01-01

    The processing of pulses with very fast risetimes for timing purposes involves many problems because of the large equivalent bandwidths involved. For pulses with risetimes in the 150 ps range (and full widths at half maximum (FWHM) of 400 ps) bandwidths in excess of 1GHz are required. Furthermore, these very narrow pulses with current amplitudes as small as 1 mA carry very small charges ( -12 coulomb), therefore, requiring very sensitive trigger circuits. The difficulty increases when timing characteristics in the picosecond range are sought especially when a wide input signal amplitude range causes a time-walk problem. The fast timing discriminator described has a time-walk of approximately +-75 ps over the input signal range from 80 mV to 3V. A schematic of the discriminator is included, and operation and performance are discussed

  20. Gender wage discrimination

    OpenAIRE

    Hirsch, Boris

    2016-01-01

    There are pronounced and persistent wage differences between men and women in all parts of the world. A significant element of these wage disparities can be attributed to differences in worker and workplace characteristics, which are likely to mirror differences in worker productivity. However, a large part of these differences remains unexplained, and it is common to attribute them to discrimination by the employer that is rooted in prejudice against female workers. Yet recent empirical evid...

  1. Diversity, discrimination, and performance

    OpenAIRE

    Leonard, Jonathan S.; Levine, David I.

    2003-01-01

    Employee diversity may affect business performance both as a result of customer discrimination and as a result of how members of a group work with each other in teams. We test for both channels with data from more than 800 retail stores employing over 70,000 individuals matched to Census data on the demographics of the community. We find little payoff to matching employee demographics to those of potential customers except when the customers do not speak English. Although age diversity doe...

  2. The use of Stress Tensor Discriminator Faults in separating heterogeneous fault-slip data with best-fit stress inversion methods. II. Compressional stress regimes

    Science.gov (United States)

    Tranos, Markos D.

    2018-02-01

    Synthetic heterogeneous fault-slip data as driven by Andersonian compressional stress tensors were used to examine the efficiency of best-fit stress inversion methods in separating them. Heterogeneous fault-slip data are separated only if (a) they have been driven by stress tensors defining 'hybrid' compression (R constitute a necessary discriminatory tool for the establishment and comparison of two compressional stress tensors determined by a best-fit stress inversion method. The best-fit stress inversion methods are not able to determine more than one 'real' compressional stress tensor, as far as the thrust stacking in an orogeny is concerned. They can only possibly discern stress differences in the late-orogenic faulting processes, but not between the main- and late-orogenic stages.

  3. Hyperspectral Image Classification Using Discriminative Dictionary Learning

    International Nuclear Information System (INIS)

    Zongze, Y; Hao, S; Kefeng, J; Huanxin, Z

    2014-01-01

    The hyperspectral image (HSI) processing community has witnessed a surge of papers focusing on the utilization of sparse prior for effective HSI classification. In sparse representation based HSI classification, there are two phases: sparse coding with an over-complete dictionary and classification. In this paper, we first apply a novel fisher discriminative dictionary learning method, which capture the relative difference in different classes. The competitive selection strategy ensures that atoms in the resulting over-complete dictionary are the most discriminative. Secondly, motivated by the assumption that spatially adjacent samples are statistically related and even belong to the same materials (same class), we propose a majority voting scheme incorporating contextual information to predict the category label. Experiment results show that the proposed method can effectively strengthen relative discrimination of the constructed dictionary, and incorporating with the majority voting scheme achieve generally an improved prediction performance

  4. A methodology for texture feature-based quality assessment in nucleus segmentation of histopathology image

    Directory of Open Access Journals (Sweden)

    Si Wen

    2017-01-01

    Full Text Available Context: Image segmentation pipelines often are sensitive to algorithm input parameters. Algorithm parameters optimized for a set of images do not necessarily produce good-quality-segmentation results for other images. Even within an image, some regions may not be well segmented due to a number of factors, including multiple pieces of tissue with distinct characteristics, differences in staining of the tissue, normal versus tumor regions, and tumor heterogeneity. Evaluation of quality of segmentation results is an important step in image analysis. It is very labor intensive to do quality assessment manually with large image datasets because a whole-slide tissue image may have hundreds of thousands of nuclei. Semi-automatic mechanisms are needed to assist researchers and application developers to detect image regions with bad segmentations efficiently. Aims: Our goal is to develop and evaluate a machine-learning-based semi-automated workflow to assess quality of nucleus segmentation results in a large set of whole-slide tissue images. Methods: We propose a quality control methodology, in which machine-learning algorithms are trained with image intensity and texture features to produce a classification model. This model is applied to image patches in a whole-slide tissue image to predict the quality of nucleus segmentation in each patch. The training step of our methodology involves the selection and labeling of regions by a pathologist in a set of images to create the training dataset. The image regions are partitioned into patches. A set of intensity and texture features is computed for each patch. A classifier is trained with the features and the labels assigned by the pathologist. At the end of this process, a classification model is generated. The classification step applies the classification model to unlabeled test images. Each test image is partitioned into patches. The classification model is applied to each patch to predict the patch

  5. [Comment on] Statistical discrimination

    Science.gov (United States)

    Chinn, Douglas

    In the December 8, 1981, issue of Eos, a news item reported the conclusion of a National Research Council study that sexual discrimination against women with Ph.D.'s exists in the field of geophysics. Basically, the item reported that even when allowances are made for motherhood the percentage of female Ph.D.'s holding high university and corporate positions is significantly lower than the percentage of male Ph.D.'s holding the same types of positions. The sexual discrimination conclusion, based only on these statistics, assumes that there are no basic psychological differences between men and women that might cause different populations in the employment group studied. Therefore, the reasoning goes, after taking into account possible effects from differences related to anatomy, such as women stopping their careers in order to bear and raise children, the statistical distributions of positions held by male and female Ph.D.'s ought to be very similar to one another. Any significant differences between the distributions must be caused primarily by sexual discrimination.

  6. Workplace discrimination and cancer.

    Science.gov (United States)

    McKenna, Maureen A; Fabian, Ellen; Hurley, Jessica E; McMahon, Brian T; West, Steven L

    2007-01-01

    Data from the Equal Employment Opportunity Commission (EEOC) Integrated Mission System database were analyzed with specific reference to allegations of workplace discrimination filed by individuals with cancer under ADA Title One. These 6,832 allegations, filed between July 27, 1992 and September 30, 2003, were compared to 167,798 allegations from a general disability population on the following dimensions: type of workplace discrimination; demographic characteristics of the charging parties (CPs); the industry designation, location, and size of employers; and the outcome or resolution of EEOC investigations. Results showed allegations derived from CPs with cancer were more likely than those in the general disability population to include issues involving discharge, terms and conditions of employment, lay-off, wages, and demotion. Compared to the general disability group, CPs with cancer were more likely to be female, older, and White. Allegations derived from CPs with cancer were also more likely to be filed against smaller employers (15-100 workers) or those in service industries. Finally, the resolution of allegations by CPs with cancer were more likely to be meritorious than those filed from the general disability population; that is, actual discrimination is more likely to have occurred.

  7. MO-FG-209-05: Towards a Feature-Based Anthropomorphic Model Observer

    International Nuclear Information System (INIS)

    Avanaki, A.

    2016-01-01

    This symposium will review recent advances in the simulation methods for evaluation of novel breast imaging systems – the subject of AAPM Task Group TG234. Our focus will be on the various approaches to development and validation of software anthropomorphic phantoms and their use in the statistical assessment of novel imaging systems using such phantoms along with computational models for the x-ray image formation process. Due to the dynamic development and complex design of modern medical imaging systems, the simulation of anatomical structures, image acquisition modalities, and the image perception and analysis offers substantial benefits of reduced cost, duration, and radiation exposure, as well as the known ground-truth and wide variability in simulated anatomies. For these reasons, Virtual Clinical Trials (VCTs) have been increasingly accepted as a viable tool for preclinical assessment of x-ray and other breast imaging methods. Activities of TG234 have encompassed the optimization of protocols for simulation studies, including phantom specifications, the simulated data representation, models of the imaging process, and statistical assessment of simulated images. The symposium will discuss the state-of-the-science of VCTs for novel breast imaging systems, emphasizing recent developments and future directions. Presentations will discuss virtual phantoms for intermodality breast imaging performance comparisons, extension of the breast anatomy simulation to the cellular level, optimized integration of the simulated imaging chain, and the novel directions in the observer models design. Learning Objectives: Review novel results in developing and applying virtual phantoms for inter-modality breast imaging performance comparisons; Discuss the efforts to extend the computer simulation of breast anatomy and pathology to the cellular level; Summarize the state of the science in optimized integration of modules in the simulated imaging chain; Compare novel directions

  8. MO-FG-209-05: Towards a Feature-Based Anthropomorphic Model Observer

    Energy Technology Data Exchange (ETDEWEB)

    Avanaki, A.

    2016-06-15

    This symposium will review recent advances in the simulation methods for evaluation of novel breast imaging systems – the subject of AAPM Task Group TG234. Our focus will be on the various approaches to development and validation of software anthropomorphic phantoms and their use in the statistical assessment of novel imaging systems using such phantoms along with computational models for the x-ray image formation process. Due to the dynamic development and complex design of modern medical imaging systems, the simulation of anatomical structures, image acquisition modalities, and the image perception and analysis offers substantial benefits of reduced cost, duration, and radiation exposure, as well as the known ground-truth and wide variability in simulated anatomies. For these reasons, Virtual Clinical Trials (VCTs) have been increasingly accepted as a viable tool for preclinical assessment of x-ray and other breast imaging methods. Activities of TG234 have encompassed the optimization of protocols for simulation studies, including phantom specifications, the simulated data representation, models of the imaging process, and statistical assessment of simulated images. The symposium will discuss the state-of-the-science of VCTs for novel breast imaging systems, emphasizing recent developments and future directions. Presentations will discuss virtual phantoms for intermodality breast imaging performance comparisons, extension of the breast anatomy simulation to the cellular level, optimized integration of the simulated imaging chain, and the novel directions in the observer models design. Learning Objectives: Review novel results in developing and applying virtual phantoms for inter-modality breast imaging performance comparisons; Discuss the efforts to extend the computer simulation of breast anatomy and pathology to the cellular level; Summarize the state of the science in optimized integration of modules in the simulated imaging chain; Compare novel directions

  9. Price Discrimination: A Classroom Experiment

    Science.gov (United States)

    Aguiló, Paula; Sard, Maria; Tugores, Maria

    2016-01-01

    In this article, the authors describe a classroom experiment aimed at familiarizing students with different types of price discrimination (first-, second-, and third-degree price discrimination). During the experiment, the students were asked to decide what tariffs to set as monopolists for each of the price discrimination scenarios under…

  10. Transgender Discrimination and the Law

    Science.gov (United States)

    Trotter, Richard

    2010-01-01

    An emerging area of law is developing regarding sex/gender identity discrimination, also referred to as transgender discrimination, as distinguished from discrimination based on sexual orientation. A transgendered individual is defined as "a person who has a gender-identity disorder which is a persistent discomfort about one?s assigned sex or…

  11. [Analysis of spectral features based on water content of desert vegetation].

    Science.gov (United States)

    Zhao, Zhao; Li, Xia; Yin, Ye-biao; Tang, Jin; Zhou, Sheng-bin

    2010-09-01

    By using HR-768 field-portable spectroradiometer made by the Spectra Vista Corporation (SVC) of America, the hyper-spectral data of nine types of desert plants were measured, and the water content of corresponding vegetation was determined by roasting in lab. The continuum of measured hyperspectral data was removed by using ENVI, and the relationship between the water content of vegetation and the reflectance spectrum was analyzed by using correlation coefficient method. The result shows that the correlation between the bands from 978 to 1030 nm and water content of vegetation is weak while it is better for the bands from 1133 to 1266 nm. The bands from 1374 to 1534 nm are the characteristic bands because of the correlation between them and water content is the best. By using cluster analysis and according to the water content, the vegetation could be marked off into three grades: high (>70%), medium (50%-70%) and low (<50%). The research reveals the relationship between water content of desert vegetation and hyperspectral data, and provides basis for the analysis of area in desert and the monitoring of desert vegetation by using remote sensing data.

  12. A feature based comparison of pen and swipe based signature characteristics.

    Science.gov (United States)

    Robertson, Joshua; Guest, Richard

    2015-10-01

    Dynamic Signature Verification (DSV) is a biometric modality that identifies anatomical and behavioral characteristics when an individual signs their name. Conventionally signature data has been captured using pen/tablet apparatus. However, the use of other devices such as the touch-screen tablets has expanded in recent years affording the possibility of assessing biometric interaction on this new technology. To explore the potential of employing DSV techniques when a user signs or swipes with their finger, we report a study to correlate pen and finger generated features. Investigating the stability and correlation between a set of characteristic features recorded in participant's signatures and touch-based swipe gestures, a statistical analysis was conducted to assess consistency between capture scenarios. The results indicate that there is a range of static and dynamic features such as the rate of jerk, size, duration and the distance the pen traveled that can lead to interoperability between these two systems for input methods for use within a potential biometric context. It can be concluded that this data indicates that a general principle is that the same underlying constructional mechanisms are evident. Copyright © 2015 Elsevier B.V. All rights reserved.

  13. A foreground object features-based stereoscopic image visual comfort assessment model

    Science.gov (United States)

    Jin, Xin; Jiang, G.; Ying, H.; Yu, M.; Ding, S.; Peng, Z.; Shao, F.

    2014-11-01

    Since stereoscopic images provide observers with both realistic and discomfort viewing experience, it is necessary to investigate the determinants of visual discomfort. By considering that foreground object draws most attention when human observing stereoscopic images. This paper proposes a new foreground object based visual comfort assessment (VCA) metric. In the first place, a suitable segmentation method is applied to disparity map and then the foreground object is ascertained as the one having the biggest average disparity. In the second place, three visual features being average disparity, average width and spatial complexity of foreground object are computed from the perspective of visual attention. Nevertheless, object's width and complexity do not consistently influence the perception of visual comfort in comparison with disparity. In accordance with this psychological phenomenon, we divide the whole images into four categories on the basis of different disparity and width, and exert four different models to more precisely predict its visual comfort in the third place. Experimental results show that the proposed VCA metric outperformance other existing metrics and can achieve a high consistency between objective and subjective visual comfort scores. The Pearson Linear Correlation Coefficient (PLCC) and Spearman Rank Order Correlation Coefficient (SROCC) are over 0.84 and 0.82, respectively.

  14. Color Feature-Based Object Tracking through Particle Swarm Optimization with Improved Inertia Weight.

    Science.gov (United States)

    Guo, Siqiu; Zhang, Tao; Song, Yulong; Qian, Feng

    2018-04-23

    This paper presents a particle swarm tracking algorithm with improved inertia weight based on color features. The weighted color histogram is used as the target feature to reduce the contribution of target edge pixels in the target feature, which makes the algorithm insensitive to the target non-rigid deformation, scale variation, and rotation. Meanwhile, the influence of partial obstruction on the description of target features is reduced. The particle swarm optimization algorithm can complete the multi-peak search, which can cope well with the object occlusion tracking problem. This means that the target is located precisely where the similarity function appears multi-peak. When the particle swarm optimization algorithm is applied to the object tracking, the inertia weight adjustment mechanism has some limitations. This paper presents an improved method. The concept of particle maturity is introduced to improve the inertia weight adjustment mechanism, which could adjust the inertia weight in time according to the different states of each particle in each generation. Experimental results show that our algorithm achieves state-of-the-art performance in a wide range of scenarios.

  15. Novel discrimination parameters for neutron-gamma discrimination with liquid scintillation detectors using wavelet transform

    International Nuclear Information System (INIS)

    Singh, H.; Singh, S.

