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Sample records for efficient independent component

  1. On an efficient modification of singular value decomposition using independent component analysis for improved MRS denoising and quantification

    International Nuclear Information System (INIS)

    Stamatopoulos, V G; Karras, D A; Mertzios, B G

    2009-01-01

    An efficient modification of singular value decomposition (SVD) is proposed in this paper aiming at denoising and more importantly at quantifying more accurately the statistically independent spectra of metabolite sources in magnetic resonance spectroscopy (MRS). Although SVD is known in MRS applications and several efficient algorithms exist for estimating SVD summation terms in which the raw MRS data are analyzed, however, it would be more beneficial for such an analysis if techniques with the ability to estimate statistically independent spectra could be employed. SVD is known to separate signal and noise subspaces but it assumes orthogonal properties for the components comprising signal subspace, which is not always the case, and might impose heavy constraints for the MRS case. A much more relaxing constraint would be to assume statistically independent components. Therefore, a modification of the main methodology incorporating techniques for calculating the assumed statistically independent spectra is proposed by applying SVD on the MRS spectrogram through application of the short time Fourier transform (STFT). This approach is based on combining SVD on STFT spectrogram followed by an iterative application of independent component analysis (ICA). Moreover, it is shown that the proposed methodology combined with a regression analysis would lead to improved quantification of the MRS signals. An experimental study based on synthetic MRS signals has been conducted to evaluate the herein proposed methodologies. The results obtained have been discussed and it is shown to be quite promising

  2. Independent component analysis: recent advances

    OpenAIRE

    Hyv?rinen, Aapo

    2013-01-01

    Independent component analysis is a probabilistic method for learning a linear transform of a random vector. The goal is to find components that are maximally independent and non-Gaussian (non-normal). Its fundamental difference to classical multi-variate statistical methods is in the assumption of non-Gaussianity, which enables the identification of original, underlying components, in contrast to classical methods. The basic theory of independent component analysis was mainly developed in th...

  3. Color Independent Components Based SIFT Descriptors for Object/Scene Classification

    Science.gov (United States)

    Ai, Dan-Ni; Han, Xian-Hua; Ruan, Xiang; Chen, Yen-Wei

    In this paper, we present a novel color independent components based SIFT descriptor (termed CIC-SIFT) for object/scene classification. We first learn an efficient color transformation matrix based on independent component analysis (ICA), which is adaptive to each category in a database. The ICA-based color transformation can enhance contrast between the objects and the background in an image. Then we compute CIC-SIFT descriptors over all three transformed color independent components. Since the ICA-based color transformation can boost the objects and suppress the background, the proposed CIC-SIFT can extract more effective and discriminative local features for object/scene classification. The comparison is performed among seven SIFT descriptors, and the experimental classification results show that our proposed CIC-SIFT is superior to other conventional SIFT descriptors.

  4. Blind Detection of Independent Dynamic Components

    DEFF Research Database (Denmark)

    Hansen, Lars Kai; Larsen, Jan; Kolenda, Thomas

    2001-01-01

    In certain applications of independent component analysis (ICA) it is of interest to test hypotheses concerning the number of components or simply to test whether a given number of components is significant relative to a "white noise" null hypothesis. We estimate probabilities of such competing h...

  5. Bayesian Independent Component Analysis

    DEFF Research Database (Denmark)

    Winther, Ole; Petersen, Kaare Brandt

    2007-01-01

    In this paper we present an empirical Bayesian framework for independent component analysis. The framework provides estimates of the sources, the mixing matrix and the noise parameters, and is flexible with respect to choice of source prior and the number of sources and sensors. Inside the engine...

  6. Signal-dependent independent component analysis by tunable mother wavelets

    International Nuclear Information System (INIS)

    Seo, Kyung Ho

    2006-02-01

    The objective of this study is to improve the standard independent component analysis when applied to real-world signals. Independent component analysis starts from the assumption that signals from different physical sources are statistically independent. But real-world signals such as EEG, ECG, MEG, and fMRI signals are not statistically independent perfectly. By definition, standard independent component analysis algorithms are not able to estimate statistically dependent sources, that is, when the assumption of independence does not hold. Therefore before independent component analysis, some preprocessing stage is needed. This paper started from simple intuition that wavelet transformed source signals by 'well-tuned' mother wavelet will be simplified sufficiently, and then the source separation will show better results. By the correlation coefficient method, the tuning process between source signal and tunable mother wavelet was executed. Gamma component of raw EEG signal was set to target signal, and wavelet transform was executed by tuned mother wavelet and standard mother wavelets. Simulation results by these wavelets was shown

  7. Independent component analysis in non-hypothesis driven metabolomics

    DEFF Research Database (Denmark)

    Li, Xiang; Hansen, Jakob; Zhao, Xinjie

    2012-01-01

    In a non-hypothesis driven metabolomics approach plasma samples collected at six different time points (before, during and after an exercise bout) were analyzed by gas chromatography-time of flight mass spectrometry (GC-TOF MS). Since independent component analysis (ICA) does not need a priori...... information on the investigated process and moreover can separate statistically independent source signals with non-Gaussian distribution, we aimed to elucidate the analytical power of ICA for the metabolic pattern analysis and the identification of key metabolites in this exercise study. A novel approach...... based on descriptive statistics was established to optimize ICA model. In the GC-TOF MS data set the number of principal components after whitening and the number of independent components of ICA were optimized and systematically selected by descriptive statistics. The elucidated dominating independent...

  8. How Many Separable Sources? Model Selection In Independent Components Analysis

    Science.gov (United States)

    Woods, Roger P.; Hansen, Lars Kai; Strother, Stephen

    2015-01-01

    Unlike mixtures consisting solely of non-Gaussian sources, mixtures including two or more Gaussian components cannot be separated using standard independent components analysis methods that are based on higher order statistics and independent observations. The mixed Independent Components Analysis/Principal Components Analysis (mixed ICA/PCA) model described here accommodates one or more Gaussian components in the independent components analysis model and uses principal components analysis to characterize contributions from this inseparable Gaussian subspace. Information theory can then be used to select from among potential model categories with differing numbers of Gaussian components. Based on simulation studies, the assumptions and approximations underlying the Akaike Information Criterion do not hold in this setting, even with a very large number of observations. Cross-validation is a suitable, though computationally intensive alternative for model selection. Application of the algorithm is illustrated using Fisher's iris data set and Howells' craniometric data set. Mixed ICA/PCA is of potential interest in any field of scientific investigation where the authenticity of blindly separated non-Gaussian sources might otherwise be questionable. Failure of the Akaike Information Criterion in model selection also has relevance in traditional independent components analysis where all sources are assumed non-Gaussian. PMID:25811988

  9. Tomato sorting using independent component analysis on spectral images

    NARCIS (Netherlands)

    Polder, G.; Heijden, van der G.W.A.M.; Young, I.T.

    2003-01-01

    Independent Component Analysis is one of the most widely used methods for blind source separation. In this paper we use this technique to estimate the most important compounds which play a role in the ripening of tomatoes. Spectral images of tomatoes were analyzed. Two main independent components

  10. Multi-spectrometer calibration transfer based on independent component analysis.

    Science.gov (United States)

    Liu, Yan; Xu, Hao; Xia, Zhenzhen; Gong, Zhiyong

    2018-02-26

    Calibration transfer is indispensable for practical applications of near infrared (NIR) spectroscopy due to the need for precise and consistent measurements across different spectrometers. In this work, a method for multi-spectrometer calibration transfer is described based on independent component analysis (ICA). A spectral matrix is first obtained by aligning the spectra measured on different spectrometers. Then, by using independent component analysis, the aligned spectral matrix is decomposed into the mixing matrix and the independent components of different spectrometers. These differing measurements between spectrometers can then be standardized by correcting the coefficients within the independent components. Two NIR datasets of corn and edible oil samples measured with three and four spectrometers, respectively, were used to test the reliability of this method. The results of both datasets reveal that spectra measurements across different spectrometers can be transferred simultaneously and that the partial least squares (PLS) models built with the measurements on one spectrometer can predict that the spectra can be transferred correctly on another.

  11. Independent component analysis for automatic note extraction from musical trills

    Science.gov (United States)

    Brown, Judith C.; Smaragdis, Paris

    2004-05-01

    The method of principal component analysis, which is based on second-order statistics (or linear independence), has long been used for redundancy reduction of audio data. The more recent technique of independent component analysis, enforcing much stricter statistical criteria based on higher-order statistical independence, is introduced and shown to be far superior in separating independent musical sources. This theory has been applied to piano trills and a database of trill rates was assembled from experiments with a computer-driven piano, recordings of a professional pianist, and commercially available compact disks. The method of independent component analysis has thus been shown to be an outstanding, effective means of automatically extracting interesting musical information from a sea of redundant data.

  12. Condition monitoring with Mean field independent components analysis

    DEFF Research Database (Denmark)

    Pontoppidan, Niels Henrik; Sigurdsson, Sigurdur; Larsen, Jan

    2005-01-01

    We discuss condition monitoring based on mean field independent components analysis of acoustic emission energy signals. Within this framework it is possible to formulate a generative model that explains the sources, their mixing and also the noise statistics of the observed signals. By using...... a novelty approach we may detect unseen faulty signals as indeed faulty with high precision, even though the model learns only from normal signals. This is done by evaluating the likelihood that the model generated the signals and adapting a simple threshold for decision. Acoustic emission energy signals...... from a large diesel engine is used to demonstrate this approach. The results show that mean field independent components analysis gives a better detection of fault compared to principal components analysis, while at the same time selecting a more compact model...

  13. A K-means multivariate approach for clustering independent components from magnetoencephalographic data.

    Science.gov (United States)

    Spadone, Sara; de Pasquale, Francesco; Mantini, Dante; Della Penna, Stefania

    2012-09-01

    Independent component analysis (ICA) is typically applied on functional magnetic resonance imaging, electroencephalographic and magnetoencephalographic (MEG) data due to its data-driven nature. In these applications, ICA needs to be extended from single to multi-session and multi-subject studies for interpreting and assigning a statistical significance at the group level. Here a novel strategy for analyzing MEG independent components (ICs) is presented, Multivariate Algorithm for Grouping MEG Independent Components K-means based (MAGMICK). The proposed approach is able to capture spatio-temporal dynamics of brain activity in MEG studies by running ICA at subject level and then clustering the ICs across sessions and subjects. Distinctive features of MAGMICK are: i) the implementation of an efficient set of "MEG fingerprints" designed to summarize properties of MEG ICs as they are built on spatial, temporal and spectral parameters; ii) the implementation of a modified version of the standard K-means procedure to improve its data-driven character. This algorithm groups the obtained ICs automatically estimating the number of clusters through an adaptive weighting of the parameters and a constraint on the ICs independence, i.e. components coming from the same session (at subject level) or subject (at group level) cannot be grouped together. The performances of MAGMICK are illustrated by analyzing two sets of MEG data obtained during a finger tapping task and median nerve stimulation. The results demonstrate that the method can extract consistent patterns of spatial topography and spectral properties across sessions and subjects that are in good agreement with the literature. In addition, these results are compared to those from a modified version of affinity propagation clustering method. The comparison, evaluated in terms of different clustering validity indices, shows that our methodology often outperforms the clustering algorithm. Eventually, these results are

  14. How Many Separable Sources? Model Selection In Independent Components Analysis

    DEFF Research Database (Denmark)

    Woods, Roger P.; Hansen, Lars Kai; Strother, Stephen

    2015-01-01

    among potential model categories with differing numbers of Gaussian components. Based on simulation studies, the assumptions and approximations underlying the Akaike Information Criterion do not hold in this setting, even with a very large number of observations. Cross-validation is a suitable, though....../Principal Components Analysis (mixed ICA/PCA) model described here accommodates one or more Gaussian components in the independent components analysis model and uses principal components analysis to characterize contributions from this inseparable Gaussian subspace. Information theory can then be used to select from...... might otherwise be questionable. Failure of the Akaike Information Criterion in model selection also has relevance in traditional independent components analysis where all sources are assumed non-Gaussian....

  15. Extracting functional components of neural dynamics with Independent Component Analysis and inverse Current Source Density.

    Science.gov (United States)

    Lęski, Szymon; Kublik, Ewa; Swiejkowski, Daniel A; Wróbel, Andrzej; Wójcik, Daniel K

    2010-12-01

    Local field potentials have good temporal resolution but are blurred due to the slow spatial decay of the electric field. For simultaneous recordings on regular grids one can reconstruct efficiently the current sources (CSD) using the inverse Current Source Density method (iCSD). It is possible to decompose the resultant spatiotemporal information about the current dynamics into functional components using Independent Component Analysis (ICA). We show on test data modeling recordings of evoked potentials on a grid of 4 × 5 × 7 points that meaningful results are obtained with spatial ICA decomposition of reconstructed CSD. The components obtained through decomposition of CSD are better defined and allow easier physiological interpretation than the results of similar analysis of corresponding evoked potentials in the thalamus. We show that spatiotemporal ICA decompositions can perform better for certain types of sources but it does not seem to be the case for the experimental data studied. Having found the appropriate approach to decomposing neural dynamics into functional components we use the technique to study the somatosensory evoked potentials recorded on a grid spanning a large part of the forebrain. We discuss two example components associated with the first waves of activation of the somatosensory thalamus. We show that the proposed method brings up new, more detailed information on the time and spatial location of specific activity conveyed through various parts of the somatosensory thalamus in the rat.

  16. Determining the optimal number of independent components for reproducible transcriptomic data analysis.

    Science.gov (United States)

    Kairov, Ulykbek; Cantini, Laura; Greco, Alessandro; Molkenov, Askhat; Czerwinska, Urszula; Barillot, Emmanuel; Zinovyev, Andrei

    2017-09-11

    Independent Component Analysis (ICA) is a method that models gene expression data as an action of a set of statistically independent hidden factors. The output of ICA depends on a fundamental parameter: the number of components (factors) to compute. The optimal choice of this parameter, related to determining the effective data dimension, remains an open question in the application of blind source separation techniques to transcriptomic data. Here we address the question of optimizing the number of statistically independent components in the analysis of transcriptomic data for reproducibility of the components in multiple runs of ICA (within the same or within varying effective dimensions) and in multiple independent datasets. To this end, we introduce ranking of independent components based on their stability in multiple ICA computation runs and define a distinguished number of components (Most Stable Transcriptome Dimension, MSTD) corresponding to the point of the qualitative change of the stability profile. Based on a large body of data, we demonstrate that a sufficient number of dimensions is required for biological interpretability of the ICA decomposition and that the most stable components with ranks below MSTD have more chances to be reproduced in independent studies compared to the less stable ones. At the same time, we show that a transcriptomics dataset can be reduced to a relatively high number of dimensions without losing the interpretability of ICA, even though higher dimensions give rise to components driven by small gene sets. We suggest a protocol of ICA application to transcriptomics data with a possibility of prioritizing components with respect to their reproducibility that strengthens the biological interpretation. Computing too few components (much less than MSTD) is not optimal for interpretability of the results. The components ranked within MSTD range have more chances to be reproduced in independent studies.

  17. Efficient algorithms for conditional independence inference

    Czech Academy of Sciences Publication Activity Database

    Bouckaert, R.; Hemmecke, R.; Lindner, S.; Studený, Milan

    2010-01-01

    Roč. 11, č. 1 (2010), s. 3453-3479 ISSN 1532-4435 R&D Projects: GA ČR GA201/08/0539; GA MŠk 1M0572 Institutional research plan: CEZ:AV0Z10750506 Keywords : conditional independence inference * linear programming approach Subject RIV: BA - General Mathematics Impact factor: 2.949, year: 2010 http://library.utia.cas.cz/separaty/2010/MTR/studeny-efficient algorithms for conditional independence inference.pdf

  18. Separation of GRACE geoid time-variations using Independent Component Analysis

    Science.gov (United States)

    Frappart, F.; Ramillien, G.; Maisongrande, P.; Bonnet, M.

    2009-12-01

    Independent Component Analysis (ICA) is a blind separation method based on the simple assumptions of the independence of the sources and the non-Gaussianity of the observations. An approach based on this numerical method is used here to extract hydrological signals over land and oceans from the polluting striping noise due to orbit repetitiveness and present in the GRACE global mass anomalies. We took advantage of the availability of monthly Level-2 solutions from three official providers (i.e., CSR, JPL and GFZ) that can be considered as different observations of the same phenomenon. The efficiency of the methodology is first demonstrated on a synthetic case. Applied to one month of GRACE solutions, it allows to clearly separate the total water storage change from the meridional-oriented spurious gravity signals on the continents but not on the oceans. This technique gives results equivalent as the destriping method for continental water storage for the hydrological patterns with less smoothing. This methodology is then used to filter the complete series of the 2002-2009 GRACE solutions.

  19. Independent component analysis of edge information for face recognition

    CERN Document Server

    Karande, Kailash Jagannath

    2013-01-01

    The book presents research work on face recognition using edge information as features for face recognition with ICA algorithms. The independent components are extracted from edge information. These independent components are used with classifiers to match the facial images for recognition purpose. In their study, authors have explored Canny and LOG edge detectors as standard edge detection methods. Oriented Laplacian of Gaussian (OLOG) method is explored to extract the edge information with different orientations of Laplacian pyramid. Multiscale wavelet model for edge detection is also propos

  20. Blind Separation of Event-Related Brain Responses into Independent Components

    National Research Council Canada - National Science Library

    Makeig, Scott

    1996-01-01

    .... We report here a method for the blind separation of event-related brain responses into spatially stationary and temporally independent subcomponents using an Independent Component Analysis algorithm...

  1. Independent component analysis for understanding multimedia content

    DEFF Research Database (Denmark)

    Kolenda, Thomas; Hansen, Lars Kai; Larsen, Jan

    2002-01-01

    Independent component analysis of combined text and image data from Web pages has potential for search and retrieval applications by providing more meaningful and context dependent content. It is demonstrated that ICA of combined text and image features has a synergistic effect, i.e., the retrieval...

  2. Fuel-Efficient Road Vehicle Non-Engine Components

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2007-07-01

    The need to address global energy issues, i.e. energy security and climate change, is more urgent than ever. Road vehicles dominate global oil consumption and are one of the fastest growing energy end-uses. This paper studies policies and measures to improve on-road fuel efficiency of vehicles by focusing on energy efficiency of automobile components not generally considered in official fuel efficiency test, namely tyres, cooling technologies and lightings. In this paper, current policies and industry activities on these components are reviewed, fuel saving potential by the components analysed and possible policies to realise the potential recommended.

  3. Partitioning diversity into independent alpha and beta components.

    Science.gov (United States)

    Jost, Lou

    2007-10-01

    Existing general definitions of beta diversity often produce a beta with a hidden dependence on alpha. Such a beta cannot be used to compare regions that differ in alpha diversity. To avoid misinterpretation, existing definitions of alpha and beta must be replaced by a definition that partitions diversity into independent alpha and beta components. Such a unique definition is derived here. When these new alpha and beta components are transformed into their numbers equivalents (effective numbers of elements), Whittaker's multiplicative law (alpha x beta = gamma) is necessarily true for all indices. The new beta gives the effective number of distinct communities. The most popular similarity and overlap measures of ecology (Jaccard, Sorensen, Horn, and Morisita-Horn indices) are monotonic transformations of the new beta diversity. Shannon measures follow deductively from this formalism and do not need to be borrowed from information theory; they are shown to be the only standard diversity measures which can be decomposed into meaningful independent alpha and beta components when community weights are unequal.

  4. Blind Separation of Acoustic Signals Combining SIMO-Model-Based Independent Component Analysis and Binary Masking

    Directory of Open Access Journals (Sweden)

    Hiekata Takashi

    2006-01-01

    Full Text Available A new two-stage blind source separation (BSS method for convolutive mixtures of speech is proposed, in which a single-input multiple-output (SIMO-model-based independent component analysis (ICA and a new SIMO-model-based binary masking are combined. SIMO-model-based ICA enables us to separate the mixed signals, not into monaural source signals but into SIMO-model-based signals from independent sources in their original form at the microphones. Thus, the separated signals of SIMO-model-based ICA can maintain the spatial qualities of each sound source. Owing to this attractive property, our novel SIMO-model-based binary masking can be applied to efficiently remove the residual interference components after SIMO-model-based ICA. The experimental results reveal that the separation performance can be considerably improved by the proposed method compared with that achieved by conventional BSS methods. In addition, the real-time implementation of the proposed BSS is illustrated.

  5. Independent component analysis based filtering for penumbral imaging

    International Nuclear Information System (INIS)

    Chen Yenwei; Han Xianhua; Nozaki, Shinya

    2004-01-01

    We propose a filtering based on independent component analysis (ICA) for Poisson noise reduction. In the proposed filtering, the image is first transformed to ICA domain and then the noise components are removed by a soft thresholding (shrinkage). The proposed filter, which is used as a preprocessing of the reconstruction, has been successfully applied to penumbral imaging. Both simulation results and experimental results show that the reconstructed image is dramatically improved in comparison to that without the noise-removing filters

  6. Independent component analysis classification of laser induced breakdown spectroscopy spectra

    International Nuclear Information System (INIS)

    Forni, Olivier; Maurice, Sylvestre; Gasnault, Olivier; Wiens, Roger C.; Cousin, Agnès; Clegg, Samuel M.; Sirven, Jean-Baptiste; Lasue, Jérémie

    2013-01-01

    The ChemCam instrument on board Mars Science Laboratory (MSL) rover uses the laser-induced breakdown spectroscopy (LIBS) technique to remotely analyze Martian rocks. It retrieves spectra up to a distance of seven meters to quantify and to quantitatively analyze the sampled rocks. Like any field application, on-site measurements by LIBS are altered by diverse matrix effects which induce signal variations that are specific to the nature of the sample. Qualitative aspects remain to be studied, particularly LIBS sample identification to determine which samples are of interest for further analysis by ChemCam and other rover instruments. This can be performed with the help of different chemometric methods that model the spectra variance in order to identify a the rock from its spectrum. In this paper we test independent components analysis (ICA) rock classification by remote LIBS. We show that using measures of distance in ICA space, namely the Manhattan and the Mahalanobis distance, we can efficiently classify spectra of an unknown rock. The Mahalanobis distance gives overall better performances and is easier to manage than the Manhattan distance for which the determination of the cut-off distance is not easy. However these two techniques are complementary and their analytical performances will improve with time during MSL operations as the quantity of available Martian spectra will grow. The analysis accuracy and performances will benefit from a combination of the two approaches. - Highlights: • We use a novel independent component analysis method to classify LIBS spectra. • We demonstrate the usefulness of ICA. • We report the performances of the ICA classification. • We compare it to other classical classification schemes

  7. A method for independent component graph analysis of resting-state fMRI

    DEFF Research Database (Denmark)

    de Paula, Demetrius Ribeiro; Ziegler, Erik; Abeyasinghe, Pubuditha M.

    2017-01-01

    Introduction Independent component analysis (ICA) has been extensively used for reducing task-free BOLD fMRI recordings into spatial maps and their associated time-courses. The spatially identified independent components can be considered as intrinsic connectivity networks (ICNs) of non-contiguou......Introduction Independent component analysis (ICA) has been extensively used for reducing task-free BOLD fMRI recordings into spatial maps and their associated time-courses. The spatially identified independent components can be considered as intrinsic connectivity networks (ICNs) of non......-contiguous regions. To date, the spatial patterns of the networks have been analyzed with techniques developed for volumetric data. Objective Here, we detail a graph building technique that allows these ICNs to be analyzed with graph theory. Methods First, ICA was performed at the single-subject level in 15 healthy...... parcellated regions. Third, between-node functional connectivity was established by building edge weights for each networks. Group-level graph analysis was finally performed for each network and compared to the classical network. Results Network graph comparison between the classically constructed network...

  8. Independent Component Analysis in Multimedia Modeling

    DEFF Research Database (Denmark)

    Larsen, Jan

    2003-01-01

    largely refers to text, images/video, audio and combinations of such data. We review a number of applications within single and combined media with the hope that this might provide inspiration for further research in this area. Finally, we provide a detailed presentation of our own recent work on modeling......Modeling of multimedia and multimodal data becomes increasingly important with the digitalization of the world. The objective of this paper is to demonstrate the potential of independent component analysis and blind sources separation methods for modeling and understanding of multimedia data, which...

  9. Selection of independent components based on cortical mapping of electromagnetic activity

    Science.gov (United States)

    Chan, Hui-Ling; Chen, Yong-Sheng; Chen, Li-Fen

    2012-10-01

    Independent component analysis (ICA) has been widely used to attenuate interference caused by noise components from the electromagnetic recordings of brain activity. However, the scalp topographies and associated temporal waveforms provided by ICA may be insufficient to distinguish functional components from artifactual ones. In this work, we proposed two component selection methods, both of which first estimate the cortical distribution of the brain activity for each component, and then determine the functional components based on the parcellation of brain activity mapped onto the cortical surface. Among all independent components, the first method can identify the dominant components, which have strong activity in the selected dominant brain regions, whereas the second method can identify those inter-regional associating components, which have similar component spectra between a pair of regions. For a targeted region, its component spectrum enumerates the amplitudes of its parceled brain activity across all components. The selected functional components can be remixed to reconstruct the focused electromagnetic signals for further analysis, such as source estimation. Moreover, the inter-regional associating components can be used to estimate the functional brain network. The accuracy of the cortical activation estimation was evaluated on the data from simulation studies, whereas the usefulness and feasibility of the component selection methods were demonstrated on the magnetoencephalography data recorded from a gender discrimination study.

  10. Extraction of Independent Structural Images for Principal Component Thermography

    Directory of Open Access Journals (Sweden)

    Dmitry Gavrilov

    2018-03-01

    Full Text Available Thermography is a powerful tool for non-destructive testing of a wide range of materials. Thermography has a number of approaches differing in both experiment setup and the way the collected data are processed. Among such approaches is the Principal Component Thermography (PCT method, which is based on the statistical processing of raw thermal images collected by thermal camera. The processed images (principal components or empirical orthogonal functions form an orthonormal basis, and often look like a superposition of all possible structural features found in the object under inspection—i.e., surface heating non-uniformity, internal defects and material structure. At the same time, from practical point of view it is desirable to have images representing independent structural features. The work presented in this paper proposes an approach for separation of independent image patterns (archetypes from a set of principal component images. The approach is demonstrated in the application of inspection of composite materials as well as the non-invasive analysis of works of art.

  11. Estimation of compound distribution in spectral images of tomatoes using independent component analysis

    NARCIS (Netherlands)

    Polder, G.; Heijden, van der G.W.A.M.

    2003-01-01

    Independent Component Analysis (ICA) is one of the most widely used methods for blind source separation. In this paper we use this technique to estimate the important compounds which play a role in the ripening of tomatoes. Spectral images of tomatoes were analyzed. Two main independent components

  12. Independent component analysis of dynamic contrast-enhanced computed tomography images

    Energy Technology Data Exchange (ETDEWEB)

    Koh, T S [School of Electrical and Electronic Engineering, Nanyang Technological University, 50 Nanyang Ave, Singapore 639798 (Singapore); Yang, X [School of Electrical and Electronic Engineering, Nanyang Technological University, 50 Nanyang Ave, Singapore 639798 (Singapore); Bisdas, S [Department of Diagnostic and Interventional Radiology, Johann Wolfgang Goethe University Hospital, Theodor-Stern-Kai 7, D-60590 Frankfurt (Germany); Lim, C C T [Department of Neuroradiology, National Neuroscience Institute, 11 Jalan Tan Tock Seng, Singapore 308433 (Singapore)

    2006-10-07

    Independent component analysis (ICA) was applied on dynamic contrast-enhanced computed tomography images of cerebral tumours to extract spatial component maps of the underlying vascular structures, which correspond to different haemodynamic phases as depicted by the passage of the contrast medium. The locations of arteries, veins and tumours can be separately identified on these spatial component maps. As the contrast enhancement behaviour of the cerebral tumour differs from the normal tissues, ICA yields a tumour component map that reveals the location and extent of the tumour. Tumour outlines can be generated using the tumour component maps, with relatively simple segmentation methods. (note)

  13. Electroencephalographic dynamics of musical emotion perception revealed by independent spectral components.

    Science.gov (United States)

    Lin, Yuan-Pin; Duann, Jeng-Ren; Chen, Jyh-Horng; Jung, Tzyy-Ping

    2010-04-21

    This study explores the electroencephalographic (EEG) correlates of emotional experience during music listening. Independent component analysis and analysis of variance were used to separate statistically independent spectral changes of the EEG in response to music-induced emotional processes. An independent brain process with equivalent dipole located in the fronto-central region exhibited distinct δ-band and θ-band power changes associated with self-reported emotional states. Specifically, the emotional valence was associated with δ-power decreases and θ-power increases in the frontal-central area, whereas the emotional arousal was accompanied by increases in both δ and θ powers. The resultant emotion-related component activations that were less interfered by the activities from other brain processes complement previous EEG studies of emotion perception to music.

  14. Emotional responses as independent components in EEG

    DEFF Research Database (Denmark)

    Jensen, Camilla Birgitte Falk; Petersen, Michael Kai; Larsen, Jakob Eg

    2014-01-01

    susceptible to noise if captured in a mobile context. Hypothesizing that retrieval of emotional responses in mobile usage scenarios could be enhanced through spatial filtering, we compare a standard EEG electrode based analysis against an approach based on independent component analysis (ICA). By clustering...... or unpleasant images; early posterior negativity (EPN) and late positive potential (LPP). Recent studies suggest that several time course components may be modulated by emotional content in images or text. However these neural signatures are characterized by small voltage changes that would be highly...... by emotional content. We propose that similar approaches to spatial filtering might allow us to retrieve more robust signals in real life mobile usage scenarios, and potentially facilitate design of cognitive interfaces that adapt the selection of media to our emotional responses....

  15. The Economics of Independent Living: Efficiency, Equity and Ethics.

    Science.gov (United States)

    O'Shea, E.; Kennelly, B.

    1996-01-01

    This article explores the meaning of efficiency and equity in the context of independent living programs for people with disabilities. Conflicts in costs and trade-offs in various scenarios of the efficiency/equity equation are examined in terms of theories of utilitarianism, contractarianism, justice and mutual advantage, and justice as…

  16. Variational Bayesian Learning for Wavelet Independent Component Analysis

    Science.gov (United States)

    Roussos, E.; Roberts, S.; Daubechies, I.