    2015-01-01

    It has been observed that the discrimination performance of the wavelet transform method strongly depends on definition of discrimination parameters. These parameters are usually obtained from a combination of scaling functions at different scales, which represents the energy density of the wavelet coefficients. In this paper, the discrete wavelet transform (DWT) at minimum possible values of scale was investigated. Novel pulse shape discrimination parameters have been proposed for neutron and gamma discrimination in a mixed radiation field and tested with modeled pulses. The performance of these parameters was also validated in terms of quality of discrimination using experimental data of mixed events from an AmBe source collected with BC501 liquid scintillation detector. The quality of discrimination was evaluated by calculating a figure of merit (FOM) with all parameters under same experimental and simulation conditions. The FOM obtained with the proposed novel parameters was also compared with the charge comparison method. The proposed parameters exhibit better FOM as compared to the charge comparison method when high levels of noise are present in the data

  16. HYDROLOGIC AND FEATURE-BASED SURFACE ANALYSIS FOR TOOL MARK INVESTIGATION ON ARCHAEOLOGICAL FINDS

    Directory of Open Access Journals (Sweden)

    K. Kovács

    2012-07-01

    Full Text Available The improvement of detailed surface documentation methods provides unique tool mark-study opportunities in the field of archaeological researches. One of these data collection techniques is short-range laser scanning, which creates a digital copy of the object’s morphological characteristics from high-resolution datasets. The aim of our work was the accurate documentation of a Bronze Age sluice box from Mitterberg, Austria with a spatial resolution of 0.2 mm. Furthermore, the investigation of the entirely preserved tool marks on the surface of this archaeological find was also accomplished by these datasets. The methodology of this tool mark-study can be summarized in the following way: At first, a local hydrologic analysis has been applied to separate the various patterns of tools on the finds’ surface. As a result, the XYZ coordinates of the special points, which represent the edge lines of the sliding tool marks, were calculated by buffer operations in a GIS environment. During the second part of the workflow, these edge points were utilized to manually clip the triangle meshes of these patterns in reverse engineering software. Finally, circle features were generated and analysed to determine the different sections along these sliding tool marks. In conclusion, the movement of the hand tool could be reproduced by the spatial analysis of the created features, since the horizontal and vertical position of the defined circle centre points indicated the various phases of the movements. This research shows an exact workflow to determine the fine morphological structures on the surface of the archaeological find.

  17. SU-E-J-98: Radiogenomics: Correspondence Between Imaging and Genetic Features Based On Clustering Analysis

    International Nuclear Information System (INIS)

    Harmon, S; Wendelberger, B; Jeraj, R

    2014-01-01

    Purpose: Radiogenomics aims to establish relationships between patient genotypes and imaging phenotypes. An open question remains on how best to integrate information from these distinct datasets. This work investigates if similarities in genetic features across patients correspond to similarities in PET-imaging features, assessed with various clustering algorithms. Methods: [ 18 F]FDG PET data was obtained for 26 NSCLC patients from a public database (TCIA). Tumors were contoured using an in-house segmentation algorithm combining gradient and region-growing techniques; resulting ROIs were used to extract 54 PET-based features. Corresponding genetic microarray data containing 48,778 elements were also obtained for each tumor. Given mismatch in feature sizes, two dimension reduction techniques were also applied to the genetic data: principle component analysis (PCA) and selective filtering of 25 NSCLC-associated genes-ofinterest (GOI). Gene datasets (full, PCA, and GOI) and PET feature datasets were independently clustered using K-means and hierarchical clustering using variable number of clusters (K). Jaccard Index (JI) was used to score similarity of cluster assignments across different datasets. Results: Patient clusters from imaging data showed poor similarity to clusters from gene datasets, regardless of clustering algorithms or number of clusters (JI mean = 0.3429±0.1623). Notably, we found clustering algorithms had different sensitivities to data reduction techniques. Using hierarchical clustering, the PCA dataset showed perfect cluster agreement to the full-gene set (JI =1) for all values of K, and the agreement between the GOI set and the full-gene set decreased as number of clusters increased (JI=0.9231 and 0.5769 for K=2 and 5, respectively). K-means clustering assignments were highly sensitive to data reduction and showed poor stability for different values of K (JI range : 0.2301–1). Conclusion: Using commonly-used clustering algorithms, we found

  18. SU-E-J-98: Radiogenomics: Correspondence Between Imaging and Genetic Features Based On Clustering Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Harmon, S; Wendelberger, B [University of Wisconsin-Madison, Madison, WI (United States); Jeraj, R [University of Wisconsin-Madison, Madison, WI (United States); University of Ljubljana (Slovenia)

    2014-06-01

    Purpose: Radiogenomics aims to establish relationships between patient genotypes and imaging phenotypes. An open question remains on how best to integrate information from these distinct datasets. This work investigates if similarities in genetic features across patients correspond to similarities in PET-imaging features, assessed with various clustering algorithms. Methods: [{sup 18}F]FDG PET data was obtained for 26 NSCLC patients from a public database (TCIA). Tumors were contoured using an in-house segmentation algorithm combining gradient and region-growing techniques; resulting ROIs were used to extract 54 PET-based features. Corresponding genetic microarray data containing 48,778 elements were also obtained for each tumor. Given mismatch in feature sizes, two dimension reduction techniques were also applied to the genetic data: principle component analysis (PCA) and selective filtering of 25 NSCLC-associated genes-ofinterest (GOI). Gene datasets (full, PCA, and GOI) and PET feature datasets were independently clustered using K-means and hierarchical clustering using variable number of clusters (K). Jaccard Index (JI) was used to score similarity of cluster assignments across different datasets. Results: Patient clusters from imaging data showed poor similarity to clusters from gene datasets, regardless of clustering algorithms or number of clusters (JI{sub mean}= 0.3429±0.1623). Notably, we found clustering algorithms had different sensitivities to data reduction techniques. Using hierarchical clustering, the PCA dataset showed perfect cluster agreement to the full-gene set (JI =1) for all values of K, and the agreement between the GOI set and the full-gene set decreased as number of clusters increased (JI=0.9231 and 0.5769 for K=2 and 5, respectively). K-means clustering assignments were highly sensitive to data reduction and showed poor stability for different values of K (JI{sub range}: 0.2301–1). Conclusion: Using commonly-used clustering algorithms

  19. Discrimination Between Inrush and Short Circuit Currents in Differential Protection of Power Transformer Based on Correlation Method Using the Wavelet Transform

    OpenAIRE

    M. Rasoulpoor; M. Banejad; A. Ahmadyfard

    2011-01-01

    This paper presents a novel technique for transformer differential protection to prevent incorrect operation due to inrush current. The proposed method in this paper is based on time-frequency transform known as the Wavelet transform. The discrete Wavelet transform is used for analysis the differential current signals in time and frequency domains. The investigation on the energy distribution of the signal on the discrete Wavelet transform components shows the difference distribution between ...

  20. Short-term retention of visual information: Evidence in support of feature-based attention as an underlying mechanism.

    Science.gov (United States)

    Sneve, Markus H; Sreenivasan, Kartik K; Alnæs, Dag; Endestad, Tor; Magnussen, Svein

    2015-01-01

    Retention of features in visual short-term memory (VSTM) involves maintenance of sensory traces in early visual cortex. However, the mechanism through which this is accomplished is not known. Here, we formulate specific hypotheses derived from studies on feature-based attention to test the prediction that visual cortex is recruited by attentional mechanisms during VSTM of low-level features. Functional magnetic resonance imaging (fMRI) of human visual areas revealed that neural populations coding for task-irrelevant feature information are suppressed during maintenance of detailed spatial frequency memory representations. The narrow spectral extent of this suppression agrees well with known effects of feature-based attention. Additionally, analyses of effective connectivity during maintenance between retinotopic areas in visual cortex show that the observed highlighting of task-relevant parts of the feature spectrum originates in V4, a visual area strongly connected with higher-level control regions and known to convey top-down influence to earlier visual areas during attentional tasks. In line with this property of V4 during attentional operations, we demonstrate that modulations of earlier visual areas during memory maintenance have behavioral consequences, and that these modulations are a result of influences from V4. Copyright © 2014 Elsevier Ltd. All rights reserved.

  1. Optical methods and differential scanning calorimetry as a potential tool for discrimination of olive oils (extra virgin and mix with vegetable oils)

    Science.gov (United States)

    Nikolova, Kr.; Yovcheva, T.; Marudova, M.; Eftimov, T.; Bodurov, I.; Viraneva, A.; Vlaeva, I.

    2016-03-01

    Eleven samples from olive oil have been investigated using four physical methods - refractive index measurement, fluorescence spectra, color parameters and differential scanning colorimetry. In pomace olive oil (POO) and extra virgin olive oil (EVOO) the oleic acid (65.24 %-78.40 %) predominates over palmitic (10.47 %-15.07 %) and linoleic (5.26 %-13.92 %) acids. The fluorescence spectra contain three peaks related to oxidation products at about λ = (500-540) nm, chlorophyll content at about λ = (675-680) nm and non determined pigments at λ = (700-750) nm. The melting point for EVOO and POO is between -1 °C and -6 °C. In contrast, the salad olive oils melt between -24 °C and -30 °C. The refractive index for EVOO is lower than that for mixed olive oils. The proposed physical methods could be used for fast and simple detection of vegetable oils in EVOO without use of chemical substances. The experimental results are in accordance with those obtained by chemical analysis.

  2. 7 CFR 15.3 - Discrimination prohibited.

    Science.gov (United States)

    2010-01-01

    ..., directly or through contractual or other arrangements, utilize criteria or methods of administration which... determining the site or location of facilities, an applicant or recipient may not make selections with the... participation in the Direct Distribution Program. (ii) Discrimination in the allocation of food to eligible...

  3. Subjective performance evaluation and gender discrimination

    NARCIS (Netherlands)

    Maas, V.S.; Torres-Gonzalez, R.

    2011-01-01

    Gender discrimination continues to be a problem in organizations. It is therefore important that organizations use performance evaluation methods that ensure equal opportunities for men and women. This article reports the results of an experiment to investigate whether and, if so, how the gender of

  4. Discriminative power of visual attributes in dermatology

    NARCIS (Netherlands)

    Giotis, Ioannis; Visser, Margaretha; Jonkman, Marcel; Petkov, Nicolai

    Background/purpose: Visual characteristics such as color and shape of skin lesions play an important role in the diagnostic process. In this contribution, we quantify the discriminative power of such attributes using an information theoretical approach. Methods: We estimate the probability of

  5. Optimal Experimental Design for Model Discrimination

    Science.gov (United States)

    Myung, Jay I.; Pitt, Mark A.

    2009-01-01

    Models of a psychological process can be difficult to discriminate experimentally because it is not easy to determine the values of the critical design variables (e.g., presentation schedule, stimulus structure) that will be most informative in differentiating them. Recent developments in sampling-based search methods in statistics make it…

  6. New method to discriminate between cathepsin B and cathepsin L in crude extracts from fish muscle based on a simple acidification procedure

    DEFF Research Database (Denmark)

    Godiksen, Helene; Nielsen, Henrik Hauch

    2007-01-01

    A new and simple method to distinguish between cathepsin B and cathepsin L in crude extracts of herring (Clupea harengus) muscle has been established. An acid treatment of crude extracts (exposed to pH 3 for 5 min) activated a latent form of cathepsin L and inactivated cathepsin B. Furthermore......, in neutral crude extract, the hydrolysis of benzyloxycarbonyl-L-phenylalanyl-L-arginyl-4-methylcoumarine (Z-Phe-Arg-MCA) (cathepsin B and cathepsin L substrates) was between 0% and 15% of the hydrolysis of benzyloxycarbonyl-L-arginyl-L-arginyl-7-amino-4-methylcoumarine (Z-Arg-Arg-MCA; cathepsin B substrate......). Cathepsin B activity is measured in neutral extract using the specific cathepsin B substrate Z-Arg-Arg-MCA and cathepsin L activity is measured in acid-treated extract with Z-Phe-Arg-MCA as substrate. The specific cathepsin B inhibitor, CA-074, did not inhibit the Z-Arg-Arg-MCA significantly without...

  7. Evaluation of the standard normal variate method for Laser-Induced Breakdown Spectroscopy data treatment applied to the discrimination of painting layers

    Science.gov (United States)

    Syvilay, D.; Wilkie-Chancellier, N.; Trichereau, B.; Texier, A.; Martinez, L.; Serfaty, S.; Detalle, V.

    2015-12-01

    Nowadays, Laser-Induced Breakdown Spectroscopy (LIBS) is frequently used for in situ analyses to identify pigments from mural paintings. Nonetheless, in situ analyses require a robust instrumentation in order to face to hard experimental conditions. This may imply variation of fluencies and thus inducing variation of LIBS signal, which degrades spectra and then results. Usually, to overcome these experimental errors, LIBS signal is processed. Signal processing methods most commonly used are the baseline subtraction and the normalization by using a spectral line. However, the latter suggests that this chosen element is a constant component of the material, which may not be the case in paint layers organized in stratigraphic layers. For this reason, it is sometimes difficult to apply this normalization. In this study, another normalization will be carried out to throw off these signal variations. Standard normal variate (SNV) is a normalization designed for these conditions. It is sometimes implemented in Diffuse Reflectance Infrared Fourier Transform Spectroscopy and in Raman Spectroscopy but rarely in LIBS. The SNV transformation is not newly applied on LIBS data, but for the first time the effect of SNV on LIBS spectra was evaluated in details (energy of laser, shot by shot, quantification). The aim of this paper is the quick visualization of the different layers of a stratigraphic painting sample by simple data representations (3D or 2D) after SNV normalization. In this investigation, we showed the potential power of SNV transformation to overcome undesired LIBS signal variations but also its limit of application. This method appears as a promising way to normalize LIBS data, which may be interesting for in-situ depth analyses.

  8. Gender discrimination and nursing: α literature review.

    Science.gov (United States)

    Kouta, Christiana; Kaite, Charis P

    2011-01-01

    This article aims to examine gender stereotypes in relation to men in nursing, discuss gender discrimination cases in nursing, and explore methods used for promoting equal educational opportunities during nursing studies. The literature review was based on related databases, such as CINAHL, Science Direct, MEDLINE, and EBSCO. Legal case studies are included in order to provide a more practical example of those barriers existing for men pursuing nursing, as well as statistical data concerning gender discrimination and male attrition to nursing schools in relation to those barriers. These strengthen the validity of the manuscript. Literature review showed that gender discrimination is still prevalent within nursing profession. Nursing faculty should prepare male nursing students to interact effectively with female clients as well. Role modeling the therapeutic relationship with clients is one strategy that may help male students. In general, the faculty should provide equal learning opportunities to nursing students. Copyright © 2011 Elsevier Inc. All rights reserved.

  9. PCR method for the rapid detection and discrimination of Legionella spp. based on the amplification of pcs, pmtA, and 16S rRNA genes.

    Science.gov (United States)

    Janczarek, Monika; Palusińska-Szysz, Marta

    2016-05-01

    Legionella bacteria are organisms of public health interest due to their ability to cause pneumonia (Legionnaires' disease) in susceptible humans and their ubiquitous presence in water supply systems. Rapid diagnosis of Legionnaires' disease allows the use of therapy specific for the disease. L. pneumophila serogroup 1 is the most common cause of infection acquired in community and hospital environments. The non-L. pneumophila infections are likely under-detected because of a lack of effective diagnosis. In this work, simplex and duplex PCR assays with the use of new molecular markers pcs and pmtA involved in phosphatidylcholine synthesis were specified for rapid and cost-efficient identification and distinguishing Legionella species. The sets of primers developed were found to be sensitive and specific for reliable detection of Legionella belonging to the eight most clinically relevant species. Among these, four primer sets I, II, VI, and VII used for duplex-PCRs proved to have the highest identification power and reliability in the detection of the bacteria. Application of this PCR-based method should improve detection of Legionella spp. in both clinical and environmental settings and facilitate molecular typing of these organisms.

  10. Morphing the feature-based multi-blocks of normative/healthy vertebral geometries to scoliosis vertebral geometries: development of personalized finite element models.

    Science.gov (United States)

    Hadagali, Prasannaah; Peters, James R; Balasubramanian, Sriram

    2018-03-12

    Personalized Finite Element (FE) models and hexahedral elements are preferred for biomechanical investigations. Feature-based multi-block methods are used to develop anatomically accurate personalized FE models with hexahedral mesh. It is tedious to manually construct multi-blocks for large number of geometries on an individual basis to develop personalized FE models. Mesh-morphing method mitigates the aforementioned tediousness in meshing personalized geometries every time, but leads to element warping and loss of geometrical data. Such issues increase in magnitude when normative spine FE model is morphed to scoliosis-affected spinal geometry. The only way to bypass the issue of hex-mesh distortion or loss of geometry as a result of morphing is to rely on manually constructing the multi-blocks for scoliosis-affected spine geometry of each individual, which is time intensive. A method to semi-automate the construction of multi-blocks on the geometry of scoliosis vertebrae from the existing multi-blocks of normative vertebrae is demonstrated in this paper. High-quality hexahedral elements were generated on the scoliosis vertebrae from the morphed multi-blocks of normative vertebrae. Time taken was 3 months to construct the multi-blocks for normative spine and less than a day for scoliosis. Efforts taken to construct multi-blocks on personalized scoliosis spinal geometries are significantly reduced by morphing existing multi-blocks.

  11. Perceptual Adaptation of Voice Gender Discrimination with Spectrally Shifted Vowels

    Science.gov (United States)

    Li, Tianhao; Fu, Qian-Jie

    2011-01-01

    Purpose: To determine whether perceptual adaptation improves voice gender discrimination of spectrally shifted vowels and, if so, which acoustic cues contribute to the improvement. Method: Voice gender discrimination was measured for 10 normal-hearing subjects, during 5 days of adaptation to spectrally shifted vowels, produced by processing the…

  12. Discrimination, Mastery, and Depressive Symptoms among African American Men

    Science.gov (United States)

    Watkins, Daphne C.; Hudson, Darrell L.; Caldwell, Cleopatra Howard; Siefert, Kristine; Jackson, James S.

    2011-01-01

    Purpose: This study examines the influence of discrimination and mastery on depressive symptoms for African American men at young (18-34), middle (35-54), and late (55+) adulthood. Method: Analyses are based on responses from 1,271 African American men from the National Survey of American Life (NSAL). Results: Discrimination was significantly…

  13. Haptic Discrimination of Distance

    Science.gov (United States)

    van Beek, Femke E.; Bergmann Tiest, Wouter M.; Kappers, Astrid M. L.

    2014-01-01

    While quite some research has focussed on the accuracy of haptic perception of distance, information on the precision of haptic perception of distance is still scarce, particularly regarding distances perceived by making arm movements. In this study, eight conditions were measured to answer four main questions, which are: what is the influence of reference distance, movement axis, perceptual mode (active or passive) and stimulus type on the precision of this kind of distance perception? A discrimination experiment was performed with twelve participants. The participants were presented with two distances, using either a haptic device or a real stimulus. Participants compared the distances by moving their hand from a start to an end position. They were then asked to judge which of the distances was the longer, from which the discrimination threshold was determined for each participant and condition. The precision was influenced by reference distance. No effect of movement axis was found. The precision was higher for active than for passive movements and it was a bit lower for real stimuli than for rendered stimuli, but it was not affected by adding cutaneous information. Overall, the Weber fraction for the active perception of a distance of 25 or 35 cm was about 11% for all cardinal axes. The recorded position data suggest that participants, in order to be able to judge which distance was the longer, tried to produce similar speed profiles in both movements. This knowledge could be useful in the design of haptic devices. PMID:25116638

  14. Haptic discrimination of distance.

    Directory of Open Access Journals (Sweden)

    Femke E van Beek

    Full Text Available While quite some research has focussed on the accuracy of haptic perception of distance, information on the precision of haptic perception of distance is still scarce, particularly regarding distances perceived by making arm movements. In this study, eight conditions were measured to answer four main questions, which are: what is the influence of reference distance, movement axis, perceptual mode (active or passive and stimulus type on the precision of this kind of distance perception? A discrimination experiment was performed with twelve participants. The participants were presented with two distances, using either a haptic device or a real stimulus. Participants compared the distances by moving their hand from a start to an end position. They were then asked to judge which of the distances was the longer, from which the discrimination threshold was determined for each participant and condition. The precision was influenced by reference distance. No effect of movement axis was found. The precision was higher for active than for passive movements and it was a bit lower for real stimuli than for rendered stimuli, but it was not affected by adding cutaneous information. Overall, the Weber fraction for the active perception of a distance of 25 or 35 cm was about 11% for all cardinal axes. The recorded position data suggest that participants, in order to be able to judge which distance was the longer, tried to produce similar speed profiles in both movements. This knowledge could be useful in the design of haptic devices.

  15. Discriminative Relational Topic Models.

    Science.gov (United States)

    Chen, Ning; Zhu, Jun; Xia, Fei; Zhang, Bo

    2015-05-01

    Relational topic models (RTMs) provide a probabilistic generative process to describe both the link structure and document contents for document networks, and they have shown promise on predicting network structures and discovering latent topic representations. However, existing RTMs have limitations in both the restricted model expressiveness and incapability of dealing with imbalanced network data. To expand the scope and improve the inference accuracy of RTMs, this paper presents three extensions: 1) unlike the common link likelihood with a diagonal weight matrix that allows the-same-topic interactions only, we generalize it to use a full weight matrix that captures all pairwise topic interactions and is applicable to asymmetric networks; 2) instead of doing standard Bayesian inference, we perform regularized Bayesian inference (RegBayes) with a regularization parameter to deal with the imbalanced link structure issue in real networks and improve the discriminative ability of learned latent representations; and 3) instead of doing variational approximation with strict mean-field assumptions, we present collapsed Gibbs sampling algorithms for the generalized relational topic models by exploring data augmentation without making restricting assumptions. Under the generic RegBayes framework, we carefully investigate two popular discriminative loss functions, namely, the logistic log-loss and the max-margin hinge loss. Experimental results on several real network datasets demonstrate the significance of these extensions on improving prediction performance.

  16. 3-D topological signatures and a new discrimination method for single-electron events and 0νββ events in CdZnTe: A Monte Carlo simulation study

    Energy Technology Data Exchange (ETDEWEB)

    Zeng, Ming; Li, Teng-Lin; Cang, Ji-Rong [Key Laboratory of Particle & Radiation Imaging (Tsinghua University), Ministry of Education (China); Department of Engineering Physics, Tsinghua University, Beijing 100084 (China); Zeng, Zhi, E-mail: zengzhi@tsinghua.edu.cn [Key Laboratory of Particle & Radiation Imaging (Tsinghua University), Ministry of Education (China); Department of Engineering Physics, Tsinghua University, Beijing 100084 (China); Fu, Jian-Qiang; Zeng, Wei-He; Cheng, Jian-Ping; Ma, Hao; Liu, Yi-Nong [Key Laboratory of Particle & Radiation Imaging (Tsinghua University), Ministry of Education (China); Department of Engineering Physics, Tsinghua University, Beijing 100084 (China)

    2017-06-21

    In neutrinoless double beta (0νββ) decay experiments, the diversity of topological signatures of different particles provides an important tool to distinguish double beta events from background events and reduce background rates. Aiming at suppressing the single-electron backgrounds which are most challenging, several groups have established Monte Carlo simulation packages to study the topological characteristics of single-electron events and 0νββ events and develop methods to differentiate them. In this paper, applying the knowledge of graph theory, a new topological signature called REF track (Refined Energy-Filtered track) is proposed and proven to be an accurate approximation of the real particle trajectory. Based on the analysis of the energy depositions along the REF track of single-electron events and 0νββ events, the REF energy deposition models for both events are proposed to indicate the significant differences between them. With these differences, this paper presents a new discrimination method, which, in the Monte Carlo simulation, achieved a single-electron rejection factor of 93.8±0.3 (stat.)% as well as a 0νββ efficiency of 85.6±0.4 (stat.)% with optimized parameters in CdZnTe.

  17. Explosion Generated Seismic Waves and P/S Methods of Discrimination from Earthquakes with Insights from the Nevada Source Physics Experiments

    Science.gov (United States)

    Walter, W. R.; Ford, S. R.; Pitarka, A.; Pyle, M. L.; Pasyanos, M.; Mellors, R. J.; Dodge, D. A.

    2017-12-01

    The relative amplitudes of seismic P-waves to S-waves are effective at identifying underground explosions among a background of natural earthquakes. These P/S methods appear to work best at frequencies above 2 Hz and at regional distances ( >200 km). We illustrate this with a variety of historic nuclear explosion data as well as with the recent DPRK nuclear tests. However, the physical basis for the generation of explosion S-waves, and therefore the predictability of this P/S technique as a function of path, frequency and event properties such as size, depth, and geology, remains incompletely understood. A goal of current research, such as the Source Physics Experiments (SPE), is to improve our physical understanding of the mechanisms of explosion S-wave generation and advance our ability to numerically model and predict them. The SPE conducted six chemical explosions between 2011 and 2016 in the same borehole in granite in southern Nevada. The explosions were at a variety of depths and sizes, ranging from 0.1 to 5 tons TNT equivalent yield. The largest were observed at near regional distances, with P/S ratios comparable to much larger historic nuclear tests. If we control for material property effects, the explosions have very similar P/S ratios independent of yield or magnitude. These results are consistent with explosion S-waves coming mainly from conversion of P- and surface waves, and are inconsistent with source-size based models. A dense sensor deployment for the largest SPE explosion allowed this conversion to be mapped in detail. This is good news for P/S explosion identification, which can work well for very small explosions and may be ultimately limited by S-wave detection thresholds. The SPE also showed explosion P-wave source models need to be updated for small and/or deeply buried cases. We are developing new P- and S-wave explosion models that better match all the empirical data. Historic nuclear explosion seismic data shows that the media in which

  18. Women Status and their Discrimination

    OpenAIRE

    PEŠKOVÁ, Pavlína

    2008-01-01

    My work deal with women status and their discrimination. Chapter one contains women status in different historical periods and development of their status to bigger equal with men. There is also written about present feminist trends. Chapter two is about women discrimination. There is about women´ job discrimination, job segregation according to gender and inequality in payment. There is also written about women status at home and unequal duties at home among family mates. Chapter three is ab...

  19. Two-dimensional neutron scintillation detector with optimal gamma discrimination

    International Nuclear Information System (INIS)

    Kanyo, M.; Reinartz, R.; Schelten, J.; Mueller, K.D.

    1993-01-01

    The gamma sensitivity of a two-dimensional scintillation neutron detector based on position sensitive photomultipliers (Hamamatsu R2387 PM) has been minimized by a digital differential discrimination unit. Since the photomultiplier gain is position-dependent by ±25% a discrimination unit was developed where digital upper and lower discrimination levels are set due to the position-dependent photomultiplier gain obtained from calibration measurements. By this method narrow discriminator windows can be used to reduce the gamma background drastically without effecting the neutron sensitivity of the detector. The new discrimination method and its performance tested by neutron measurements will be described. Experimental results concerning spatial resolution and γ-sensitivity are presented

  20. Genetic discrimination: international perspectives.

    Science.gov (United States)

    Otlowski, M; Taylor, S; Bombard, Y

    2012-01-01

    Genetic discrimination (GD) is a complex, multifaceted ethical, psychosocial, and legal phenomenon. It is defined as the differential treatment of asymptomatic individuals or their relatives on the basis of their real or assumed genetic characteristics. This article presents an overview of GD within the contemporary international context. It describes the concept of GD and its contextual features, reviews research evidence regarding people's experiences of GD and the impact of GD within a range of domains, and provides an overview of legal and policy responses to GD that have emerged globally. We argue that GD is a significant and internationally established phenomenon that requires multilevel responses to ensure social justice and equitable outcomes for all citizens. Future research should monitor GD and its impacts within the community as well as institutions and should evaluate the effectiveness of legislative, policy, community education, and systemic responses.

  1. Gaussian discriminating strength

    Science.gov (United States)

    Rigovacca, L.; Farace, A.; De Pasquale, A.; Giovannetti, V.

    2015-10-01

    We present a quantifier of nonclassical correlations for bipartite, multimode Gaussian states. It is derived from the Discriminating Strength measure, introduced for finite dimensional systems in Farace et al., [New J. Phys. 16, 073010 (2014), 10.1088/1367-2630/16/7/073010]. As the latter the new measure exploits the quantum Chernoff bound to gauge the susceptibility of the composite system with respect to local perturbations induced by unitary gates extracted from a suitable set of allowed transformations (the latter being identified by posing some general requirements). Closed expressions are provided for the case of two-mode Gaussian states obtained by squeezing or by linearly mixing via a beam splitter a factorized two-mode thermal state. For these density matrices, we study how nonclassical correlations are related with the entanglement present in the system and with its total photon number.

  2. Weight discrimination and bullying.

    Science.gov (United States)

    Puhl, Rebecca M; King, Kelly M

    2013-04-01

    Despite significant attention to the medical impacts of obesity, often ignored are the negative outcomes that obese children and adults experience as a result of stigma, bias, and discrimination. Obese individuals are frequently stigmatized because of their weight in many domains of daily life. Research spanning several decades has documented consistent weight bias and stigmatization in employment, health care, schools, the media, and interpersonal relationships. For overweight and obese youth, weight stigmatization translates into pervasive victimization, teasing, and bullying. Multiple adverse outcomes are associated with exposure to weight stigmatization, including depression, anxiety, low self-esteem, body dissatisfaction, suicidal ideation, poor academic performance, lower physical activity, maladaptive eating behaviors, and avoidance of health care. This review summarizes the nature and extent of weight stigmatization against overweight and obese individuals, as well as the resulting consequences that these experiences create for social, psychological, and physical health for children and adults who are targeted. Copyright © 2013 Elsevier Ltd. All rights reserved.

  3. Perceived discrimination: why applicants and employees expect and perceive discrimination

    NARCIS (Netherlands)

    Abu Ghazaleh, N.

    2012-01-01

    In this dissertation we have investigated perceptions of discrimination. We have shown discrimination exists in the eyes of applicants and employees and especially when from an ethnic minority group. There are psychological variables that influence these perceptions differently for minority and

  4. Estimating the mental health costs of racial discrimination

    Directory of Open Access Journals (Sweden)

    Amanuel Elias

    2016-11-01

    Full Text Available Abstract Background Racial discrimination is a pervasive social problem in several advanced countries such as the U.S., U.K., and Australia. Public health research also indicates a range of associations between exposure to racial discrimination and negative health, particularly, mental health including depression, anxiety, and post-traumatic stress disorder (PTSD. However, the direct negative health impact of racial discrimination has not been costed so far although economists have previously estimated indirect non-health related productivity costs. In this study, we estimate the burden of disease due to exposure to racial discrimination and measure the cost of this exposure. Methods Using prevalence surveys and data on the association of racial discrimination with health outcomes from a global meta-analysis, we apply a cost of illness method to measure the impact of racial discrimination. This estimate indicates the direct health cost attributable to racial discrimination and we convert the estimates to monetary values based on conventional parameters. Results Racial discrimination costs the Australian economy 235,452 in disability adjusted life years lost, equivalent to $37.9 billion per annum, roughly 3.02% of annual gross domestic product (GDP over 2001–11, indicating a sizeable loss for the economy. Conclusion Substantial cost is incurred due to increased prevalence of racial discrimination as a result of its association with negative health outcomes (e.g. depression, anxiety and PTSD. This implies that potentially significant cost savings can be made through measures that target racial discrimination. Our research contributes to the debate on the social impact of racial discrimination, with implications for policies and efforts addressing it.

  5. Perceived weight discrimination and obesity.

    Directory of Open Access Journals (Sweden)

    Angelina R Sutin

    Full Text Available Weight discrimination is prevalent in American society. Although associated consistently with psychological and economic outcomes, less is known about whether weight discrimination is associated with longitudinal changes in obesity. The objectives of this research are (1 to test whether weight discrimination is associated with risk of becoming obese (Body Mass Index≥30; BMI by follow-up among those not obese at baseline, and (2 to test whether weight discrimination is associated with risk of remaining obese at follow-up among those already obese at baseline. Participants were drawn from the Health and Retirement Study, a nationally representative longitudinal survey of community-dwelling US residents. A total of 6,157 participants (58.6% female completed the discrimination measure and had weight and height available from the 2006 and 2010 assessments. Participants who experienced weight discrimination were approximately 2.5 times more likely to become obese by follow-up (OR = 2.54, 95% CI = 1.58-4.08 and participants who were obese at baseline were three times more likely to remain obese at follow up (OR = 3.20, 95% CI = 2.06-4.97 than those who had not experienced such discrimination. These effects held when controlling for demographic factors (age, sex, ethnicity, education and when baseline BMI was included as a covariate. These effects were also specific to weight discrimination; other forms of discrimination (e.g., sex, race were unrelated to risk of obesity at follow-up. The present research demonstrates that, in addition to poorer mental health outcomes, weight discrimination has implications for obesity. Rather than motivating individuals to lose weight, weight discrimination increases risk for obesity.