    2005-11-01

    In an exploratory approach to data analysis, it is often useful to consider the observations as generated from a set of latent generators or "sources" via a generally unknown mapping. For the noisy overcomplete case, where we have more sources than observations, the problem becomes extremely ill-posed. Solutions to such inverse problems can, in many cases, be achieved by incorporating prior knowledge about the problem, captured in the form of constraints. This setting is a natural candidate for the application of the Bayesian methodology, allowing us to incorporate "soft" constraints in a natural manner. The work described in this paper is mainly driven by problems in functional magnetic resonance imaging of the brain, for the neuro-scientific goal of extracting relevant "maps" from the data. This can be stated as a `blind' source separation problem. Recent experiments in the field of neuroscience show that these maps are sparse, in some appropriate sense. The separation problem can be solved by independent component analysis (ICA), viewed as a technique for seeking sparse components, assuming appropriate distributions for the sources. We derive a hybrid wavelet-ICA model, transforming the signals into a domain where the modeling assumption of sparsity of the coefficients with respect to a dictionary is natural. We follow a graphical modeling formalism, viewing ICA as a probabilistic generative model. We use hierarchical source and mixing models and apply Bayesian inference to the problem. This allows us to perform model selection in order to infer the complexity of the representation, as well as automatic denoising. Since exact inference and learning in such a model is intractable, we follow a variational Bayesian mean-field approach in the conjugate-exponential family of distributions, for efficient unsupervised learning in multi-dimensional settings. The performance of the proposed algorithm is demonstrated on some representative experiments.

  17. Gene Module Identification from Microarray Data Using Nonnegative Independent Component Analysis

    Directory of Open Access Journals (Sweden)

    Ting Gong

    2007-01-01

    Full Text Available Genes mostly interact with each other to form transcriptional modules for performing single or multiple functions. It is important to unravel such transcriptional modules and to determine how disturbances in them may lead to disease. Here, we propose a non-negative independent component analysis (nICA approach for transcriptional module discovery. nICA method utilizes the non-negativity constraint to enforce the independence of biological processes within the participated genes. In such, nICA decomposes the observed gene expression into positive independent components, which fi ts better to the reality of corresponding putative biological processes. In conjunction with nICA modeling, visual statistical data analyzer (VISDA is applied to group genes into modules in latent variable space. We demonstrate the usefulness of the approach through the identification of composite modules from yeast data and the discovery of pathway modules in muscle regeneration.

  18. A first application of independent component analysis to extracting structure from stock returns.

    Science.gov (United States)

    Back, A D; Weigend, A S

    1997-08-01

    This paper explores the application of a signal processing technique known as independent component analysis (ICA) or blind source separation to multivariate financial time series such as a portfolio of stocks. The key idea of ICA is to linearly map the observed multivariate time series into a new space of statistically independent components (ICs). We apply ICA to three years of daily returns of the 28 largest Japanese stocks and compare the results with those obtained using principal component analysis. The results indicate that the estimated ICs fall into two categories, (i) infrequent large shocks (responsible for the major changes in the stock prices), and (ii) frequent smaller fluctuations (contributing little to the overall level of the stocks). We show that the overall stock price can be reconstructed surprisingly well by using a small number of thresholded weighted ICs. In contrast, when using shocks derived from principal components instead of independent components, the reconstructed price is less similar to the original one. ICA is shown to be a potentially powerful method of analyzing and understanding driving mechanisms in financial time series. The application to portfolio optimization is described in Chin and Weigend (1998).

  19. Independent principal component analysis for simulation of soil water content and bulk density in a Canadian Watershed

    Directory of Open Access Journals (Sweden)

    Alaba Boluwade

    2016-09-01

    Full Text Available Accurate characterization of soil properties such as soil water content (SWC and bulk density (BD is vital for hydrologic processes and thus, it is importance to estimate θ (water content and ρ (soil bulk density among other soil surface parameters involved in water retention and infiltration, runoff generation and water erosion, etc. The spatial estimation of these soil properties are important in guiding agricultural management decisions. These soil properties vary both in space and time and are correlated. Therefore, it is important to find an efficient and robust technique to simulate spatially correlated variables. Methods such as principal component analysis (PCA and independent component analysis (ICA can be used for the joint simulations of spatially correlated variables, but they are not without their flaws. This study applied a variant of PCA called independent principal component analysis (IPCA that combines the strengths of both PCA and ICA for spatial simulation of SWC and BD using the soil data set from an 11 km2 Castor watershed in southern Quebec, Canada. Diagnostic checks using the histograms and cumulative distribution function (cdf both raw and back transformed simulations show good agreement. Therefore, the results from this study has potential in characterization of water content variability and bulk density variation for precision agriculture.

  20. Determination of the optimal number of components in independent components analysis.

    Science.gov (United States)

    Kassouf, Amine; Jouan-Rimbaud Bouveresse, Delphine; Rutledge, Douglas N

    2018-03-01

    Independent components analysis (ICA) may be considered as one of the most established blind source separation techniques for the treatment of complex data sets in analytical chemistry. Like other similar methods, the determination of the optimal number of latent variables, in this case, independent components (ICs), is a crucial step before any modeling. Therefore, validation methods are required in order to decide about the optimal number of ICs to be used in the computation of the final model. In this paper, three new validation methods are formally presented. The first one, called Random_ICA, is a generalization of the ICA_by_blocks method. Its specificity resides in the random way of splitting the initial data matrix into two blocks, and then repeating this procedure several times, giving a broader perspective for the selection of the optimal number of ICs. The second method, called KMO_ICA_Residuals is based on the computation of the Kaiser-Meyer-Olkin (KMO) index of the transposed residual matrices obtained after progressive extraction of ICs. The third method, called ICA_corr_y, helps to select the optimal number of ICs by computing the correlations between calculated proportions and known physico-chemical information about samples, generally concentrations, or between a source signal known to be present in the mixture and the signals extracted by ICA. These three methods were tested using varied simulated and experimental data sets and compared, when necessary, to ICA_by_blocks. Results were relevant and in line with expected ones, proving the reliability of the three proposed methods. Copyright © 2017 Elsevier B.V. All rights reserved.

  1. Learning Algorithms for Audio and Video Processing: Independent Component Analysis and Support Vector Machine Based Approaches

    National Research Council Canada - National Science Library

    Qi, Yuan

    2000-01-01

    In this thesis, we propose two new machine learning schemes, a subband-based Independent Component Analysis scheme and a hybrid Independent Component Analysis/Support Vector Machine scheme, and apply...

  2. Constrained independent component analysis approach to nonobtrusive pulse rate measurements

    Science.gov (United States)

    Tsouri, Gill R.; Kyal, Survi; Dianat, Sohail; Mestha, Lalit K.

    2012-07-01

    Nonobtrusive pulse rate measurement using a webcam is considered. We demonstrate how state-of-the-art algorithms based on independent component analysis suffer from a sorting problem which hinders their performance, and propose a novel algorithm based on constrained independent component analysis to improve performance. We present how the proposed algorithm extracts a photoplethysmography signal and resolves the sorting problem. In addition, we perform a comparative study between the proposed algorithm and state-of-the-art algorithms over 45 video streams using a finger probe oxymeter for reference measurements. The proposed algorithm provides improved accuracy: the root mean square error is decreased from 20.6 and 9.5 beats per minute (bpm) for existing algorithms to 3.5 bpm for the proposed algorithm. An error of 3.5 bpm is within the inaccuracy expected from the reference measurements. This implies that the proposed algorithm provided performance of equal accuracy to the finger probe oximeter.

  3. Bridge Diagnosis by Using Nonlinear Independent Component Analysis and Displacement Analysis

    Science.gov (United States)

    Zheng, Juanqing; Yeh, Yichun; Ogai, Harutoshi

    A daily diagnosis system for bridge monitoring and maintenance is developed based on wireless sensors, signal processing, structure analysis, and displacement analysis. The vibration acceleration data of a bridge are firstly collected through the wireless sensor network by exerting. Nonlinear independent component analysis (ICA) and spectral analysis are used to extract the vibration frequencies of the bridge. After that, through a band pass filter and Simpson's rule the vibration displacement is calculated and the vibration model is obtained to diagnose the bridge. Since linear ICA algorithms work efficiently only in linear mixing environments, a nonlinear ICA model, which is more complicated, is more practical for bridge diagnosis systems. In this paper, we firstly use the post nonlinear method to change the signal data, after that perform linear separation by FastICA, and calculate the vibration displacement of the bridge. The processed data can be used to understand phenomena like corrosion and crack, and evaluate the health condition of the bridge. We apply this system to Nakajima Bridge in Yahata, Kitakyushu, Japan.

  4. Representation for dialect recognition using topographic independent component analysis

    Science.gov (United States)

    Wei, Qu

    2004-10-01

    In dialect speech recognition, the feature of tone in one dialect is subject to changes in pitch frequency as well as the length of tone. It is beneficial for the recognition if a representation can be derived to account for the frequency and length changes of tone in an effective and meaningful way. In this paper, we propose a method for learning such a representation from a set of unlabeled speech sentences containing the features of the dialect changed from various pitch frequencies and time length. Topographic independent component analysis (TICA) is applied for the unsupervised learning to produce an emergent result that is a topographic matrix made up of basis components. The dialect speech is topographic in the following sense: the basis components as the units of the speech are ordered in the feature matrix such that components of one dialect are grouped in one axis and changes in time windows are accounted for in the other axis. This provides a meaningful set of basis vectors that may be used to construct dialect subspaces for dialect speech recognition.

  5. Entropy-based automated classification of independent components separated from fMCG

    International Nuclear Information System (INIS)

    Comani, S; Srinivasan, V; Alleva, G; Romani, G L

    2007-01-01

    Fetal magnetocardiography (fMCG) is a noninvasive technique suitable for the prenatal diagnosis of the fetal heart function. Reliable fetal cardiac signals can be reconstructed from multi-channel fMCG recordings by means of independent component analysis (ICA). However, the identification of the separated components is usually accomplished by visual inspection. This paper discusses a novel automated system based on entropy estimators, namely approximate entropy (ApEn) and sample entropy (SampEn), for the classification of independent components (ICs). The system was validated on 40 fMCG datasets of normal fetuses with the gestational age ranging from 22 to 37 weeks. Both ApEn and SampEn were able to measure the stability and predictability of the physiological signals separated with ICA, and the entropy values of the three categories were significantly different at p <0.01. The system performances were compared with those of a method based on the analysis of the time and frequency content of the components. The outcomes of this study showed a superior performance of the entropy-based system, in particular for early gestation, with an overall ICs detection rate of 98.75% and 97.92% for ApEn and SampEn respectively, as against a value of 94.50% obtained with the time-frequency-based system. (note)

  6. Advances in independent component analysis and learning machines

    CERN Document Server

    Bingham, Ella; Laaksonen, Jorma; Lampinen, Jouko

    2015-01-01

    In honour of Professor Erkki Oja, one of the pioneers of Independent Component Analysis (ICA), this book reviews key advances in the theory and application of ICA, as well as its influence on signal processing, pattern recognition, machine learning, and data mining. Examples of topics which have developed from the advances of ICA, which are covered in the book are: A unifying probabilistic model for PCA and ICA Optimization methods for matrix decompositions Insights into the FastICA algorithmUnsupervised deep learning Machine vision and image retrieval A review of developments in the t

  7. Functional Connectivity Parcellation of the Human Thalamus by Independent Component Analysis.

    Science.gov (United States)

    Zhang, Sheng; Li, Chiang-Shan R

    2017-11-01

    As a key structure to relay and integrate information, the thalamus supports multiple cognitive and affective functions through the connectivity between its subnuclei and cortical and subcortical regions. Although extant studies have largely described thalamic regional functions in anatomical terms, evidence accumulates to suggest a more complex picture of subareal activities and connectivities of the thalamus. In this study, we aimed to parcellate the thalamus and examine whole-brain connectivity of its functional clusters. With resting state functional magnetic resonance imaging data from 96 adults, we used independent component analysis (ICA) to parcellate the thalamus into 10 components. On the basis of the independence assumption, ICA helps to identify how subclusters overlap spatially. Whole brain functional connectivity of each subdivision was computed for independent component's time course (ICtc), which is a unique time series to represent an IC. For comparison, we computed seed-region-based functional connectivity using the averaged time course across all voxels within a thalamic subdivision. The results showed that, at p analysis, ICtc analysis revealed patterns of connectivity that were more distinguished between thalamic clusters. ICtc analysis demonstrated thalamic connectivity to the primary motor cortex, which has eluded the analysis as well as previous studies based on averaged time series, and clarified thalamic connectivity to the hippocampus, caudate nucleus, and precuneus. The new findings elucidate functional organization of the thalamus and suggest that ICA clustering in combination with ICtc rather than seed-region analysis better distinguishes whole-brain connectivities among functional clusters of a brain region.

  8. Dual-energy x-ray image decomposition by independent component analysis

    Science.gov (United States)

    Jiang, Yifeng; Jiang, Dazong; Zhang, Feng; Zhang, Dengfu; Lin, Gang

    2001-09-01

    The spatial distributions of bone and soft tissue in human body are separated by independent component analysis (ICA) of dual-energy x-ray images. It is because of the dual energy imaging modelí-s conformity to the ICA model that we can apply this method: (1) the absorption in body is mainly caused by photoelectric absorption and Compton scattering; (2) they take place simultaneously but are mutually independent; and (3) for monochromatic x-ray sources the total attenuation is achieved by linear combination of these two absorption. Compared with the conventional method, the proposed one needs no priori information about the accurate x-ray energy magnitude for imaging, while the results of the separation agree well with the conventional one.

  9. Applying independent component analysis to clinical fMRI at 7 T

    Directory of Open Access Journals (Sweden)

    Simon Daniel Robinson

    2013-09-01

    Full Text Available Increased BOLD sensitivity at 7 T offers the possibility to increase the reliability of fMRI, but ultra-high field is also associated with an increase in artifacts related to head motion, Nyquist ghosting and parallel imaging reconstruction errors. In this study, the ability of Independent Component Analysis (ICA to separate activation from these artifacts was assessed in a 7 T study of neurological patients performing chin and hand motor tasks. ICA was able to isolate primary motor activation with negligible contamination by motion effects. The results of General Linear Model (GLM analysis of these data were, in contrast, heavily contaminated by motion. Secondary motor areas, basal ganglia and thalamus involvement were apparent in ICA results, but there was low capability to isolate activation in the same brain regions in the GLM analysis, indicating that ICA was more sensitive as well as more specific. A method was developed to simplify the assessment of the large number of independent components. Task-related activation components could be automatically identified via intuitive and effective features. These findings demonstrate that ICA is a practical and sensitive analysis approach in high field fMRI studies, particularly where motion is evoked. Promising applications of ICA in clinical fMRI include presurgical planning and the study of pathologies affecting subcortical brain areas.

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

    Science.gov (United States)

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

    2015-03-01

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

  11. Long-term intensive gymnastic training induced changes in intra- and inter-network functional connectivity: an independent component analysis.

    Science.gov (United States)

    Huang, Huiyuan; Wang, Junjing; Seger, Carol; Lu, Min; Deng, Feng; Wu, Xiaoyan; He, Yuan; Niu, Chen; Wang, Jun; Huang, Ruiwang

    2018-01-01

    Long-term intensive gymnastic training can induce brain structural and functional reorganization. Previous studies have identified structural and functional network differences between world class gymnasts (WCGs) and non-athletes at the whole-brain level. However, it is still unclear how interactions within and between functional networks are affected by long-term intensive gymnastic training. We examined both intra- and inter-network functional connectivity of gymnasts relative to non-athletes using resting-state fMRI (R-fMRI). R-fMRI data were acquired from 13 WCGs and 14 non-athlete controls. Group-independent component analysis (ICA) was adopted to decompose the R-fMRI data into spatial independent components and associated time courses. An automatic component identification method was used to identify components of interest associated with resting-state networks (RSNs). We identified nine RSNs, the basal ganglia network (BG), sensorimotor network (SMN), cerebellum (CB), anterior and posterior default mode networks (aDMN/pDMN), left and right fronto-parietal networks (lFPN/rFPN), primary visual network (PVN), and extrastriate visual network (EVN). Statistical analyses revealed that the intra-network functional connectivity was significantly decreased within the BG, aDMN, lFPN, and rFPN, but increased within the EVN in the WCGs compared to the controls. In addition, the WCGs showed uniformly decreased inter-network functional connectivity between SMN and BG, CB, and PVN, BG and PVN, and pDMN and rFPN compared to the controls. We interpret this generally weaker intra- and inter-network functional connectivity in WCGs during the resting state as a result of greater efficiency in the WCGs' brain associated with long-term motor skill training.

  12. Adaptive tools in virtual environments: Independent component analysis for multimedia

    DEFF Research Database (Denmark)

    Kolenda, Thomas

    2002-01-01

    The thesis investigates the role of independent component analysis in the setting of virtual environments, with the purpose of finding properties that reflect human context. A general framework for performing unsupervised classification with ICA is presented in extension to the latent semantic in...... were compared to investigate computational differences and separation results. The ICA properties were finally implemented in a chat room analysis tool and briefly investigated for visualization of search engines results....

  13. Fast and accurate methods of independent component analysis: A survey

    Czech Academy of Sciences Publication Activity Database

    Tichavský, Petr; Koldovský, Zbyněk

    2011-01-01

    Roč. 47, č. 3 (2011), s. 426-438 ISSN 0023-5954 R&D Projects: GA MŠk 1M0572; GA ČR GA102/09/1278 Institutional research plan: CEZ:AV0Z10750506 Keywords : Blind source separation * artifact removal * electroencephalogram * audio signal processing Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.454, year: 2011 http://library.utia.cas.cz/separaty/2011/SI/tichavsky-fast and accurate methods of independent component analysis a survey.pdf

  14. Systems of independent Markov components and their transient behavior

    International Nuclear Information System (INIS)

    Keilson, J.

    1975-01-01

    The transient behavior of redundant systems of independent, repairable, memoryless (two state) components is studied. Four failure times for such systems are considered, each an exit time from the set of working states for initial system conditions of interest: the failure time from the perfect state, the post-recovery exit time, the ergodic exit time, and the quasi-stationary exit time. The structure of these failure time distributions and their interrelation are discussed and asymptotic estimates and bounds for their expectations are presented. When such systems have high reliability, the failure time distributions are approximately exponential and asymptotically equivalent

  15. Influence of Gasoline Components on Engine Efficiency and Emissions

    Directory of Open Access Journals (Sweden)

    Machado Guilherme B.

    2016-01-01

    Full Text Available For the next few decades, it is expected that fossil fuels and bio-fuels used in internal combustion engines will remain the primary source for vehicular propulsion. This justifies the intense worldwide research and development effort to comply with the challenges of increasing efficiency and reducing internal combustion engine emissions. The modeling of commercial fuels and engine combustion processes presents great challenges. There is also the need to better understand how different fuel components interact and influence engine combustion and performance parameters. In the present work, surrogate fuels were used to implement methodologies to evaluate the influence of fuel components on fuel properties and multiple engine combustion and performance parameters. Special attention is given to engine efficiency and emissions behavior and their correlations to fuel properties and others performance parameters of the engine. The potentials of each component and corresponding chemical group were identified for different engine designs. The results combine information and methodologies that can be used to develop fuels for different applications.

  16. Cognitive Component Analysis

    DEFF Research Database (Denmark)

    Feng, Ling

    2008-01-01

    This dissertation concerns the investigation of the consistency of statistical regularities in a signaling ecology and human cognition, while inferring appropriate actions for a speech-based perceptual task. It is based on unsupervised Independent Component Analysis providing a rich spectrum...... of audio contexts along with pattern recognition methods to map components to known contexts. It also involves looking for the right representations for auditory inputs, i.e. the data analytic processing pipelines invoked by human brains. The main ideas refer to Cognitive Component Analysis, defined...... as the process of unsupervised grouping of generic data such that the ensuing group structure is well-aligned with that resulting from human cognitive activity. Its hypothesis runs ecologically: features which are essentially independent in a context defined ensemble, can be efficiently coded as sparse...

  17. A Novel Algorithm for Efficient Downlink Packet Scheduling for Multiple-Component-Carrier Cellular Systems

    Directory of Open Access Journals (Sweden)

    Yao-Liang Chung

    2016-11-01

    Full Text Available The simultaneous aggregation of multiple component carriers (CCs for use by a base station constitutes one of the more promising strategies for providing substantially enhanced bandwidths for packet transmissions in 4th and 5th generation cellular systems. To the best of our knowledge, however, few previous studies have undertaken a thorough investigation of various performance aspects of the use of a simple yet effective packet scheduling algorithm in which multiple CCs are aggregated for transmission in such systems. Consequently, the present study presents an efficient packet scheduling algorithm designed on the basis of the proportional fair criterion for use in multiple-CC systems for downlink transmission. The proposed algorithm includes a focus on providing simultaneous transmission support for both real-time (RT and non-RT traffic. This algorithm can, when applied with sufficiently efficient designs, provide adequate utilization of spectrum resources for the purposes of transmissions, while also improving energy efficiency to some extent. According to simulation results, the performance of the proposed algorithm in terms of system throughput, mean delay, and fairness constitute substantial improvements over those of an algorithm in which the CCs are used independently instead of being aggregated.

  18. Application of independent component analysis to H-1 MR spectroscopic imaging exams of brain tumours

    NARCIS (Netherlands)

    Szabo de Edelenyi, F.; Simonetti, A.W.; Postma, G.; Huo, R.; Buydens, L.M.C.

    2005-01-01

    The low spatial resolution of clinical H-1 MRSI leads to partial volume effects. To overcome this problem, we applied independent component analysis (ICA) on a set of H-1 MRSI exams of brain turnours. With this method, tissue types that yield statistically independent spectra can be separated. Up to

  19. A novel approach to analyzing fMRI and SNP data via parallel independent component analysis

    Science.gov (United States)

    Liu, Jingyu; Pearlson, Godfrey; Calhoun, Vince; Windemuth, Andreas

    2007-03-01

    There is current interest in understanding genetic influences on brain function in both the healthy and the disordered brain. Parallel independent component analysis, a new method for analyzing multimodal data, is proposed in this paper and applied to functional magnetic resonance imaging (fMRI) and a single nucleotide polymorphism (SNP) array. The method aims to identify the independent components of each modality and the relationship between the two modalities. We analyzed 92 participants, including 29 schizophrenia (SZ) patients, 13 unaffected SZ relatives, and 50 healthy controls. We found a correlation of 0.79 between one fMRI component and one SNP component. The fMRI component consists of activations in cingulate gyrus, multiple frontal gyri, and superior temporal gyrus. The related SNP component is contributed to significantly by 9 SNPs located in sets of genes, including those coding for apolipoprotein A-I, and C-III, malate dehydrogenase 1 and the gamma-aminobutyric acid alpha-2 receptor. A significant difference in the presences of this SNP component is found between the SZ group (SZ patients and their relatives) and the control group. In summary, we constructed a framework to identify the interactions between brain functional and genetic information; our findings provide new insight into understanding genetic influences on brain function in a common mental disorder.

  20. Equivalent water height extracted from GRACE gravity field model with robust independent component analysis

    Science.gov (United States)

    Guo, Jinyun; Mu, Dapeng; Liu, Xin; Yan, Haoming; Dai, Honglei

    2014-08-01

    The Level-2 monthly GRACE gravity field models issued by Center for Space Research (CSR), GeoForschungs Zentrum (GFZ), and Jet Propulsion Laboratory (JPL) are treated as observations used to extract the equivalent water height (EWH) with the robust independent component analysis (RICA). The smoothing radii of 300, 400, and 500 km are tested, respectively, in the Gaussian smoothing kernel function to reduce the observation Gaussianity. Three independent components are obtained by RICA in the spatial domain; the first component matches the geophysical signal, and the other two match the north-south strip and the other noises. The first mode is used to estimate EWHs of CSR, JPL, and GFZ, and compared with the classical empirical decorrelation method (EDM). The EWH STDs for 12 months in 2010 extracted by RICA and EDM show the obvious fluctuation. The results indicate that the sharp EWH changes in some areas have an important global effect, like in Amazon, Mekong, and Zambezi basins.

  1. Efficient transfer of sensitivity information in multi-component models

    International Nuclear Information System (INIS)

    Abdel-Khalik, Hany S.; Rabiti, Cristian

    2011-01-01

    In support of adjoint-based sensitivity analysis, this manuscript presents a new method to efficiently transfer adjoint information between components in a multi-component model, whereas the output of one component is passed as input to the next component. Often, one is interested in evaluating the sensitivities of the responses calculated by the last component to the inputs of the first component in the overall model. The presented method has two advantages over existing methods which may be classified into two broad categories: brute force-type methods and amalgamated-type methods. First, the presented method determines the minimum number of adjoint evaluations for each component as opposed to the brute force-type methods which require full evaluation of all sensitivities for all responses calculated by each component in the overall model, which proves computationally prohibitive for realistic problems. Second, the new method treats each component as a black-box as opposed to amalgamated-type methods which requires explicit knowledge of the system of equations associated with each component in order to reach the minimum number of adjoint evaluations. (author)

  2. Analysis of independent components of cognitive event related potentials in a group of ADHD adults.

    Science.gov (United States)

    Markovska-Simoska, Silvana; Pop-Jordanova, Nada; Pop-Jordanov, Jordan

    In the last decade, many studies have tried to define the neural correlates of attention deficit hyperactivity disorder (ADHD). The main aim of this study is the comparison of the ERPs independent components in the four QEEG subtypes in a group of ADHD adults as a basis for defining the corresponding endophenotypes among ADHD population. Sixty-seven adults diagnosed as ADHD according to the DSM-IV criteria and 50 age-matched control subjects participated in the study. The brain activity of the subjects was recorded by 19 channel quantitative electroencephalography (QEEG) system in two neuropsychological tasks (visual and emotional continuous performance tests). The ICA method was applied for separation of the independent ERPs components. The components were associated with distinct psychological operations, such as engagement operations (P3bP component), comparison (vcomTL and vcom TR), motor inhibition (P3supF) and monitoring (P4monCC) operations. The ERPs results point out that there is disturbance in executive functioning in investigated ADHD group obtained by the significantly lower amplitude and longer latency for the engagement (P3bP), motor inhibition (P3supF) and monitoring (P4monCC) components. Particularly, the QEEG subtype IV was with the most significant ERPs differences comparing to the other subtypes. In particular, the most prominent difference in the ERPs independent components for the QEEG subtype IV in comparison to other three subtypes, rise many questions and becomes the subject for future research. This study aims to advance and facilitate the use of neurophysiological procedures (QEEG and ERPs) in clinical practice as objective measures of ADHD for better assessment, subtyping and treatment of ADHD.

  3. Crude oil price analysis and forecasting based on variational mode decomposition and independent component analysis

    Science.gov (United States)

    E, Jianwei; Bao, Yanling; Ye, Jimin

    2017-10-01

    As one of the most vital energy resources in the world, crude oil plays a significant role in international economic market. The fluctuation of crude oil price has attracted academic and commercial attention. There exist many methods in forecasting the trend of crude oil price. However, traditional models failed in predicting accurately. Based on this, a hybrid method will be proposed in this paper, which combines variational mode decomposition (VMD), independent component analysis (ICA) and autoregressive integrated moving average (ARIMA), called VMD-ICA-ARIMA. The purpose of this study is to analyze the influence factors of crude oil price and predict the future crude oil price. Major steps can be concluded as follows: Firstly, applying the VMD model on the original signal (crude oil price), the modes function can be decomposed adaptively. Secondly, independent components are separated by the ICA, and how the independent components affect the crude oil price is analyzed. Finally, forecasting the price of crude oil price by the ARIMA model, the forecasting trend demonstrates that crude oil price declines periodically. Comparing with benchmark ARIMA and EEMD-ICA-ARIMA, VMD-ICA-ARIMA can forecast the crude oil price more accurately.

  4. COMPARING INDEPENDENT COMPONENT ANALYSIS WITH PRINCIPLE COMPONENT ANALYSIS IN DETECTING ALTERATIONS OF PORPHYRY COPPER DEPOSIT (CASE STUDY: ARDESTAN AREA, CENTRAL IRAN

    Directory of Open Access Journals (Sweden)

    S. Mahmoudishadi

    2017-09-01

    Full Text Available The image processing techniques in transform domain are employed as analysis tools for enhancing the detection of mineral deposits. The process of decomposing the image into important components increases the probability of mineral extraction. In this study, the performance of Principal Component Analysis (PCA and Independent Component Analysis (ICA has been evaluated for the visible and near-infrared (VNIR and Shortwave infrared (SWIR subsystems of ASTER data. Ardestan is located in part of Central Iranian Volcanic Belt that hosts many well-known porphyry copper deposits. This research investigated the propylitic and argillic alteration zones and outer mineralogy zone in part of Ardestan region. The two mentioned approaches were applied to discriminate alteration zones from igneous bedrock using the major absorption of indicator minerals from alteration and mineralogy zones in spectral rang of ASTER bands. Specialized PC components (PC2, PC3 and PC6 were used to identify pyrite and argillic and propylitic zones that distinguish from igneous bedrock in RGB color composite image. Due to the eigenvalues, the components 2, 3 and 6 account for 4.26% ,0.9% and 0.09% of the total variance of the data for Ardestan scene, respectively. For the purpose of discriminating the alteration and mineralogy zones of porphyry copper deposit from bedrocks, those mentioned percentages of data in ICA independent components of IC2, IC3 and IC6 are more accurately separated than noisy bands of PCA. The results of ICA method conform to location of lithological units of Ardestan region, as well.

  5. Comparing Independent Component Analysis with Principle Component Analysis in Detecting Alterations of Porphyry Copper Deposit (case Study: Ardestan Area, Central Iran)

    Science.gov (United States)

    Mahmoudishadi, S.; Malian, A.; Hosseinali, F.