  6. Perceived Discrimination in LGBTIQ Discourse: A Typology of Verbal Discrimination

    Directory of Open Access Journals (Sweden)

    Sol Rojas Lizana

    2014-08-01

    Full Text Available New within the field of Discourse Analysis, Perceived Discrimination (PD is the study of discourse that focuses on the perspective of the victims of discrimination. This article explores the experiences of verbal discrimination as reported by eighteen LGBTIQ participants during semi-structured, co-constructed interviews. Data were classified in order to develop a taxonomy of discrimination based on Mellor’s (2003, 2004. This taxonomy foregrounds two types of discrimination: verbal and behavioural. In this paper, I exemplify the forms of verbal discrimination encountered and offer an analysis of the discourse used in the construction of the experiences and of the effects reported. The results show that verbal discrimination is an overt phenomenon and that participants are stressed by the ever present possibility of facing it. Verbal discrimination is mainly triggered by a perceived transgression to the normalised standards of people’s behaviour, movements and look in a heterosexist society. It presents three subtypes: name calling, abuse and remarks. These subtypes are described through the analysis of keywords, effects and expressions (such as faggot, gay, dyke, queer, the pronoun ‘it’, religious comments and other remarks. The type of discrimination used was associated with the level of acquaintance perpetrators have with the experiencers; that is, name calling was used by people unknown to the victims while abuse and remarks by acquaintances and family members. Participants resorted to several discursive strategies to convey their intentions. They used mitigation strategies when wanting to minimize the experience, hedging and repetition were used for emphasis, and to convey urgency and pervasiveness. Metaphorical expressions related to internal or external injuries were also used to express the powerful effect of verbal discrimination on people.

  7. Deep Convolutional Neural Networks Outperform Feature-Based But Not Categorical Models in Explaining Object Similarity Judgments

    Science.gov (United States)

    Jozwik, Kamila M.; Kriegeskorte, Nikolaus; Storrs, Katherine R.; Mur, Marieke

    2017-01-01

    Recent advances in Deep convolutional Neural Networks (DNNs) have enabled unprecedentedly accurate computational models of brain representations, and present an exciting opportunity to model diverse cognitive functions. State-of-the-art DNNs achieve human-level performance on object categorisation, but it is unclear how well they capture human behavior on complex cognitive tasks. Recent reports suggest that DNNs can explain significant variance in one such task, judging object similarity. Here, we extend these findings by replicating them for a rich set of object images, comparing performance across layers within two DNNs of different depths, and examining how the DNNs’ performance compares to that of non-computational “conceptual” models. Human observers performed similarity judgments for a set of 92 images of real-world objects. Representations of the same images were obtained in each of the layers of two DNNs of different depths (8-layer AlexNet and 16-layer VGG-16). To create conceptual models, other human observers generated visual-feature labels (e.g., “eye”) and category labels (e.g., “animal”) for the same image set. Feature labels were divided into parts, colors, textures and contours, while category labels were divided into subordinate, basic, and superordinate categories. We fitted models derived from the features, categories, and from each layer of each DNN to the similarity judgments, using representational similarity analysis to evaluate model performance. In both DNNs, similarity within the last layer explains most of the explainable variance in human similarity judgments. The last layer outperforms almost all feature-based models. Late and mid-level layers outperform some but not all feature-based models. Importantly, categorical models predict similarity judgments significantly better than any DNN layer. Our results provide further evidence for commonalities between DNNs and brain representations. Models derived from visual features

  8. Quality-aware features-based noise level estimator for block matching and three-dimensional filtering algorithm

    Science.gov (United States)

    Xu, Shaoping; Hu, Lingyan; Yang, Xiaohui

    2016-01-01

    The performance of conventional denoising algorithms is usually controlled by one or several parameters whose optimal settings depend on the contents of the processed images and the characteristics of the noises. Among these parameters, noise level is a fundamental parameter that is always assumed to be known by most of the existing denoising algorithms (so-called nonblind denoising algorithms), which largely limits the applicability of these nonblind denoising algorithms in many applications. Moreover, these nonblind algorithms do not always achieve the best denoised images in visual quality even when fed with the actual noise level parameter. To address these shortcomings, in this paper we propose a new quality-aware features-based noise level estimator (NLE), which consists of quality-aware features extraction and optimal noise level parameter prediction. First, considering that image local contrast features convey important structural information that is closely related to image perceptual quality, we utilize the marginal statistics of two local contrast operators, i.e., the gradient magnitude and the Laplacian of Gaussian (LOG), to extract quality-aware features. The proposed quality-aware features have very low computational complexity, making them well suited for time-constrained applications. Then we propose a learning-based framework where the noise level parameter is estimated based on the quality-aware features. Based on the proposed NLE, we develop a blind block matching and three-dimensional filtering (BBM3D) denoising algorithm which is capable of effectively removing additive white Gaussian noise, even coupled with impulse noise. The noise level parameter of the BBM3D algorithm is automatically tuned according to the quality-aware features, guaranteeing the best performance. As such, the classical block matching and three-dimensional algorithm can be transformed into a blind one in an unsupervised manner. Experimental results demonstrate that the

  9. Children's Perceptions of Gender Discrimination

    Science.gov (United States)

    Brown, Christia Spears; Bigler, Rebecca S.

    2004-01-01

    Children (N = 76; ages 5-10 years) participated in a study designed to examine perceptions of gender discrimination. Children were read scenarios in which a teacher determined outcomes for 2 students (1 boy and 1 girl). Contextual information (i.e., teacher's past behavior), the gender of the target of discrimination (i.e., student), and the…

  10. Discrimination aware decision tree learning

    NARCIS (Netherlands)

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

    2010-01-01

    Recently, the following problem of discrimination aware classification was introduced: given a labeled dataset and an attribute B, find a classifier with high predictive accuracy that at the same time does not discriminate on the basis of the given attribute B. This problem is motivated by the fact

  11. Discrimination aware decision tree learning

    NARCIS (Netherlands)

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

    2010-01-01

    Recently, the following discrimination aware classification problem was introduced: given a labeled dataset and an attribute B, find a classifier with high predictive accuracy that at the same time does not discriminate on the basis of the given attribute B. This problem is motivated by the fact

  12. Discrimination against Muslim American Adolescents

    Science.gov (United States)

    Aroian, Karen J.

    2012-01-01

    Although there is ample evidence of discrimination toward Muslim Americans in general, there is limited information specific to Muslim American adolescents. The few existing studies specific to this age group suggest that Muslim American adolescents encounter much discrimination from teachers, school administrators, and classmates. This…

  13. Perceived discrimination in the Netherlands

    NARCIS (Netherlands)

    Iris Andriessen; Henk Fernee; Karin Wittebrood

    2014-01-01

    Only available in electronic version There is no systematic structure in the Netherlands for mapping out the discrimination experiences of different groups in different areas of society. As in many other countries, discrimination studies in the Netherlands mostly focus on the experiences

  14. Gender Discrimination in Jessica's Career.

    Science.gov (United States)

    Cook, Ellen Piel

    1997-01-01

    Focuses on the sexual harassment and other gender-related difficulties faced by a Chinese-American woman. Profiles her encounters with gender discrimination and how it hindered career advancement and led to professional isolation. Relates how this case study can be used to sensitize workers to gender discrimination. (RJM)

  15. Children's perceptions of gender discrimination.

    Science.gov (United States)

    Spears Brown, Christia; Bigler, Rebecca S

    2004-09-01

    Children (N = 76; ages 5-10 years) participated in a study designed to examine perceptions of gender discrimination. Children were read scenarios in which a teacher determined outcomes for 2 students (1 boy and 1 girl). Contextual information (i.e., teacher's past behavior), the gender of the target of discrimination (i.e., student), and the gender of the perpetrator (i.e., teacher) were manipulated. Results indicated that older children were more likely than younger children to make attributions to discrimination when contextual information suggested that it was likely. Girls (but not boys) were more likely to view girls than boys as victims of discrimination, and children with egalitarian gender attitudes were more likely to perceive discrimination than were their peers. Copyright 2004 American Psychological Association

  16. Pulse discrimination of scintillator detector with artificial neural network

    International Nuclear Information System (INIS)

    Chen Man; Cai Yuerong; Yang Chaowen

    2006-01-01

    The features of signal for scintillator detectors are analyzed. According to the difference in the fraction of slow and fast scintillation for different particles, three intrinsic parameters (signal amplitude, integration of signal during rinsing, integration of frequency spectrum of signals in middle frequencies) of signals are defined. The artificial neural network method for pulse discrimination of scintillator detector is studied. The signals with different shapes under real condition are simulated with computer, and discriminated by the method. Results of discrimination are gotten and discussed. (authors)

  17. Questionnaire discrimination: (re-introducing coefficient δ

    Directory of Open Access Journals (Sweden)

    Hankins Matthew

    2007-05-01

    Full Text Available Abstract Background Questionnaires are used routinely in clinical research to measure health status and quality of life. Questionnaire measurements are traditionally formally assessed by indices of reliability (the degree of measurement error and validity (the extent to which the questionnaire measures what it is supposed to measure. Neither of these indices assesses the degree to which the questionnaire is able to discriminate between individuals, an important aspect of measurement. This paper introduces and extends an existing index of a questionnaire's ability to distinguish between individuals, that is, the questionnaire's discrimination. Methods Ferguson (1949 1 derived an index of test discrimination, coefficient δ, for psychometric tests with dichotomous (correct/incorrect items. In this paper a general form of the formula, δG, is derived for the more general class of questionnaires allowing for several response choices. The calculation and characteristics of δG are then demonstrated using questionnaire data (GHQ-12 from 2003–2004 British Household Panel Survey (N = 14761. Coefficients for reliability (α and discrimination (δG are computed for two commonly-used GHQ-12 coding methods: dichotomous coding and four-point Likert-type coding. Results Both scoring methods were reliable (α > 0.88. However, δG was substantially lower (0.73 for the dichotomous coding of the GHQ-12 than for the Likert-type method (δG = 0.96, indicating that the dichotomous coding, although reliable, failed to discriminate between individuals. Conclusion Coefficient δG was shown to have decisive utility in distinguishing between the cross-sectional discrimination of two equally reliable scoring methods. Ferguson's δ has been neglected in discussions of questionnaire design and performance, perhaps because it has not been implemented in software and was restricted to questionnaires with dichotomous items, which are rare in health care research. It is

  18. Discriminative Projection Selection Based Face Image Hashing

    Science.gov (United States)

    Karabat, Cagatay; Erdogan, Hakan

    Face image hashing is an emerging method used in biometric verification systems. In this paper, we propose a novel face image hashing method based on a new technique called discriminative projection selection. We apply the Fisher criterion for selecting the rows of a random projection matrix in a user-dependent fashion. Moreover, another contribution of this paper is to employ a bimodal Gaussian mixture model at the quantization step. Our simulation results on three different databases demonstrate that the proposed method has superior performance in comparison to previously proposed random projection based methods.

  19. Neural correlates supporting sensory discrimination after left hemisphere stroke

    Science.gov (United States)

    Borstad, Alexandra; Schmalbrock, Petra; Choi, Seongjin; Nichols-Larsen, Deborah S.

    2012-01-01

    Background Nearly half of stroke patients have impaired sensory discrimination, however, the neural structures that support post-stroke sensory function have not been described. Objectives 1) To evaluate the role of the primary somatosensory (S1) cortex in post-stroke sensory discrimination and 2) To determine the relationship between post-stroke sensory discrimination and structural integrity of the sensory component of the superior thalamic radiation (sSTR). Methods 10 healthy adults and 10 individuals with left hemisphere stroke participated. Stroke participants completed sensory discrimination testing. An fMRI was conducted during right, impaired hand sensory discrimination. Fractional anisotropy and volume of the sSTR were quantified using diffusion tensor tractography. Results Sensory discrimination was impaired in 60% of participants with left stroke. Peak activation in the left (S1) did not correlate with sensory discrimination ability, rather a more distributed pattern of activation was evident in post-stroke subjects with a positive correlation between peak activation in the parietal cortex and discrimination ability (r=.70, p=.023). The only brain region in which stroke participants had significantly different cortical activation than control participants was the precuneus. Region of interest analysis of the precuneus across stroke participants revealed a positive correlation between peak activation and sensory discrimination ability (r=.77, p=.008). The L/R ratio of sSTR fractional anisotropy also correlated with right hand sensory discrimination (r=.69, p=.027). Conclusions Precuneus cortex, distributed parietal lobe activity, and microstructure of the sSTR support sensory discrimination after left hemisphere stroke. PMID:22592076

  20. Discriminative power of visual attributes in dermatology.

    Science.gov (United States)

    Giotis, Ioannis; Visser, Margaretha; Jonkman, Marcel; Petkov, Nicolai

    2013-02-01

    Visual characteristics such as color and shape of skin lesions play an important role in the diagnostic process. In this contribution, we quantify the discriminative power of such attributes using an information theoretical approach. We estimate the probability of occurrence of each attribute as a function of the skin diseases. We use the distribution of this probability across the studied diseases and its entropy to define the discriminative power of the attribute. The discriminative power has a maximum value for attributes that occur (or do not occur) for only one disease and a minimum value for those which are equally likely to be observed among all diseases. Verrucous surface, red and brown colors, and the presence of more than 10 lesions are among the most informative attributes. A ranking of attributes is also carried out and used together with a naive Bayesian classifier, yielding results that confirm the soundness of the proposed method. proposed measure is proven to be a reliable way of assessing the discriminative power of dermatological attributes, and it also helps generate a condensed dermatological lexicon. Therefore, it can be of added value to the manual or computer-aided diagnostic process. © 2012 John Wiley & Sons A/S.

  1. Fluid discrimination based on rock physics templates

    International Nuclear Information System (INIS)

    Liu, Qian; Yin, Xingyao; Li, Chao

    2015-01-01

    Reservoir fluid discrimination is an indispensable part of seismic exploration. Reliable fluid discrimination helps to decrease the risk of exploration and to increase the success ratio of drilling. There are many kinds of fluid indicators that are used in fluid discriminations, most of which are single indicators. But single indicators do not always work well under complicated reservoir conditions. Therefore, combined fluid indicators are needed to increase accuracies of discriminations. In this paper, we have proposed an alternative strategy for the combination of fluid indicators. An alternative fluid indicator, the rock physics template-based indicator (RPTI) has been derived to combine the advantages of two single indicators. The RPTI is more sensitive to the contents of fluid than traditional indicators. The combination is implemented based on the characteristic of the fluid trend in the rock physics template, which means few subjective factors are involved. We also propose an inversion method to assure the accuracy of the RPTI input data. The RPTI profile is an intuitionistic interpretation of fluid content. Real data tests demonstrate the applicability and validity. (paper)

  2. Mining consumer reviews to generate ratings of different product attributes while producing feature-based review-summary

    Science.gov (United States)

    Kangale, Akshay; Krishna Kumar, S.; Arshad Naeem, Mohd; Williams, Mark; Tiwari, M. K.

    2016-10-01

    With the massive growth of the internet, product reviews increasingly serve as an important source of information for customers to make choices online. Customers depend on these reviews to understand users' experience, and manufacturers rely on this user-generated content to capture user sentiments about their product. Therefore, it is in the best interest of both customers and manufacturers to have a portal where they can read a complete comprehensive summary of these reviews in minimum time. With this in mind, we arrived at our first objective which is to generate a feature-based review-summary. Our second objective is to develop a predictive model to know the next week's product sales based on numerical review ratings and textual features embedded in the reviews. When it comes to product features, every user has different priorities for different features. To capture this aspect of decision-making, we have designed a new mechanism to generate a numerical rating for every feature of the product individually. The data have been collected from a well-known commercial website for two different products. The validation of the model is carried out using a crowd-sourcing technique.

  3. Studies in genetic discrimination. Final progress report

    Energy Technology Data Exchange (ETDEWEB)

    1994-06-01

    We have screened 1006 respondents in a study of genetic discrimination. Analysis of these responses has produced evidence of the range of institutions engaged in genetic discrimination and demonstrates the impact of this discrimination on the respondents to the study. We have found that both ignorance and policy underlie genetic discrimination and that anti-discrimination laws are being violated.

  4. JUSTIFICATION FOR INDIRECT DISCRIMINATION IN EU

    Directory of Open Access Journals (Sweden)

    Cătălina-Adriana Ivănuş

    2014-11-01

    Full Text Available The right to non-discrimination is very important for a civilized society. EU legislation establishes direct and indirect discrimination, harassment, sexual harassment, instruction to discriminate and any less favourable treatment of a woman related to pregnancy or maternity leave as forms of discrimination. The law and the Court of Justice permit the justification of indirect discrimination.

  5. JUSTIFICATION FOR INDIRECT DISCRIMINATION IN EU

    OpenAIRE

    Cătălina-Adriana Ivănuş

    2014-01-01

    The right to non-discrimination is very important for a civilized society. EU legislation establishes direct and indirect discrimination, harassment, sexual harassment, instruction to discriminate and any less favourable treatment of a woman related to pregnancy or maternity leave as forms of discrimination. The law and the Court of Justice permit the justification of indirect discrimination.