    2017-09-01

    The image processing techniques in transform domain are employed as analysis tools for enhancing the detection of mineral deposits. The process of decomposing the image into important components increases the probability of mineral extraction. In this study, the performance of Principal Component Analysis (PCA) and Independent Component Analysis (ICA) has been evaluated for the visible and near-infrared (VNIR) and Shortwave infrared (SWIR) subsystems of ASTER data. Ardestan is located in part of Central Iranian Volcanic Belt that hosts many well-known porphyry copper deposits. This research investigated the propylitic and argillic alteration zones and outer mineralogy zone in part of Ardestan region. The two mentioned approaches were applied to discriminate alteration zones from igneous bedrock using the major absorption of indicator minerals from alteration and mineralogy zones in spectral rang of ASTER bands. Specialized PC components (PC2, PC3 and PC6) were used to identify pyrite and argillic and propylitic zones that distinguish from igneous bedrock in RGB color composite image. Due to the eigenvalues, the components 2, 3 and 6 account for 4.26% ,0.9% and 0.09% of the total variance of the data for Ardestan scene, respectively. For the purpose of discriminating the alteration and mineralogy zones of porphyry copper deposit from bedrocks, those mentioned percentages of data in ICA independent components of IC2, IC3 and IC6 are more accurately separated than noisy bands of PCA. The results of ICA method conform to location of lithological units of Ardestan region, as well.

  6. Two efficient label-equivalence-based connected-component labeling algorithms for 3-D binary images.

    Science.gov (United States)

    He, Lifeng; Chao, Yuyan; Suzuki, Kenji

    2011-08-01

    Whenever one wants to distinguish, recognize, and/or measure objects (connected components) in binary images, labeling is required. This paper presents two efficient label-equivalence-based connected-component labeling algorithms for 3-D binary images. One is voxel based and the other is run based. For the voxel-based one, we present an efficient method of deciding the order for checking voxels in the mask. For the run-based one, instead of assigning each foreground voxel, we assign each run a provisional label. Moreover, we use run data to label foreground voxels without scanning any background voxel in the second scan. Experimental results have demonstrated that our voxel-based algorithm is efficient for 3-D binary images with complicated connected components, that our run-based one is efficient for those with simple connected components, and that both are much more efficient than conventional 3-D labeling algorithms.

  7. Applying independent component analysis to clinical fMRI at 7 T

    OpenAIRE

    Simon Daniel Robinson; Veronika eSchöpf; Pedro eCardoso; Alexander eGeissler; Alexander eGeissler; Florian Ph.S Fischmeister; Florian Ph.S Fischmeister; Moritz eWurnig; Moritz eWurnig; Siegfried eTrattnig; Roland eBeisteiner; Roland eBeisteiner

    2013-01-01

    Increased BOLD sensitivity at 7 T offers the possibility to increase the reliability of fMRI, but ultra-high field is also associated with an increase in artifacts related to head motion, Nyquist ghosting and parallel imaging reconstruction errors. In this study, the ability of Independent Component Analysis (ICA) to separate activation from these artifacts was assessed in a 7 T study of neurological patients performing chin and hand motor tasks. ICA was able to isolate primary motor activati...

  8. Diagnosis of Connective Tissue Disorders based on Independent Component Analysis of Aortic Shape and Motion from 4D MR Images

    DEFF Research Database (Denmark)

    Hansen, Michael Sass; Zhao, Fei; Zhang, Honghai

    2006-01-01

    Independent component analysis (ICA) is employed for com\\$\\backslash\\$-puter-aided diagnosis (CAD) allowing objective identification of subjects with connective tissue disorder from 4D aortic MR images. Stationary independent components assist in the disease detection, which is the first...

  9. Fetal ECG extraction using independent component analysis by Jade approach

    Science.gov (United States)

    Giraldo-Guzmán, Jader; Contreras-Ortiz, Sonia H.; Lasprilla, Gloria Isabel Bautista; Kotas, Marian

    2017-11-01

    Fetal ECG monitoring is a useful method to assess the fetus health and detect abnormal conditions. In this paper we propose an approach to extract fetal ECG from abdomen and chest signals using independent component analysis based on the joint approximate diagonalization of eigenmatrices approach. The JADE approach avoids redundancy, what reduces matrix dimension and computational costs. Signals were filtered with a high pass filter to eliminate low frequency noise. Several levels of decomposition were tested until the fetal ECG was recognized in one of the separated sources output. The proposed method shows fast and good performance.

  10. Applying independent component analysis to clinical FMRI at 7 t

    OpenAIRE

    Robinson, Simon Daniel; Schöpf, Veronika; Cardoso, Pedro; Geissler, Alexander; Fischmeister, Florian P S; Wurnig, Moritz; Trattnig, Siegfried; Beisteiner, Roland

    2013-01-01

    Increased BOLD sensitivity at 7 T offers the possibility to increase the reliability of fMRI, but ultra-high field is also associated with an increase in artifacts related to head motion, Nyquist ghosting, and parallel imaging reconstruction errors. In this study, the ability of independent component analysis (ICA) to separate activation from these artifacts was assessed in a 7 T study of neurological patients performing chin and hand motor tasks. ICA was able to isolate primary motor activat...

  11. Characterizing functional connectivity during rest in multiple sclerosis patients versus healthy volunteers using independent component analysis

    Energy Technology Data Exchange (ETDEWEB)

    Palacio Garcia, L.; Andrzejak, R.; Prchkovska, V.; Rodrigues, P.

    2016-07-01

    It is commonly thought that our brain is not active when it does not receive any external input. However, during rest, there are still certain distant regions of the brain that are functionally correlated between them: the so-called resting-state networks. This functional connectivity of the brain is disrupted in many neurological diseases. In particular, it has been shown that one of the most studied resting-state networks (the default-mode network) is affected in multiple sclerosis, which is the most common disabling neurological condition affecting the central nervous system of young adults. In this work, I focus on the study of the differences in the resting-state networks between multiple sclerosis patients and healthy volunteers. In order to study the effects of multiple sclerosis on the functional connectivity of the brain, a numerical method known as independent component analysis (ICA) is applied. This technique divides the resting-state fMRI data into independent components. Nonetheless, noise, which could be due to head motion or physiological artifacts, may corrupt the data by indicating a false activation. Therefore, I create a web user interface that allows the user to manually classify all the independent components for a given subject. Eventually, the components classified as noise should be removed from the functional data in order to prevent them from taking part in any further analysis. (Author)

  12. Independent component analysis using prior information for signal detection in a functional imaging system of the retina

    NARCIS (Netherlands)

    Barriga, E. Simon; Pattichis, Marios; Ts’o, Dan; Abramoff, Michael; Kardon, Randy; Kwon, Young; Soliz, Peter

    2011-01-01

    Independent component analysis (ICA) is a statistical technique that estimates a set of sources mixed by an unknown mixing matrix using only a set of observations. For this purpose, the only assumption is that the sources are statistically independent. In many applications, some information about

  13. Independent component analysis-based artefact reduction: application to the electrocardiogram for improved magnetic resonance imaging triggering

    International Nuclear Information System (INIS)

    Oster, Julien; Pietquin, Olivier; Felblinger, Jacques; Abächerli, Roger; Kraemer, Michel

    2009-01-01

    Electrocardiogram (ECG) is required during magnetic resonance (MR) examination for monitoring patients under anaesthesia or with heart diseases and for synchronizing image acquisition with heart activity (triggering). Accurate and fast QRS detection is therefore desirable, but this task is complicated by artefacts related to the complex MR environment (high magnetic field, radio-frequency pulses and fast switching magnetic gradients). Specific signal processing has been proposed, whether using specific MR QRS detectors or ECG denoising methods. Most state-of-the-art techniques use a connection to the MR system for achieving their task, which is a major drawback since access to the MR system is often restricted. This paper introduces a new method for on-line ECG signal enhancement, called ICARE, which takes advantage of using multi-lead ECG and does not require any connection to the MR system. It is based on independent component analysis (ICA) and applied in real time. This algorithm yields accurate QRS detection for efficient triggering

  14. Gas Bubbles Investigation in Contaminated Water Using Optical Tomography Based on Independent Component Analysis Method

    Directory of Open Access Journals (Sweden)

    Mohd Taufiq Mohd Khairi

    2016-01-01

    Full Text Available This paper presents the results of concentration profiles for gas bubble flow in a vertical pipeline containing contaminated water using an optical tomography system. The concentration profiles for the bubble flow quantities are investigated under five different flows conditions, a single bubble, double bubbles, 25% of air opening, 50% of air opening, and 100% of air opening flow rates where a valve is used to control the gas flow in the vertical pipeline. The system is aided by the independent component analysis (ICA algorithm to reconstruct the concentration profiles of the liquid-gas flow. The behaviour of the gas bubbles was investigated in contaminated water in which the water sample was prepared by adding 25 mL of colour ingredients to 3 liters of pure water. The result shows that the application of ICA has enabled the system to detect the presence of gas bubbles in contaminated water. This information provides vital information on the flow inside the pipe and hence could be very significant in increasing the efficiency of the process industries.

  15. A coenzyme-independent decarboxylase/oxygenase cascade for the efficient synthesis of vanillin.

    Science.gov (United States)

    Furuya, Toshiki; Miura, Misa; Kino, Kuniki

    2014-10-13

    Vanillin is one of the most widely used flavor compounds in the world as well as a promising versatile building block. The biotechnological production of vanillin from plant-derived ferulic acid has attracted much attention as a new alternative to chemical synthesis. One limitation of the known metabolic pathway to vanillin is its requirement for expensive coenzymes. Here, we developed a novel route to vanillin from ferulic acid that does not require any coenzymes. This artificial pathway consists of a coenzyme-independent decarboxylase and a coenzyme-independent oxygenase. When Escherichia coli cells harboring the decarboxylase/oxygenase cascade were incubated with ferulic acid, the cells efficiently synthesized vanillin (8.0 mM, 1.2 g L(-1) ) via 4-vinylguaiacol in one pot, without the generation of any detectable aromatic by-products. The efficient method described here might be applicable to the synthesis of other high-value chemicals from plant-derived aromatics. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  16. Developing a complex independent component analysis technique to extract non-stationary patterns from geophysical time-series

    Science.gov (United States)

    Forootan, Ehsan; Kusche, Jürgen

    2016-04-01

    Geodetic/geophysical observations, such as the time series of global terrestrial water storage change or sea level and temperature change, represent samples of physical processes and therefore contain information about complex physical interactionswith many inherent time scales. Extracting relevant information from these samples, for example quantifying the seasonality of a physical process or its variability due to large-scale ocean-atmosphere interactions, is not possible by rendering simple time series approaches. In the last decades, decomposition techniques have found increasing interest for extracting patterns from geophysical observations. Traditionally, principal component analysis (PCA) and more recently independent component analysis (ICA) are common techniques to extract statistical orthogonal (uncorrelated) and independent modes that represent the maximum variance of observations, respectively. PCA and ICA can be classified as stationary signal decomposition techniques since they are based on decomposing the auto-covariance matrix or diagonalizing higher (than two)-order statistical tensors from centered time series. However, the stationary assumption is obviously not justifiable for many geophysical and climate variables even after removing cyclic components e.g., the seasonal cycles. In this paper, we present a new decomposition method, the complex independent component analysis (CICA, Forootan, PhD-2014), which can be applied to extract to non-stationary (changing in space and time) patterns from geophysical time series. Here, CICA is derived as an extension of real-valued ICA (Forootan and Kusche, JoG-2012), where we (i) define a new complex data set using a Hilbert transformation. The complex time series contain the observed values in their real part, and the temporal rate of variability in their imaginary part. (ii) An ICA algorithm based on diagonalization of fourth-order cumulants is then applied to decompose the new complex data set in (i

  17. Improved application of independent component analysis to functional magnetic resonance imaging study via linear projection techniques.

    Science.gov (United States)

    Long, Zhiying; Chen, Kewei; Wu, Xia; Reiman, Eric; Peng, Danling; Yao, Li

    2009-02-01

    Spatial Independent component analysis (sICA) has been widely used to analyze functional magnetic resonance imaging (fMRI) data. The well accepted implicit assumption is the spatially statistical independency of intrinsic sources identified by sICA, making the sICA applications difficult for data in which there exist interdependent sources and confounding factors. This interdependency can arise, for instance, from fMRI studies investigating two tasks in a single session. In this study, we introduced a linear projection approach and considered its utilization as a tool to separate task-related components from two-task fMRI data. The robustness and feasibility of the method are substantiated through simulation on computer data and fMRI real rest data. Both simulated and real two-task fMRI experiments demonstrated that sICA in combination with the projection method succeeded in separating spatially dependent components and had better detection power than pure model-based method when estimating activation induced by each task as well as both tasks.

  18. Efficient implementation of one- and two-component analytical energy gradients in exact two-component theory

    Science.gov (United States)

    Franzke, Yannick J.; Middendorf, Nils; Weigend, Florian

    2018-03-01

    We present an efficient algorithm for one- and two-component analytical energy gradients with respect to nuclear displacements in the exact two-component decoupling approach to the one-electron Dirac equation (X2C). Our approach is a generalization of the spin-free ansatz by Cheng and Gauss [J. Chem. Phys. 135, 084114 (2011)], where the perturbed one-electron Hamiltonian is calculated by solving a first-order response equation. Computational costs are drastically reduced by applying the diagonal local approximation to the unitary decoupling transformation (DLU) [D. Peng and M. Reiher, J. Chem. Phys. 136, 244108 (2012)] to the X2C Hamiltonian. The introduced error is found to be almost negligible as the mean absolute error of the optimized structures amounts to only 0.01 pm. Our implementation in TURBOMOLE is also available within the finite nucleus model based on a Gaussian charge distribution. For a X2C/DLU gradient calculation, computational effort scales cubically with the molecular size, while storage increases quadratically. The efficiency is demonstrated in calculations of large silver clusters and organometallic iridium complexes.

  19. Is Cognitive Activity of Speech Based On Statistical Independence?

    DEFF Research Database (Denmark)

    Feng, Ling; Hansen, Lars Kai

    2008-01-01

    This paper explores the generality of COgnitive Component Analysis (COCA), which is defined as the process of unsupervised grouping of data such that the ensuing group structure is well-aligned with that resulting from human cognitive activity. The hypothesis of {COCA} is ecological......: the essentially independent features in a context defined ensemble can be efficiently coded using a sparse independent component representation. Our devised protocol aims at comparing the performance of supervised learning (invoking cognitive activity) and unsupervised learning (statistical regularities) based...... on similar representations, and the only difference lies in the human inferred labels. Inspired by the previous research on COCA, we introduce a new pair of models, which directly employ the independent hypothesis. Statistical regularities are revealed at multiple time scales on phoneme, gender, age...

  20. Quantifying identifiability in independent component analysis

    DEFF Research Database (Denmark)

    Sokol, Alexander; Maathuis, Marloes H.; Falkeborg, Benjamin

    2014-01-01

    We are interested in consistent estimation of the mixing matrix in the ICA model, when the error distribution is close to (but different from) Gaussian. In particular, we consider $n$ independent samples from the ICA model $X = A\\epsilon$, where we assume that the coordinates of $\\epsilon......$ are independent and identically distributed according to a contaminated Gaussian distribution, and the amount of contamination is allowed to depend on $n$. We then investigate how the ability to consistently estimate the mixing matrix depends on the amount of contamination. Our results suggest...

  1. Progressive Disintegration of Brain Networking from Normal Aging to Alzheimer Disease: Analysis of Independent Components of 18F-FDG PET Data.

    Science.gov (United States)

    Pagani, Marco; Giuliani, Alessandro; Öberg, Johanna; De Carli, Fabrizio; Morbelli, Silvia; Girtler, Nicola; Arnaldi, Dario; Accardo, Jennifer; Bauckneht, Matteo; Bongioanni, Francesca; Chincarini, Andrea; Sambuceti, Gianmario; Jonsson, Cathrine; Nobili, Flavio

    2017-07-01

    Brain connectivity has been assessed in several neurodegenerative disorders investigating the mutual correlations between predetermined regions or nodes. Selective breakdown of brain networks during progression from normal aging to Alzheimer disease dementia (AD) has also been observed. Methods: We implemented independent-component analysis of 18 F-FDG PET data in 5 groups of subjects with cognitive states ranging from normal aging to AD-including mild cognitive impairment (MCI) not converting or converting to AD-to disclose the spatial distribution of the independent components in each cognitive state and their accuracy in discriminating the groups. Results: We could identify spatially distinct independent components in each group, with generation of local circuits increasing proportionally to the severity of the disease. AD-specific independent components first appeared in the late-MCI stage and could discriminate converting MCI and AD from nonconverting MCI with an accuracy of 83.5%. Progressive disintegration of the intrinsic networks from normal aging to MCI to AD was inversely proportional to the conversion time. Conclusion: Independent-component analysis of 18 F-FDG PET data showed a gradual disruption of functional brain connectivity with progression of cognitive decline in AD. This information might be useful as a prognostic aid for individual patients and as a surrogate biomarker in intervention trials. © 2017 by the Society of Nuclear Medicine and Molecular Imaging.

  2. Denoising of chaotic signal using independent component analysis and empirical mode decomposition with circulate translating

    International Nuclear Information System (INIS)

    Wang Wen-Bo; Zhang Xiao-Dong; Chang Yuchan; Wang Xiang-Li; Wang Zhao; Chen Xi; Zheng Lei

    2016-01-01

    In this paper, a new method to reduce noises within chaotic signals based on ICA (independent component analysis) and EMD (empirical mode decomposition) is proposed. The basic idea is decomposing chaotic signals and constructing multidimensional input vectors, firstly, on the base of EMD and its translation invariance. Secondly, it makes the independent component analysis on the input vectors, which means that a self adapting denoising is carried out for the intrinsic mode functions (IMFs) of chaotic signals. Finally, all IMFs compose the new denoised chaotic signal. Experiments on the Lorenz chaotic signal composed of different Gaussian noises and the monthly observed chaotic sequence on sunspots were put into practice. The results proved that the method proposed in this paper is effective in denoising of chaotic signals. Moreover, it can correct the center point in the phase space effectively, which makes it approach the real track of the chaotic attractor. (paper)

  3. Extraction of a Weak Co-Channel Interfering Communication Signal Using Complex Independent Component Analysis

    Science.gov (United States)

    2013-06-01

    zarzoso/ biblio /tnn10.pdf"> % "Robust independent component analysis by iterative maximization</a> % <a href = "http://www.i3s.unice.fr/~zarzoso... biblio /tnn10.pdf"> % of the kurtosis contrast with algebraic optimal step size"</a>, % IEEE Transactions on Neural Networks, vol. 21, no. 2, % pp

  4. Research on CO2 ejector component efficiencies by experiment measurement and distributed-parameter modeling

    International Nuclear Information System (INIS)

    Zheng, Lixing; Deng, Jianqiang

    2017-01-01

    Highlights: • The ejector distributed-parameter model is developed to study ejector efficiencies. • Feasible component and total efficiency correlations of ejector are established. • New efficiency correlations are applied to obtain dynamic characteristics of EERC. • More suitable fixed efficiency value can be determined by the proposed correlations. - Abstract: In this study we combine the experimental measurement data and the theoretical model of ejector to determine CO 2 ejector component efficiencies including the motive nozzle, suction chamber, mixing section, diffuser as well as the total ejector efficiency. The ejector is modeled utilizing the distributed-parameter method, and the flow passage is divided into a number of elements and the governing equations are formulated based on the differential equation of mass, momentum and energy conservation. The efficiencies of ejector are investigated under different ejector geometric parameters and operational conditions, and the corresponding empirical correlations are established. Moreover, the correlations are incorporated into a transient model of transcritical CO 2 ejector expansion refrigeration cycle (EERC) and the dynamic simulations is performed based on variable component efficiencies and fixed values. The motive nozzle, suction chamber, mixing section and diffuser efficiencies vary from 0.74 to 0.89, 0.86 to 0.96, 0.73 to 0.9 and 0.75 to 0.95 under the studied conditions, respectively. The response diversities of suction flow pressure and discharge pressure are obvious between the variable efficiencies and fixed efficiencies referring to the previous studies, while when the fixed value is determined by the presented correlations, their response differences are basically the same.

  5. Independent component analysis based digital signal processing in coherent optical fiber communication systems

    Science.gov (United States)

    Li, Xiang; Luo, Ming; Qiu, Ying; Alphones, Arokiaswami; Zhong, Wen-De; Yu, Changyuan; Yang, Qi

    2018-02-01

    In this paper, channel equalization techniques for coherent optical fiber transmission systems based on independent component analysis (ICA) are reviewed. The principle of ICA for blind source separation is introduced. The ICA based channel equalization after both single-mode fiber and few-mode fiber transmission for single-carrier and orthogonal frequency division multiplexing (OFDM) modulation formats are investigated, respectively. The performance comparisons with conventional channel equalization techniques are discussed.

  6. A hybrid sales forecasting scheme by combining independent component analysis with K-means clustering and support vector regression.

    Science.gov (United States)

    Lu, Chi-Jie; Chang, Chi-Chang

    2014-01-01

    Sales forecasting plays an important role in operating a business since it can be used to determine the required inventory level to meet consumer demand and avoid the problem of under/overstocking. Improving the accuracy of sales forecasting has become an important issue of operating a business. This study proposes a hybrid sales forecasting scheme by combining independent component analysis (ICA) with K-means clustering and support vector regression (SVR). The proposed scheme first uses the ICA to extract hidden information from the observed sales data. The extracted features are then applied to K-means algorithm for clustering the sales data into several disjoined clusters. Finally, the SVR forecasting models are applied to each group to generate final forecasting results. Experimental results from information technology (IT) product agent sales data reveal that the proposed sales forecasting scheme outperforms the three comparison models and hence provides an efficient alternative for sales forecasting.

  7. Time-independent and time-dependent contributions to the unavailability of standby safety system components

    International Nuclear Information System (INIS)

    Lofgren, E.V.; Uryasev, S.; Samanta, P.

    1997-01-01

    The unavailability of standby safety system components due to failures in nuclear power plants is considered to involve a time-independent and a time-dependent part. The former relates to the component's unavailability from demand stresses due to usage, and the latter represents the component's unavailability due to standby-time stresses related to the environment. In this paper, data from the nuclear plant reliability data system (NPRDS) were used to partition the component's unavailability into the contributions from standby-time stress (i.e., due to environmental factors) and demand stress (i.e., due to usage). Analyses are presented of motor-operated valves (MOVs), motor-driven pumps (MDPs), and turbine-driven pumps (TDPs). MOVs fail predominantly (approx. 78 %) from environmental factors (standby-time stress failures). MDPs fail slightly more frequently from demand stresses (approx. 63 %) than standby-time stresses, while TDPs fail predominantly from standby-time stresses (approx. 78 %). Such partitions of component unavailability have many uses in risk-informed and performance-based regulation relating to modifications to Technical Specification, in-service testing, precise determination of dominant accident sequences, and implementation of maintenance rules

  8. Ownership balance, supervisory efficiency of independent directors and the quality of management earnings forecasts

    Directory of Open Access Journals (Sweden)

    Yunling Song

    2013-06-01

    Full Text Available In the Chinese securities market, with its characteristics of influence through personal relationships (Guanxi and underdeveloped standards of law and enforcement, can independent directors play the supervisory role expected by securities regulators? In this study we use the degree of precision and accuracy in corporate earnings forecasts as proxies for the quality of information disclosure by listed companies and examine the supervisory efficiency of independent directors with respect to information disclosure. Using data from 2007 to 2009, we find that in the absence of ownership balance, independent directors have a significant positive effect on the accuracy of management forecasts. In addition, the personal backgrounds of independent directors have specific effects on management earnings forecasts. Directors with certified public accountant (CPA expertise significantly improve the precision of management forecasts. However, directors with industrial expertise significantly reduce the precision of management forecasts. In other words, having directors with CPA expertise improves the independence of boards, but having independent directors with industrial expertise has the opposite effect.

  9. Classification of fMRI independent components using IC-fingerprints and support vector machine classifiers.

    Science.gov (United States)

    De Martino, Federico; Gentile, Francesco; Esposito, Fabrizio; Balsi, Marco; Di Salle, Francesco; Goebel, Rainer; Formisano, Elia

    2007-01-01

    We present a general method for the classification of independent components (ICs) extracted from functional MRI (fMRI) data sets. The method consists of two steps. In the first step, each fMRI-IC is associated with an IC-fingerprint, i.e., a representation of the component in a multidimensional space of parameters. These parameters are post hoc estimates of global properties of the ICs and are largely independent of a specific experimental design and stimulus timing. In the second step a machine learning algorithm automatically separates the IC-fingerprints into six general classes after preliminary training performed on a small subset of expert-labeled components. We illustrate this approach in a multisubject fMRI study employing visual structure-from-motion stimuli encoding faces and control random shapes. We show that: (1) IC-fingerprints are a valuable tool for the inspection, characterization and selection of fMRI-ICs and (2) automatic classifications of fMRI-ICs in new subjects present a high correspondence with those obtained by expert visual inspection of the components. Importantly, our classification procedure highlights several neurophysiologically interesting processes. The most intriguing of which is reflected, with high intra- and inter-subject reproducibility, in one IC exhibiting a transiently task-related activation in the 'face' region of the primary sensorimotor cortex. This suggests that in addition to or as part of the mirror system, somatotopic regions of the sensorimotor cortex are involved in disambiguating the perception of a moving body part. Finally, we show that the same classification algorithm can be successfully applied, without re-training, to fMRI collected using acquisition parameters, stimulation modality and timing considerably different from those used for training.

  10. The SPAtial EFficiency metric (SPAEF): multiple-component evaluation of spatial patterns for optimization of hydrological models

    Science.gov (United States)

    Koch, Julian; Cüneyd Demirel, Mehmet; Stisen, Simon

    2018-05-01

    The process of model evaluation is not only an integral part of model development and calibration but also of paramount importance when communicating modelling results to the scientific community and stakeholders. The modelling community has a large and well-tested toolbox of metrics to evaluate temporal model performance. In contrast, spatial performance evaluation does not correspond to the grand availability of spatial observations readily available and to the sophisticate model codes simulating the spatial variability of complex hydrological processes. This study makes a contribution towards advancing spatial-pattern-oriented model calibration by rigorously testing a multiple-component performance metric. The promoted SPAtial EFficiency (SPAEF) metric reflects three equally weighted components: correlation, coefficient of variation and histogram overlap. This multiple-component approach is found to be advantageous in order to achieve the complex task of comparing spatial patterns. SPAEF, its three components individually and two alternative spatial performance metrics, i.e. connectivity analysis and fractions skill score, are applied in a spatial-pattern-oriented model calibration of a catchment model in Denmark. Results suggest the importance of multiple-component metrics because stand-alone metrics tend to fail to provide holistic pattern information. The three SPAEF components are found to be independent, which allows them to complement each other in a meaningful way. In order to optimally exploit spatial observations made available by remote sensing platforms, this study suggests applying bias insensitive metrics which further allow for a comparison of variables which are related but may differ in unit. This study applies SPAEF in the hydrological context using the mesoscale Hydrologic Model (mHM; version 5.8), but we see great potential across disciplines related to spatially distributed earth system modelling.

  11. The Removal of EOG Artifacts From EEG Signals Using Independent Component Analysis and Multivariate Empirical Mode Decomposition.

    Science.gov (United States)

    Wang, Gang; Teng, Chaolin; Li, Kuo; Zhang, Zhonglin; Yan, Xiangguo

    2016-09-01

    The recorded electroencephalography (EEG) signals are usually contaminated by electrooculography (EOG) artifacts. In this paper, by using independent component analysis (ICA) and multivariate empirical mode decomposition (MEMD), the ICA-based MEMD method was proposed to remove EOG artifacts (EOAs) from multichannel EEG signals. First, the EEG signals were decomposed by the MEMD into multiple multivariate intrinsic mode functions (MIMFs). The EOG-related components were then extracted by reconstructing the MIMFs corresponding to EOAs. After performing the ICA of EOG-related signals, the EOG-linked independent components were distinguished and rejected. Finally, the clean EEG signals were reconstructed by implementing the inverse transform of ICA and MEMD. The results of simulated and real data suggested that the proposed method could successfully eliminate EOAs from EEG signals and preserve useful EEG information with little loss. By comparing with other existing techniques, the proposed method achieved much improvement in terms of the increase of signal-to-noise and the decrease of mean square error after removing EOAs.

  12. The effect of image position on the Independent Components of natural binocular images.

    Science.gov (United States)

    Hunter, David W; Hibbard, Paul B

    2018-01-11

    Human visual performance degrades substantially as the angular distance from the fovea increases. This decrease in performance is found for both binocular and monocular vision. Although analysis of the statistics of natural images has provided significant insights into human visual processing, little research has focused on the statistical content of binocular images at eccentric angles. We applied Independent Component Analysis to rectangular image patches cut from locations within binocular images corresponding to different degrees of eccentricity. The distribution of components learned from the varying locations was examined to determine how these distributions varied across eccentricity. We found a general trend towards a broader spread of horizontal and vertical position disparity tunings in eccentric regions compared to the fovea, with the horizontal spread more pronounced than the vertical spread. Eccentric locations above the centroid show a strong bias towards far-tuned components, eccentric locations below the centroid show a strong bias towards near-tuned components. These distributions exhibit substantial similarities with physiological measurements in V1, however in common with previous research we also observe important differences, in particular distributions of binocular phase disparity which do not match physiology.

  13. GPR Detection of Buried Symmetrically Shaped Mine-like Objects using Selective Independent Component Analysis

    DEFF Research Database (Denmark)

    Karlsen, Brian; Sørensen, Helge Bjarup Dissing; Larsen, Jan

    2003-01-01

    from small-scale anti-personal (AP) mines to large-scale anti-tank (AT) mines were designed. Large-scale SF-GPR measurements on this series of mine-like objects buried in soil were performed. The SF-GPR data was acquired using a wideband monostatic bow-tie antenna operating in the frequency range 750......This paper addresses the detection of mine-like objects in stepped-frequency ground penetrating radar (SF-GPR) data as a function of object size, object content, and burial depth. The detection approach is based on a Selective Independent Component Analysis (SICA). SICA provides an automatic...... ranking of components, which enables the suppression of clutter, hence extraction of components carrying mine information. The goal of the investigation is to evaluate various time and frequency domain ICA approaches based on SICA. Performance comparison is based on a series of mine-like objects ranging...

  14. Quantitative assessment of cooperative components in an effective and efficient cooperation in construction

    DEFF Research Database (Denmark)

    Bohnstedt, Kristian Ditlev; Wandahl, Søren

    2018-01-01

    Collaboration takes place on many levels among several professions and the implementation varies dependent on the project and location. The author believes that components in effective collaboration can be identified, used in set situations, and have a particular outcome. Collaboration in the con......Collaboration takes place on many levels among several professions and the implementation varies dependent on the project and location. The author believes that components in effective collaboration can be identified, used in set situations, and have a particular outcome. Collaboration...... in the construction industry is thus dissected in the need to create a more effective and efficient collaboration. In a sequential study based on both interviews and a survey, eight components were molded though theoretical evaluation of the structural coherence of found collaborative elements in the study....... The contribution in this paper are eight components facilitating collaboration, parties' behavior in the collaboration, communication, mutual relationships, capabilities and the framework. These components will in future research help form the backbone of a model for effective and efficient situational...

  15. Independent component analysis separates spikes of different origin in the EEG.

    Science.gov (United States)

    Urrestarazu, Elena; Iriarte, Jorge; Artieda, Julio; Alegre, Manuel; Valencia, Miguel; Viteri, César

    2006-02-01

    Independent component analysis (ICA) is a novel system that finds independent sources in recorded signals. Its usefulness in separating epileptiform activity of different origin has not been determined. The goal of this study was to demonstrate that ICA is useful for separating different spikes using samples of EEG of patients with focal epilepsy. Digital EEG samples from four patients with focal epilepsy were included. The patients had temporal (n = 2), centrotemporal (n = 1) or frontal spikes (n = 1). Twenty-six samples with two (or more) spikes from two different patients were created. The selection of the two spikes for each mixed EEG was performed randomly, trying to have all the different combinations and rejecting the mixture of two spikes from the same patient. Two different examiners studied the EEGs using ICA with JADE paradigm in Matlab platform, trying to separate and to identify the spikes. They agreed in the correct separation of the spikes in 24 of the 26 samples, classifying the spikes as frontal, temporal or centrotemporal, left or right sided. The demonstration of the possibility of detecting different artificially mixed spikes confirms that ICA may be useful in separating spikes or other elements in real EEGs.

  16. Quantitative profiling of polar metabolites in herbal medicine injections for multivariate statistical evaluation based on independence principal component analysis.

    Directory of Open Access Journals (Sweden)

    Miaomiao Jiang

    Full Text Available Botanical primary metabolites extensively exist in herbal medicine injections (HMIs, but often were ignored to control. With the limitation of bias towards hydrophilic substances, the primary metabolites with strong polarity, such as saccharides, amino acids and organic acids, are usually difficult to detect by the routinely applied reversed-phase chromatographic fingerprint technology. In this study, a proton nuclear magnetic resonance (1H NMR profiling method was developed for efficient identification and quantification of small polar molecules, mostly primary metabolites in HMIs. A commonly used medicine, Danhong injection (DHI, was employed as a model. With the developed method, 23 primary metabolites together with 7 polyphenolic acids were simultaneously identified, of which 13 metabolites with fully separated proton signals were quantified and employed for further multivariate quality control assay. The quantitative 1H NMR method was validated with good linearity, precision, repeatability, stability and accuracy. Based on independence principal component analysis (IPCA, the contents of 13 metabolites were characterized and dimensionally reduced into the first two independence principal components (IPCs. IPC1 and IPC2 were then used to calculate the upper control limits (with 99% confidence ellipsoids of χ2 and Hotelling T2 control charts. Through the constructed upper control limits, the proposed method was successfully applied to 36 batches of DHI to examine the out-of control sample with the perturbed levels of succinate, malonate, glucose, fructose, salvianic acid and protocatechuic aldehyde. The integrated strategy has provided a reliable approach to identify and quantify multiple polar metabolites of DHI in one fingerprinting spectrum, and it has also assisted in the establishment of IPCA models for the multivariate statistical evaluation of HMIs.

  17. Blind Extraction of Chaotic Signals by Using the Fast Independent Component Analysis Algorithm

    International Nuclear Information System (INIS)

    Hong-Bin, Chen; Jiu-Chao, Feng; Yong, Fang

    2008-01-01

    We report the results of using the fast independent component analysis (FastICA) algorithm to realize blind extraction of chaotic signals. Two cases are taken into consideration: namely, the mixture is noiseless or contaminated by noise. Pre-whitening is employed to reduce the effect of noise before using the FastICA algorithm. The correlation coefficient criterion is adopted to evaluate the performance, and the success rate is defined as a new criterion to indicate the performance with respect to noise or different mixing matrices. Simulation results show that the FastICA algorithm can extract the chaotic signals effectively. The impact of noise, the length of a signal frame, the number of sources and the number of observed mixtures on the performance is investigated in detail. It is also shown that regarding a noise as an independent source is not always correct

  18. A short study to assess the potential of independent component analysis for motion artifact separation in wearable pulse oximeter signals.

    Science.gov (United States)

    Yao, Jianchu; Warren, Steve

    2005-01-01

    Motion artifact reduction and separation become critical when medical sensors are used in wearable monitoring scenarios. Previous research has demonstrated that independent component analysis (ICA) can be applied to pulse oximeter signals to separate photoplethysmographic (PPG) data from motion artifacts, ambient light, and other interference in low-motion environments. However, ICA assumes that all source signal component pairs are mutually independent. It is important to assess the statistical independence of the source components in PPG data, especially if ICA is to be applied in ambulatory monitoring environments, where motion artifacts can have a substantial effect on the quality of data received from light-based sensors. This paper addresses the statistical relationship between motion artifacts and PPG data by calculating the correlation coefficients between arterial volume variations and motion over a range of stationary to high-motion conditions. Analyses indicate that motion significantly affects arterial flow, so care must be taken when applying ICA to light-based sensor data acquired from wearable platforms.

  19. Independent component analysis: A new possibility for analysing series of electron energy loss spectra

    International Nuclear Information System (INIS)

    Bonnet, Nogl; Nuzillard, Danielle

    2005-01-01

    A complementary approach is proposed for analysing series of electron energy-loss spectra that can be recorded with the spectrum-line technique, across an interface for instance. This approach, called blind source separation (BSS) or independent component analysis (ICA), complements two existing methods: the spatial difference approach and multivariate statistical analysis. The principle of the technique is presented and illustrations are given through one simulated example and one real example

  20. Economic efficiency, independent power producers and wheeling

    International Nuclear Information System (INIS)

    Fytche, E.L.

    1991-01-01

    Traditionally, electric utilities have sought to decrease the cost of production by such means as merit order running of machines, by improving equipment efficiency, by fuel mix, by interconnection and exchange of cheap energy, and by unit participation and firm purchase and sale contracts for long term savings. In the ''new look'', it was suggested that financial and technical competition is not enough, and that economic gains could be achieved through fostering independent power producers, i.e., non-utility generators (NUG's), greater exchanges of economy energy, unrestricted access to the transmission network for moving cheap energy through facilities of third parties, and by bidding to supply energy to non-generators, etc. Naturally, the proposals to change the comfortable and time-hallowed practices by which utility business had been carried out in the past has created an ongoing debate both pro and con, much of it acrimonious, and, unfortunately, some of it ill-informed. The turmoil in the political context impacts on a utility's technical and financial planners, and on their managements, all of whom contribute to justifying and maintaining the flow of capital to the industry and energy to the customer. They must now seek new ways to implement both short- and long-term planning of power supply. Some of the factors that were neglected in the past will demand more attention in the future. This paper discusses some of the costs that, under the anticipated modus operandi, must be integrated into the planning process while meeting the new challenges. The costs are those relating to third-parties, costs of transmission constraints, and costs of wheeling. The opinion is ventured that much of the efficiency improvement anticipated during the debate has already been achieved by conscientious utility managements. (author)

  1. Efficient and robust relaxation procedures for multi-component mixtures including phase transition

    International Nuclear Information System (INIS)

    Han, Ee; Hantke, Maren; Müller, Siegfried

    2017-01-01

    We consider a thermodynamic consistent multi-component model in multi-dimensions that is a generalization of the classical two-phase flow model of Baer and Nunziato. The exchange of mass, momentum and energy between the phases is described by additional source terms. Typically these terms are handled by relaxation procedures. Available relaxation procedures suffer from efficiency and robustness resulting in very costly computations that in general only allow for one-dimensional computations. Therefore we focus on the development of new efficient and robust numerical methods for relaxation processes. We derive exact procedures to determine mechanical and thermal equilibrium states. Further we introduce a novel iterative method to treat the mass transfer for a three component mixture. All new procedures can be extended to an arbitrary number of inert ideal gases. We prove existence, uniqueness and physical admissibility of the resulting states and convergence of our new procedures. Efficiency and robustness of the procedures are verified by means of numerical computations in one and two space dimensions. - Highlights: • We develop novel relaxation procedures for a generalized, thermodynamically consistent Baer–Nunziato type model. • Exact procedures for mechanical and thermal relaxation procedures avoid artificial parameters. • Existence, uniqueness and physical admissibility of the equilibrium states are proven for special mixtures. • A novel iterative method for mass transfer is introduced for a three component mixture providing a unique and admissible equilibrium state.

  2. Comparison of common components analysis with principal components analysis and independent components analysis: Application to SPME-GC-MS volatolomic signatures.

    Science.gov (United States)

    Bouhlel, Jihéne; Jouan-Rimbaud Bouveresse, Delphine; Abouelkaram, Said; Baéza, Elisabeth; Jondreville, Catherine; Travel, Angélique; Ratel, Jérémy; Engel, Erwan; Rutledge, Douglas N

    2018-02-01

    The aim of this work is to compare a novel exploratory chemometrics method, Common Components Analysis (CCA), with Principal Components Analysis (PCA) and Independent Components Analysis (ICA). CCA consists in adapting the multi-block statistical method known as Common Components and Specific Weights Analysis (CCSWA or ComDim) by applying it to a single data matrix, with one variable per block. As an application, the three methods were applied to SPME-GC-MS volatolomic signatures of livers in an attempt to reveal volatile organic compounds (VOCs) markers of chicken exposure to different types of micropollutants. An application of CCA to the initial SPME-GC-MS data revealed a drift in the sample Scores along CC2, as a function of injection order, probably resulting from time-related evolution in the instrument. This drift was eliminated by orthogonalization of the data set with respect to CC2, and the resulting data are used as the orthogonalized data input into each of the three methods. Since the first step in CCA is to norm-scale all the variables, preliminary data scaling has no effect on the results, so that CCA was applied only to orthogonalized SPME-GC-MS data, while, PCA and ICA were applied to the "orthogonalized", "orthogonalized and Pareto-scaled", and "orthogonalized and autoscaled" data. The comparison showed that PCA results were highly dependent on the scaling of variables, contrary to ICA where the data scaling did not have a strong influence. Nevertheless, for both PCA and ICA the clearest separations of exposed groups were obtained after autoscaling of variables. The main part of this work was to compare the CCA results using the orthogonalized data with those obtained with PCA and ICA applied to orthogonalized and autoscaled variables. The clearest separations of exposed chicken groups were obtained by CCA. CCA Loadings also clearly identified the variables contributing most to the Common Components giving separations. The PCA Loadings did not

  3. Independent component analysis reveals new and biologically significant structures in micro array data

    Directory of Open Access Journals (Sweden)

    Veerla Srinivas

    2006-06-01

    Full Text Available Abstract Background An alternative to standard approaches to uncover biologically meaningful structures in micro array data is to treat the data as a blind source separation (BSS problem. BSS attempts to separate a mixture of signals into their different sources and refers to the problem of recovering signals from several observed linear mixtures. In the context of micro array data, "sources" may correspond to specific cellular responses or to co-regulated genes. Results We applied independent component analysis (ICA to three different microarray data sets; two tumor data sets and one time series experiment. To obtain reliable components we used iterated ICA to estimate component centrotypes. We found that many of the low ranking components indeed may show a strong biological coherence and hence be of biological significance. Generally ICA achieved a higher resolution when compared with results based on correlated expression and a larger number of gene clusters with significantly enriched for gene ontology (GO categories. In addition, components characteristic for molecular subtypes and for tumors with specific chromosomal translocations were identified. ICA also identified more than one gene clusters significant for the same GO categories and hence disclosed a higher level of biological heterogeneity, even within coherent groups of genes. Conclusion Although the ICA approach primarily detects hidden variables, these surfaced as highly correlated genes in time series data and in one instance in the tumor data. This further strengthens the biological relevance of latent variables detected by ICA.

  4. An assessment of independent component analysis for detection of military targets from hyperspectral images

    Science.gov (United States)

    Tiwari, K. C.; Arora, M. K.; Singh, D.

    2011-10-01

    Hyperspectral data acquired over hundreds of narrow contiguous wavelength bands are extremely suitable for target detection due to their high spectral resolution. Though spectral response of every material is expected to be unique, but in practice, it exhibits variations, which is known as spectral variability. Most target detection algorithms depend on spectral modelling using a priori available target spectra In practice, target spectra is, however, seldom available a priori. Independent component analysis (ICA) is a new evolving technique that aims at finding out components which are statistically independent or as independent as possible. The technique therefore has the potential of being used for target detection applications. A assessment of target detection from hyperspectral images using ICA and other algorithms based on spectral modelling may be of immense interest, since ICA does not require a priori target information. The aim of this paper is, thus, to assess the potential of ICA based algorithm vis a vis other prevailing algorithms for military target detection. Four spectral matching algorithms namely Orthogonal Subspace Projection (OSP), Constrained Energy Minimisation (CEM), Spectral Angle Mapper (SAM) and Spectral Correlation Mapper (SCM), and four anomaly detection algorithms namely OSP anomaly detector (OSPAD), Reed-Xiaoli anomaly detector (RXD), Uniform Target Detector (UTD) and a combination of Reed-Xiaoli anomaly detector and Uniform Target Detector (RXD-UTD) were considered. The experiments were conducted using a set of synthetic and AVIRIS hyperspectral images containing aircrafts as military targets. A comparison of true positive and false positive rates of target detections obtained from ICA and other algorithms plotted on a receiver operating curves (ROC) space indicates the superior performance of the ICA over other algorithms.

  5. Automatic denoising of functional MRI data: combining independent component analysis and hierarchical fusion of classifiers.

    Science.gov (United States)

    Salimi-Khorshidi, Gholamreza; Douaud, Gwenaëlle; Beckmann, Christian F; Glasser, Matthew F; Griffanti, Ludovica; Smith, Stephen M

    2014-04-15

    Many sources of fluctuation contribute to the fMRI signal, and this makes identifying the effects that are truly related to the underlying neuronal activity difficult. Independent component analysis (ICA) - one of the most widely used techniques for the exploratory analysis of fMRI data - has shown to be a powerful technique in identifying various sources of neuronally-related and artefactual fluctuation in fMRI data (both with the application of external stimuli and with the subject "at rest"). ICA decomposes fMRI data into patterns of activity (a set of spatial maps and their corresponding time series) that are statistically independent and add linearly to explain voxel-wise time series. Given the set of ICA components, if the components representing "signal" (brain activity) can be distinguished form the "noise" components (effects of motion, non-neuronal physiology, scanner artefacts and other nuisance sources), the latter can then be removed from the data, providing an effective cleanup of structured noise. Manual classification of components is labour intensive and requires expertise; hence, a fully automatic noise detection algorithm that can reliably detect various types of noise sources (in both task and resting fMRI) is desirable. In this paper, we introduce FIX ("FMRIB's ICA-based X-noiseifier"), which provides an automatic solution for denoising fMRI data via accurate classification of ICA components. For each ICA component FIX generates a large number of distinct spatial and temporal features, each describing a different aspect of the data (e.g., what proportion of temporal fluctuations are at high frequencies). The set of features is then fed into a multi-level classifier (built around several different classifiers). Once trained through the hand-classification of a sufficient number of training datasets, the classifier can then automatically classify new datasets. The noise components can then be subtracted from (or regressed out of) the original

  6. Objective selection of EEG late potentials through residual dependence estimation of independent components

    International Nuclear Information System (INIS)

    Milanesi, M; James, C J; Martini, N; Menicucci, D; Gemignani, A; Ghelarducci, B; Landini, L

    2009-01-01

    This paper presents a novel method to objectively select electroencephalographic (EEG) cortical sources estimated by independent component analysis (ICA) in event-related potential (ERP) studies. A proximity measure based on mutual information is employed to estimate residual dependences of the components that are then hierarchically clustered based on these residual dependences. Next, the properties of each group of components are evaluated at each level of the hierarchical tree by two indices that aim to assess both cluster tightness and physiological reliability through a template matching process. These two indices are combined in three different approaches to bring to light the hierarchical structure of the cluster organizations. Our method is tested on a set of experiments with the purpose of enhancing late positive ERPs elicited by emotional picture stimuli. Results suggest that the best way to look for physiologically plausible late positive potential (LPP) sources is to explore in depth the tightness of those clusters that, taken together, best resemble the template. According to our results, after brain sources clustering, LPPs are always identified more accurately than from ensemble-averaged raw data. Since the late components of an ERP involve the same associative areas, regardless of the modality of stimulation or specific tasks administered, the proposed method can be simply adapted to other ERP studies, and extended from psychophysiological studies to pathological or sport training evaluation support

  7. A comparative and combined study of EMIS and GPR detectors by the use of Independent Component Analysis

    DEFF Research Database (Denmark)

    Morgenstjerne, Axel; Karlsen, Brian; Larsen, Jan

    2005-01-01

    Independent Component Analysis (ICA) is applied to classify unexploded ordnance (UXO) on laboratory UXO test-field data, acquired by stand-off detection. The data are acquired by an Electromagnetic Induction Spectroscopy (EMIS) metal detector and a ground penetrating radar (GPR) detector. The metal...

  8. Efficiency Analysis of Independent and Centralized Heating Systems for Residential Buildings in Northern Italy

    Directory of Open Access Journals (Sweden)

    Fabio Rinaldi

    2011-11-01

    Full Text Available The primary energy consumption in residential buildings is determined by the envelope thermal characteristics, air change, outside climatic data, users’ behaviour and the adopted heating system and its control. The new Italian regulations strongly suggest the installation of centralized boilers in renovated buildings with more than four apartments. This work aims to investigate the differences in primary energy consumption and efficiency among several independent and centralized heating systems installed in Northern Italy. The analysis is carried out through the following approach: firstly building heating loads are evaluated using the software TRNSYS® and, then, heating system performances are estimated through a simplified model based on the European Standard EN 15316. Several heating systems have been analyzed, evaluating: independent and centralized configurations, condensing and traditional boilers, radiator and radiant floor emitters and solar plant integration. The heating systems are applied to four buildings dating back to 2010, 2006, 1960s and 1930s. All the combinations of heating systems and buildings are analyzed in detail, evaluating efficiency and primary energy consumption. In most of the cases the choice between centralized and independent heating systems has minor effects on primary energy consumption, less than 3%: the introduction of condensing technology and the integration with solar heating plant can reduce energy consumption by 11% and 29%, respectively.

  9. Efficient Device-Independent Entanglement Detection for Multipartite Systems

    Science.gov (United States)

    Baccari, F.; Cavalcanti, D.; Wittek, P.; Acín, A.

    2017-04-01

    Entanglement is one of the most studied properties of quantum mechanics for its application in quantum information protocols. Nevertheless, detecting the presence of entanglement in large multipartite states continues to be a great challenge both from the theoretical and the experimental point of view. Most of the known methods either have computational costs that scale inefficiently with the number of particles or require more information on the state than what is attainable in everyday experiments. We introduce a new technique for entanglement detection that provides several important advantages in these respects. First, it scales efficiently with the number of particles, thus allowing for application to systems composed by up to few tens of particles. Second, it needs only the knowledge of a subset of all possible measurements on the state, therefore being apt for experimental implementation. Moreover, since it is based on the detection of nonlocality, our method is device independent. We report several examples of its implementation for well-known multipartite states, showing that the introduced technique has a promising range of applications.

  10. Independent Component Analysis and Time-Frequency Masking for Speech Recognition in Multitalker Conditions

    Directory of Open Access Journals (Sweden)

    Reinhold Orglmeister

    2010-01-01

    Full Text Available When a number of speakers are simultaneously active, for example in meetings or noisy public places, the sources of interest need to be separated from interfering speakers and from each other in order to be robustly recognized. Independent component analysis (ICA has proven a valuable tool for this purpose. However, ICA outputs can still contain strong residual components of the interfering speakers whenever noise or reverberation is high. In such cases, nonlinear postprocessing can be applied to the ICA outputs, for the purpose of reducing remaining interferences. In order to improve robustness to the artefacts and loss of information caused by this process, recognition can be greatly enhanced by considering the processed speech feature vector as a random variable with time-varying uncertainty, rather than as deterministic. The aim of this paper is to show the potential to improve recognition of multiple overlapping speech signals through nonlinear postprocessing together with uncertainty-based decoding techniques.

  11. Detection of Connective Tissue Disorders from 3D Aortic MR Images Using Independent Component Analysis

    DEFF Research Database (Denmark)

    Hansen, Michael Sass; Zhao, Fei; Zhang, Honghai

    2006-01-01

    A computer-aided diagnosis (CAD) method is reported that allows the objective identification of subjects with connective tissue disorders from 3D aortic MR images using segmentation and independent component analysis (ICA). The first step to extend the model to 4D (3D + time) has also been taken....... ICA is an effective tool for connective tissue disease detection in the presence of sparse data using prior knowledge to order the components, and the components can be inspected visually. 3D+time MR image data sets acquired from 31 normal and connective tissue disorder subjects at end-diastole (R......-wave peak) and at 45\\$\\backslash\\$% of the R-R interval were used to evaluate the performance of our method. The automated 3D segmentation result produced accurate aortic surfaces covering the aorta. The CAD method distinguished between normal and connective tissue disorder subjects with a classification...

  12. RFI Detection and Mitigation using Independent Component Analysis as a Pre-Processor

    Science.gov (United States)

    Schoenwald, Adam J.; Gholian, Armen; Bradley, Damon C.; Wong, Mark; Mohammed, Priscilla N.; Piepmeier, Jeffrey R.

    2016-01-01

    Radio-frequency interference (RFI) has negatively impacted scientific measurements of passive remote sensing satellites. This has been observed in the L-band radiometers Soil Moisture and Ocean Salinity (SMOS), Aquarius and more recently, Soil Moisture Active Passive (SMAP). RFI has also been observed at higher frequencies such as K band. Improvements in technology have allowed wider bandwidth digital back ends for passive microwave radiometry. A complex signal kurtosis radio frequency interference detector was developed to help identify corrupted measurements. This work explores the use of Independent Component Analysis (ICA) as a blind source separation (BSS) technique to pre-process radiometric signals for use with the previously developed real and complex signal kurtosis detectors.

  13. On Phonemes As Cognitive Components of Speech

    DEFF Research Database (Denmark)

    Feng, Ling; Hansen, Lars Kai

    2008-01-01

    . The basic features are 25-dimensional short time (20ms) melfrequency weighted cepstral coefficients. Features are integrated by means of stacking to obtain features at longer time scales. Energy based sparsification is carried out to achieve sparse representations. Our hypothesis is ecological: we assume...... that features that essentially independent in a context defined ensemble can be efficiently coded using a sparse independent component representation. This means that supervised and unsupervised learning should result in similar representations. We indeed find that supervised and unsupervised learning seem...

  14. Estimation of Frame Independent and Enhancement Components for Speech Communication over Packet Networks

    DEFF Research Database (Denmark)

    Giacobello, Daniele; Murthi, Manohar N.; Christensen, Mads Græsbøll

    2010-01-01

    In this paper, we describe a new approach to cope with packet loss in speech coders. The idea is to split the information present in each speech packet into two components, one to independently decode the given speech frame and one to enhance it by exploiting interframe dependencies. The scheme...... is based on sparse linear prediction and a redefinition of the analysis-by-synthesis process. We present Mean Opinion Scores for the presented coder with different degrees of packet loss and show that it performs similarly to frame dependent coders for low packet loss probability and similarly to frame...

  15. Identifying constituents in commercial gasoline using Fourier transform-infrared spectroscopy and independent component analysis.

    Science.gov (United States)

    Pasadakis, Nikos; Kardamakis, Andreas A

    2006-09-25

    A new method is proposed that enables the identification of five refinery fractions present in commercial gasoline mixtures using infrared spectroscopic analysis. The data analysis and interpretation was carried out based on independent component analysis (ICA) and spectral similarity techniques. The FT-IR spectra of the gasoline constituents were determined using the ICA method, exclusively based on the spectra of their mixtures as a blind separation procedure, i.e. assuming unknown the spectra of the constituents. The identity of the constituents was subsequently determined using similarity measures commonly employed in spectra library searches against the spectra of the constituent components. The high correlation scores that were obtained in the identification of the constituents indicates that the developed method can be employed as a rapid and effective tool in quality control, fingerprinting or forensic applications, where gasoline constituents are suspected.

  16. Efficient point cloud data processing in shipbuilding: Reformative component extraction method and registration method

    Directory of Open Access Journals (Sweden)

    Jingyu Sun

    2014-07-01

    Full Text Available To survive in the current shipbuilding industry, it is of vital importance for shipyards to have the ship components’ accuracy evaluated efficiently during most of the manufacturing steps. Evaluating components’ accuracy by comparing each component’s point cloud data scanned by laser scanners and the ship’s design data formatted in CAD cannot be processed efficiently when (1 extract components from point cloud data include irregular obstacles endogenously, or when (2 registration of the two data sets have no clear direction setting. This paper presents reformative point cloud data processing methods to solve these problems. K-d tree construction of the point cloud data fastens a neighbor searching of each point. Region growing method performed on the neighbor points of the seed point extracts the continuous part of the component, while curved surface fitting and B-spline curved line fitting at the edge of the continuous part recognize the neighbor domains of the same component divided by obstacles’ shadows. The ICP (Iterative Closest Point algorithm conducts a registration of the two sets of data after the proper registration’s direction is decided by principal component analysis. By experiments conducted at the shipyard, 200 curved shell plates are extracted from the scanned point cloud data, and registrations are conducted between them and the designed CAD data using the proposed methods for an accuracy evaluation. Results show that the methods proposed in this paper support the accuracy evaluation targeted point cloud data processing efficiently in practice.

  17. Complex Signal Kurtosis and Independent Component Analysis for Wideband Radio Frequency Interference Detection

    Science.gov (United States)

    Schoenwald, Adam; Mohammed, Priscilla; Bradley, Damon; Piepmeier, Jeffrey; Wong, Englin; Gholian, Armen

    2016-01-01

    Radio-frequency interference (RFI) has negatively implicated scientific measurements across a wide variation passive remote sensing satellites. This has been observed in the L-band radiometers SMOS, Aquarius and more recently, SMAP [1, 2]. RFI has also been observed at higher frequencies such as K band [3]. Improvements in technology have allowed wider bandwidth digital back ends for passive microwave radiometry. A complex signal kurtosis radio frequency interference detector was developed to help identify corrupted measurements [4]. This work explores the use of ICA (Independent Component Analysis) as a blind source separation technique to pre-process radiometric signals for use with the previously developed real and complex signal kurtosis detectors.

  18. Detection of explosives on the surface of banknotes by Raman hyperspectral imaging and independent component analysis.

    Science.gov (United States)

    Almeida, Mariana R; Correa, Deleon N; Zacca, Jorge J; Logrado, Lucio Paulo Lima; Poppi, Ronei J

    2015-02-20

    The aim of this study was to develop a methodology using Raman hyperspectral imaging and chemometric methods for identification of pre- and post-blast explosive residues on banknote surfaces. The explosives studied were of military, commercial and propellant uses. After the acquisition of the hyperspectral imaging, independent component analysis (ICA) was applied to extract the pure spectra and the distribution of the corresponding image constituents. The performance of the methodology was evaluated by the explained variance and the lack of fit of the models, by comparing the ICA recovered spectra with the reference spectra using correlation coefficients and by the presence of rotational ambiguity in the ICA solutions. The methodology was applied to forensic samples to solve an automated teller machine explosion case. Independent component analysis proved to be a suitable method of resolving curves, achieving equivalent performance with the multivariate curve resolution with alternating least squares (MCR-ALS) method. At low concentrations, MCR-ALS presents some limitations, as it did not provide the correct solution. The detection limit of the methodology presented in this study was 50 μg cm(-2). Copyright © 2014 Elsevier B.V. All rights reserved.

  19. TECHNOLOGY FOR EFFICIENT USAGE OF HYDROCARBON-CONTAINING WASTE IN PRODUCTION OF MULTI-COMPONENT SOLID FUEL

    Directory of Open Access Journals (Sweden)

    B. M. Khroustalev

    2016-01-01

    Full Text Available The paper considers modern approaches to usage of hydrocarbon-containing waste as energy resources and presents description of investigations, statistic materials, analysis results on formation of hydrocarbon-containing waste in the Republic of Belarus. Main problems pertaining to usage of waste as a fuel and technologies for their application have been given in the paper. The paper describes main results of the investigations and a method for efficient application of viscous hydrocarbon-containing waste as an energy-packed component and a binding material while producing a solid fuel. A technological scheme, a prototype industrial unit which are necessary to realize a method for obtaining multi-component solid fuel are represented in the paper. A paper also provides a model of technological process with efficient sequence of technological operations and parameters of optimum component composition. Main factors exerting significant structure-formation influence in creation of structural composition of multi-component solid fuel have been presented in the paper. The paper gives a graphical representation of the principle for selection of mixture particles of various coarseness to form a solid fuel while using a briquetting method and comprising viscous hydrocarbon-containing waste. A dependence of dimensionless concentration g of emissions into atmosphere during burning of two-component solid fuel has been described in the paper. The paper analyzes an influence of the developed methodology for emission calculation of multi-component solid fuels and reveals a possibility to optimize the component composition in accordance with ecological function and individual peculiar features of fuel-burning equipment. Special features concerning storage and transportation, advantages and disadvantages, comparative characteristics, practical applicability of the developed multi-component solid fuel have been considered and presented in the paper. The paper

  20. The influence of select losses components on induction squirrel-cage motor efficiency

    Energy Technology Data Exchange (ETDEWEB)

    Dabala, K. [Electrical Machines Dept., Electrotechnical Inst., Warsaw (Poland)

    2000-07-01

    There is taken into consideration the influence of measured core and friction and windage losses on induction squirrel-cage motor in this paper. This paper presents a way of exact core losses determination in full-load motor. There are also compared efficiencies obtained for three core losses values: from no-load test (IEC 34-2); from draft IEC 2G/102/CDV; from presented in this paper method. This paper presents the influence of the friction and windage losses determined from no-load test and the mechanical losses appeared under the rated speed on the efficiency, too. There is compared the influence of the core and mechanical losses sum on the efficiency dependently on the way of this losses components determination. (orig.)