  6. Action Recognition Using Discriminative Structured Trajectory Groups

    KAUST Repository

    Atmosukarto, Indriyati

    2015-01-06

    In this paper, we develop a novel framework for action recognition in videos. The framework is based on automatically learning the discriminative trajectory groups that are relevant to an action. Different from previous approaches, our method does not require complex computation for graph matching or complex latent models to localize the parts. We model a video as a structured bag of trajectory groups with latent class variables. We model action recognition problem in a weakly supervised setting and learn discriminative trajectory groups by employing multiple instance learning (MIL) based Support Vector Machine (SVM) using pre-computed kernels. The kernels depend on the spatio-temporal relationship between the extracted trajectory groups and their associated features. We demonstrate both quantitatively and qualitatively that the classification performance of our proposed method is superior to baselines and several state-of-the-art approaches on three challenging standard benchmark datasets.

  7. Modeling the characteristic of the optical wavelength discriminator with fiber Bragg grating

    Science.gov (United States)

    Sikora, Aleksandra

    2017-08-01

    Using the transfer matrix method, the influence of fiber Bragg gratings' (FBG) characteristics on the optical wavelength discriminator characteristics was analyzed. The wavelength discriminator forms FBG and cooperates with the identical FBG sensor. The calculation was made for uniform and chirped FBGs. The comparison of the discriminators processing range measurement was analyzed. Presented results are crucial while choosing parameters of FBG used in constructing optical wavelength discriminators for strain and pressure sensor.

  8. Timbre discrimination in musical patterns.

    Science.gov (United States)

    Grey, J M

    1978-08-01

    Most research on timbre perception has studied isolated tones. This study compares timbre discrimination of isolated tones with discrimination in various musical contexts, both single-voiced and multivoiced. Twelve different contexts were used (four isolated tonal comparisons, four single-voice musical patterns, and four multivoice patterns). Listerners judged whether the timbre remained the same or changed during the trial. Two possible versions of any instrumental timbre differed in the physical information used in their synthesis. Three instrumental timbres were tested in all contexts: clarinet, trumpet, and bassoon. The effects of context upon discrimination varied across instruments. The clarinet and trumpet versions were best discriminated in isolated contexts, with discrimination progressively worse in single-voice and multivoice patterns. The bassoon versions were best discriminated in the single-voice patterns, with equal discrimination in the isolated and multivoice cases. It is suggested that these results were due to pronounced physical differences observed between the spectra of the two versions of the bassoon that were not apparent between the versions of the clarinet or trumpet.

  9. Quantile forecast discrimination ability and value

    DEFF Research Database (Denmark)

    Ben Bouallègue, Zied; Pinson, Pierre; Friederichs, Petra

    2015-01-01

    While probabilistic forecast verification for categorical forecasts is well established, some of the existing concepts and methods have not found their equivalent for the case of continuous variables. New tools dedicated to the assessment of forecast discrimination ability and forecast value are ...... is illustrated based on synthetic datasets, as well as for the case of global radiation forecasts from the high resolution ensemble COSMO-DE-EPS of the German Weather Service....

  10. Pulse shape discrimination with fast digitizers

    International Nuclear Information System (INIS)

    Cester, D.; Lunardon, M.; Nebbia, G.; Stevanato, L.; Viesti, G.; Petrucci, S.; Tintori, C.

    2014-01-01

    The pulse shape discrimination (PSD) between neutrons and gamma rays in liquid scintillators is studied by using the charge integration method with fast digitizers having different technical characteristics. The use of the Figure of Merit (FoM) to verify the PSD capability is discussed. The dependence of the FoM on the digitizer sampling rate and resolution is experimentally determined. The effects due to the type of source and the irradiation geometry are also evidenced and discussed

  11. Large number discrimination by mosquitofish.

    Directory of Open Access Journals (Sweden)

    Christian Agrillo

    Full Text Available BACKGROUND: Recent studies have demonstrated that fish display rudimentary numerical abilities similar to those observed in mammals and birds. The mechanisms underlying the discrimination of small quantities (<4 were recently investigated while, to date, no study has examined the discrimination of large numerosities in fish. METHODOLOGY/PRINCIPAL FINDINGS: Subjects were trained to discriminate between two sets of small geometric figures using social reinforcement. In the first experiment mosquitofish were required to discriminate 4 from 8 objects with or without experimental control of the continuous variables that co-vary with number (area, space, density, total luminance. Results showed that fish can use the sole numerical information to compare quantities but that they preferentially use cumulative surface area as a proxy of the number when this information is available. A second experiment investigated the influence of the total number of elements to discriminate large quantities. Fish proved to be able to discriminate up to 100 vs. 200 objects, without showing any significant decrease in accuracy compared with the 4 vs. 8 discrimination. The third experiment investigated the influence of the ratio between the numerosities. Performance was found to decrease when decreasing the numerical distance. Fish were able to discriminate numbers when ratios were 1:2 or 2:3 but not when the ratio was 3:4. The performance of a sample of undergraduate students, tested non-verbally using the same sets of stimuli, largely overlapped that of fish. CONCLUSIONS/SIGNIFICANCE: Fish are able to use pure numerical information when discriminating between quantities larger than 4 units. As observed in human and non-human primates, the numerical system of fish appears to have virtually no upper limit while the numerical ratio has a clear effect on performance. These similarities further reinforce the view of a common origin of non-verbal numerical systems in all

  12. Optimisation and validation of a HS-SPME-GC-IT/MS method for analysis of carbonyl volatile compounds as biomarkers in human urine: Application in a pilot study to discriminate individuals with smoking habits.

    Science.gov (United States)

    Calejo, Isabel; Moreira, Nathalie; Araújo, Ana Margarida; Carvalho, Márcia; Bastos, Maria de Lourdes; de Pinho, Paula Guedes

    2016-02-01

    A new and simple analytical approach consisting of an automated headspace solid-phase microextraction (HS-SPME) sampler coupled to gas chromatography-ion trap/mass spectrometry detection (GC-IT/MS) with a prior derivatization step with O-(2,3,4,5,6-pentafluorobenzyl)hydroxylamine hydrochloride (PFBHA) was developed to detect volatile carbonyl metabolites with low molecular weights in human urine. A central composite design (CCD) was used to optimise the PFBHA concentration and extraction conditions that affect the efficiency of the SPME procedure. With a sample volume of 1 mL, optimal conditions were achieved by adding 300 mg/L of PFBHA and allowing the sample to equilibrate for 6 min at 62°C and then extracting the samples for 51 min at the same temperature, using a divinylbenzene/polydimethylsiloxane (DVB/PDMS) fibre. The method allowed the simultaneous identification and quantification of 44 carbonyl compounds consisting of aldehydes, dialdehydes, heterocyclic aldehydes and ketones. The method was validated with regards to the linearity, inter- and intra-day precision and accuracy. The detection limits ranged from 0.009 to 0.942 ng/mL, except for 4-hydroxy-2-nonenal (15 ng/mL), and the quantification limits varied from 0.029 to 1.66 ng/mL, except for butanal (2.78 ng/mL), 2-butanone (2.67 ng/mL), 4-heptanone (3.14 ng/mL) and 4-hydroxy-2-nonenal (50.0 ng/mL). The method accuracy was satisfactory, with recoveries ranging from 90 to 107%. The proof of applicability of the methodology was performed in a pilot target analysis of urine samples obtained from 18 healthy smokers and 18 healthy non-smokers (control group). Chemometric supervised analysis was performed using the volatile patterns acquired for these samples and clearly showed the potential of the volatile carbonyl profiles to discriminate urine from smoker and non-smoker subjects. 5-Methyl-2-furfural (p<0.0001), 2-methylpropanal, nonanal and 2-methylbutanal (p<0.05) were identified as potentially useful

  13. Contrasting effects of feature-based statistics on the categorisation and basic-level identification of visual objects.

    Science.gov (United States)

    Taylor, Kirsten I; Devereux, Barry J; Acres, Kadia; Randall, Billi; Tyler, Lorraine K

    2012-03-01

    Conceptual representations are at the heart of our mental lives, involved in every aspect of cognitive functioning. Despite their centrality, a long-standing debate persists as to how the meanings of concepts are represented and processed. Many accounts agree that the meanings of concrete concepts are represented by their individual features, but disagree about the importance of different feature-based variables: some views stress the importance of the information carried by distinctive features in conceptual processing, others the features which are shared over many concepts, and still others the extent to which features co-occur. We suggest that previously disparate theoretical positions and experimental findings can be unified by an account which claims that task demands determine how concepts are processed in addition to the effects of feature distinctiveness and co-occurrence. We tested these predictions in a basic-level naming task which relies on distinctive feature information (Experiment 1) and a domain decision task which relies on shared feature information (Experiment 2). Both used large-scale regression designs with the same visual objects, and mixed-effects models incorporating participant, session, stimulus-related and feature statistic variables to model the performance. We found that concepts with relatively more distinctive and more highly correlated distinctive relative to shared features facilitated basic-level naming latencies, while concepts with relatively more shared and more highly correlated shared relative to distinctive features speeded domain decisions. These findings demonstrate that the feature statistics of distinctiveness (shared vs. distinctive) and correlational strength, as well as the task demands, determine how concept meaning is processed in the conceptual system. Copyright © 2011 Elsevier B.V. All rights reserved.

  14. Hue discrimination in Iberoamerican Observers

    Science.gov (United States)

    Carranza, Jazmín; Medina, Juana

    2008-04-01

    In this work we analyze the Farnsworth Munsell 100 Hue Test results, this test offers a simple method for testing color discrimination and was applied to a sample of 129 observers, with natural daylight in the same conditions (the observers were men and women), all of these were participants in colorimetric training courses, and aged 20 to 76, with two to twenty five years experience in the color control manufacturer laboratories (of plastics, rugs, dyes, textiles, and paints). Their job titles included mixers, inspectors, shaders, matchers, passers, and dyers. The test was applied twice and the results here presented are the comparison between both tests, taking into account errors by mistakes incidence in each hue position, as well as the redeeming of each participant in both test. The comparison shows us that most of the mistakes are in the green hue in both tests, but in the second test, approximately 20 percent of the observers reduced those. Also we can to separate persons with normal color vision of those which have zones of color confusion. In this work it is show some ones results of the comparison between men and women.

  15. Face adaptation improves gender discrimination.

    Science.gov (United States)

    Yang, Hua; Shen, Jianhong; Chen, Juan; Fang, Fang

    2011-01-01

    Adaptation to a visual pattern can alter the sensitivities of neuronal populations encoding the pattern. However, the functional roles of adaptation, especially in high-level vision, are still equivocal. In the present study, we performed three experiments to investigate if face gender adaptation could affect gender discrimination. Experiments 1 and 2 revealed that adapting to a male/female face could selectively enhance discrimination for male/female faces. Experiment 3 showed that the discrimination enhancement induced by face adaptation could transfer across a substantial change in three-dimensional face viewpoint. These results provide further evidence suggesting that, similar to low-level vision, adaptation in high-level vision could calibrate the visual system to current inputs of complex shapes (i.e. face) and improve discrimination at the adapted characteristic. Copyright © 2010 Elsevier Ltd. All rights reserved.

  16. Optimum filter-based discrimination of neutrons and gamma rays

    International Nuclear Information System (INIS)

    Amiri, Moslem; Prenosil, Vaclav; Cvachovec, Frantisek

    2015-01-01

    An optimum filter-based method for discrimination of neutrons and gamma-rays in a mixed radiation field is presented. The existing filter-based implementations of discriminators require sample pulse responses in advance of the experiment run to build the filter coefficients, which makes them less practical. Our novel technique creates the coefficients during the experiment and improves their quality gradually. Applied to several sets of mixed neutron and photon signals obtained through different digitizers using stilbene scintillator, this approach is analyzed and its discrimination quality is measured. (authors)

  17. EU Law and Multiple Discrimination

    DEFF Research Database (Denmark)

    Nielsen, Ruth

    2006-01-01

    In EU law, nationality and gender were the only equality issues on the legal agenda from the outset in 1958 and for about 40 years. Multiple discrimination was not addressed until the 1990's. The intersectionality approach which has been widely discussed outside Europe has mainly been used...... with a view to gendermainstreaming the fight against other kinds of discrimination (on grounds of ethnic origin, age, etc)....

  18. Discrimination and Equality of Opportunity

    OpenAIRE

    J. Ignacio García-Pérez; Antonio Villar

    2009-01-01

    This paper presents a measure of social discrimination based on the principle of equality of opportunity. According to this principle we only have to care about the inequality derived from people’s differential circumstances (and not about outcome differences due to people’s diverse degree of effort). We propose approaching the measurement of group discrimination as the “welfare loss” attributed to the inequality between social groups of similar characteristics. We also provide an empirical a...

  19. Sexual orientation discrimination in hiring

    OpenAIRE

    Doris Weichselbaumer

    2000-01-01

    Little research has been done to examine discrimination against gays and lesbians in the labor market. Badgett (1995) conducted the only previous study investigating labor market outcomes of gays and lesbians using a random data set. However, due to the structure of the data, the wage differential between heterosexuals and gays and lesbians that is found can not be directly assigned to employer discrimination. Some gays and lesbians might deploy passing strategies to hide their sexual orienta...

  20. Discriminative Elastic-Net Regularized Linear Regression.

    Science.gov (United States)

    Zhang, Zheng; Lai, Zhihui; Xu, Yong; Shao, Ling; Wu, Jian; Xie, Guo-Sen

    2017-03-01

    In this paper, we aim at learning compact and discriminative linear regression models. Linear regression has been widely used in different problems. However, most of the existing linear regression methods exploit the conventional zero-one matrix as the regression targets, which greatly narrows the flexibility of the regression model. Another major limitation of these methods is that the learned projection matrix fails to precisely project the image features to the target space due to their weak discriminative capability. To this end, we present an elastic-net regularized linear regression (ENLR) framework, and develop two robust linear regression models which possess the following special characteristics. First, our methods exploit two particular strategies to enlarge the margins of different classes by relaxing the strict binary targets into a more feasible variable matrix. Second, a robust elastic-net regularization of singular values is introduced to enhance the compactness and effectiveness of the learned projection matrix. Third, the resulting optimization problem of ENLR has a closed-form solution in each iteration, which can be solved efficiently. Finally, rather than directly exploiting the projection matrix for recognition, our methods employ the transformed features as the new discriminate representations to make final image classification. Compared with the traditional linear regression model and some of its variants, our method is much more accurate in image classification. Extensive experiments conducted on publicly available data sets well demonstrate that the proposed framework can outperform the state-of-the-art methods. The MATLAB codes of our methods can be available at http://www.yongxu.org/lunwen.html.

  1. Unambiguous discrimination among oracle operators

    International Nuclear Information System (INIS)

    Chefles, Anthony; Kitagawa, Akira; Takeoka, Masahiro; Sasaki, Masahide; Twamley, Jason

    2007-01-01

    We address the problem of unambiguous discrimination among oracle operators. The general theory of unambiguous discrimination among unitary operators is extended with this application in mind. We prove that entanglement with an ancilla cannot assist any discrimination strategy for commuting unitary operators. We also obtain a simple, practical test for the unambiguous distinguishability of an arbitrary set of unitary operators on a given system. Using this result, we prove that the unambiguous distinguishability criterion is the same for both standard and minimal oracle operators. We then show that, except in certain trivial cases, unambiguous discrimination among all standard oracle operators corresponding to integer functions with fixed domain and range is impossible. However, we find that it is possible to unambiguously discriminate among the Grover oracle operators corresponding to an arbitrarily large unsorted database. The unambiguous distinguishability of standard oracle operators corresponding to totally indistinguishable functions, which possess a strong form of classical indistinguishability, is analysed. We prove that these operators are not unambiguously distinguishable for any finite set of totally indistinguishable functions on a Boolean domain and with arbitrary fixed range. Sets of such functions on a larger domain can have unambiguously distinguishable standard oracle operators, and we provide a complete analysis of the simplest case, that of four functions. We also examine the possibility of unambiguous oracle operator discrimination with multiple parallel calls and investigate an intriguing unitary superoperator transformation between standard and entanglement-assisted minimal oracle operators

  2. Discrimination between biological interfaces and crystal-packing contacts

    Directory of Open Access Journals (Sweden)

    Yuko Tsuchiya

    2008-11-01

    Full Text Available Yuko Tsuchiya1, Haruki Nakamura2, Kengo Kinoshita1,31Institute of Medical Science, The University of Tokyo, 4-6-1 Shirokanedai, Minatoku, Tokyo, 108-8639, Japan; 2Institute for Protein Research, Osaka University, 3-2 Yamadaoka, Suita, Osaka, 565-0871, Japan; 3Bioinformatics Research and Development, JST, 4-1-8 Honcho, Kawaguchi, Saitama, 332-0012, JapanAbstract: A discrimination method between biologically relevant interfaces and artificial crystal-packing contacts in crystal structures was constructed. The method evaluates protein-protein interfaces in terms of complementarities for hydrophobicity, electrostatic potential and shape on the protein surfaces, and chooses the most probable biological interfaces among all possible contacts in the crystal. The method uses a discriminator named as “COMP”, which is a linear combination of the complementarities for the above three surface features and does not correlate with the contact area. The discrimination of homo-dimer interfaces from symmetry-related crystal-packing contacts based on the COMP value achieved the modest success rate. Subsequent detailed review of the discrimination results raised the success rate to about 88.8%. In addition, our discrimination method yielded some clues for understanding the interaction patterns in several examples in the PDB. Thus, the COMP discriminator can also be used as an indicator of the “biological-ness” of protein-protein interfaces.Keywords: protein-protein interaction, complementarity analysis, homo-dimer interface, crystal-packing contact, biological interfaces

  3. Linear discriminant analysis for welding fault detection

    International Nuclear Information System (INIS)

    Li, X.; Simpson, S.W.