  1. Efficient generation of connectivity in neuronal networks from simulator-independent descriptions

    Directory of Open Access Journals (Sweden)

    Mikael eDjurfeldt

    2014-04-01

    Full Text Available Simulator-independent descriptions of connectivity in neuronal networks promise greater ease of model sharing, improved reproducibility of simulation results, and reduced programming effort for computational neuroscientists. However, until now, enabling the use of such descriptions in a given simulator in a computationally efficient way has entailed considerable work for simulator developers, which must be repeated for each new connectivity-generating library that is developed.We have developed a generic connection generator interface that provides a standard way to connect a connectivity-generating library to a simulator, such that one library can easily be replaced by another, according to the modeller's needs. We have used the connection generator interface to connect C++ and Python implementations of the connection-set algebra to the NEST simulator. We also demonstrate how the simulator-independent modelling framework PyNN can transparently take advantage of this, passing a connection description through to the simulator layer for rapid processing in C++ where a simulator supports the connection generator interface and falling-back to slower iteration in Python otherwise. A set of benchmarks demonstrates the good performance of the interface.

  2. Spatiotemporal analysis of single-trial EEG of emotional pictures based on independent component analysis and source location

    Science.gov (United States)

    Liu, Jiangang; Tian, Jie

    2007-03-01

    The present study combined the Independent Component Analysis (ICA) and low-resolution brain electromagnetic tomography (LORETA) algorithms to identify the spatial distribution and time course of single-trial EEG record differences between neural responses to emotional stimuli vs. the neutral. Single-trial multichannel (129-sensor) EEG records were collected from 21 healthy, right-handed subjects viewing the emotion emotional (pleasant/unpleasant) and neutral pictures selected from International Affective Picture System (IAPS). For each subject, the single-trial EEG records of each emotional pictures were concatenated with the neutral, and a three-step analysis was applied to each of them in the same way. First, the ICA was performed to decompose each concatenated single-trial EEG records into temporally independent and spatially fixed components, namely independent components (ICs). The IC associated with artifacts were isolated. Second, the clustering analysis classified, across subjects, the temporally and spatially similar ICs into the same clusters, in which nonparametric permutation test for Global Field Power (GFP) of IC projection scalp maps identified significantly different temporal segments of each emotional condition vs. neutral. Third, the brain regions accounted for those significant segments were localized spatially with LORETA analysis. In each cluster, a voxel-by-voxel randomization test identified significantly different brain regions between each emotional condition vs. the neutral. Compared to the neutral, both emotional pictures elicited activation in the visual, temporal, ventromedial and dorsomedial prefrontal cortex and anterior cingulated gyrus. In addition, the pleasant pictures activated the left middle prefrontal cortex and the posterior precuneus, while the unpleasant pictures activated the right orbitofrontal cortex, posterior cingulated gyrus and somatosensory region. Our results were well consistent with other functional imaging

  3. Integration of independent component analysis with near-infrared spectroscopy for analysis of bioactive components in the medicinal plant Gentiana scabra Bunge

    Directory of Open Access Journals (Sweden)

    Yung-Kun Chuang

    2014-09-01

    Full Text Available Independent component (IC analysis was applied to near-infrared spectroscopy for analysis of gentiopicroside and swertiamarin; the two bioactive components of Gentiana scabra Bunge. ICs that are highly correlated with the two bioactive components were selected for the analysis of tissue cultures, shoots and roots, which were found to distribute in three different positions within the domain [two-dimensional (2D and 3D] constructed by the ICs. This setup could be used for quantitative determination of respective contents of gentiopicroside and swertiamarin within the plants. For gentiopicroside, the spectral calibration model based on the second derivative spectra produced the best effect in the wavelength ranges of 600–700 nm, 1600–1700 nm, and 2000–2300 nm (correlation coefficient of calibration = 0.847, standard error of calibration = 0.865%, and standard error of validation = 0.909%. For swertiamarin, a spectral calibration model based on the first derivative spectra produced the best effect in the wavelength ranges of 600–800 nm and 2200–2300 nm (correlation coefficient of calibration = 0.948, standard error of calibration = 0.168%, and standard error of validation = 0.216%. Both models showed a satisfactory predictability. This study successfully established qualitative and quantitative correlations for gentiopicroside and swertiamarin with near-infrared spectra, enabling rapid and accurate inspection on the bioactive components of G. scabra Bunge at different growth stages.

  4. Independent component analysis of gait-related movement artifact recorded using EEG electrodes during treadmill walking.

    Directory of Open Access Journals (Sweden)

    Kristine Lynne Snyder

    2015-12-01

    Full Text Available There has been a recent surge in the use of electroencephalography (EEG as a tool for mobile brain imaging due to its portability and fine time resolution. When EEG is combined with independent component analysis (ICA and source localization techniques, it can model electrocortical activity as arising from temporally independent signals located in spatially distinct cortical areas. However, for mobile tasks, it is not clear how movement artifacts influence ICA and source localization. We devised a novel method to collect pure movement artifact data (devoid of any electrophysiological signals with a 256-channel EEG system. We first blocked true electrocortical activity using a silicone swim cap. Over the silicone layer, we placed a simulated scalp with electrical properties similar to real human scalp. We collected EEG movement artifact signals from ten healthy, young subjects wearing this setup as they walked on a treadmill at speeds from 0.4-1.6 m/s. We performed ICA and dipole fitting on the EEG movement artifact data to quantify how accurately these methods would identify the artifact signals as non-neural. ICA and dipole fitting accurately localized 99% of the independent components in non-neural locations or lacked dipolar characteristics. The remaining 1% of sources had locations within the brain volume and low residual variances, but had topographical maps, power spectra, time courses, and event related spectral perturbations typical of non-neural sources. Caution should be exercised when interpreting ICA for data that includes semi-periodic artifacts including artifact arising from human walking. Alternative methods are needed for the identification and separation of movement artifact in mobile EEG signals, especially methods that can be performed in real time. Separating true brain signals from motion artifact could clear the way for EEG brain computer interfaces for assistance during mobile activities, such as walking.

  5. Hydrogen Production Cost Estimate Using Biomass Gasification: Independent Review

    Energy Technology Data Exchange (ETDEWEB)

    Ruth, M.

    2011-10-01

    This independent review is the conclusion arrived at from data collection, document reviews, interviews and deliberation from December 2010 through April 2011 and the technical potential of Hydrogen Production Cost Estimate Using Biomass Gasification. The Panel reviewed the current H2A case (Version 2.12, Case 01D) for hydrogen production via biomass gasification and identified four principal components of hydrogen levelized cost: CapEx; feedstock costs; project financing structure; efficiency/hydrogen yield. The panel reexamined the assumptions around these components and arrived at new estimates and approaches that better reflect the current technology and business environments.

  6. Investigation of Heat Sink Efficiency for Electronic Component Cooling Applications

    DEFF Research Database (Denmark)

    Staliulionis, Ž.; Zhang, Zhe; Pittini, Riccardo

    2014-01-01

    Research and optimisation of cooling of electronic components using heat sinks becomes increasingly important in modern industry. Numerical methods with experimental real-world verification are the main tools to evaluate efficiency of heat sinks or heat sink systems. Here the investigation...... of relatively simple heat sink application is performed using modeling based on finite element method, and also the potential of such analysis was demonstrated by real-world measurements and comparing obtained results. Thermal modeling was accomplished using finite element analysis software COMSOL and thermo...

  7. High-efficient extraction of principal medicinal components from fresh Phellodendron bark (cortex phellodendri

    Directory of Open Access Journals (Sweden)

    Keqin Xu

    2018-05-01

    Full Text Available There are three key medicinal components (phellodendrine, berberine and palmatine in the extracts of Phellodendron bark, as one of the fundamental herbs of traditional Chinese medicine. Different extraction methods and solvent combinations were investigated to obtain the optimal technologies for high-efficient extraction of these medicinal components. Results: The results showed that combined solvents have higher extracting effect of phellodendrine, berberine and palmatine than single solvent, and the effect of ultrasonic extraction is distinctly better than those of distillation and soxhlet extraction. Conclusion: The hydrochloric acid/methanol-ultrasonic extraction has the best effect for three medicinal components of fresh Phellodendron bark, providing an extraction yield of 103.12 mg/g berberine, 24.41 mg/g phellodendrine, 1.25 mg/g palmatine. Keywords: Phellodendron, Cortex phellodendri, Extraction methods, Medicinal components

  8. Separating complex compound patient motion tracking data using independent component analysis

    Science.gov (United States)

    Lindsay, C.; Johnson, K.; King, M. A.

    2014-03-01

    In SPECT imaging, motion from respiration and body motion can reduce image quality by introducing motion-related artifacts. A minimally-invasive way to track patient motion is to attach external markers to the patient's body and record their location throughout the imaging study. If a patient exhibits multiple movements simultaneously, such as respiration and body-movement, each marker location data will contain a mixture of these motions. Decomposing this complex compound motion into separate simplified motions can have the benefit of applying a more robust motion correction to the specific type of motion. Most motion tracking and correction techniques target a single type of motion and either ignore compound motion or treat it as noise. Few methods account for compound motion exist, but they fail to disambiguate super-position in the compound motion (i.e. inspiration in addition to body movement in the positive anterior/posterior direction). We propose a new method for decomposing the complex compound patient motion using an unsupervised learning technique called Independent Component Analysis (ICA). Our method can automatically detect and separate different motions while preserving nuanced features of the motion without the drawbacks of previous methods. Our main contributions are the development of a method for addressing multiple compound motions, the novel use of ICA in detecting and separating mixed independent motions, and generating motion transform with 12 DOFs to account for twisting and shearing. We show that our method works with clinical datasets and can be employed to improve motion correction in single photon emission computed tomography (SPECT) images.

  9. Independent component processes underlying emotions during natural music listening.

    Science.gov (United States)

    Rogenmoser, Lars; Zollinger, Nina; Elmer, Stefan; Jäncke, Lutz

    2016-09-01

    The aim of this study was to investigate the brain processes underlying emotions during natural music listening. To address this, we recorded high-density electroencephalography (EEG) from 22 subjects while presenting a set of individually matched whole musical excerpts varying in valence and arousal. Independent component analysis was applied to decompose the EEG data into functionally distinct brain processes. A k-means cluster analysis calculated on the basis of a combination of spatial (scalp topography and dipole location mapped onto the Montreal Neurological Institute brain template) and functional (spectra) characteristics revealed 10 clusters referring to brain areas typically involved in music and emotion processing, namely in the proximity of thalamic-limbic and orbitofrontal regions as well as at frontal, fronto-parietal, parietal, parieto-occipital, temporo-occipital and occipital areas. This analysis revealed that arousal was associated with a suppression of power in the alpha frequency range. On the other hand, valence was associated with an increase in theta frequency power in response to excerpts inducing happiness compared to sadness. These findings are partly compatible with the model proposed by Heller, arguing that the frontal lobe is involved in modulating valenced experiences (the left frontal hemisphere for positive emotions) whereas the right parieto-temporal region contributes to the emotional arousal. © The Author (2016). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  10. Detection and Characterization of Ground Displacement Sources from Variational Bayesian Independent Component Analysis of GPS Time Series

    Science.gov (United States)

    Gualandi, A.; Serpelloni, E.; Belardinelli, M. E.

    2014-12-01

    A critical point in the analysis of ground displacements time series is the development of data driven methods that allow to discern and characterize the different sources that generate the observed displacements. A widely used multivariate statistical technique is the Principal Component Analysis (PCA), which allows to reduce the dimensionality of the data space maintaining most of the variance of the dataset explained. It reproduces the original data using a limited number of Principal Components, but it also shows some deficiencies. Indeed, PCA does not perform well in finding the solution to the so-called Blind Source Separation (BSS) problem, i.e. in recovering and separating the original sources that generated the observed data. This is mainly due to the assumptions on which PCA relies: it looks for a new Euclidean space where the projected data are uncorrelated. Usually, the uncorrelation condition is not strong enough and it has been proven that the BSS problem can be tackled imposing on the components to be independent. The Independent Component Analysis (ICA) is, in fact, another popular technique adopted to approach this problem, and it can be used in all those fields where PCA is also applied. An ICA approach enables us to explain the time series imposing a fewer number of constraints on the model, and to reveal anomalies in the data such as transient signals. However, the independence condition is not easy to impose, and it is often necessary to introduce some approximations. To work around this problem, we use a variational bayesian ICA (vbICA) method, which models the probability density function (pdf) of each source signal using a mix of Gaussian distributions. This technique allows for more flexibility in the description of the pdf of the sources, giving a more reliable estimate of them. Here we present the application of the vbICA technique to GPS position time series. First, we use vbICA on synthetic data that simulate a seismic cycle

  11. A new efficient algorithm for computing the imprecise reliability of monotone systems

    International Nuclear Information System (INIS)

    Utkin, Lev V.

    2004-01-01

    Reliability analysis of complex systems by partial information about reliability of components and by different conditions of independence of components may be carried out by means of the imprecise probability theory which provides a unified framework (natural extension, lower and upper previsions) for computing the system reliability. However, the application of imprecise probabilities to reliability analysis meets with a complexity of optimization problems which have to be solved for obtaining the system reliability measures. Therefore, an efficient simplified algorithm to solve and decompose the optimization problems is proposed in the paper. This algorithm allows us to practically implement reliability analysis of monotone systems under partial and heterogeneous information about reliability of components and under conditions of the component independence or the lack of information about independence. A numerical example illustrates the algorithm

  12. Spatiotemporal Patterns of Precipitation-Modulated Landslide Deformation From Independent Component Analysis of InSAR Time Series

    Science.gov (United States)

    Cohen-Waeber, J.; Bürgmann, R.; Chaussard, E.; Giannico, C.; Ferretti, A.

    2018-02-01

    Long-term landslide deformation is disruptive and costly in urbanized environments. We rely on TerraSAR-X satellite images (2009-2014) and an improved data processing algorithm (SqueeSAR™) to produce an exceptionally dense Interferometric Synthetic Aperture Radar ground deformation time series for the San Francisco East Bay Hills. Independent and principal component analyses of the time series reveal four distinct spatial and temporal surface deformation patterns in the area around Blakemont landslide, which we relate to different geomechanical processes. Two components of time-dependent landslide deformation isolate continuous motion and motion driven by precipitation-modulated pore pressure changes controlled by annual seasonal cycles and multiyear drought conditions. Two components capturing more widespread seasonal deformation separate precipitation-modulated soil swelling from annual cycles that may be related to groundwater level changes and thermal expansion of buildings. High-resolution characterization of landslide response to precipitation is a first step toward improved hazard forecasting.

  13. Cross coherence independent component analysis in resting and action states EEG discrimination

    International Nuclear Information System (INIS)

    Almurshedi, A; Ismail, A K

    2014-01-01

    Cross Coherence time frequency transform and independent component analysis (ICA) method were used to analyse the electroencephalogram (EEG) signals in resting and action states during open and close eyes conditions. From the topographical scalp distributions of delta, theta, alpha, and beta power spectrum can clearly discriminate between the signal when the eyes were open or closed, but it was difficult to distinguish between resting and action states when the eyes were closed. In open eyes condition, the frontal area (Fp1, Fp2) was activated (higher power) in delta and theta bands whilst occipital (O1, O2) and partial (P3, P4, Pz) area of brain was activated alpha band in closed eyes condition. The cross coherence method of time frequency analysis is capable of discrimination between rest and action brain signals in closed eyes condition

  14. The Independence Pipeline project : ANR's supply link - Independence Pipeline, Transco's market link

    International Nuclear Information System (INIS)

    Persells, T.

    1998-01-01

    An overview of the Independence Pipeline project was presented. The project offers access from Chicago to the U.S. Midwest market, as well as to Ontario via MichCon, Consumers Power, Great Lakes and Panhandle. The project has three components: ANR's Supply Link, the Independence Pipeline and Transco's MarketLink. The three components are budgeted at $ 1.332 billion dollars and projected for completion between Nov 1999 and Nov 2000. Each component (services, access advantages, market links, rates, storage services, etc ) are described separately. figs

  15. Origins of mass-dependent and mass-independent Ca isotope variations in meteoritic components and meteorites

    Science.gov (United States)

    Bermingham, K. R.; Gussone, N.; Mezger, K.; Krause, J.

    2018-04-01

    The Ca isotope composition of meteorites and their components may vary due to mass-dependent and/or -independent isotope effects. In order to evaluate the origin of these effects, five amoeboid olivine aggregates (AOAs), three calcium aluminum inclusions (CAIs), five chondrules (C), a dark inclusion from Allende (CV3), two dark fragments from North West Africa 753 (NWA 753; R3.9), and a whole rock sample of Orgueil (CI1) were analyzed. This is the first coupled mass-dependent and -independent Ca isotope dataset to include AOAs, a dark inclusion, and dark fragments. Where sample masses permit, Ca isotope data are reported with corresponding petrographic analyses and rare earth element (REE) relative abundance patterns. The CAIs and AOAs are enriched in light Ca isotopes (δ44/40Ca -5.32 to +0.72, where δ44/40Ca is reported relative to SRM 915a). Samples CAI 5 and AOA 1 have anomalous Group II REE patterns. These REE and δ44/40Ca data suggest that the CAI 5 and AOA 1 compositions were set via kinetic isotope fractionation during condensation and evaporation. The remaining samples show mass-dependent Ca isotope variations which cluster between δ44/40Ca +0.53 and +1.59, some of which are coupled with unfractionated REE abundance patterns. These meteoritic components likely formed through the coaccretion of the evaporative residue and condensate following Group II CAI formation or their chemical and isotopic signatures were decoupled (e.g., via nebular or parent-body alteration). The whole rock sample of Orgueil has a δ44/40Ca +0.67 ± 0.18 which is in agreement with most published data. Parent-body alteration, terrestrial alteration, and variable sampling of Ca-rich meteoritic components can have an effect on δ44/40Ca compositions in whole rock meteorites. Samples AOA 1, CAI 5, C 2, and C 4 display mass-independent 48/44Ca anomalies (ε48/44Ca +6 to +12) which are resolved from the standard composition. Other samples measured for these effects (AOA 5, CAI 1, CAI 2

  16. Denoising of chaotic signal using independent component analysis and empirical mode decomposition with circulate translating

    Science.gov (United States)

    Wen-Bo, Wang; Xiao-Dong, Zhang; Yuchan, Chang; Xiang-Li, Wang; Zhao, Wang; Xi, Chen; Lei, Zheng

    2016-01-01

    In this paper, a new method to reduce noises within chaotic signals based on ICA (independent component analysis) and EMD (empirical mode decomposition) is proposed. The basic idea is decomposing chaotic signals and constructing multidimensional input vectors, firstly, on the base of EMD and its translation invariance. Secondly, it makes the independent component analysis on the input vectors, which means that a self adapting denoising is carried out for the intrinsic mode functions (IMFs) of chaotic signals. Finally, all IMFs compose the new denoised chaotic signal. Experiments on the Lorenz chaotic signal composed of different Gaussian noises and the monthly observed chaotic sequence on sunspots were put into practice. The results proved that the method proposed in this paper is effective in denoising of chaotic signals. Moreover, it can correct the center point in the phase space effectively, which makes it approach the real track of the chaotic attractor. Project supported by the National Science and Technology, China (Grant No. 2012BAJ15B04), the National Natural Science Foundation of China (Grant Nos. 41071270 and 61473213), the Natural Science Foundation of Hubei Province, China (Grant No. 2015CFB424), the State Key Laboratory Foundation of Satellite Ocean Environment Dynamics, China (Grant No. SOED1405), the Hubei Provincial Key Laboratory Foundation of Metallurgical Industry Process System Science, China (Grant No. Z201303), and the Hubei Key Laboratory Foundation of Transportation Internet of Things, Wuhan University of Technology, China (Grant No.2015III015-B02).

  17. Raman hyperspectral imaging in conjunction with independent component analysis as a forensic tool for explosive analysis: The case of an ATM explosion.

    Science.gov (United States)

    Almeida, Mariana Ramos; Logrado, Lucio Paulo Lima; Zacca, Jorge Jardim; Correa, Deleon Nascimento; Poppi, Ronei Jesus

    2017-11-01

    In this work, Raman hyperspectral imaging, in conjunction with independent component analysis, was employed as an analytical methodology to detect an ammonium nitrate fuel oil (ANFO) explosive in banknotes after an ATM explosion experiment. The proposed methodology allows for the identification of the ANFO explosive without sample preparation or destroying the sample, at quantities as small as 70μgcm -2 . The explosive was identified following ICA data decomposition by the characteristic nitrate band at 1044cm -1 . The use of Raman hyperspectral imaging and independent component analysis shows great potential for identifying forensic samples by providing chemical and spatial information. Copyright © 2017 Elsevier B.V. All rights reserved.

  18. High-efficient extraction of principal medicinal components from fresh Phellodendron bark (cortex phellodendri).

    Science.gov (United States)

    Xu, Keqin; He, Gongxiu; Qin, Jieming; Cheng, Xuexiang; He, Hanjie; Zhang, Dangquan; Peng, Wanxi

    2018-05-01

    There are three key medicinal components (phellodendrine, berberine and palmatine) in the extracts of Phellodendron bark, as one of the fundamental herbs of traditional Chinese medicine. Different extraction methods and solvent combinations were investigated to obtain the optimal technologies for high-efficient extraction of these medicinal components. The results showed that combined solvents have higher extracting effect of phellodendrine, berberine and palmatine than single solvent, and the effect of ultrasonic extraction is distinctly better than those of distillation and soxhlet extraction. The hydrochloric acid/methanol-ultrasonic extraction has the best effect for three medicinal components of fresh Phellodendron bark, providing an extraction yield of 103.12 mg/g berberine, 24.41 mg/g phellodendrine, 1.25 mg/g palmatine.

  19. Sea level reconstructions from altimetry and tide gauges using independent component analysis

    Science.gov (United States)

    Brunnabend, Sandra-Esther; Kusche, Jürgen; Forootan, Ehsan

    2017-04-01

    Many reconstructions of global and regional sea level rise derived from tide gauges and satellite altimetry used the method of empirical orthogonal functions (EOF) to reduce noise, improving the spatial resolution of the reconstructed outputs and investigate the different signals in climate time series. However, the second order EOF method has some limitations, e.g. in the separation of individual physical signals into different modes of sea level variations and in the capability to physically interpret the different modes as they are assumed to be orthogonal. Therefore, we investigate the use of the more advanced statistical signal decomposition technique called independent component analysis (ICA) to reconstruct global and regional sea level change from satellite altimetry and tide gauge records. Our results indicate that the used method has almost no influence on the reconstruction of global mean sea level change (1.6 mm/yr from 1960-2010 and 2.9 mm/yr from 1993-2013). Only different numbers of modes are needed for the reconstruction. Using the ICA method is advantageous for separating independent climate variability signals from regional sea level variations as the mixing problem of the EOF method is strongly reduced. As an example, the modes most dominated by the El Niño-Southern Oscillation (ENSO) signal are compared. Regional sea level changes near Tianjin, China, Los Angeles, USA, and Majuro, Marshall Islands are reconstructed and the contributions from ENSO are identified.

  20. Prefrontal cortex and somatosensory cortex in tactile crossmodal association: an independent component analysis of ERP recordings.

    Directory of Open Access Journals (Sweden)

    Yixuan Ku

    2007-08-01

    Full Text Available Our previous studies on scalp-recorded event-related potentials (ERPs showed that somatosensory N140 evoked by a tactile vibration in working memory tasks was enhanced when human subjects expected a coming visual stimulus that had been paired with the tactile stimulus. The results suggested that such enhancement represented the cortical activities involved in tactile-visual crossmodal association. In the present study, we further hypothesized that the enhancement represented the neural activities in somatosensory and frontal cortices in the crossmodal association. By applying independent component analysis (ICA to the ERP data, we found independent components (ICs located in the medial prefrontal cortex (around the anterior cingulate cortex, ACC and the primary somatosensory cortex (SI. The activity represented by the IC in SI cortex showed enhancement in expectation of the visual stimulus. Such differential activity thus suggested the participation of SI cortex in the task-related crossmodal association. Further, the coherence analysis and the Granger causality spectral analysis of the ICs showed that SI cortex appeared to cooperate with ACC in attention and perception of the tactile stimulus in crossmodal association. The results of our study support with new evidence an important idea in cortical neurophysiology: higher cognitive operations develop from the modality-specific sensory cortices (in the present study, SI cortex that are involved in sensation and perception of various stimuli.

  1. Time course based artifact identification for independent components of resting state fMRI

    Directory of Open Access Journals (Sweden)

    Christian eRummel

    2013-05-01

    Full Text Available In functional magnetic resonance imaging (fMRI coherent oscillations of the blood oxygen level dependent (BOLD signal can be detected. These arise when brain regions respond to external stimuli or are activated by tasks. The same networks have been characterized during wakeful rest when functional connectivity of the human brain is organized in generic resting state networks (RSN. Alterations of RSN emerge as neurobiological markers of pathological conditions such as altered mental state. In single-subject fMRI data the coherent components can be identified by blind source separation of the pre-processed BOLD data using spatial independent component analysis (ICA and related approaches. The resulting maps may represent physiological RSNs or may be due to various artifacts. In this methodological study, we propose a conceptually simple and fully automatic time course based filtering procedure to detect obvious artifacts in the ICA output for resting state fMRI. The filter is trained on six and tested on 29 healthy subjects, yielding mean filter accuracy, sensitivity and specificity of 0.80, 0.82 and 0.75 in out-of-sample tests. To estimate the impact of clearly artifactual single-subject components on group resting state studies we analyze unfiltered and filtered output with a second level ICA procedure. Although the automated filter does not reach performance values of visual analysis by human raters, we propose that resting state compatible analysis of ICA time courses could be very useful to complement the existing map or task/event oriented artifact classification algorithms.

  2. All-phase MR angiography using independent component analysis of dynamic contrast enhanced MRI time series. φ-MRA

    International Nuclear Information System (INIS)

    Suzuki, Kiyotaka; Matsuzawa, Hitoshi; Watanabe, Masaki; Nakada, Tsutomu; Nakayama, Naoki; Kwee, I.L.

    2003-01-01

    Dynamic contrast enhanced magnetic resonance imaging (dynamic MRI) represents a MRI version of non-diffusible tracer methods, the main clinical use of which is the physiological construction of what is conventionally referred to as perfusion images. The raw data utilized for constructing MRI perfusion images are time series of pixel signal alterations associated with the passage of a gadolinium containing contrast agent. Such time series are highly compatible with independent component analysis (ICA), a novel statistical signal processing technique capable of effectively separating a single mixture of multiple signals into their original independent source signals (blind separation). Accordingly, we applied ICA to dynamic MRI time series. The technique was found to be powerful, allowing for hitherto unobtainable assessment of regional cerebral hemodynamics in vivo. (author)

  3. A tool for efficient, model-independent management optimization under uncertainty

    Science.gov (United States)

    White, Jeremy; Fienen, Michael N.; Barlow, Paul M.; Welter, Dave E.

    2018-01-01

    To fill a need for risk-based environmental management optimization, we have developed PESTPP-OPT, a model-independent tool for resource management optimization under uncertainty. PESTPP-OPT solves a sequential linear programming (SLP) problem and also implements (optional) efficient, “on-the-fly” (without user intervention) first-order, second-moment (FOSM) uncertainty techniques to estimate model-derived constraint uncertainty. Combined with a user-specified risk value, the constraint uncertainty estimates are used to form chance-constraints for the SLP solution process, so that any optimal solution includes contributions from model input and observation uncertainty. In this way, a “single answer” that includes uncertainty is yielded from the modeling analysis. PESTPP-OPT uses the familiar PEST/PEST++ model interface protocols, which makes it widely applicable to many modeling analyses. The use of PESTPP-OPT is demonstrated with a synthetic, integrated surface-water/groundwater model. The function and implications of chance constraints for this synthetic model are discussed.

  4. A Fourier-series-based kernel-independent fast multipole method

    International Nuclear Information System (INIS)

    Zhang Bo; Huang Jingfang; Pitsianis, Nikos P.; Sun Xiaobai

    2011-01-01

    We present in this paper a new kernel-independent fast multipole method (FMM), named as FKI-FMM, for pairwise particle interactions with translation-invariant kernel functions. FKI-FMM creates, using numerical techniques, sufficiently accurate and compressive representations of a given kernel function over multi-scale interaction regions in the form of a truncated Fourier series. It provides also economic operators for the multipole-to-multipole, multipole-to-local, and local-to-local translations that are typical and essential in the FMM algorithms. The multipole-to-local translation operator, in particular, is readily diagonal and does not dominate in arithmetic operations. FKI-FMM provides an alternative and competitive option, among other kernel-independent FMM algorithms, for an efficient application of the FMM, especially for applications where the kernel function consists of multi-physics and multi-scale components as those arising in recent studies of biological systems. We present the complexity analysis and demonstrate with experimental results the FKI-FMM performance in accuracy and efficiency.

  5. Efficient direct yaw moment control: tyre slip power loss minimisation for four-independent wheel drive vehicle

    Science.gov (United States)

    Kobayashi, Takao; Katsuyama, Etsuo; Sugiura, Hideki; Ono, Eiichi; Yamamoto, Masaki

    2018-05-01

    This paper proposes an efficient direct yaw moment control (DYC) capable of minimising tyre slip power loss on contact patches for a four-independent wheel drive vehicle. Simulations identified a significant power loss reduction with a direct yaw moment due to a change in steer characteristics during acceleration or deceleration while turning. Simultaneously, the vehicle motion can be stabilised. As a result, the proposed control method can ensure compatibility between vehicle dynamics performance and energy efficiency. This paper also describes the results of a full-vehicle simulation that was conducted to examine the effectiveness of the proposed DYC.