    2010-01-01

    This work presents a new method for real time welding fault detection in industry based on Linear Discriminant Analysis (LDA). A set of parameters was calculated from one second blocks of electrical data recorded during welding and based on control data from reference welds under good conditions, as well as faulty welds. Optimised linear combinations of the parameters were determined with LDA and tested with independent data. Short arc welds in overlap joints were studied with various power sources, shielding gases, wire diameters, and process geometries. Out-of-position faults were investigated. Application of LDA fault detection to a broad range of welding procedures was investigated using a similarity measure based on Principal Component Analysis. The measure determines which reference data are most similar to a given industrial procedure and the appropriate LDA weights are then employed. Overall, results show that Linear Discriminant Analysis gives an effective and consistent performance in real-time welding fault detection.

  4. [Discrimination of Rice Syrup Adulterant of Acacia Honey Based Using Near-Infrared Spectroscopy].

    Science.gov (United States)

    Zhang, Yan-nan; Chen, Lan-zhen; Xue, Xiao-feng; Wu, Li-ming; Li, Yi; Yang, Juan

    2015-09-01

    At present, the rice syrup as a low price of the sweeteners was often adulterated into acacia honey and the adulterated honeys were sold in honey markets, while there is no suitable and fast method to identify honey adulterated with rice syrup. In this study, Near infrared spectroscopy (NIR) combined with chemometric methods were used to discriminate authenticity of honey. 20 unprocessed acacia honey samples from the different honey producing areas, mixed? with different proportion of rice syrup, were prepared of seven different concentration gradient? including 121 samples. The near infrared spectrum (NIR) instrument and spectrum processing software have been applied in the? spectrum? scanning and data conversion on adulterant samples, respectively. Then it was analyzed by Principal component analysis (PCA) and canonical discriminant analysis methods in order to discriminating adulterated honey. The results showed that after principal components analysis, the first two principal components accounted for 97.23% of total variation, but the regionalism of the score plot of the first two PCs was not obvious, so the canonical discriminant analysis was used to make the further discrimination, all samples had been discriminated correctly, the first two discriminant functions accounted for 91.6% among the six canonical discriminant functions, Then the different concentration of adulterant samples can be discriminated correctly, it illustrate that canonical discriminant analysis method combined with NIR spectroscopy is not only feasible but also practical for rapid and effective discriminate of the rice syrup adulterant of acacia honey.

  5. Discrete Discriminant analysis based on tree-structured graphical models

    DEFF Research Database (Denmark)

    Perez de la Cruz, Gonzalo; Eslava, Guillermina

    The purpose of this paper is to illustrate the potential use of discriminant analysis based on tree{structured graphical models for discrete variables. This is done by comparing its empirical performance using estimated error rates for real and simulated data. The results show that discriminant a...... analysis based on tree{structured graphical models is a simple nonlinear method competitive with, and sometimes superior to, other well{known linear methods like those assuming mutual independence between variables and linear logistic regression.......The purpose of this paper is to illustrate the potential use of discriminant analysis based on tree{structured graphical models for discrete variables. This is done by comparing its empirical performance using estimated error rates for real and simulated data. The results show that discriminant...

  6. Unsupervised spike sorting based on discriminative subspace learning.

    Science.gov (United States)

    Keshtkaran, Mohammad Reza; Yang, Zhi

    2014-01-01

    Spike sorting is a fundamental preprocessing step for many neuroscience studies which rely on the analysis of spike trains. In this paper, we present two unsupervised spike sorting algorithms based on discriminative subspace learning. The first algorithm simultaneously learns the discriminative feature subspace and performs clustering. It uses histogram of features in the most discriminative projection to detect the number of neurons. The second algorithm performs hierarchical divisive clustering that learns a discriminative 1-dimensional subspace for clustering in each level of the hierarchy until achieving almost unimodal distribution in the subspace. The algorithms are tested on synthetic and in-vivo data, and are compared against two widely used spike sorting methods. The comparative results demonstrate that our spike sorting methods can achieve substantially higher accuracy in lower dimensional feature space, and they are highly robust to noise. Moreover, they provide significantly better cluster separability in the learned subspace than in the subspace obtained by principal component analysis or wavelet transform.

  7. The role of perceived discrimination on active aging.

    OpenAIRE

    Fernández Ballesteros, Rocío; Olmos, Ricardo; Santacreu, Marta; Bustillos, Antonio; Molina Martínez, Mª Ángeles

    2017-01-01

    Among older adults, perceived age discrimination is highly associated with unhealthy outcomes and dissatisfaction. Active aging is a multidimensional concept described by a set of characteristics, particularly health, positive mood and control; most importantly, active aging is currently at the core of public policies. The aim of the present study was to test to what extent perceived discrimination influences active aging. Methods A total of 2,005 older adults in three represen...

  8. Ethnic and gender discrimination in recruitment: experimental evidence from Finland

    OpenAIRE

    Liebkind, Karmela; Larja, Lisa; Brylka, Asteria Anna

    2016-01-01

    We ask (1) how the position of an ethnic (majority or minority) group in the local ethnic hierarchy affects the amount of recruitment discrimination faced by applicants from that group, and (2) whether gender discrimination is dependent on occupational gender stereotypes in the same way among ethnic majority and minority applicants. We use the situation testing method for the first time in Finland: In an experimental study (Study 1), 103 dentistry students made recruitment decisions based on ...

  9. Practical Discrimination Strategies for Application to Live Sites

    Science.gov (United States)

    2009-11-01

    evaluate the discrimination potential of the Geonics EM63 at Fort McClellan, AL, when deployed in a cued interrogation mode. Pasion - Oldenburg...the Geonics EM63 at Fort McClellan, AL, when deployed in a cued interrogation mode. Pasion - Oldenburg polarization tensor models were fit to each of... Pasion & Oldenburg, 2001; Zhang et al., 2003a, 2003b; Billings, 2004). The most promising discrimination methods typically proceed by first

  10. Lower bound on inconclusive probability of unambiguous discrimination

    International Nuclear Information System (INIS)

    Feng Yuan; Zhang Shengyu; Duan Runyao; Ying Mingsheng

    2002-01-01

    We derive a lower bound on the inconclusive probability of unambiguous discrimination among n linearly independent quantum states by using the constraint of no signaling. It improves the bound presented in the paper of Zhang, Feng, Sun, and Ying [Phys. Rev. A 64, 062103 (2001)], and when the optimal discrimination can be reached, these two bounds coincide with each other. An alternative method of constructing an appropriate measurement to prove the lower bound is also presented

  11. Discrimination and Psychological Distress: Gender Differences among Arab Americans

    OpenAIRE

    Assari, Shervin; Lankarani, Maryam Moghani

    2017-01-01

    Background Despite the existing knowledge on the association between discrimination and poor mental health, very few studies have explored gender differences in this association in Arab Americans. Objective The current study aimed to investigate whether gender moderates the association between the experience of discrimination and psychological distress in a representative sample of Arab Americans in Michigan. Methods Using data from the Detroit Arab American Study (DAAS), 2...

  12. Radioactive anomaly discrimination from spectral ratios

    Science.gov (United States)

    Maniscalco, James; Sjoden, Glenn; Chapman, Mac Clements

    2013-08-20

    A method for discriminating a radioactive anomaly from naturally occurring radioactive materials includes detecting a first number of gamma photons having energies in a first range of energy values within a predetermined period of time and detecting a second number of gamma photons having energies in a second range of energy values within the predetermined period of time. The method further includes determining, in a controller, a ratio of the first number of gamma photons having energies in the first range and the second number of gamma photons having energies in the second range, and determining that a radioactive anomaly is present when the ratio exceeds a threshold value.

  13. The role of perceived discrimination on active aging.

    Science.gov (United States)

    Fernandez-Ballesteros, Rocio; Olmos, Ricardo; Santacreu, Marta; Bustillos, Antonio; Molina, Maria Angeles

    2017-07-01

    Among older adults, perceived age discrimination is highly associated with unhealthy outcomes and dissatisfaction. Active aging is a multidimensional concept described by a set of characteristics, particularly health, positive mood and control; most importantly, active aging is currently at the core of public policies. The aim of the present study was to test to what extent perceived discrimination influences active aging. Methods A total of 2005 older adults in three representative samples from regions of Germany, Mexico and Spain participated; they were tested on active aging and perceived discrimination. First, active aging was defined as high reported health, life satisfaction and self-perception of aging. Second, authors introduced the assumption that, in the total sample, structural equation modelling would confirm the hypothesis of a direct negative link between perceived age discrimination and active aging. Finally, multiple group comparison performed through structural equation modelling also provided support for the negative association between perceived discrimination and active aging proposed. In spite of the differences found among the three countries in both active aging variables and age discrimination perception, multiple group comparison indicates that regardless of the culture, perceived discrimination is a negative predictor of active aging. Copyright © 2017 Elsevier B.V. All rights reserved.

  14. Exploiting Reject Option in Classification for Social Discrimination Control

    KAUST Repository

    Kamiran, Faisal

    2017-09-29

    Social discrimination is said to occur when an unfavorable decision for an individual is influenced by her membership to certain protected groups such as females and minority ethnic groups. Such discriminatory decisions often exist in historical data. Despite recent works in discrimination-aware data mining, there remains the need for robust, yet easily usable, methods for discrimination control. In this paper, we utilize reject option in classification, a general decision theoretic framework for handling instances whose labels are uncertain, for modeling and controlling discriminatory decisions. Specifically, this framework permits a formal treatment of the intuition that instances close to the decision boundary are more likely to be discriminated in a dataset. Based on this framework, we present three different solutions for discrimination-aware classification. The first solution invokes probabilistic rejection in single or multiple probabilistic classifiers while the second solution relies upon ensemble rejection in classifier ensembles. The third solution integrates one of the first two solutions with situation testing which is a procedure commonly used in the court of law. All solutions are easy to use and provide strong justifications for the decisions. We evaluate our solutions extensively on four real-world datasets and compare their performances with previously proposed discrimination-aware classifiers. The results demonstrate the superiority of our solutions in terms of both performance and flexibility of applicability. In particular, our solutions are effective at removing illegal discrimination from the predictions.

  15. Ethical thinking and discrimination in health care

    Directory of Open Access Journals (Sweden)

    Aleksander Mlinšek

    2012-02-01

    Full Text Available RQ: Personal excellence of nursing focusing on self-transcendence and achievements is crucial for achieving excellence in health care. The question is whether there is unequal treatment of patients despite high ethical standards placed in health care.Purpose: Professional nurses code is a guide in assessing their ethical performance. People are different amongst each other, but have the same rights in the health system, which should be provided by health care services. The need to overcome inequalities has become a cornerstone of excellence in health care.Method: A small quantitative survey of nurses was conducted in one of the departments in a Slovenian hospital. To analyse the results, we used frequency statistics, Spearman's rank correlation test and chi-square test. Results: Providers of health care services are aware of the importance of ethics in its formation. Professional Code is relatively well known; 8.4 % of the respondents were not sure if they clearly define the principles of respect for equality. Discrimination, caused by providers of health care, is of a less extent. Ethical awareness among health care providers does not affect identification with the profession. The education level ofnursing personnel and the perception of discrimination based on religious affiliation influenced one another. Education has no influence on the perception of discrimination based on other circumstances.Organization: Health care organizations should integrate hygieneethical thinking among its strategic goals. Quality is not only quantifying the data. Personal excellence of health care providers, which is difficult to measure, is the basic building block of organizational excellence and patient satisfaction.Originality: There are not many research studies on perceptionsof discrimination in health care. The article raises the sensitive issue that we should talk more about.Limitations: The survey was conducted on a small sample size. Further research

  16. Discriminative object tracking via sparse representation and online dictionary learning.

    Science.gov (United States)

    Xie, Yuan; Zhang, Wensheng; Li, Cuihua; Lin, Shuyang; Qu, Yanyun; Zhang, Yinghua

    2014-04-01

    We propose a robust tracking algorithm based on local sparse coding with discriminative dictionary learning and new keypoint matching schema. This algorithm consists of two parts: the local sparse coding with online updated discriminative dictionary for tracking (SOD part), and the keypoint matching refinement for enhancing the tracking performance (KP part). In the SOD part, the local image patches of the target object and background are represented by their sparse codes using an over-complete discriminative dictionary. Such discriminative dictionary, which encodes the information of both the foreground and the background, may provide more discriminative power. Furthermore, in order to adapt the dictionary to the variation of the foreground and background during the tracking, an online learning method is employed to update the dictionary. The KP part utilizes refined keypoint matching schema to improve the performance of the SOD. With the help of sparse representation and online updated discriminative dictionary, the KP part are more robust than the traditional method to reject the incorrect matches and eliminate the outliers. The proposed method is embedded into a Bayesian inference framework for visual tracking. Experimental results on several challenging video sequences demonstrate the effectiveness and robustness of our approach.

  17. 45 CFR 1624.4 - Discrimination prohibited.

    Science.gov (United States)

    2010-10-01

    ... 45 Public Welfare 4 2010-10-01 2010-10-01 false Discrimination prohibited. 1624.4 Section 1624.4... AGAINST DISCRIMINATION ON THE BASIS OF DISABILITY § 1624.4 Discrimination prohibited. (a) No qualified... the benefits of, or otherwise be subjected to discrimination by any legal services program, directly...

  18. 20 CFR 405.30 - Discrimination complaints.

    Science.gov (United States)

    2010-04-01

    ... 20 Employees' Benefits 2 2010-04-01 2010-04-01 false Discrimination complaints. 405.30 Section 405... INITIAL DISABILITY CLAIMS Introduction, General Description, and Definitions § 405.30 Discrimination... that an adjudicator has improperly discriminated against you, you may file a discrimination complaint...

  19. 14 CFR 399.36 - Unreasonable discrimination.

    Science.gov (United States)

    2010-01-01

    ... 14 Aeronautics and Space 4 2010-01-01 2010-01-01 false Unreasonable discrimination. 399.36 Section... Unreasonable discrimination. (a) As used in this section: (1) Unreasonable discrimination means unjust discrimination or unreasonable preference or prejudice; and (2) Rate means rate, fare, or charge. (b) Except in...

  20. Unambiguous discrimination of mixed quantum states

    International Nuclear Information System (INIS)

    Zhang Chi; Feng Yuan; Ying Mingsheng

    2006-01-01

    The problem of unambiguous discrimination between mixed quantum states is addressed by isolating the part of each mixed state which has no contribution to discrimination and by employing the strategy of set discrimination of pure states. A necessary and sufficient condition of unambiguous mixed state discrimination is presented. An upper bound of the efficiency is also derived

  1. International Trade and Labor Market Discrimination

    NARCIS (Netherlands)

    R. Chisik (Richard); J.E. Namini (Julian Emami)

    2016-01-01

    textabstractWe embed a competitive search model with labor market discrimination, or nepotism, into a two-sector, two-country framework in order to analyze how labor market discrimination impacts the pattern of international trade and also how trade trade affects discrimination. Discrimination, or

  2. Quantity Discrimination in Trained Lizards (Podarcis sicula

    Directory of Open Access Journals (Sweden)

    Maria Elena Miletto Petrazzini

    2018-03-01

    Full Text Available Quantitative abilities have been reported in many animal species. Two main methods have been extensively used: spontaneous choice tests and training procedures. A recent study showed that ruin lizards are capable of spontaneously discriminating between the surface area of two food items of different size, but failed when food was presented in sets of discrete items differing in number. In the present study, we used a training procedure to further investigate quantitative abilities in ruin lizards. Subjects were presented with two sets of yellow disks differing either in number (Experiment 1 or in area (Experiment 2 and were trained on different discriminations of increasing difficulty (1 vs. 4, 2 vs. 4, and 2 vs. 3. Results showed that lizards were more accurate in discriminating sets of discrete items differing in number than the area of two individual items, in contrast to what had earlier been observed in spontaneous choice tests. Although we cannot exclude other factors that affected the performance of ruin lizards, the poor accuracy here observed in both experiments might reflect a true limit in lizards’ quantitative abilities.

  3. Forms, Frequency, and Correlates of Perceived Anti-Atheist Discrimination

    Directory of Open Access Journals (Sweden)

    Joseph H. Hammer

    2012-10-01

    Full Text Available The nationally representative 2008 American Religious Identification Survey found that 41% of self-identified atheists reported experiencing discrimination in the last 5 years due to their lack of religious identification.  This mixed-method study explored the forms and frequency of discrimination reported by 796 self-identified atheists living in the United States.  Participants reported experiencing different types of discrimination to varying degrees, including slander; coercion; social ostracism; denial of opportunities, goods, and services; and hate crime.  Similar to other minority groups with concealable stigmatized identities, atheists who more strongly identified with their atheism, who were “out” about their atheism to more people, and who grew up with stricter familial religious expectations reported experiencing more frequent discrimination.  Implications for future research tied to the ongoing religion/spirituality-health debate are discussed.

  4. MIDAS: Regionally linear multivariate discriminative statistical mapping.

    Science.gov (United States)

    Varol, Erdem; Sotiras, Aristeidis; Davatzikos, Christos

    2018-07-01

    Statistical parametric maps formed via voxel-wise mass-univariate tests, such as the general linear model, are commonly used to test hypotheses about regionally specific effects in neuroimaging cross-sectional studies where each subject is represented by a single image. Despite being informative, these techniques remain limited as they ignore multivariate relationships in the data. Most importantly, the commonly employed local Gaussian smoothing, which is important for accounting for registration errors and making the data follow Gaussian distributions, is usually chosen in an ad hoc fashion. Thus, it is often suboptimal for the task of detecting group differences and correlations with non-imaging variables. Information mapping techniques, such as searchlight, which use pattern classifiers to exploit multivariate information and obtain more powerful statistical maps, have become increasingly popular in recent years. However, existing methods may lead to important interpretation errors in practice (i.e., misidentifying a cluster as informative, or failing to detect truly informative voxels), while often being computationally expensive. To address these issues, we introduce a novel efficient multivariate statistical framework for cross-sectional studies, termed MIDAS, seeking highly sensitive and specific voxel-wise brain maps, while leveraging the power of regional discriminant analysis. In MIDAS, locally linear discriminative learning is applied to estimate the pattern that best discriminates between two groups, or predicts a variable of interest. This pattern is equivalent to local filtering by an optimal kernel whose coefficients are the weights of the linear discriminant. By composing information from all neighborhoods that contain a given voxel, MIDAS produces a statistic that collectively reflects the contribution of the voxel to the regional classifiers as well as the discriminative power of the classifiers. Critically, MIDAS efficiently assesses the

  5. MR PROSTATE SEGMENTATION VIA DISTRIBUTED DISCRIMINATIVE DICTIONARY (DDD) LEARNING.

    Science.gov (United States)

    Guo, Yanrong; Zhan, Yiqiang; Gao, Yaozong; Jiang, Jianguo; Shen, Dinggang

    2013-01-01

    Segmenting prostate from MR images is important yet challenging. Due to non-Gaussian distribution of prostate appearances in MR images, the popular active appearance model (AAM) has its limited performance. Although the newly developed sparse dictionary learning method[1, 2] can model the image appearance in a non-parametric fashion, the learned dictionaries still lack the discriminative power between prostate and non-prostate tissues, which is critical for accurate prostate segmentation. In this paper, we propose to integrate deformable model with a novel learning scheme, namely the Distributed Discriminative Dictionary ( DDD ) learning, which can capture image appearance in a non-parametric and discriminative fashion. In particular, three strategies are designed to boost the tissue discriminative power of DDD. First , minimum Redundancy Maximum Relevance (mRMR) feature selection is performed to constrain the dictionary learning in a discriminative feature space. Second , linear discriminant analysis (LDA) is employed to assemble residuals from different dictionaries for optimal separation between prostate and non-prostate tissues. Third , instead of learning the global dictionaries, we learn a set of local dictionaries for the local regions (each with small appearance variations) along prostate boundary, thus achieving better tissue differentiation locally. In the application stage, DDDs will provide the appearance cues to robustly drive the deformable model onto the prostate boundary. Experiments on 50 MR prostate images show that our method can yield a Dice Ratio of 88% compared to the manual segmentations, and have 7% improvement over the conventional AAM.

  6. Employment Discrimination against LGBT Utahns

    OpenAIRE

    Rosky, Clifford; Mallory, Christy; Smith, Jenni; Badgett, M.V. Lee

    2011-01-01

    This study analyzes data from a 2010 survey on the employment experiences of 939 LGBT people living in Utah.  The study found that 44% of LGB people and 66% of transgender people in Utah have experienced employment discrimination.  The data showed that employment discrimination based on sexual orientation and gender identity currently occurs in Utah, with close to 30% of LGB respondents and 45% of transgender respondents reporting that they experienced some form of workplace harassment on a w...

  7. Labor Market Discrimination: Vietnamese Immigrants

    Directory of Open Access Journals (Sweden)

    Linus Yamane

    2012-01-01

    Full Text Available Vietnamese and East European immigrants face similar obstacles in the U.S. labor market. This provides for an interesting test of racial discrimination in the labor market. Does it make any difference if an immigrant is Asian or White? When Vietnamese immigrants are compared to East European immigrants, Vietnamese men earn 7-9% less than comparable East European men, with more discrimination among the less educated, and in the larger Vietnamese population centers like California. Vietnamese women earn as much as comparable East European women. Vietnamese immigrants, male and female, are much less likely to hold managerial and supervisory positions than comparable East European immigrants.

  8. Labor Market Discrimination: Vietnamese Immigrants

    Directory of Open Access Journals (Sweden)

    Linus Yamane

    2012-01-01

    Full Text Available Vietnamese and East European immigrants face similar obstacles in the US labor market. This provides for an interesting test of racial discrimination in the labor market. Does it make any difference if an immigrant is Asian or White? When Vietnamese immigrants are compared to East European immigrants, Vietnamese men earn 7-9% less than comparable East European men, with more discrimination among the less educated, and in the larger Vietnamese population centers like California. Vietnamese women earn as much as comparable East European women. Vietnamese immigrants, male and female, are much less likely to hold managerial and supervisory positions than comparable East European immigrants.

  9. Neutron-gamma discrimination based on pulse shape discrimination in a Ce:LiCaAlF{sub 6} scintillator

    Energy Technology Data Exchange (ETDEWEB)

    Yamazaki, Atsushi, E-mail: a-yamazaki@nucl.nagoya-u.ac.jp [Department of Materials, Physics and Energy Engineering, Graduate School of Engineering, Nagoya University (Japan); Watanabe, Kenichi; Uritani, Akira [Department of Materials, Physics and Energy Engineering, Graduate School of Engineering, Nagoya University (Japan); Iguchi, Tetsuo [Department of Quantum Engineering, Graduate School of Engineering, Nagoya University (Japan); Kawaguchi, Noriaki [Tokuyama Corporation (Japan); Yanagida, Takayuki; Fujimoto, Yutaka; Yokota, Yuui; Kamada, Kei [Institute of Multidisciplinary Research for Advanced Materials (IMRAM), Tohoku University (Japan); Fukuda, Kentaro; Suyama, Toshihisa [Tokuyama Corporation (Japan); Yoshikawa, Akira [Institute of Multidisciplinary Research for Advanced Materials (IMRAM), Tohoku University (Japan); New Industry Creation Hatchery Center (NICHe), Tohoku University (Japan)

    2011-10-01

    We demonstrate neutron-gamma discrimination based on a pulse shape discrimination method in a Ce:LiCAF scintillator. We have tried neutron-gamma discrimination using a difference in the pulse shape or the decay time of the scintillation light pulse. The decay time is converted into the rise time through an integrating circuit. A {sup 252}Cf enclosed in a polyethylene container is used as the source of thermal neutrons and prompt gamma-rays. Obvious separation of neutron and gamma-ray events is achieved using the information of the rise time of the scintillation light pulse. In the separated neutron spectrum, the gamma-ray events are effectively suppressed with little loss of neutron events. The pulse shape discrimination is confirmed to be useful to detect neutrons with the Ce:LiCAF scintillator under an intense high-energy gamma-ray condition.

  10. DISCRIMINATION BY ASSOCIATION IN EUROPEAN LAW

    Directory of Open Access Journals (Sweden)

    Cătălina-Adriana Ivănuș

    2013-11-01

    Full Text Available The european law prohibit direct and indirect discrimination and harrasment on grounds of sex, racial or ethnic, religion or belief, disability, age or sexual orientation. The question is what is the situation when someone is discriminated on can claim to be the victim of unlawful discrimination because he or she is associated with another person who has the protected characteristic. The the Court of Justice of the European Union’s judgment in Coleman v Attridge Law and Steve Law confirms, for the first time in European law, the existence of the concept of discrimination by association. In this article I examine the implications of this case on all conceps of discrimination concepts of discrimination in European law (direct discrimination, indirect discrimination and harassment. I also examine the application of discrimination by association to grounds other than disability.

  11. Spatial layout affects speed discrimination

    Science.gov (United States)

    Verghese, P.; Stone, L. S.

    1997-01-01

    We address a surprising result in a previous study of speed discrimination with multiple moving gratings: discrimination thresholds decreased when the number of stimuli was increased, but remained unchanged when the area of a single stimulus was increased [Verghese & Stone (1995). Vision Research, 35, 2811-2823]. In this study, we manipulated the spatial- and phase relationship between multiple grating patches to determine their effect on speed discrimination thresholds. In a fusion experiment, we merged multiple stimulus patches, in stages, into a single patch. Thresholds increased as the patches were brought closer and their phase relationship was adjusted to be consistent with a single patch. Thresholds increased further still as these patches were fused into a single patch. In a fission experiment, we divided a single large patch into multiple patches by superimposing a cross with luminance equal to that of the background. Thresholds decreased as the large patch was divided into quadrants and decreased further as the quadrants were maximally separated. However, when the cross luminance was darker than the background, it was perceived as an occluder and thresholds, on average, were unchanged from that for the single large patch. A control experiment shows that the observed trend in discrimination thresholds is not due to the differences in perceived speed of the stimuli. These results suggest that the parsing of the visual image into entities affects the combination of speed information across space, and that each discrete entity effectively provides a single independent estimate of speed.

  12. A Talk on Sex Discrimination.

    Science.gov (United States)

    Evers, Irving C.

    The topic of this speech covers the 1972 amendments to Title VII of the Civil Rights Act of 1964 and the subsequent court cases dealing with sex discrimination. The cases discussed cover maternity leaves for tenured as well as untenured teachers and other public employees. The issues basic to these cases involve mandatory maternity leaves at…

  13. Don't demotivate, discriminate

    NARCIS (Netherlands)

    J.J.A. Kamphorst (Jurjen); O.H. Swank (Otto)

    2013-01-01

    markdownabstract__Abstract__ This paper offers a new theory of discrimination in the workplace. We consider a manager who has to assign two tasks to two employees. The manager has superior information about the employees' abilities. We show that besides an equilibrium where the manager does not

  14. Sex Discrimination in Employment Practices.

    Science.gov (United States)

    California Univ., Los Angeles. Univ. Extension.

    The conference on sex discrimination in employment practices was held at the University of California at Los Angeles in cooperation with the Women's Bureau of the Department of Labor. Speeches included: (1) "New Legislation--New Action" by Rosalind K. Loring and William Foster, (2) "Compliance Policies and Procedures for Business and Industry" by…

  15. Gender discrimination and job characteristics

    NARCIS (Netherlands)

    Dubbelt, L.; Rispens, S.; Demerouti, E.

    2016-01-01

    Purpose – The purpose of this paper is to examine the relationship between gender discrimination and the perceived job demands and job resources of women and men. This is important because it may provide insight into what factors contribute to women’s disadvantaged position at work.

  16. Quantifying explainable discrimination and removing illegal discrimination in automated decision making

    NARCIS (Netherlands)

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

    2013-01-01

    Recently, the following discrimination-aware classification problem was introduced. Historical data used for supervised learning may contain discrimination, for instance, with respect to gender. The question addressed by discrimination-aware techniques is, given sensitive attribute, how to train

  17. Social Status Correlates of Reporting Racial Discrimination and Gender Discrimination among Racially Diverse Women

    OpenAIRE

    Ro, Annie E.; Choi, Kyung-Hee

    2009-01-01

    The growing body of research on discrimination and health indicates a deleterious effect of discrimination on various health outcomes. However, less is known about the sociodemographic correlates of reporting racial discrimination and gender discrimination among racially diverse women. We examined the associations of social status characteristics with lifetime experiences of racial discrimination and gender discrimination using a racially-diverse sample of 754 women attending family planning ...

  18. Origin discrimination and quality evaluation of Gastrodiae rhizoma ...

    African Journals Online (AJOL)

    Purpose: To develop a high-performance liquid chromatography (HPLC) fingerprint method for the quality control and origin discrimination of Gastrodiae rhizoma. Methods: Twelve batches of G. rhizoma collected from Sichuan, Guizhou and Shanxi provinces in china were used to establish the fingerprint.

  19. Weighted Discriminative Dictionary Learning based on Low-rank Representation

    International Nuclear Information System (INIS)

    Chang, Heyou; Zheng, Hao

    2017-01-01

    Low-rank representation has been widely used in the field of pattern classification, especially when both training and testing images are corrupted with large noise. Dictionary plays an important role in low-rank representation. With respect to the semantic dictionary, the optimal representation matrix should be block-diagonal. However, traditional low-rank representation based dictionary learning methods cannot effectively exploit the discriminative information between data and dictionary. To address this problem, this paper proposed weighted discriminative dictionary learning based on low-rank representation, where a weighted representation regularization term is constructed. The regularization associates label information of both training samples and dictionary atoms, and encourages to generate a discriminative representation with class-wise block-diagonal structure, which can further improve the classification performance where both training and testing images are corrupted with large noise. Experimental results demonstrate advantages of the proposed method over the state-of-the-art methods. (paper)

  20. Discrimination of genetically modified sugar beets based on terahertz spectroscopy

    Science.gov (United States)

    Chen, Tao; Li, Zhi; Yin, Xianhua; Hu, Fangrong; Hu, Cong

    2016-01-01

    The objective of this paper was to apply terahertz (THz) spectroscopy combined with chemometrics techniques for discrimination of genetically modified (GM) and non-GM sugar beets. In this paper, the THz spectra of 84 sugar beet samples (36 GM sugar beets and 48 non-GM ones) were obtained by using terahertz time-domain spectroscopy (THz-TDS) system in the frequency range from 0.2 to 1.2 THz. Three chemometrics methods, principal component analysis (PCA), discriminant analysis (DA) and discriminant partial least squares (DPLS), were employed to classify sugar beet samples into two groups: genetically modified organisms (GMOs) and non-GMOs. The DPLS method yielded the best classification result, and the percentages of successful classification for GM and non-GM sugar beets were both 100%. Results of the present study demonstrate the usefulness of THz spectroscopy together with chemometrics methods as a powerful tool to distinguish GM and non-GM sugar beets.

  1. Covariate-adjusted measures of discrimination for survival data

    DEFF Research Database (Denmark)

    White, Ian R; Rapsomaniki, Eleni; Frikke-Schmidt, Ruth

    2015-01-01

    by the study design (e.g. age and sex) influence discrimination and can make it difficult to compare model discrimination between studies. Although covariate adjustment is a standard procedure for quantifying disease-risk factor associations, there are no covariate adjustment methods for discrimination...... statistics in censored survival data. OBJECTIVE: To develop extensions of the C-index and D-index that describe the prognostic ability of a model adjusted for one or more covariate(s). METHOD: We define a covariate-adjusted C-index and D-index for censored survival data, propose several estimators......, and investigate their performance in simulation studies and in data from a large individual participant data meta-analysis, the Emerging Risk Factors Collaboration. RESULTS: The proposed methods perform well in simulations. In the Emerging Risk Factors Collaboration data, the age-adjusted C-index and D-index were...