  6. On the interpretation of the independent components underlying the abdominal phonogram: a study of their physiological relevance

    International Nuclear Information System (INIS)

    Jiménez-González, A; James, C J

    2012-01-01

    Recorded by positioning a sensitive acoustic sensor over the maternal womb, the abdominal phonogram is a signal that contains valuable information for foetal surveillance (e.g. heart rate), which is hidden by maternal and environmental sources. To recover such information, previous work used single-channel independent component analysis (SCICA) to separate the abdominal phonogram into statistically independent components (ICs) that, once acquired, must be objectively associated with the real sources underlying the abdominal phonogram—either physiological or environmental. This is a typical challenge for blind source separation methodologies and requires further research on the signals of interest to find a suitable solution. Here, we have conducted a joint study on 75 sets of ICs by means of statistical, spectral, complexity and time-structure analysis methods. As a result, valuable and consistent characteristics of the components separated from the abdominal phonogram by SCICA have been revealed: (1) the ICs are spectrally disjoint and sorted according to their frequency content, (2) only the ICs with lower frequency content present strong regular patterns and (3) such regular patterns are driven by well-known physiological processes given by the maternal breathing rate, the maternal heart rate and the foetal heart rate. This information was so promising that it has been used in current work for automatic classification of ICs and recovery of the traces of the physiological sources underlying the abdominal phonogram. Future work will look for the extraction of information useful for surveillance (e.g. heart rate), not only about foetal well-being, but also about maternal condition. (paper)

  7. Biclustered Independent Component Analysis for Complex Biomarker and Subtype Identification from Structural Magnetic Resonance Images in Schizophrenia

    Directory of Open Access Journals (Sweden)

    Cota Navin Gupta

    2017-09-01

    Full Text Available Clinical and cognitive symptoms domain-based subtyping in schizophrenia (Sz has been critiqued due to the lack of neurobiological correlates and heterogeneity in symptom scores. We, therefore, present a novel data-driven framework using biclustered independent component analysis to detect subtypes from the reliable and stable gray matter concentration (GMC of patients with Sz. The developed methodology consists of the following steps: source-based morphometry (SBM decomposition, selection and sorting of two component loadings, subtype component reconstruction using group information-guided ICA (GIG-ICA. This framework was applied to the top two group discriminative components namely the insula/superior temporal gyrus/inferior frontal gyrus (I-STG-IFG component and the superior frontal gyrus/middle frontal gyrus/medial frontal gyrus (SFG-MiFG-MFG component from our previous SBM study, which showed diagnostic group difference and had the highest effect sizes. The aggregated multisite dataset consisted of 382 patients with Sz regressed of age, gender, and site voxelwise. We observed two subtypes (i.e., two different subsets of subjects each heavily weighted on these two components, respectively. These subsets of subjects were characterized by significant differences in positive and negative syndrome scale (PANSS positive clinical symptoms (p = 0.005. We also observed an overlapping subtype weighing heavily on both of these components. The PANSS general clinical symptom of this subtype was trend level correlated with the loading coefficients of the SFG-MiFG-MFG component (r = 0.25; p = 0.07. The reconstructed subtype-specific component using GIG-ICA showed variations in voxel regions, when compared to the group component. We observed deviations from mean GMC along with conjunction of features from two components characterizing each deciphered subtype. These inherent variations in GMC among patients with Sz could possibly indicate the

  8. Characterization of the powertrain components for a hybrid quadricycle

    Science.gov (United States)

    De Santis, M.; Agnelli, S.; Silvestri, L.; Di Ilio, G.; Giannini, O.

    2016-06-01

    This paper presents the experimental characterization of a prototyping hybrid electric quadricycle, which is equipped with two independently actuated hub (in-wheel) motors and powered by a 51 V 132 Ah LiFeYPO4 battery pack. Such a vehicle employs two hub motors located in the rear axles in order to independently drive/brake the rear wheels; such architecture allows to implement a torque vectoring system to improve the vehicle dynamics. Due to its actuation flexibility, energy efficiency and performance potentials, this architecture is one of the promising powertrain design for electric quadricycle. Experimental data obtained from measurements on the vehicle powertrain components going from the battery pack to the inverter and to the in-wheel motor were employed to generate the hub motor torque response and power efficiency maps in both driving and regenerative braking modes. Furthermore, the vehicle is equipped with a gasoline internal combustion engine as range extender whose efficiency was also characterized.

  9. Music video shot segmentation using independent component analysis and keyframe extraction based on image complexity

    Science.gov (United States)

    Li, Wei; Chen, Ting; Zhang, Wenjun; Shi, Yunyu; Li, Jun

    2012-04-01

    In recent years, Music video data is increasing at an astonishing speed. Shot segmentation and keyframe extraction constitute a fundamental unit in organizing, indexing, retrieving video content. In this paper a unified framework is proposed to detect the shot boundaries and extract the keyframe of a shot. Music video is first segmented to shots by illumination-invariant chromaticity histogram in independent component (IC) analysis feature space .Then we presents a new metric, image complexity, to extract keyframe in a shot which is computed by ICs. Experimental results show the framework is effective and has a good performance.

  10. Temporal and Spatial Independent Component Analysis for fMRI Data Sets Embedded in the AnalyzeFMRI R Package

    Directory of Open Access Journals (Sweden)

    Pierre Lafaye de Micheaux

    2011-10-01

    Full Text Available For statistical analysis of functional magnetic resonance imaging (fMRI data sets, we propose a data-driven approach based on independent component analysis (ICA implemented in a new version of the AnalyzeFMRI R package. For fMRI data sets, spatial dimension being much greater than temporal dimension, spatial ICA is the computationally tractable approach generally proposed. However, for some neuroscientific applications, temporal independence of source signals can be assumed and temporal ICA becomes then an attractive exploratory technique. In this work, we use a classical linear algebra result ensuring the tractability of temporal ICA. We report several experiments on synthetic data and real MRI data sets that demonstrate the potential interest of our R package.

  11. Characterization of Ground Displacement Sources from Variational Bayesian Independent Component Analysis of Space Geodetic Time Series

    Science.gov (United States)

    Gualandi, Adriano; Serpelloni, Enrico; Elina Belardinelli, Maria; Bonafede, Maurizio; Pezzo, Giuseppe; Tolomei, Cristiano

    2015-04-01

    A critical point in the analysis of ground displacement time series, as those measured by modern space geodetic techniques (primarly continuous GPS/GNSS and InSAR) is the development of data driven methods that allow to discern and characterize the different sources that generate the observed displacements. A widely used multivariate statistical technique is the Principal Component Analysis (PCA), which allows to reduce the dimensionality of the data space maintaining most of the variance of the dataset explained. It reproduces the original data using a limited number of Principal Components, but it also shows some deficiencies, since PCA does not perform well in finding the solution to the so-called Blind Source Separation (BSS) problem. The recovering and separation of the different sources that generate the observed ground deformation is a fundamental task in order to provide a physical meaning to the possible different sources. PCA fails in the BSS problem since it looks for a new Euclidean space where the projected data are uncorrelated. Usually, the uncorrelation condition is not strong enough and it has been proven that the BSS problem can be tackled imposing on the components to be independent. The Independent Component Analysis (ICA) is, in fact, another popular technique adopted to approach this problem, and it can be used in all those fields where PCA is also applied. An ICA approach enables us to explain the displacement time series imposing a fewer number of constraints on the model, and to reveal anomalies in the data such as transient deformation signals. However, the independence condition is not easy to impose, and it is often necessary to introduce some approximations. To work around this problem, we use a variational bayesian ICA (vbICA) method, which models the probability density function (pdf) of each source signal using a mix of Gaussian distributions. This technique allows for more flexibility in the description of the pdf of the sources

  12. Component Energy Efficiencies in a Novel Linear to Rotary Motion Inter-conversion Hydro-mechanism Running a Solar Tracker

    Directory of Open Access Journals (Sweden)

    Kant Eliab Kanyarusoke

    2018-01-01

    Full Text Available A new mechanism interconverting linear and rotary motion was investigated for energy transfers among its components. It employed a gear-rack set, a Hooke coupling and a specially designed bladder-valve system that regulated the motion. The purpose was to estimate individual component mechanical efficiencies as they existed in the prototype so that future reengineering of the mechanism could be properly targeted. Theoretical modelling of the mechanism was first done to obtain equations for efficiencies of the key components. Two-stage experimentation followed when running a solar tracker. The first stage produced data for inputting into the model to determine the efficiencies’ theoretical variation with the Hooke coupling shaft angle. The second one verified results of the Engineering Equation Solver (EES software solutions of the model. It was found that the energy transfer to focus on was that between the Hooke coupling and the output shaft because its efficiency was below 4%

  13. Central Bank independence

    Directory of Open Access Journals (Sweden)

    Vasile DEDU

    2012-08-01

    Full Text Available In this paper we present the key aspects regarding central bank’s independence. Most economists consider that the factor which positively influences the efficiency of monetary policy measures is the high independence of the central bank. We determined that the National Bank of Romania (NBR has a high degree of independence. NBR has both goal and instrument independence. We also consider that the hike of NBR’s independence played an important role in the significant disinflation process, as headline inflation dropped inside the targeted band of 3% ± 1 percentage point recently.

  14. Toward the detection of gravitational waves under non-Gaussian noises II. Independent component analysis.

    Science.gov (United States)

    Morisaki, Soichiro; Yokoyama, Jun'ichi; Eda, Kazunari; Itoh, Yousuke

    2016-01-01

    We introduce a new analysis method to deal with stationary non-Gaussian noises in gravitational wave detectors in terms of the independent component analysis. First, we consider the simplest case where the detector outputs are linear combinations of the inputs, consisting of signals and various noises, and show that this method may be helpful to increase the signal-to-noise ratio. Next, we take into account the time delay between the inputs and the outputs. Finally, we extend our method to nonlinearly correlated noises and show that our method can identify the coupling coefficients and remove non-Gaussian noises. Although we focus on gravitational wave data analysis, our methods are applicable to the detection of any signals under non-Gaussian noises.

  15. A Novel Method for Surface Defect Detection of Photovoltaic Module Based on Independent Component Analysis

    Directory of Open Access Journals (Sweden)

    Xuewu Zhang

    2013-01-01

    Full Text Available This paper proposed a new method for surface defect detection of photovoltaic module based on independent component analysis (ICA reconstruction algorithm. Firstly, a faultless image is used as the training image. The demixing matrix and corresponding ICs are obtained by applying the ICA in the training image. Then we reorder the ICs according to the range values and reform the de-mixing matrix. Then the reformed de-mixing matrix is used to reconstruct the defect image. The resulting image can remove the background structures and enhance the local anomalies. Experimental results have shown that the proposed method can effectively detect the presence of defects in periodically patterned surfaces.

  16. Independent component analysis applied to long bunch beams in the Los Alamos Proton Storage Ring

    Science.gov (United States)

    Kolski, Jeffrey S.; Macek, Robert J.; McCrady, Rodney C.; Pang, Xiaoying

    2012-11-01

    Independent component analysis (ICA) is a powerful blind source separation (BSS) method. Compared to the typical BSS method, principal component analysis, ICA is more robust to noise, coupling, and nonlinearity. The conventional ICA application to turn-by-turn position data from multiple beam position monitors (BPMs) yields information about cross-BPM correlations. With this scheme, multi-BPM ICA has been used to measure the transverse betatron phase and amplitude functions, dispersion function, linear coupling, sextupole strength, and nonlinear beam dynamics. We apply ICA in a new way to slices along the bunch revealing correlations of particle motion within the beam bunch. We digitize beam signals of the long bunch at the Los Alamos Proton Storage Ring with a single device (BPM or fast current monitor) for an entire injection-extraction cycle. ICA of the digitized beam signals results in source signals, which we identify to describe varying betatron motion along the bunch, locations of transverse resonances along the bunch, measurement noise, characteristic frequencies of the digitizing oscilloscopes, and longitudinal beam structure.

  17. Independent component analysis applied to long bunch beams in the Los Alamos Proton Storage Ring

    Directory of Open Access Journals (Sweden)

    Jeffrey S. Kolski

    2012-11-01

    Full Text Available Independent component analysis (ICA is a powerful blind source separation (BSS method. Compared to the typical BSS method, principal component analysis, ICA is more robust to noise, coupling, and nonlinearity. The conventional ICA application to turn-by-turn position data from multiple beam position monitors (BPMs yields information about cross-BPM correlations. With this scheme, multi-BPM ICA has been used to measure the transverse betatron phase and amplitude functions, dispersion function, linear coupling, sextupole strength, and nonlinear beam dynamics. We apply ICA in a new way to slices along the bunch revealing correlations of particle motion within the beam bunch. We digitize beam signals of the long bunch at the Los Alamos Proton Storage Ring with a single device (BPM or fast current monitor for an entire injection-extraction cycle. ICA of the digitized beam signals results in source signals, which we identify to describe varying betatron motion along the bunch, locations of transverse resonances along the bunch, measurement noise, characteristic frequencies of the digitizing oscilloscopes, and longitudinal beam structure.

  18. Highly efficient one-pot three-component synthesis of naphthopyran derivatives in water catalyzed by hydroxyapatite

    Science.gov (United States)

    An expeditious and efficient protocol for the synthesis of naphthopyrans has been developed that proceeds via one-pot three-component sequential reaction in water catalyzed by hydroxyapatite or sodium-modified-hydroxyapatite. The title compounds have been obtained in high yield a...

  19. Wavelet decomposition based principal component analysis for face recognition using MATLAB

    Science.gov (United States)

    Sharma, Mahesh Kumar; Sharma, Shashikant; Leeprechanon, Nopbhorn; Ranjan, Aashish

    2016-03-01

    For the realization of face recognition systems in the static as well as in the real time frame, algorithms such as principal component analysis, independent component analysis, linear discriminate analysis, neural networks and genetic algorithms are used for decades. This paper discusses an approach which is a wavelet decomposition based principal component analysis for face recognition. Principal component analysis is chosen over other algorithms due to its relative simplicity, efficiency, and robustness features. The term face recognition stands for identifying a person from his facial gestures and having resemblance with factor analysis in some sense, i.e. extraction of the principal component of an image. Principal component analysis is subjected to some drawbacks, mainly the poor discriminatory power and the large computational load in finding eigenvectors, in particular. These drawbacks can be greatly reduced by combining both wavelet transform decomposition for feature extraction and principal component analysis for pattern representation and classification together, by analyzing the facial gestures into space and time domain, where, frequency and time are used interchangeably. From the experimental results, it is envisaged that this face recognition method has made a significant percentage improvement in recognition rate as well as having a better computational efficiency.

  20. Efficient testing of the homogeneity, scale parameters and number of components in the Rayleigh mixture

    International Nuclear Information System (INIS)

    Stehlik, M.; Ososkov, G.A.

    2003-01-01

    The statistical problem to expand the experimental distribution of transverse momenta into Rayleigh distribution is considered. A high-efficient testing procedure for testing the hypothesis of the homogeneity of the observed measurements which is optimal in the sense of Bahadur is constructed. The exact likelihood ratio (LR) test of the scale parameter of the Rayleigh distribution is proposed for cases when the hypothesis of homogeneity holds. Otherwise the efficient procedure for testing the number of components in the mixture is also proposed

  1. Genetic algorithm using independent component analysis in x-ray reflectivity curve fitting of periodic layer structures

    International Nuclear Information System (INIS)

    Tiilikainen, J; Bosund, V; Tilli, J-M; Sormunen, J; Mattila, M; Hakkarainen, T; Lipsanen, H

    2007-01-01

    A novel genetic algorithm (GA) utilizing independent component analysis (ICA) was developed for x-ray reflectivity (XRR) curve fitting. EFICA was used to reduce mutual information, or interparameter dependences, during the combinatorial phase. The performance of the new algorithm was studied by fitting trial XRR curves to target curves which were computed using realistic multilayer models. The median convergence properties of conventional GA, GA using principal component analysis and the novel GA were compared. GA using ICA was found to outperform the other methods with problems having 41 parameters or more to be fitted without additional XRR curve calculations. The computational complexity of the conventional methods was linear but the novel method had a quadratic computational complexity due to the applied ICA method which sets a practical limit for the dimensionality of the problem to be solved. However, the novel algorithm had the best capability to extend the fitting analysis based on Parratt's formalism to multiperiodic layer structures

  2. MRI Study on the Functional and Spatial Consistency of Resting State-Related Independent Components of the Brain Network

    Energy Technology Data Exchange (ETDEWEB)

    Jeong, Bum Seok [Korea Advanced Institute of Science and Technology, Daejeon (Korea, Republic of); Choi, Jee Wook [Daejeon St. Mary' s Hospital, The Catholic University of Korea College of Medicine, Daejeon (Korea, Republic of); Kim, Ji Woong [College of Medical Science, Konyang University, Daejeon(Korea, Republic of)

    2012-06-15

    Resting-state networks (RSNs), including the default mode network (DMN), have been considered as markers of brain status such as consciousness, developmental change, and treatment effects. The consistency of functional connectivity among RSNs has not been fully explored, especially among resting-state-related independent components (RSICs). This resting-state fMRI study addressed the consistency of functional connectivity among RSICs as well as their spatial consistency between 'at day 1' and 'after 4 weeks' in 13 healthy volunteers. We found that most RSICs, especially the DMN, are reproducible across time, whereas some RSICs were variable in either their spatial characteristics or their functional connectivity. Relatively low spatial consistency was found in the basal ganglia, a parietal region of left frontoparietal network, and the supplementary motor area. The functional connectivity between two independent components, the bilateral angular/supramarginal gyri/intraparietal lobule and bilateral middle temporal/occipital gyri, was decreased across time regardless of the correlation analysis method employed, (Pearson's or partial correlation). RSICs showing variable consistency are different between spatial characteristics and functional connectivity. To understand the brain as a dynamic network, we recommend further investigation of both changes in the activation of specific regions and the modulation of functional connectivity in the brain network.

  3. MRI Study on the Functional and Spatial Consistency of Resting State-Related Independent Components of the Brain Network

    International Nuclear Information System (INIS)

    Jeong, Bum Seok; Choi, Jee Wook; Kim, Ji Woong

    2012-01-01

    Resting-state networks (RSNs), including the default mode network (DMN), have been considered as markers of brain status such as consciousness, developmental change, and treatment effects. The consistency of functional connectivity among RSNs has not been fully explored, especially among resting-state-related independent components (RSICs). This resting-state fMRI study addressed the consistency of functional connectivity among RSICs as well as their spatial consistency between 'at day 1' and 'after 4 weeks' in 13 healthy volunteers. We found that most RSICs, especially the DMN, are reproducible across time, whereas some RSICs were variable in either their spatial characteristics or their functional connectivity. Relatively low spatial consistency was found in the basal ganglia, a parietal region of left frontoparietal network, and the supplementary motor area. The functional connectivity between two independent components, the bilateral angular/supramarginal gyri/intraparietal lobule and bilateral middle temporal/occipital gyri, was decreased across time regardless of the correlation analysis method employed, (Pearson's or partial correlation). RSICs showing variable consistency are different between spatial characteristics and functional connectivity. To understand the brain as a dynamic network, we recommend further investigation of both changes in the activation of specific regions and the modulation of functional connectivity in the brain network.

  4. Efficient Mutagenesis Independent of Ligation (EMILI).

    Science.gov (United States)

    Füzik, Tibor; Ulbrich, Pavel; Ruml, Tomáš

    2014-11-01

    Site-directed mutagenesis is one of the most widely used techniques in life sciences. Here we describe an improved and simplified method for introducing mutations at desired sites. It consists of an inverse PCR using a plasmid template and two partially complementary primers. The synthesis step is followed by annealing of the PCR product's sticky ends, which are generated by exonuclease digestion. This method is fast, extremely efficient and cost-effective. It can be used to introduce large insertions and deletions, but also for multiple point mutations in a single step. To show the principle and to prove the efficiency of the method, we present a series of basic mutations (insertions, deletions, point mutations) on pUC19 plasmid DNA. Copyright © 2014 Elsevier B.V. All rights reserved.

  5. Classification in hyperspectral images by independent component analysis, segmented cross-validation and uncertainty estimates

    Directory of Open Access Journals (Sweden)

    Beatriz Galindo-Prieto

    2018-02-01

    Full Text Available Independent component analysis combined with various strategies for cross-validation, uncertainty estimates by jack-knifing and critical Hotelling’s T2 limits estimation, proposed in this paper, is used for classification purposes in hyperspectral images. To the best of our knowledge, the combined approach of methods used in this paper has not been previously applied to hyperspectral imaging analysis for interpretation and classification in the literature. The data analysis performed here aims to distinguish between four different types of plastics, some of them containing brominated flame retardants, from their near infrared hyperspectral images. The results showed that the method approach used here can be successfully used for unsupervised classification. A comparison of validation approaches, especially leave-one-out cross-validation and regions of interest scheme validation is also evaluated.

  6. Evaluation of the promotion program 'Energy efficiency consultation' as a component of the special fund Energy efficiency in small and medium enterprises (SME). Final report; Evaluation des Foerderprogramms ''Energieeffizienzberatung'' als eine Komponente des Sonderfonds' Energieeffizienz in kleinen und mittleren Unternehmen (KMU). Schlussbericht

    Energy Technology Data Exchange (ETDEWEB)

    Frahm, Birgit-Jo; Gruber, Edelgard; Mai, Michael; Roser, Annette [Institut fuer Ressourceneffizienz und Energiestrategien (IREES) GmbH, Karlsruhe (Germany); Fleiter, Tobias; Schlomann, Barbara [Fraunhofer-Institut fuer Systemtechnik und Innovationsforschung (ISI), Karlsruhe (Germany)

    2010-11-18

    With the energy consultation as a component in the 'special fund energy efficiency in SMEs' of the Federal Ministry for Economics and Technology (Berlin, Federal Republic of Germany) and KfW development bank (Frankfurt (Main), Federal Republic of Germany) lack of information in small and medium enterprises (SMEs) are to be overcome by qualified and independent energy consulting, and potentials of energy efficiency are to be made accessible. The funded advice is to give incentives to the implementation of investments for the improvement of energy efficiency. In addition, low-interest development loans are accessible in special funds in order to facilitate an investment. On 20 February 2008, the 'Special Fund for Energy Efficiency in SMEs' was launched. In the meantime, in early October 2009 two framework conditions have changed with the introduction of the new online platform for the application as well as for the extension of the maximum consultation period of eight weeks to three months. The energy consultancy component of the Special Fund should now be evaluated in order to study the recent effects of the program and optimization. This should be done from the perspective of te funded organizations, the regional planning and energy efficiency consultants. In addition, a random selection of consulting reports regarding their quality was verified.

  7. Energy efficient drying strategies to retain nutritional components in broccoli broccoli (Brassica oleracea var. italica)

    NARCIS (Netherlands)

    Jin, X.; Sman, van der R.G.M.; Straten, van G.; Boom, R.M.; Boxtel, van A.J.B.

    2014-01-01

    This work concerns the combined optimization of the retention of bioactive components and energy efficiency during drying of broccoli. Kinetics for the degradation of glucosinolates, vitamin C and drying of broccoli are used to calculate optimal drying trajectories for the control variables air flow

  8. Independent component analysis for the extraction of reliable protein signal profiles from MALDI-TOF mass spectra.

    Science.gov (United States)

    Mantini, Dante; Petrucci, Francesca; Del Boccio, Piero; Pieragostino, Damiana; Di Nicola, Marta; Lugaresi, Alessandra; Federici, Giorgio; Sacchetta, Paolo; Di Ilio, Carmine; Urbani, Andrea

    2008-01-01

    Independent component analysis (ICA) is a signal processing technique that can be utilized to recover independent signals from a set of their linear mixtures. We propose ICA for the analysis of signals obtained from large proteomics investigations such as clinical multi-subject studies based on MALDI-TOF MS profiling. The method is validated on simulated and experimental data for demonstrating its capability of correctly extracting protein profiles from MALDI-TOF mass spectra. The comparison on peak detection with an open-source and two commercial methods shows its superior reliability in reducing the false discovery rate of protein peak masses. Moreover, the integration of ICA and statistical tests for detecting the differences in peak intensities between experimental groups allows to identify protein peaks that could be indicators of a diseased state. This data-driven approach demonstrates to be a promising tool for biomarker-discovery studies based on MALDI-TOF MS technology. The MATLAB implementation of the method described in the article and both simulated and experimental data are freely available at http://www.unich.it/proteomica/bioinf/.

  9. Model-independent separation of poorly resolved hypperfine split spectra by a linear combination method

    International Nuclear Information System (INIS)

    Nagy, D.L.; Dengler, J.; Ritter, G.

    1988-01-01

    A model-independent evaluation of the components of poorly resolved Moessbauer spectra based on a linear combination method is possible if there is a parameter as a function of which the shape of the individual components do not but their intensities do change and the dependence of the intensities on this parameter is known. The efficiency of the method is demonstrated on the example of low temperature magnetically split spectra of the high-T c superconductor YBa 2 (Cu 0.9 Fe 0 .1 ) 3 O 7-y . (author)

  10. Signal extraction and wave field separation in tunnel seismic prediction by independent component analysis

    Science.gov (United States)

    Yue, Y.; Jiang, T.; Zhou, Q.

    2017-12-01

    In order to ensure the rationality and the safety of tunnel excavation, the advanced geological prediction has been become an indispensable step in tunneling. However, the extraction of signal and the separation of P and S waves directly influence the accuracy of geological prediction. Generally, the raw data collected in TSP system is low quality because of the numerous disturb factors in tunnel projects, such as the power interference and machine vibration interference. It's difficult for traditional method (band-pass filtering) to remove interference effectively as well as bring little loss to signal. The power interference, machine vibration interference and the signal are original variables and x, y, z component as observation signals, each component of the representation is a linear combination of the original variables, which satisfy applicable conditions of independent component analysis (ICA). We perform finite-difference simulations of elastic wave propagation to synthetic a tunnel seismic reflection record. The method of ICA was adopted to process the three-component data, and the results show that extract the estimates of signal and the signals are highly correlated (the coefficient correlation is up to more than 0.93). In addition, the estimates of interference that separated from ICA and the interference signals are also highly correlated, and the coefficient correlation is up to more than 0.99. Thus, simulation results showed that the ICA is an ideal method for extracting high quality data from mixed signals. For the separation of P and S waves, the conventional separation techniques are based on physical characteristics of wave propagation, which require knowledge of the near-surface P and S waves velocities and density. Whereas the ICA approach is entirely based on statistical differences between P and S waves, and the statistical technique does not require a priori information. The concrete results of the wave field separation will be presented in

  11. Stabilizing bidirectional associative memory with Principles in Independent Component Analysis and Null Space (PICANS)

    Science.gov (United States)

    LaRue, James P.; Luzanov, Yuriy

    2013-05-01

    A new extension to the way in which the Bidirectional Associative Memory (BAM) algorithms are implemented is presented here. We will show that by utilizing the singular value decomposition (SVD) and integrating principles of independent component analysis (ICA) into the nullspace (NS) we have created a novel approach to mitigating spurious attractors. We demonstrate this with two applications. The first application utilizes a one-layer association while the second application is modeled after the several hierarchal associations of ventral pathways. The first application will detail the way in which we manage the associations in terms of matrices. The second application will take what we have learned from the first example and apply it to a cascade of a convolutional neural network (CNN) and perceptron this being our signal processing model of the ventral pathways, i.e., visual systems.

  12. TITANIUM ISOTOPE SOURCE RELATIONS AND THE EXTENT OF MIXING IN THE PROTO-SOLAR NEBULA EXAMINED BY INDEPENDENT COMPONENT ANALYSIS

    Energy Technology Data Exchange (ETDEWEB)

    Steele, Robert C. J.; Boehnke, Patrick [Department of Earth, Planetary, and Space Sciences, University of California, Los Angeles, CA 90095 (United States)

    2015-04-01

    The Ti isotope variations observed in hibonites represent some of the largest isotope anomalies observed in the solar system. Titanium isotope compositions have previously been reported for a wide variety of different early solar system materials, including calcium, aluminum rich inclusions (CAIs) and CM hibonite grains, some of the earliest materials to form in the solar system, and bulk meteorites which formed later. These data have the potential to allow mixing of material to be traced between many different regions of the early solar system. We have used independent component analysis to examine the mixing end-members required to produce the compositions observed in the different data sets. The independent component analysis yields results identical to a linear regression for the bulk meteorites. The components identified for hibonite suggest that most of the grains are consistent with binary mixing from one of three highly anomalous nucleosynthetic sources. Comparison of these end-members show that the sources which dominate the variation of compositions in the meteorite parent body forming regions was not present in the region in which the hibonites formed. This suggests that the source which dominates variation in Ti isotope anomalies between the bulk meteorites was not present when the hibonite grains were forming. One explanation is that the bulk meteorite source may not be a primary nucleosynthetic source but was created by mixing two or more of the hibonite sources. Alternatively, the hibonite sources may have been diluted during subsequent nebula processing and are not a dominant solar system signatures.

  13. Component reliability criticality or importance metrics for systems with degrading components

    NARCIS (Netherlands)

    Peng, H.; Coit, D.W.; Feng, Q.

    2012-01-01

    This paper proposes two new importance measures: one new importance measure for systems with -independent degrading components, and another one for systems with -correlated degrading components. Importance measures in previous research are inadequate for systems with degrading components because

  14. Digital visual communications using a Perceptual Components Architecture

    Science.gov (United States)

    Watson, Andrew B.

    1991-01-01

    The next era of space exploration will generate extraordinary volumes of image data, and management of this image data is beyond current technical capabilities. We propose a strategy for coding visual information that exploits the known properties of early human vision. This Perceptual Components Architecture codes images and image sequences in terms of discrete samples from limited bands of color, spatial frequency, orientation, and temporal frequency. This spatiotemporal pyramid offers efficiency (low bit rate), variable resolution, device independence, error-tolerance, and extensibility.

  15. A Fixed Point VHDL Component Library for a High Efficiency Reconfigurable Radio Design Methodology

    Science.gov (United States)

    Hoy, Scott D.; Figueiredo, Marco A.

    2006-01-01

    Advances in Field Programmable Gate Array (FPGA) technologies enable the implementation of reconfigurable radio systems for both ground and space applications. The development of such systems challenges the current design paradigms and requires more robust design techniques to meet the increased system complexity. Among these techniques is the development of component libraries to reduce design cycle time and to improve design verification, consequently increasing the overall efficiency of the project development process while increasing design success rates and reducing engineering costs. This paper describes the reconfigurable radio component library developed at the Software Defined Radio Applications Research Center (SARC) at Goddard Space Flight Center (GSFC) Microwave and Communications Branch (Code 567). The library is a set of fixed-point VHDL components that link the Digital Signal Processing (DSP) simulation environment with the FPGA design tools. This provides a direct synthesis path based on the latest developments of the VHDL tools as proposed by the BEE VBDL 2004 which allows for the simulation and synthesis of fixed-point math operations while maintaining bit and cycle accuracy. The VHDL Fixed Point Reconfigurable Radio Component library does not require the use of the FPGA vendor specific automatic component generators and provide a generic path from high level DSP simulations implemented in Mathworks Simulink to any FPGA device. The access to the component synthesizable, source code provides full design verification capability:

  16. Speckle noise reduction technique for Lidar echo signal based on self-adaptive pulse-matching independent component analysis

    Science.gov (United States)

    Xu, Fan; Wang, Jiaxing; Zhu, Daiyin; Tu, Qi

    2018-04-01

    Speckle noise has always been a particularly tricky problem in improving the ranging capability and accuracy of Lidar system especially in harsh environment. Currently, effective speckle de-noising techniques are extremely scarce and should be further developed. In this study, a speckle noise reduction technique has been proposed based on independent component analysis (ICA). Since normally few changes happen in the shape of laser pulse itself, the authors employed the laser source as a reference pulse and executed the ICA decomposition to find the optimal matching position. In order to achieve the self-adaptability of algorithm, local Mean Square Error (MSE) has been defined as an appropriate criterion for investigating the iteration results. The obtained experimental results demonstrated that the self-adaptive pulse-matching ICA (PM-ICA) method could effectively decrease the speckle noise and recover the useful Lidar echo signal component with high quality. Especially, the proposed method achieves 4 dB more improvement of signal-to-noise ratio (SNR) than a traditional homomorphic wavelet method.

  17. Multiple brain networks underpinning word learning from fluent speech revealed by independent component analysis.

    Science.gov (United States)

    López-Barroso, Diana; Ripollés, Pablo; Marco-Pallarés, Josep; Mohammadi, Bahram; Münte, Thomas F; Bachoud-Lévi, Anne-Catherine; Rodriguez-Fornells, Antoni; de Diego-Balaguer, Ruth

    2015-04-15

    Although neuroimaging studies using standard subtraction-based analysis from functional magnetic resonance imaging (fMRI) have suggested that frontal and temporal regions are involved in word learning from fluent speech, the possible contribution of different brain networks during this type of learning is still largely unknown. Indeed, univariate fMRI analyses cannot identify the full extent of distributed networks that are engaged by a complex task such as word learning. Here we used Independent Component Analysis (ICA) to characterize the different brain networks subserving word learning from an artificial language speech stream. Results were replicated in a second cohort of participants with a different linguistic background. Four spatially independent networks were associated with the task in both cohorts: (i) a dorsal Auditory-Premotor network; (ii) a dorsal Sensory-Motor network; (iii) a dorsal Fronto-Parietal network; and (iv) a ventral Fronto-Temporal network. The level of engagement of these networks varied through the learning period with only the dorsal Auditory-Premotor network being engaged across all blocks. In addition, the connectivity strength of this network in the second block of the learning phase correlated with the individual variability in word learning performance. These findings suggest that: (i) word learning relies on segregated connectivity patterns involving dorsal and ventral networks; and (ii) specifically, the dorsal auditory-premotor network connectivity strength is directly correlated with word learning performance. Copyright © 2015 Elsevier Inc. All rights reserved.

  18. An Efficient Data Compression Model Based on Spatial Clustering and Principal Component Analysis in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Yihang Yin

    2015-08-01

    Full Text Available Wireless sensor networks (WSNs have been widely used to monitor the environment, and sensors in WSNs are usually power constrained. Because inner-node communication consumes most of the power, efficient data compression schemes are needed to reduce the data transmission to prolong the lifetime of WSNs. In this paper, we propose an efficient data compression model to aggregate data, which is based on spatial clustering and principal component analysis (PCA. First, sensors with a strong temporal-spatial correlation are grouped into one cluster for further processing with a novel similarity measure metric. Next, sensor data in one cluster are aggregated in the cluster head sensor node, and an efficient adaptive strategy is proposed for the selection of the cluster head to conserve energy. Finally, the proposed model applies principal component analysis with an error bound guarantee to compress the data and retain the definite variance at the same time. Computer simulations show that the proposed model can greatly reduce communication and obtain a lower mean square error than other PCA-based algorithms.

  19. An Efficient Data Compression Model Based on Spatial Clustering and Principal Component Analysis in Wireless Sensor Networks.

    Science.gov (United States)

    Yin, Yihang; Liu, Fengzheng; Zhou, Xiang; Li, Quanzhong

    2015-08-07

    Wireless sensor networks (WSNs) have been widely used to monitor the environment, and sensors in WSNs are usually power constrained. Because inner-node communication consumes most of the power, efficient data compression schemes are needed to reduce the data transmission to prolong the lifetime of WSNs. In this paper, we propose an efficient data compression model to aggregate data, which is based on spatial clustering and principal component analysis (PCA). First, sensors with a strong temporal-spatial correlation are grouped into one cluster for further processing with a novel similarity measure metric. Next, sensor data in one cluster are aggregated in the cluster head sensor node, and an efficient adaptive strategy is proposed for the selection of the cluster head to conserve energy. Finally, the proposed model applies principal component analysis with an error bound guarantee to compress the data and retain the definite variance at the same time. Computer simulations show that the proposed model can greatly reduce communication and obtain a lower mean square error than other PCA-based algorithms.

  20. Controleum - an independently extensible control system

    DEFF Research Database (Denmark)

    Jensen, Martin Lykke Rytter

    2014-01-01

    challenging kind of system to design for independent extension. This thesis presents two new software technologies that improve the extensibility of control systems: First, the concept of dynamic links is introduced and Decouplink – an implementation of dynamic links for Java - is presented. Dynamic links...... is introduced, and an implementation is presented. The extensible controller is a component framework designed to automatically resolve conflicts among mutually unaware components in a control system. The solution is based on the idea that independent components implement different kinds of control concerns...

  1. Independent component analysis for cochlear implant artifacts attenuation from electrically evoked auditory steady-state response measurements

    Science.gov (United States)

    Deprez, Hanne; Gransier, Robin; Hofmann, Michael; van Wieringen, Astrid; Wouters, Jan; Moonen, Marc

    2018-02-01

    Objective. Electrically evoked auditory steady-state responses (EASSRs) are potentially useful for objective cochlear implant (CI) fitting and follow-up of the auditory maturation in infants and children with a CI. EASSRs are recorded in the electro-encephalogram (EEG) in response to electrical stimulation with continuous pulse trains, and are distorted by significant CI artifacts related to this electrical stimulation. The aim of this study is to evaluate a CI artifacts attenuation method based on independent component analysis (ICA) for three EASSR datasets. Approach. ICA has often been used to remove CI artifacts from the EEG to record transient auditory responses, such as cortical evoked auditory potentials. Independent components (ICs) corresponding to CI artifacts are then often manually identified. In this study, an ICA based CI artifacts attenuation method was developed and evaluated for EASSR measurements with varying CI artifacts and EASSR characteristics. Artifactual ICs were automatically identified based on their spectrum. Main results. For 40 Hz amplitude modulation (AM) stimulation at comfort level, in high SNR recordings, ICA succeeded in removing CI artifacts from all recording channels, without distorting the EASSR. For lower SNR recordings, with 40 Hz AM stimulation at lower levels, or 90 Hz AM stimulation, ICA either distorted the EASSR or could not remove all CI artifacts in most subjects, except for two of the seven subjects tested with low level 40 Hz AM stimulation. Noise levels were reduced after ICA was applied, and up to 29 ICs were rejected, suggesting poor ICA separation quality. Significance. We hypothesize that ICA is capable of separating CI artifacts and EASSR in case the contralateral hemisphere is EASSR dominated. For small EASSRs or large CI artifact amplitudes, ICA separation quality is insufficient to ensure complete CI artifacts attenuation without EASSR distortion.

  2. Efficient algorithms to assess component and gate importance in fault tree analysis

    International Nuclear Information System (INIS)

    Dutuit, Y.; Rauzy, A.

    2001-01-01

    One of the principal activities of risk assessment is either the ranking or the categorization of structures, systems and components with respect to their risk-significance or their safety-significance. Several measures, so-called importance factors, of such a significance have been proposed for the case where the support model is a fault tree. In this article, we show how binary decision diagrams can be use to assess efficiently a number of classical importance factors. This work completes the preliminary results obtained recently by Andrews and Sinnamon, and the authors. It deals also with the concept of joint reliability importance

  3. Identification of independent modules in fault trees which contain dependent basic events

    International Nuclear Information System (INIS)

    Sun, H.; Andrews, J.D.

    2004-01-01

    The reliability performance of a system is frequently a function of component failures of which some are independent whilst others are interdependent. It is possible to represent the system failure logic in a fault tree diagram, however only the sections containing independent events can be assessed using the conventional fault tree analysis methodology. The analysis of the dependent sections will require a Markov analysis. Since the efficiency of the Markov analysis largely depends on the size of the established Markov model, the key is to extract from the fault tree the smallest sections which contain dependencies. This paper proposes a method aimed at establishing the smallest Markov model for the dependencies contained within the fault tree

  4. Electrically evoked compound action potentials artefact rejection by independent component analysis: procedure automation.

    Science.gov (United States)

    Akhoun, Idrick; McKay, Colette; El-Deredy, Wael

    2015-01-15

    Independent-components-analysis (ICA) successfully separated electrically-evoked compound action potentials (ECAPs) from the stimulation artefact and noise (ECAP-ICA, Akhoun et al., 2013). This paper shows how to automate the ECAP-ICA artefact cancellation process. Raw-ECAPs without artefact rejection were consecutively recorded for each stimulation condition from at least 8 intra-cochlear electrodes. Firstly, amplifier-saturated recordings were discarded, and the data from different stimulus conditions (different current-levels) were concatenated temporally. The key aspect of the automation procedure was the sequential deductive source categorisation after ICA was applied with a restriction to 4 sources. The stereotypical aspect of the 4 sources enables their automatic classification as two artefact components, a noise and the sought ECAP based on theoretical and empirical considerations. The automatic procedure was tested using 8 cochlear implant (CI) users and one to four stimulus electrodes. The artefact and noise sources were successively identified and discarded, leaving the ECAP as the remaining source. The automated ECAP-ICA procedure successfully extracted the correct ECAPs compared to standard clinical forward masking paradigm in 22 out of 26 cases. ECAP-ICA does not require extracting the ECAP from a combination of distinct buffers as it is the case with regular methods. It is an alternative that does not have the possible bias of traditional artefact rejections such as alternate-polarity or forward-masking paradigms. The ECAP-ICA procedure bears clinical relevance, for example as the artefact rejection sub-module of automated ECAP-threshold detection techniques, which are common features of CI clinical fitting software. Copyright © 2014. Published by Elsevier B.V.

  5. Comparing brain graphs in which nodes are regions of interest or independent components: A simulation study.

    Science.gov (United States)

    Yu, Qingbao; Du, Yuhui; Chen, Jiayu; He, Hao; Sui, Jing; Pearlson, Godfrey; Calhoun, Vince D

    2017-11-01

    A key challenge in building a brain graph using fMRI data is how to define the nodes. Spatial brain components estimated by independent components analysis (ICA) and regions of interest (ROIs) determined by brain atlas are two popular methods to define nodes in brain graphs. It is difficult to evaluate which method is better in real fMRI data. Here we perform a simulation study and evaluate the accuracies of a few graph metrics in graphs with nodes of ICA components, ROIs, or modified ROIs in four simulation scenarios. Graph measures with ICA nodes are more accurate than graphs with ROI nodes in all cases. Graph measures with modified ROI nodes are modulated by artifacts. The correlations of graph metrics across subjects between graphs with ICA nodes and ground truth are higher than the correlations between graphs with ROI nodes and ground truth in scenarios with large overlapped spatial sources. Moreover, moving the location of ROIs would largely decrease the correlations in all scenarios. Evaluating graphs with different nodes is promising in simulated data rather than real data because different scenarios can be simulated and measures of different graphs can be compared with a known ground truth. Since ROIs defined using brain atlas may not correspond well to real functional boundaries, overall findings of this work suggest that it is more appropriate to define nodes using data-driven ICA than ROI approaches in real fMRI data. Copyright © 2017 Elsevier B.V. All rights reserved.

  6. Biological efficiency of component crops in different geometrical patterns of wheat-linseed intercropping

    International Nuclear Information System (INIS)

    Nazir, M. S.; Saeed, M.; Khan, I.; Ghaffar, A.

    2005-01-01

    An experiment to determine the biological efficiency and agro-economic relationships of component crops in wheat-linseed intercropping under different geometrical patterns, was conducted on sandy-clay loam soil at Faisalabad (Pakistan). Wheat was sown in 100-cm spaced 4, 6, 8, and 10 row strips and was intercropped with three rows of linseed. The component crops were also grown alone in 30-cm spaced single row. Wheat grain yield was reduced by 25.6%, 19.2%, 14.7% and 11.9% by intercropping linseed in wheat grown in the pattern of 4, 6 and 10-row strips, respectively. However, at the cost of this much reduction in wheat yield, linseed gave an additional yields of 516, 412, 335 kg/ha in the respective patterns which resulted in yield advantages of 41%, 31%, 29% and 27%, respectively over sole cropping of wheat. Intercropping also generated higher net monetary gain/ha (Rs. 12378-12826) than monocropped wheat (Rs. 11034) and linseed (Rs. 4249). (author)

  7. Multi-level and Multi-component Bitmap Encoding for Efficient Search Operations

    Directory of Open Access Journals (Sweden)

    Madhu BHAN, Department of Computer Applications

    2012-12-01

    Full Text Available The growing interest in data warehousing for decision makers is becoming more and more crucial to make faster and efficient decisions. On-line decision needs short response times. Many indexing techniques have been created to achieve this goal in read only environments. Indexing technique that has attracted attention in multidimensional databases is Bitmap Indexing. The paper discusses the various existing bitmap indexing techniques along with their performance characteristics. The paper proposes two new bitmap indexing techniques in the class of multi-level and multi-component encoding schemes and prove that the two techniques have better space–time performance than some of the existing techniques used for range queries. We provide an analytical model for comparing the performance of our proposed encoding schemes with that of the existing ones.

  8. Fetal source extraction from magnetocardiographic recordings by dependent component analysis

    Energy Technology Data Exchange (ETDEWEB)

    Araujo, Draulio B de [Department of Physics and Mathematics, FFCLRP, University of Sao Paulo, Ribeirao Preto, SP (Brazil); Barros, Allan Kardec [Department of Electrical Engineering, Federal University of Maranhao, Sao Luis, Maranhao (Brazil); Estombelo-Montesco, Carlos [Department of Physics and Mathematics, FFCLRP, University of Sao Paulo, Ribeirao Preto, SP (Brazil); Zhao, Hui [Department of Medical Physics, University of Wisconsin, Madison, WI (United States); Filho, A C Roque da Silva [Department of Physics and Mathematics, FFCLRP, University of Sao Paulo, Ribeirao Preto, SP (Brazil); Baffa, Oswaldo [Department of Physics and Mathematics, FFCLRP, University of Sao Paulo, Ribeirao Preto, SP (Brazil); Wakai, Ronald [Department of Medical Physics, University of Wisconsin, Madison, WI (United States); Ohnishi, Noboru [Department of Information Engineering, Nagoya University (Japan)

    2005-10-07

    Fetal magnetocardiography (fMCG) has been extensively reported in the literature as a non-invasive, prenatal technique that can be used to monitor various functions of the fetal heart. However, fMCG signals often have low signal-to-noise ratio (SNR) and are contaminated by strong interference from the mother's magnetocardiogram signal. A promising, efficient tool for extracting signals, even under low SNR conditions, is blind source separation (BSS), or independent component analysis (ICA). Herein we propose an algorithm based on a variation of ICA, where the signal of interest is extracted using a time delay obtained from an autocorrelation analysis. We model the system using autoregression, and identify the signal component of interest from the poles of the autocorrelation function. We show that the method is effective in removing the maternal signal, and is computationally efficient. We also compare our results to more established ICA methods, such as FastICA.

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

    Directory of Open Access Journals (Sweden)

    Dong-Sup Lee

    2015-01-01

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

  10. Performance comparison of six independent components analysis algorithms for fetal signal extraction from real fMCG data

    International Nuclear Information System (INIS)

    Hild, Kenneth E; Alleva, Giovanna; Nagarajan, Srikantan; Comani, Silvia

    2007-01-01

    In this study we compare the performance of six independent components analysis (ICA) algorithms on 16 real fetal magnetocardiographic (fMCG) datasets for the application of extracting the fetal cardiac signal. We also compare the extraction results for real data with the results previously obtained for synthetic data. The six ICA algorithms are FastICA, CubICA, JADE, Infomax, MRMI-SIG and TDSEP. The results obtained using real fMCG data indicate that the FastICA method consistently outperforms the others in regard to separation quality and that the performance of an ICA method that uses temporal information suffers in the presence of noise. These two results confirm the previous results obtained using synthetic fMCG data. There were also two notable differences between the studies based on real and synthetic data. The differences are that all six ICA algorithms are independent of gestational age and sensor dimensionality for synthetic data, but depend on gestational age and sensor dimensionality for real data. It is possible to explain these differences by assuming that the number of point sources needed to completely explain the data is larger than the dimensionality used in the ICA extraction

  11. Toxin-independent virulence of Bacillus anthracis in rabbits.

    Directory of Open Access Journals (Sweden)

    Haim Levy

    Full Text Available The accepted paradigm states that anthrax is both an invasive and toxinogenic disease and that the toxins play a major role in pathogenicity. In the guinea pig (GP model we have previously shown that deletion of all three toxin components results in a relatively moderate attenuation in virulence, indicating that B. anthracis possesses an additional toxin-independent virulence mechanism. To characterize this toxin-independent mechanism in anthrax disease, we developed a new rabbit model by intravenous injection (IV of B. anthracis encapsulated vegetative cells, artificially creating bacteremia. Using this model we were able to demonstrate that also in rabbits, B. anthracis mutants lacking the toxins are capable of killing the host within 24 hours. This virulent trait depends on the activity of AtxA in the presence of pXO2, as, in the absence of the toxin genes, deletion of either component abolishes virulence. Furthermore, this IV virulence depends mainly on AtxA rather than the whole pXO1. A similar pattern was shown in the GP model using subcutaneous (SC administration of spores of the mutant strains, demonstrating the generality of the phenomenon. The virulent strains showed higher bacteremia levels and more efficient tissue dissemination; however our interpretation is that tissue dissemination per se is not the main determinant of virulence whose exact nature requires further elucidation.

  12. Quick assessment of binary distillation efficiency using a heat engine perspective

    International Nuclear Information System (INIS)

    Blahušiak, M.; Kiss, A.A.; Kersten, S.R.A.; Schuur, B.

    2016-01-01

    With emphasis on close boiling, (near-)ideal VLE mixtures, this paper links the efficiency of distillation to the binary feed composition and thermal properties of the compounds. The proposed approach, treating the process as a heat engine, allows to directly quantify distillation performance (in terms of energy intensity & efficiency) based on the components boiling points and feed composition. In addition, this approach reviews and formulates simple, approximate and essentially non-iterative calculation procedures to quickly estimate the energy efficiency of distillation. These estimations may be applied to identify opportunities to save significant amounts of energy. The results show that the reboiler duty for low relative volatility is relatively independent of the heat of vaporization and feed composition, while being reciprocally proportional to the Carnot efficiency of the distillation column. The internal efficiency for distillation of mixtures with low relative volatility has a maximum of about 70% for a symmetrical feed (equimolar ratio) and decreases to zero for unsymmetrical feed compositions approaching infinite dilution. With increasing relative volatility, the maximum efficiency is preserved, but the locus shifts towards lower light component fractions. At very high relative volatility, the internal efficiency increases with decreasing concentration of light component, as typical for evaporators. - Highlights: • A heat engine perspective was applied to estimate binary distillation efficiency. • The method was derived from first principles. • Validation on industrial cases showed the strength of the method.

  13. Automatic flow analysis of digital subtraction angiography using independent component analysis in patients with carotid stenosis.

    Directory of Open Access Journals (Sweden)

    Han-Jui Lee

    Full Text Available Current time-density curve analysis of digital subtraction angiography (DSA provides intravascular flow information but requires manual vasculature selection. We developed an angiographic marker that represents cerebral perfusion by using automatic independent component analysis.We retrospectively analyzed the data of 44 patients with unilateral carotid stenosis higher than 70% according to North American Symptomatic Carotid Endarterectomy Trial criteria. For all patients, magnetic resonance perfusion (MRP was performed one day before DSA. Fixed contrast injection protocols and DSA acquisition parameters were used before stenting. The cerebral circulation time (CCT was defined as the difference in the time to peak between the parietal vein and cavernous internal carotid artery in a lateral angiogram. Both anterior-posterior and lateral DSA views were processed using independent component analysis, and the capillary angiogram was extracted automatically. The full width at half maximum of the time-density curve in the capillary phase in the anterior-posterior and lateral DSA views was defined as the angiographic mean transient time (aMTT; i.e., aMTTAP and aMTTLat. The correlations between the degree of stenosis, CCT, aMTTAP and aMTTLat, and MRP parameters were evaluated.The degree of stenosis showed no correlation with CCT, aMTTAP, aMTTLat, or any MRP parameter. CCT showed a strong correlation with aMTTAP (r = 0.67 and aMTTLat (r = 0.72. Among the MRP parameters, CCT showed only a moderate correlation with MTT (r = 0.67 and Tmax (r = 0.40. aMTTAP showed a moderate correlation with Tmax (r = 0.42 and a strong correlation with MTT (r = 0.77. aMTTLat also showed similar correlations with Tmax (r = 0.59 and MTT (r = 0.73.Apart from vascular anatomy, aMTT estimates brain parenchyma hemodynamics from DSA and is concordant with MRP. This process is completely automatic and provides immediate measurement of quantitative peritherapeutic brain parenchyma

  14. A Parcellation Based Nonparametric Algorithm for Independent Component Analysis with Application to fMRI Data

    Directory of Open Access Journals (Sweden)

    Shanshan eLi

    2016-01-01

    Full Text Available Independent Component analysis (ICA is a widely used technique for separating signals that have been mixed together. In this manuscript, we propose a novel ICA algorithm using density estimation and maximum likelihood, where the densities of the signals are estimated via p-spline based histogram smoothing and the mixing matrix is simultaneously estimated using an optimization algorithm. The algorithm is exceedingly simple, easy to implement and blind to the underlying distributions of the source signals. To relax the identically distributed assumption in the density function, a modified algorithm is proposed to allow for different density functions on different regions. The performance of the proposed algorithm is evaluated in different simulation settings. For illustration, the algorithm is applied to a research investigation with a large collection of resting state fMRI datasets. The results show that the algorithm successfully recovers the established brain networks.

  15. Stimulus-related independent component and voxel-wise analysis of human brain activity during free viewing of a feature film.

    Science.gov (United States)

    Lahnakoski, Juha M; Salmi, Juha; Jääskeläinen, Iiro P; Lampinen, Jouko; Glerean, Enrico; Tikka, Pia; Sams, Mikko

    2012-01-01

    Understanding how the brain processes stimuli in a rich natural environment is a fundamental goal of neuroscience. Here, we showed a feature film to 10 healthy volunteers during functional magnetic resonance imaging (fMRI) of hemodynamic brain activity. We then annotated auditory and visual features of the motion picture to inform analysis of the hemodynamic data. The annotations were fitted to both voxel-wise data and brain network time courses extracted by independent component analysis (ICA). Auditory annotations correlated with two independent components (IC) disclosing two functional networks, one responding to variety of auditory stimulation and another responding preferentially to speech but parts of the network also responding to non-verbal communication. Visual feature annotations correlated with four ICs delineating visual areas according to their sensitivity to different visual stimulus features. In comparison, a separate voxel-wise general linear model based analysis disclosed brain areas preferentially responding to sound energy, speech, music, visual contrast edges, body motion and hand motion which largely overlapped the results revealed by ICA. Differences between the results of IC- and voxel-based analyses demonstrate that thorough analysis of voxel time courses is important for understanding the activity of specific sub-areas of the functional networks, while ICA is a valuable tool for revealing novel information about functional connectivity which need not be explained by the predefined model. Our results encourage the use of naturalistic stimuli and tasks in cognitive neuroimaging to study how the brain processes stimuli in rich natural environments.

  16. Independent EEG sources are dipolar.

    Directory of Open Access Journals (Sweden)

    Arnaud Delorme

    Full Text Available Independent component analysis (ICA and blind source separation (BSS methods are increasingly used to separate individual brain and non-brain source signals mixed by volume conduction in electroencephalographic (EEG and other electrophysiological recordings. We compared results of decomposing thirteen 71-channel human scalp EEG datasets by 22 ICA and BSS algorithms, assessing the pairwise mutual information (PMI in scalp channel pairs, the remaining PMI in component pairs, the overall mutual information reduction (MIR effected by each decomposition, and decomposition 'dipolarity' defined as the number of component scalp maps matching the projection of a single equivalent dipole with less than a given residual variance. The least well-performing algorithm was principal component analysis (PCA; best performing were AMICA and other likelihood/mutual information based ICA methods. Though these and other commonly-used decomposition methods returned many similar components, across 18 ICA/BSS algorithms mean dipolarity varied linearly with both MIR and with PMI remaining between the resulting component time courses, a result compatible with an interpretation of many maximally independent EEG components as being volume-conducted projections of partially-synchronous local cortical field activity within single compact cortical domains. To encourage further method comparisons, the data and software used to prepare the results have been made available (http://sccn.ucsd.edu/wiki/BSSComparison.

  17. Effect of the ODS-4 surfactant and its components on the efficiency of decontamination of solid surfaces

    International Nuclear Information System (INIS)

    Dvorak, J.; Duris, P.

    1994-01-01

    The efficiency was examined of the desorption of carrier-free traces of 147 Pm adsorbed from an acid aqueous solution at pH 2.6 in static conditions on a paint routinely applied to military facilities. The desorption was performed by using the ODS-4 decontamination and deactivation mixture and its components at various concentrations. It is concluded that the surfactant is not very well suited to the decontamination of solid surfaces contaminated with radionuclides which form the water-soluble component of radioactive contamination (in dependence on pH). This is due to the composition and the associated high alkalinity of the ODS-4 agent, which, however, is necessary if detoxication of toxic agents is required. In practice, however, the efficiency of decontamination will be appreciably higher because the military decontamination procedures involve dynamic (mechanical) treatment of the surfaces using brushes with flowing liquid, pressure application of the surfactant and water, moving baths, etc. (P.A.). 7 tabs., 2 figs., 10 refs

  18. Extraction of fast neuronal changes from multichannel functional near-infrared spectroscopy signals using independent component analysis

    Science.gov (United States)

    Morren, Geert; Wolf, Martin; Lemmerling, Philippe; Wolf, Ursula; Choi, Jee H.; Gratton, Enrico; De Lathauwer, Lieven; Van Huffel, Sabine

    2002-06-01

    Fast changes in the range of milliseconds in the optical properties of cerebral tissue, which are associated with brain activity, can be detected using non-invasive near-infrared spectroscopy (NIRS). These changes in light scattering are due to an alteration in the refractive index at neuronal membranes. The aim of this study was to develop highly sensitive data analysis algorithms to detect this fast signal, which is small compared to other physiological signals. A frequency-domain tissue oximeter, whose laser diodes were modulated at 110MHz was used. The amplitude, mean intensity and phase of the modulated optical signal was measured at 96Hz sample rate. The probe consisting of 4 crossed source detector pairs was placed above the motor cortex, contralateral to the hand performing a tapping exercise consisting of alternating rest- and tapping periods of 20s each. The tapping frequency, which was set to 3.55Hz or 2.5 times the heart rate of the subject to avoid the influence of harmonics on the signal, could not be observed in any of the individual signals measured by the detectors. An adaptive filter was used to remove the arterial pulsatility from the optical signals. Independent Component Analysis allowed to separate signal components in which the tapping frequency was clearly visible.

  19. Determination of arterial input function in dynamic susceptibility contrast MRI using group independent component analysis technique

    International Nuclear Information System (INIS)

    Chen, S.; Liu, H.-L.; Yang Yihong; Hsu, Y.-Y.; Chuang, K.-S.

    2006-01-01

    Quantification of cerebral blood flow (CBF) with dynamic susceptibility contrast (DSC) magnetic resonance imaging (MRI) requires the determination of the arterial input function (AIF). The segmentation of surrounding tissue by manual selection is error-prone due to the partial volume artifacts. Independent component analysis (ICA) has the advantage in automatically decomposing the signals into interpretable components. Recently group ICA technique has been applied to fMRI study and showed reduced variance caused by motion artifact and noise. In this work, we investigated the feasibility and efficacy of the use of group ICA technique to extract the AIF. Both simulated and in vivo data were analyzed in this study. The simulation data of eight phantoms were generated using randomized lesion locations and time activity curves. The clinical data were obtained from spin-echo EPI MR scans performed in seven normal subjects. Group ICA technique was applied to analyze data through concatenating across seven subjects. The AIFs were calculated from the weighted average of the signals in the region selected by ICA. Preliminary results of this study showed that group ICA technique could not extract accurate AIF information from regions around the vessel. The mismatched location of vessels within the group reduced the benefits of group study

  20. Robust efficient video fingerprinting

    Science.gov (United States)

    Puri, Manika; Lubin, Jeffrey

    2009-02-01

    We have developed a video fingerprinting system with robustness and efficiency as the primary and secondary design criteria. In extensive testing, the system has shown robustness to cropping, letter-boxing, sub-titling, blur, drastic compression, frame rate changes, size changes and color changes, as well as to the geometric distortions often associated with camcorder capture in cinema settings. Efficiency is afforded by a novel two-stage detection process in which a fast matching process first computes a number of likely candidates, which are then passed to a second slower process that computes the overall best match with minimal false alarm probability. One key component of the algorithm is a maximally stable volume computation - a three-dimensional generalization of maximally stable extremal regions - that provides a content-centric coordinate system for subsequent hash function computation, independent of any affine transformation or extensive cropping. Other key features include an efficient bin-based polling strategy for initial candidate selection, and a final SIFT feature-based computation for final verification. We describe the algorithm and its performance, and then discuss additional modifications that can provide further improvement to efficiency and accuracy.