  2. Discrimination of nuclear-explosion and lightning electromagnetic pulse

    International Nuclear Information System (INIS)

    Qi Shufeng; Li Ximei; Han Shaoqing; Niu Chao; Feng Jun; Liu Daizhi

    2012-01-01

    The discrimination of nuclear-explosion and lightning electromagnetic pulses was studied using empirical mode decomposition and the fractal analytical method. The box dimensions of nuclear-explosion and lightning electromagnetic pulses' original signals were calculated, and the box dimensions of the intrinsic mode functions (IMFs) of nuclear-explosion and lightning electromagnetic pulses' original signals after empirical mode decomposition were also obtained. The discrimination of nuclear explosion and lightning was studied using the nearest neighbor classification. The experimental results show that, the discrimination rate of the box dimension based on the first and second IMF after the original signal empirical mode decomposition is higher than that based on the third and forth IMF; the discrimination rate of the box dimension based on the original signal is higher than that based on any IMF; and the discrimination rate based on two-dimensional and three-dimensional characters is higher and more stable than that based on one-dimensional character, besides, the discrimination rate based on three-dimensional character is over 90%. (authors)

  3. Functional discrimination of membrane proteins using machine learning techniques

    Directory of Open Access Journals (Sweden)

    Yabuki Yukimitsu

    2008-03-01

    Full Text Available Abstract Background Discriminating membrane proteins based on their functions is an important task in genome annotation. In this work, we have analyzed the characteristic features of amino acid residues in membrane proteins that perform major functions, such as channels/pores, electrochemical potential-driven transporters and primary active transporters. Results We observed that the residues Asp, Asn and Tyr are dominant in channels/pores whereas the composition of hydrophobic residues, Phe, Gly, Ile, Leu and Val is high in electrochemical potential-driven transporters. The composition of all the amino acids in primary active transporters lies in between other two classes of proteins. We have utilized different machine learning algorithms, such as, Bayes rule, Logistic function, Neural network, Support vector machine, Decision tree etc. for discriminating these classes of proteins. We observed that most of the algorithms have discriminated them with similar accuracy. The neural network method discriminated the channels/pores, electrochemical potential-driven transporters and active transporters with the 5-fold cross validation accuracy of 64% in a data set of 1718 membrane proteins. The application of amino acid occurrence improved the overall accuracy to 68%. In addition, we have discriminated transporters from other α-helical and β-barrel membrane proteins with the accuracy of 85% using k-nearest neighbor method. The classification of transporters and all other proteins (globular and membrane showed the accuracy of 82%. Conclusion The performance of discrimination with amino acid occurrence is better than that with amino acid composition. We suggest that this method could be effectively used to discriminate transporters from all other globular and membrane proteins, and classify them into channels/pores, electrochemical and active transporters.

  4. Pulse discrimination of background and gamma-ray source by digital pulse shape discrimination in a BF3 detector

    International Nuclear Information System (INIS)

    Kim, Jinhyung; Kim, J. H.; Choi, H. D.

    2014-01-01

    As a representative method of non-destructive assay, accurate neutron measurement is difficult due to large background radiation such as γ-ray, secondary radiation, spurious pulse, etc. In a BF 3 detector, the process of signal generation is different between neutron and other radiations. As the development of detection technique, all of signal data can be digitized by digital measurement method. In the previous study, Applied Nuclear Physics Group in Seoul National University has developed digital Pulse Shape Discrimination (PSD) method using digital oscilloscope. In this study, optimization of parameters for pulse discrimination is discussed and γ-ray region is determined by measuring 60 Co source. The background signal of BF 3 detector is discriminated by digital PSD system. Parameters for PSD are optimized through FOM calculation. And the γ-ray region is determined by measuring 60 Co source. In the future, the performance of developed system will be tested in low and high intensity neutron field

  5. STARTING BLOCK PERFORMANCE IN SPRINTERS: A STATISTICAL METHOD FOR IDENTIFYING DISCRIMINATIVE PARAMETERS OF THE PERFORMANCE AND AN ANALYSIS OF THE EFFECT OF PROVIDING FEEDBACK OVER A 6-WEEK PERIOD

    Directory of Open Access Journals (Sweden)

    Sylvie Fortier

    2005-06-01

    Full Text Available The purpose of this study was twofold: (a to examine if kinetic and kinematic parameters of the sprint start could differentiate elite from sub-elite sprinters and, (b to investigate whether providing feedback (FB about selected parameters could improve starting block performance of intermediate sprinters over a 6-week training period. Twelve male sprinters, assigned to an elite or a sub-elite group, participated in Experiment 1. Eight intermediate sprinters participated in Experiment 2. All athletes were required to perform three sprint starts at maximum intensity followed by a 10-m run. To detect differences between elite and sub-elite groups, comparisons were made using t-tests for independent samples. Parameters reaching a significant group difference were retained for the linear discriminant analysis (LDA. The LDA yielded four discriminative kinetic parameters. Feedback about these selected parameters was given to sprinters in Experiment 2. For this experiment, data acquisition was divided into three periods. The first six sessions were without specific FB, whereas the following six sessions were enriched by kinetic FB. Finally, athletes underwent a retention session (without FB 4 weeks after the twelfth session. Even though differences were found in the time to front peak force, the time to rear peak force, and the front peak force in the retention session, the results of the present study showed that providing FB about selected kinetic parameters differentiating elite from sub-elite sprinters did not improve the starting block performance of intermediate sprinters

  6. Discriminating Bacteria with Optical Sensors Based on Functionalized Nanoporous Xerogels

    Directory of Open Access Journals (Sweden)

    Sabine Crunaire

    2014-06-01

    Full Text Available An innovative and low-cost method is proposed for the detection and discrimination of indole-positive pathogen bacteria. The method allows the non-invasive detection of gaseous indole, released by bacteria, with nanoporous colorimetric sensors. The innovation comes from the use of nanoporous matrices doped with 4-(dimethylamino-cinnamaldehyde, which act as sponges to trap and concentrate the targeted analyte and turn from transparent to dark green, long before the colonies get visible with naked eyes. With such sensors, it was possible to discriminate E. coli from H. alvei, two indole-positive and negative bacteria after seven hours of incubation.

  7. Extraction of multi-scale landslide morphological features based on local Gi* using airborne LiDAR-derived DEM

    Science.gov (United States)

    Shi, Wenzhong; Deng, Susu; Xu, Wenbing

    2018-02-01

    For automatic landslide detection, landslide morphological features should be quantitatively expressed and extracted. High-resolution Digital Elevation Models (DEMs) derived from airborne Light Detection and Ranging (LiDAR) data allow fine-scale morphological features to be extracted, but noise in DEMs influences morphological feature extraction, and the multi-scale nature of landslide features should be considered. This paper proposes a method to extract landslide morphological features characterized by homogeneous spatial patterns. Both profile and tangential curvature are utilized to quantify land surface morphology, and a local Gi* statistic is calculated for each cell to identify significant patterns of clustering of similar morphometric values. The method was tested on both synthetic surfaces simulating natural terrain and airborne LiDAR data acquired over an area dominated by shallow debris slides and flows. The test results of the synthetic data indicate that the concave and convex morphologies of the simulated terrain features at different scales and distinctness could be recognized using the proposed method, even when random noise was added to the synthetic data. In the test area, cells with large local Gi* values were extracted at a specified significance level from the profile and the tangential curvature image generated from the LiDAR-derived 1-m DEM. The morphologies of landslide main scarps, source areas and trails were clearly indicated, and the morphological features were represented by clusters of extracted cells. A comparison with the morphological feature extraction method based on curvature thresholds proved the proposed method's robustness to DEM noise. When verified against a landslide inventory, the morphological features of almost all recent (historical (> 10 years) landslides were extracted. This finding indicates that the proposed method can facilitate landslide detection, although the cell clusters extracted from curvature images should

  8. Discriminative sparse coding on multi-manifolds

    KAUST Repository

    Wang, J.J.-Y.; Bensmail, H.; Yao, N.; Gao, Xin

    2013-01-01

    Sparse coding has been popularly used as an effective data representation method in various applications, such as computer vision, medical imaging and bioinformatics. However, the conventional sparse coding algorithms and their manifold-regularized variants (graph sparse coding and Laplacian sparse coding), learn codebooks and codes in an unsupervised manner and neglect class information that is available in the training set. To address this problem, we propose a novel discriminative sparse coding method based on multi-manifolds, that learns discriminative class-conditioned codebooks and sparse codes from both data feature spaces and class labels. First, the entire training set is partitioned into multiple manifolds according to the class labels. Then, we formulate the sparse coding as a manifold-manifold matching problem and learn class-conditioned codebooks and codes to maximize the manifold margins of different classes. Lastly, we present a data sample-manifold matching-based strategy to classify the unlabeled data samples. Experimental results on somatic mutations identification and breast tumor classification based on ultrasonic images demonstrate the efficacy of the proposed data representation and classification approach. 2013 The Authors. All rights reserved.

  9. DISCRIMINANT ANALYSIS OF BANK PROFITABILITY LEVELS

    Directory of Open Access Journals (Sweden)

    Ante Rozga

    2013-02-01

    Full Text Available Discriminant analysis has been employed in this paper in order to identify and explain key features of bank profitability levels. Bank profitability is set up in the form of two categorical variables: profit or loss recorded and above or below average return on equity. Predictor variables are selected from various groups of financial indicators usually included in the empirical work on microeconomic determinants of bank profitability. The data from the Croatian banking sector is analyzed using the Enter method. General recommendations for a more profitable business of banking found in the bank management literature and existing empirical framework such as rationalization of overhead costs, asset growth, increase of non-interest income by expanding scale and scope of financial products proved to be important for classification of banks in different profitability levels. A higher market share may bring additional advantages. Classification results, canonical correlation and Wilks’ Lambda test confirm statistical significance of research results. Altogether, discriminant analysis turns out to be a suitable statistical method for solving presented research problem and moving forward from the bankruptcy, credit rating or default issues in finance.

  10. Discriminative sparse coding on multi-manifolds

    KAUST Repository

    Wang, J.J.-Y.

    2013-09-26

    Sparse coding has been popularly used as an effective data representation method in various applications, such as computer vision, medical imaging and bioinformatics. However, the conventional sparse coding algorithms and their manifold-regularized variants (graph sparse coding and Laplacian sparse coding), learn codebooks and codes in an unsupervised manner and neglect class information that is available in the training set. To address this problem, we propose a novel discriminative sparse coding method based on multi-manifolds, that learns discriminative class-conditioned codebooks and sparse codes from both data feature spaces and class labels. First, the entire training set is partitioned into multiple manifolds according to the class labels. Then, we formulate the sparse coding as a manifold-manifold matching problem and learn class-conditioned codebooks and codes to maximize the manifold margins of different classes. Lastly, we present a data sample-manifold matching-based strategy to classify the unlabeled data samples. Experimental results on somatic mutations identification and breast tumor classification based on ultrasonic images demonstrate the efficacy of the proposed data representation and classification approach. 2013 The Authors. All rights reserved.

  11. Newborns' Discrimination of Chromatic from Achromatic Stimuli.

    Science.gov (United States)

    Adams, Russell J.; And Others

    1986-01-01

    Two experiments assessed the extent of newborns' ability to discriminate color. Results imply that newborns have some, albeit limited, capacity to discriminate chromatic from achromatic stimuli, and hence, are at least dichromats. (Author/DR)

  12. 14 CFR 1250.103 - Discrimination prohibited.

    Science.gov (United States)

    2010-01-01

    ... 14 Aeronautics and Space 5 2010-01-01 2010-01-01 false Discrimination prohibited. 1250.103 Section 1250.103 Aeronautics and Space NATIONAL AERONAUTICS AND SPACE ADMINISTRATION NONDISCRIMINATION IN... Discrimination prohibited. ...

  13. Automated, feature-based image alignment for high-resolution imaging mass spectrometry of large biological samples

    NARCIS (Netherlands)

    Broersen, A.; Liere, van R.; Altelaar, A.F.M.; Heeren, R.M.A.; McDonnell, L.A.

    2008-01-01

    High-resolution imaging mass spectrometry of large biological samples is the goal of several research groups. In mosaic imaging, the most common method, the large sample is divided into a mosaic of small areas that are then analyzed with high resolution. Here we present an automated alignment

  14. Evaluating score- and feature-based likelihood ratio models for multivariate continuous data: applied to forensic MDMA comparison

    NARCIS (Netherlands)

    Bolck, A.; Ni, H.; Lopatka, M.

    2015-01-01

    Likelihood ratio (LR) models are moving into the forefront of forensic evidence evaluation as these methods are adopted by a diverse range of application areas in forensic science. We examine the fundamentally different results that can be achieved when feature- and score-based methodologies are

  15. Structural Discrimination and Autonomous Vehicles

    DEFF Research Database (Denmark)

    Liu, Hin-Yan

    2016-01-01

    This paper examines the potential for structural discrimination to be woven into the fabric of autonomous vehicle developments, which remain underexplored and undiscussed. The prospect for structural discrimination arises as a result of the coordinated modes of autonomous vehicle behaviour...... individual identity, and potentially relative worth, to autonomous vehicles engaging in a crash damage calculus. At the risk of introducing these ideas into the development of autonomous vehicles, this paper hopes to spark a debate to foreclose these eventualities....... that is prescribed by its code. This leads to the potential for individuated outcomes to be networked and thereby multiplied consistently to any number of vehicles implementing such a code. The aggregated effects of such algorithmic policy preferences will thus cumulate in the reallocation of benefits and burdens...

  16. Limited taste discrimination in Drosophila.

    Science.gov (United States)

    Masek, Pavel; Scott, Kristin

    2010-08-17

    In the gustatory systems of mammals and flies, different populations of sensory cells recognize different taste modalities, such that there are cells that respond selectively to sugars and others to bitter compounds. This organization readily allows animals to distinguish compounds of different modalities but may limit the ability to distinguish compounds within one taste modality. Here, we developed a behavioral paradigm in Drosophila melanogaster to evaluate directly the tastes that a fly distinguishes. These studies reveal that flies do not discriminate among different sugars, or among different bitter compounds, based on chemical identity. Instead, flies show a limited ability to distinguish compounds within a modality based on intensity or palatability. Taste associative learning, similar to olfactory learning, requires the mushroom bodies, suggesting fundamental similarities in brain mechanisms underlying behavioral plasticity. Overall, these studies provide insight into the discriminative capacity of the Drosophila gustatory system and the modulation of taste behavior.

  17. Testing for Statistical Discrimination based on Gender

    OpenAIRE

    Lesner, Rune Vammen

    2016-01-01

    This paper develops a model which incorporates the two most commonly cited strands of the literature on statistical discrimination, namely screening discrimination and stereotyping. The model is used to provide empirical evidence of statistical discrimination based on gender in the labour market. It is shown that the implications of both screening discrimination and stereotyping are consistent with observable wage dynamics. In addition, it is found that the gender wage gap decreases in tenure...

  18. A simple neutron-gamma discriminating system

    International Nuclear Information System (INIS)

    Liu Zhongming; Xing Shilin; Wang Zhongmin

    1986-01-01

    A simple neutron-gamma discriminating system is described. A detector and a pulse shape discriminator are suitable for the neutron-gamma discriminating system. The influence of the constant fraction discriminator threshold energy on the neutron-gamma resolution properties is shown. The neutron-gamma timing distributions from an 241 Am-Be source, 2.5 MeV neutron beam and 14 MeV neutron beam are presented

  19. Discrimination Against Migrant Workers in Malaysia

    OpenAIRE

    Badarulzaman, Muhammad Hafiz; Ayub, Zainal A; Yusoff, Zuryati M; Wahab, Harlida A

    2016-01-01

    AbstractMigrant workers are often discriminated against in almost every aspect of life. Discrimination against them is due to irrational dislike of them and also negative perception towards them. It is alleged that migrant workers contribute to the crimes hike in Malaysia. Using doctrinal research methodology, this article discusses direct and perceptive discrimination against them. This article concludes that physical discriminations are mostly happened because ineffective enforcement of the...

  20. Age discrimination: the new Regulations

    OpenAIRE

    Sprack, John

    2006-01-01

    A summary of the principal changes introduced by the Employment Equality (Age) Regulations 2006 as they came into effect in England and Wales. Extracts from the Regulations follow the commentary. Article by John Sprack (Barrister, part-time Chairman of Employment Tribunals and author of Tottel's Guide to the Age Discrimination Regulations 2006) published in Amicus Curiae – Journal of the Society for Advanced Legal Studies at the Institute of Advanced Legal Studies. The Journal is produced by ...