  1. Memory Efficient PCA Methods for Large Group ICA.

    Science.gov (United States)

    Rachakonda, Srinivas; Silva, Rogers F; Liu, Jingyu; Calhoun, Vince D

    2016-01-01

    Principal component analysis (PCA) is widely used for data reduction in group independent component analysis (ICA) of fMRI data. Commonly, group-level PCA of temporally concatenated datasets is computed prior to ICA of the group principal components. This work focuses on reducing very high dimensional temporally concatenated datasets into its group PCA space. Existing randomized PCA methods can determine the PCA subspace with minimal memory requirements and, thus, are ideal for solving large PCA problems. Since the number of dataloads is not typically optimized, we extend one of these methods to compute PCA of very large datasets with a minimal number of dataloads. This method is coined multi power iteration (MPOWIT). The key idea behind MPOWIT is to estimate a subspace larger than the desired one, while checking for convergence of only the smaller subset of interest. The number of iterations is reduced considerably (as well as the number of dataloads), accelerating convergence without loss of accuracy. More importantly, in the proposed implementation of MPOWIT, the memory required for successful recovery of the group principal components becomes independent of the number of subjects analyzed. Highly efficient subsampled eigenvalue decomposition techniques are also introduced, furnishing excellent PCA subspace approximations that can be used for intelligent initialization of randomized methods such as MPOWIT. Together, these developments enable efficient estimation of accurate principal components, as we illustrate by solving a 1600-subject group-level PCA of fMRI with standard acquisition parameters, on a regular desktop computer with only 4 GB RAM, in just a few hours. MPOWIT is also highly scalable and could realistically solve group-level PCA of fMRI on thousands of subjects, or more, using standard hardware, limited only by time, not memory. Also, the MPOWIT algorithm is highly parallelizable, which would enable fast, distributed implementations ideal for big

  2. Memory efficient PCA methods for large group ICA

    Directory of Open Access Journals (Sweden)

    Srinivas eRachakonda

    2016-02-01

    Full Text Available Principal component analysis (PCA is widely used for data reduction in group independent component analysis (ICA of fMRI data. Commonly, group-level PCA of temporally concatenated datasets is computed prior to ICA of the group principal components. This work focuses on reducing very high dimensional temporally concatenated datasets into its group PCA space. Existing randomized PCA methods can determine the PCA subspace with minimal memory requirements and, thus, are ideal for solving large PCA problems. Since the number of dataloads is not typically optimized, we extend one of these methods to compute PCA of very large datasets with a minimal number of dataloads. This method is coined multi power iteration (MPOWIT. The key idea behind MPOWIT is to estimate a subspace larger than the desired one, while checking for convergence of only the smaller subset of interest. The number of iterations is reduced considerably (as well as the number of dataloads, accelerating convergence without loss of accuracy. More importantly, in the proposed implementation of MPOWIT, the memory required for successful recovery of the group principal components becomes independent of the number of subjects analyzed. Highly efficient subsampled eigenvalue decomposition techniques are also introduced, furnishing excellent PCA subspace approximations that can be used for intelligent initialization of randomized methods such as MPOWIT. Together, these developments enable efficient estimation of accurate principal components, as we illustrate by solving a 1600-subject group-level PCA of fMRI with standard acquisition parameters, on a regular desktop computer with only 4GB RAM, in just a few hours. MPOWIT is also highly scalable and could realistically solve group-level PCA of fMRI on thousands of subjects, or more, using standard hardware, limited only by time, not memory. Also, the MPOWIT algorithm is highly parallelizable, which would enable fast, distributed implementations

  3. Improved separability of dipole sources by tripolar versus conventional disk electrodes: a modeling study using independent component analysis.

    Science.gov (United States)

    Cao, H; Besio, W; Jones, S; Medvedev, A

    2009-01-01

    Tripolar electrodes have been shown to have less mutual information and higher spatial resolution than disc electrodes. In this work, a four-layer anisotropic concentric spherical head computer model was programmed, then four configurations of time-varying dipole signals were used to generate the scalp surface signals that would be obtained with tripolar and disc electrodes, and four important EEG artifacts were tested: eye blinking, cheek movements, jaw movements, and talking. Finally, a fast fixed-point algorithm was used for signal independent component analysis (ICA). The results show that signals from tripolar electrodes generated better ICA separation results than from disc electrodes for EEG signals with these four types of artifacts.

  4. Key issues in decomposing fMRI during naturalistic and continuous music experience with independent component analysis.

    Science.gov (United States)

    Cong, Fengyu; Puoliväli, Tuomas; Alluri, Vinoo; Sipola, Tuomo; Burunat, Iballa; Toiviainen, Petri; Nandi, Asoke K; Brattico, Elvira; Ristaniemi, Tapani

    2014-02-15

    Independent component analysis (ICA) has been often used to decompose fMRI data mostly for the resting-state, block and event-related designs due to its outstanding advantage. For fMRI data during free-listening experiences, only a few exploratory studies applied ICA. For processing the fMRI data elicited by 512-s modern tango, a FFT based band-pass filter was used to further pre-process the fMRI data to remove sources of no interest and noise. Then, a fast model order selection method was applied to estimate the number of sources. Next, both individual ICA and group ICA were performed. Subsequently, ICA components whose temporal courses were significantly correlated with musical features were selected. Finally, for individual ICA, common components across majority of participants were found by diffusion map and spectral clustering. The extracted spatial maps (by the new ICA approach) common across most participants evidenced slightly right-lateralized activity within and surrounding the auditory cortices. Meanwhile, they were found associated with the musical features. Compared with the conventional ICA approach, more participants were found to have the common spatial maps extracted by the new ICA approach. Conventional model order selection methods underestimated the true number of sources in the conventionally pre-processed fMRI data for the individual ICA. Pre-processing the fMRI data by using a reasonable band-pass digital filter can greatly benefit the following model order selection and ICA with fMRI data by naturalistic paradigms. Diffusion map and spectral clustering are straightforward tools to find common ICA spatial maps. Copyright © 2013 Elsevier B.V. All rights reserved.

  5. A multi-level maintenance policy for a multi-component and multifailure mode system with two independent failure modes

    International Nuclear Information System (INIS)

    Zhu, Wenjin; Fouladirad, Mitra; Bérenguer, Christophe

    2016-01-01

    This paper studies the maintenance modelling of a multi-component system with two independent failure modes with imperfect prediction signal in the context of a system of systems. Each individual system consists of multiple series components and the failure modes of all the components are divided into two classes due to their consequences: hard failure and soft failure, where the former causes system failure while the later results in inferior performance (production reduction) of system. Besides, the system is monitored and can be alerted by imperfect prediction signal before hard failure. Based on an illustration example of offshore wind farm, in this paper three maintenance strategies are considered: periodic routine, reactive and opportunistic maintenance. The periodic routine maintenance is scheduled at fixed period for each individual system in the perspective of system of systems. Between two successive routine maintenances, the reactive maintenance is instructed by the imperfect prediction signal according to two criterion proposed in this study for the system components. Due to the high setup cost and practical restraints of implementing maintenance activities, both routine and reactive maintenance can create the opportunities of maintenance for the other components of an individual system. The life cycle of the system and the cost of the proposed maintenance policies are analytically derived. Restrained by the complexity from both the system failure modelling and maintenance strategies, the performances and application scope of the proposed maintenance model are evaluated by numerical simulations. - Highlights: • We study the life behavior of a complex system with two failure modes. • We consider the imperfect prediction signal of potential failure by monitoring. • We propose an integrated maintenance policy with three levels based on wind turbine. • We derive the mathematical cost formulations for the proposed maintenance policy.

  6. Cost efficiency of the non-associative flow rule simulation of an industrial component

    Science.gov (United States)

    Galdos, Lander; de Argandoña, Eneko Saenz; Mendiguren, Joseba

    2017-10-01

    In the last decade, metal forming industry is becoming more and more competitive. In this context, the FEM modeling has become a primary tool of information for the component and process design. Numerous researchers have been focused on improving the accuracy of the material models implemented on the FEM in order to improve the efficiency of the simulations. Aimed at increasing the efficiency of the anisotropic behavior modelling, in the last years the use of non-associative flow rule models (NAFR) has been presented as an alternative to the classic associative flow rule models (AFR). In this work, the cost efficiency of the used flow rule model has been numerically analyzed by simulating an industrial drawing operation with two different models of the same degree of flexibility: one AFR model and one NAFR model. From the present study, it has been concluded that the flow rule has a negligible influence on the final drawing prediction; this is mainly driven by the model parameter identification procedure. Even though the NAFR formulation is complex when compared to the AFR, the present study shows that the total simulation time while using explicit FE solvers has been reduced without loss of accuracy. Furthermore, NAFR formulations have an advantage over AFR formulations in parameter identification because the formulation decouples the yield stress and the Lankford coefficients.

  7. Independent component analysis of normal and abnormal rhythm in twin pregnancies

    International Nuclear Information System (INIS)

    Mensah-Brown, Nana Aba; Lutter, William J; Wakai, Ronald T; Comani, Silvia; Strasburger, Janette F

    2011-01-01

    We investigated the utility of ICA for evaluation of fetal rhythm in five uncomplicated twin pregnancies and in five twin pregnancies complicated by fetal arrhythmia. Using objective and subjective criteria, we sought to determine how the signal-to-noise ratio, signal fidelity and interference rejection are affected when synthesizing the fetal signal using all the signal-containing ICA components (rank-p ICA) versus using the single dominant component (rank-1 ICA). The signal of each fetus was most commonly distributed over 1 or 2 ICA components, as previously observed in studies of singleton pregnancies; however, in 8 of 26 (31%) cases the signal of each fetus was distributed over 3, 4 or even 5 ICA components. Rank-1 ICA provided the highest SNR and interference rejection, but at the cost of reduced signal fidelity. Our results corroborate that in twin pregnancies, including twin pregnancies complicated by fetal arrhythmia, rank-1 ICA is very effective in isolating the QRS complexes of each fetus; however, it has some limitations when used for fetal rhythm evaluation due to signal distortion. Occasionally, rank-1 ICA completely separates the P-wave and the T-wave from the QRS complex, thus requiring the mixing of several ICA components to achieve acceptable signal fidelity

  8. Stimulus-Related Independent Component and Voxel-Wise Analysis of Human Brain Activity during Free Viewing of a Feature Film

    Science.gov (United States)

    Lahnakoski, Juha M.; Salmi, Juha; Jääskeläinen, Iiro P.; Lampinen, Jouko; Glerean, Enrico; Tikka, Pia; Sams, Mikko

    2012-01-01

    Understanding how the brain processes stimuli in a rich natural environment is a fundamental goal of neuroscience. Here, we showed a feature film to 10 healthy volunteers during functional magnetic resonance imaging (fMRI) of hemodynamic brain activity. We then annotated auditory and visual features of the motion picture to inform analysis of the hemodynamic data. The annotations were fitted to both voxel-wise data and brain network time courses extracted by independent component analysis (ICA). Auditory annotations correlated with two independent components (IC) disclosing two functional networks, one responding to variety of auditory stimulation and another responding preferentially to speech but parts of the network also responding to non-verbal communication. Visual feature annotations correlated with four ICs delineating visual areas according to their sensitivity to different visual stimulus features. In comparison, a separate voxel-wise general linear model based analysis disclosed brain areas preferentially responding to sound energy, speech, music, visual contrast edges, body motion and hand motion which largely overlapped the results revealed by ICA. Differences between the results of IC- and voxel-based analyses demonstrate that thorough analysis of voxel time courses is important for understanding the activity of specific sub-areas of the functional networks, while ICA is a valuable tool for revealing novel information about functional connectivity which need not be explained by the predefined model. Our results encourage the use of naturalistic stimuli and tasks in cognitive neuroimaging to study how the brain processes stimuli in rich natural environments. PMID:22496909

  9. Stimulus-related independent component and voxel-wise analysis of human brain activity during free viewing of a feature film.

    Directory of Open Access Journals (Sweden)

    Juha M Lahnakoski

    Full Text Available Understanding how the brain processes stimuli in a rich natural environment is a fundamental goal of neuroscience. Here, we showed a feature film to 10 healthy volunteers during functional magnetic resonance imaging (fMRI of hemodynamic brain activity. We then annotated auditory and visual features of the motion picture to inform analysis of the hemodynamic data. The annotations were fitted to both voxel-wise data and brain network time courses extracted by independent component analysis (ICA. Auditory annotations correlated with two independent components (IC disclosing two functional networks, one responding to variety of auditory stimulation and another responding preferentially to speech but parts of the network also responding to non-verbal communication. Visual feature annotations correlated with four ICs delineating visual areas according to their sensitivity to different visual stimulus features. In comparison, a separate voxel-wise general linear model based analysis disclosed brain areas preferentially responding to sound energy, speech, music, visual contrast edges, body motion and hand motion which largely overlapped the results revealed by ICA. Differences between the results of IC- and voxel-based analyses demonstrate that thorough analysis of voxel time courses is important for understanding the activity of specific sub-areas of the functional networks, while ICA is a valuable tool for revealing novel information about functional connectivity which need not be explained by the predefined model. Our results encourage the use of naturalistic stimuli and tasks in cognitive neuroimaging to study how the brain processes stimuli in rich natural environments.

  10. Interception efficiency of CVM-based lightning protection systems for buildings and the fractional Poisson model

    OpenAIRE

    Haller, Harold S.; Woyczynski, Wojbor A.

    2016-01-01

    The purpose of this paper is to resolve a question regarding efficiency of a lightning protection system (LPS) for buildings based on the collection volume method (CVM) . The paper has two components. The first, following suggestions of other authors [Abidin and Ibrahim 2004], takes advantage of count data from installed devices, and independent installation-site inspections to develop our statistical analysis. The second component investigates the validity of the underlying theory by introdu...

  11. EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis.

    Science.gov (United States)

    Delorme, Arnaud; Makeig, Scott

    2004-03-15

    We have developed a toolbox and graphic user interface, EEGLAB, running under the crossplatform MATLAB environment (The Mathworks, Inc.) for processing collections of single-trial and/or averaged EEG data of any number of channels. Available functions include EEG data, channel and event information importing, data visualization (scrolling, scalp map and dipole model plotting, plus multi-trial ERP-image plots), preprocessing (including artifact rejection, filtering, epoch selection, and averaging), independent component analysis (ICA) and time/frequency decompositions including channel and component cross-coherence supported by bootstrap statistical methods based on data resampling. EEGLAB functions are organized into three layers. Top-layer functions allow users to interact with the data through the graphic interface without needing to use MATLAB syntax. Menu options allow users to tune the behavior of EEGLAB to available memory. Middle-layer functions allow users to customize data processing using command history and interactive 'pop' functions. Experienced MATLAB users can use EEGLAB data structures and stand-alone signal processing functions to write custom and/or batch analysis scripts. Extensive function help and tutorial information are included. A 'plug-in' facility allows easy incorporation of new EEG modules into the main menu. EEGLAB is freely available (http://www.sccn.ucsd.edu/eeglab/) under the GNU public license for noncommercial use and open source development, together with sample data, user tutorial and extensive documentation.

  12. Performance comparison of independent component analysis algorithms for fetal cardiac signal reconstruction: a study on synthetic fMCG data

    International Nuclear Information System (INIS)

    Mantini, D; II, K E Hild; Alleva, G; Comani, S

    2006-01-01

    Independent component analysis (ICA) algorithms have been successfully used for signal extraction tasks in the field of biomedical signal processing. We studied the performances of six algorithms (FastICA, CubICA, JADE, Infomax, TDSEP and MRMI-SIG) for fetal magnetocardiography (fMCG). Synthetic datasets were used to check the quality of the separated components against the original traces. Real fMCG recordings were simulated with linear combinations of typical fMCG source signals: maternal and fetal cardiac activity, ambient noise, maternal respiration, sensor spikes and thermal noise. Clusters of different dimensions (19, 36 and 55 sensors) were prepared to represent different MCG systems. Two types of signal-to-interference ratios (SIR) were measured. The first involves averaging over all estimated components and the second is based solely on the fetal trace. The computation time to reach a minimum of 20 dB SIR was measured for all six algorithms. No significant dependency on gestational age or cluster dimension was observed. Infomax performed poorly when a sub-Gaussian source was included; TDSEP and MRMI-SIG were sensitive to additive noise, whereas FastICA, CubICA and JADE showed the best performances. Of all six methods considered, FastICA had the best overall performance in terms of both separation quality and computation times

  13. Development of quantification methods for the myocardial blood flow using ensemble independent component analysis for dynamic H215O PET

    International Nuclear Information System (INIS)

    Lee, Byeong Il; Lee, Jae Sung; Lee, Dong Soo; Kang, Won Jun; Lee, Jong Jin; Kim, Soo Jin; Chung, June Key; Lee, Myung Chul; Choi, Seung Jin

    2004-01-01

    Factor analysis and independent component analysis (lCA) has been used for handling dynamic image sequences. Theoretical advantages of a newly suggested ICA method, ensemble ICA, leaded us to consider applying this method to the analysis of dynamic myocardial H 2 15 O PET data. In this study, we quantified patients, blood flow using the ensemble ICA method. Twenty subjects underwent H 2 15 O PET scans using ECAT EXACT 47 scanner and myocardial perfusion SPECT using Vertex scanner. After transmission scanning, dynamic emission scans were initiated simultaneously with the injection of 555∼740 MBq H 2 15 O. Hidden independent components can be extracted from the observed mixed data (PET image) by means of ICA algorithms. Ensemble learning is a variational Bayesian method that provides an analytical approximation to the parameter posterior using a tractable distribution. Variational approximation forms a lower bound on the ensemble likelihood and the maximization of the lower bound is achieved through minimizing the Kullback-Leibler divergence between the true posterior and the variational posterior. In this study, posterior pdf was approximated by a rectified Gaussian distribution to incorporate non-negativity constraint, which is suitable to dynamic images in nuclear medicine. Blood flow was measured in 9 regions - apex, four areas in mid wall, and four areas in base wall. Myocardial perfusion SPECT score and angiography results were compared with the regional blood flow. Major cardiac components were separated successfully by the ensemble ICA method and blood flow could be estimated in 15 among 20 patients. Mean myocardial blood flow was 1.2±0.40 ml/min/g in rest, 1.85±1.12 ml/min/g in stress state. Blood flow values obtained by an operator in two different occasion were highly correlated (r=0.99). In myocardium component image, the image contrast between left ventricle and myocardium was 1:2.7 in average. Perfusion reserve was significantly different between

  14. Robust spinal cord resting-state fMRI using independent component analysis-based nuisance regression noise reduction.

    Science.gov (United States)

    Hu, Yong; Jin, Richu; Li, Guangsheng; Luk, Keith Dk; Wu, Ed X

    2018-04-16

    Physiological noise reduction plays a critical role in spinal cord (SC) resting-state fMRI (rsfMRI). To reduce physiological noise and increase the robustness of SC rsfMRI by using an independent component analysis (ICA)-based nuisance regression (ICANR) method. Retrospective. Ten healthy subjects (female/male = 4/6, age = 27 ± 3 years, range 24-34 years). 3T/gradient-echo echo planar imaging (EPI). We used three alternative methods (no regression [Nil], conventional region of interest [ROI]-based noise reduction method without ICA [ROI-based], and correction of structured noise using spatial independent component analysis [CORSICA]) to compare with the performance of ICANR. Reduction of the influence of physiological noise on the SC and the reproducibility of rsfMRI analysis after noise reduction were examined. The correlation coefficient (CC) was calculated to assess the influence of physiological noise. Reproducibility was calculated by intraclass correlation (ICC). Results from different methods were compared by one-way analysis of variance (ANOVA) with post-hoc analysis. No significant difference in cerebrospinal fluid (CSF) pulsation influence or tissue motion influence were found (P = 0.223 in CSF, P = 0.2461 in tissue motion) in the ROI-based (CSF: 0.122 ± 0.020; tissue motion: 0.112 ± 0.015), and Nil (CSF: 0.134 ± 0.026; tissue motion: 0.124 ± 0.019). CORSICA showed a significantly stronger influence of CSF pulsation and tissue motion (CSF: 0.166 ± 0.045, P = 0.048; tissue motion: 0.160 ± 0.032, P = 0.048) than Nil. ICANR showed a significantly weaker influence of CSF pulsation and tissue motion (CSF: 0.076 ± 0.007, P = 0.0003; tissue motion: 0.081 ± 0.014, P = 0.0182) than Nil. The ICC values in the Nil, ROI-based, CORSICA, and ICANR were 0.669, 0.645, 0.561, and 0.766, respectively. ICANR more effectively reduced physiological noise from both tissue motion and CSF pulsation than three alternative methods. ICANR increases the robustness of SC rsf

  15. Temporal dynamics of sensorimotor integration in speech perception and production: Independent component analysis of EEG data

    Directory of Open Access Journals (Sweden)

    David eJenson

    2014-07-01

    Full Text Available Activity in premotor and sensorimotor cortices is found in speech production and some perception tasks. Yet, how sensorimotor integration supports these functions is unclear due to a lack of data examining the timing of activity from these regions. Beta (~20Hz and alpha (~10Hz spectral power within the EEG µ rhythm are considered indices of motor and somatosensory activity, respectively. In the current study, perception conditions required discrimination (same/different of syllables pairs (/ba/ and /da/ in quiet and noisy conditions. Production conditions required covert and overt syllable productions and overt word production. Independent component analysis was performed on EEG data obtained during these conditions to 1 identify clusters of µ components common to all conditions and 2 examine real-time event-related spectral perturbations (ERSP within alpha and beta bands. 17 and 15 out of 20 participants produced left and right µ-components, respectively, localized to precentral gyri. Discrimination conditions were characterized by significant (pFDR<.05 early alpha event-related synchronization (ERS prior to and during stimulus presentation and later alpha event-related desynchronization (ERD following stimulus offset. Beta ERD began early and gained strength across time. Differences were found between quiet and noisy discrimination conditions. Both overt syllable and word productions yielded similar alpha/beta ERD that began prior to production and was strongest during muscle activity. Findings during covert production were weaker than during overt production. One explanation for these findings is that µ-beta ERD indexes early predictive coding (e.g., internal modeling and/or overt and covert attentional / motor processes. µ-alpha ERS may index inhibitory input to the premotor cortex from sensory regions prior to and during discrimination, while µ-alpha ERD may index re-afferent sensory feedback during speech rehearsal and production.

  16. Towards Cognitive Component Analysis

    DEFF Research Database (Denmark)

    Hansen, Lars Kai; Ahrendt, Peter; Larsen, Jan

    2005-01-01

    Cognitive component analysis (COCA) is here defined as the process of unsupervised grouping of data such that the ensuing group structure is well-aligned with that resulting from human cognitive activity. We have earlier demonstrated that independent components analysis is relevant for representing...

  17. Performance comparison of machine learning algorithms and number of independent components used in fMRI decoding of belief vs. disbelief.

    Science.gov (United States)

    Douglas, P K; Harris, Sam; Yuille, Alan; Cohen, Mark S

    2011-05-15

    Machine learning (ML) has become a popular tool for mining functional neuroimaging data, and there are now hopes of performing such analyses efficiently in real-time. Towards this goal, we compared accuracy of six different ML algorithms applied to neuroimaging data of persons engaged in a bivariate task, asserting their belief or disbelief of a variety of propositional statements. We performed unsupervised dimension reduction and automated feature extraction using independent component (IC) analysis and extracted IC time courses. Optimization of classification hyperparameters across each classifier occurred prior to assessment. Maximum accuracy was achieved at 92% for Random Forest, followed by 91% for AdaBoost, 89% for Naïve Bayes, 87% for a J48 decision tree, 86% for K*, and 84% for support vector machine. For real-time decoding applications, finding a parsimonious subset of diagnostic ICs might be useful. We used a forward search technique to sequentially add ranked ICs to the feature subspace. For the current data set, we determined that approximately six ICs represented a meaningful basis set for classification. We then projected these six IC spatial maps forward onto a later scanning session within subject. We then applied the optimized ML algorithms to these new data instances, and found that classification accuracy results were reproducible. Additionally, we compared our classification method to our previously published general linear model results on this same data set. The highest ranked IC spatial maps show similarity to brain regions associated with contrasts for belief > disbelief, and disbelief < belief. Copyright © 2010 Elsevier Inc. All rights reserved.

  18. Techniques to extract physical modes in model-independent analysis of rings

    International Nuclear Information System (INIS)

    Wang, C.-X.

    2004-01-01

    A basic goal of Model-Independent Analysis is to extract the physical modes underlying the beam histories collected at a large number of beam position monitors so that beam dynamics and machine properties can be deduced independent of specific machine models. Here we discuss techniques to achieve this goal, especially the Principal Component Analysis and the Independent Component Analysis.

  19. Stealthy false data injection attacks using matrix recovery and independent component analysis in smart grid

    Science.gov (United States)

    JiWei, Tian; BuHong, Wang; FuTe, Shang; Shuaiqi, Liu

    2017-05-01

    Exact state estimation is vital important to maintain common operations of smart grids. Existing researches demonstrate that state estimation output could be compromised by malicious attacks. However, to construct the attack vectors, a usual presumption in most works is that the attacker has perfect information regarding the topology and so on even such information is difficult to acquire in practice. Recent research shows that Independent Component Analysis (ICA) can be used for inferring topology information which can be used to originate undetectable attacks and even to alter the price of electricity for the profits of attackers. However, we found that the above ICA-based blind attack tactics is merely feasible in the environment with Gaussian noises. If there are outliers (device malfunction and communication errors), the Bad Data Detector will easily detect the attack. Hence, we propose a robust ICA based blind attack strategy that one can use matrix recovery to circumvent the outlier problem and construct stealthy attack vectors. The proposed attack strategies are tested with IEEE representative 14-bus system. Simulations verify the feasibility of the proposed method.

  20. Revealing spatio-spectral electroencephalographic dynamics of musical mode and tempo perception by independent component analysis.

    Science.gov (United States)

    Lin, Yuan-Pin; Duann, Jeng-Ren; Feng, Wenfeng; Chen, Jyh-Horng; Jung, Tzyy-Ping

    2014-02-28

    Music conveys emotion by manipulating musical structures, particularly musical mode- and tempo-impact. The neural correlates of musical mode and tempo perception revealed by electroencephalography (EEG) have not been adequately addressed in the literature. This study used independent component analysis (ICA) to systematically assess spatio-spectral EEG dynamics associated with the changes of musical mode and tempo. Empirical results showed that music with major mode augmented delta-band activity over the right sensorimotor cortex, suppressed theta activity over the superior parietal cortex, and moderately suppressed beta activity over the medial frontal cortex, compared to minor-mode music, whereas fast-tempo music engaged significant alpha suppression over the right sensorimotor cortex. The resultant EEG brain sources were comparable with previous studies obtained by other neuroimaging modalities, such as functional magnetic resonance imaging (fMRI) and positron emission tomography (PET). In conjunction with advanced dry and mobile EEG technology, the EEG results might facilitate the translation from laboratory-oriented research to real-life applications for music therapy, training and entertainment in naturalistic environments.

  1. Software component quality evaluation

    Science.gov (United States)

    Clough, A. J.

    1991-01-01

    The paper describes a software inspection process that can be used to evaluate the quality of software components. Quality criteria, process application, independent testing of the process and proposed associated tool support are covered. Early results indicate that this technique is well suited for assessing software component quality in a standardized fashion. With automated machine assistance to facilitate both the evaluation and selection of software components, such a technique should promote effective reuse of software components.

  2. Optimized Kernel Entropy Components.

    Science.gov (United States)

    Izquierdo-Verdiguier, Emma; Laparra, Valero; Jenssen, Robert; Gomez-Chova, Luis; Camps-Valls, Gustau

    2017-06-01

    This brief addresses two main issues of the standard kernel entropy component analysis (KECA) algorithm: the optimization of the kernel decomposition and the optimization of the Gaussian kernel parameter. KECA roughly reduces to a sorting of the importance of kernel eigenvectors by entropy instead of variance, as in the kernel principal components analysis. In this brief, we propose an extension of the KECA method, named optimized KECA (OKECA), that directly extracts the optimal features retaining most of the data entropy by means of compacting the information in very few features (often in just one or two). The proposed method produces features which have higher expressive power. In particular, it is based on the independent component analysis framework, and introduces an extra rotation to the eigen decomposition, which is optimized via gradient-ascent search. This maximum entropy preservation suggests that OKECA features are more efficient than KECA features for density estimation. In addition, a critical issue in both the methods is the selection of the kernel parameter, since it critically affects the resulting performance. Here, we analyze the most common kernel length-scale selection criteria. The results of both the methods are illustrated in different synthetic and real problems. Results show that OKECA returns projections with more expressive power than KECA, the most successful rule for estimating the kernel parameter is based on maximum likelihood, and OKECA is more robust to the selection of the length-scale parameter in kernel density estimation.

  3. Independent component analysis applied to pulse oximetry in the estimation of the arterial oxygen saturation (SpO2) - a comparative study

    DEFF Research Database (Denmark)

    Jensen, Thomas; Duun, Sune Bro; Larsen, Jan

    2009-01-01

    We examine various independent component analysis (ICA) digital signal processing algorithms for estimating the arterial oxygen saturation (SpO2) as measured by a reflective pulse oximeter. The ICA algorithms examined are FastICA, Maximum Likelihood ICA (ICAML), Molgedey and Schuster ICA (ICAMS......), and Mean Field ICA (ICAMF). The signal processing includes pre-processing bandpass filtering to eliminate noise, and post-processing by calculating the SpO2. The algorithms are compared to the commercial state-of-the-art algorithm Discrete Saturation Transform (DST) by Masimo Corporation...

  4. An efficient 3-D eddy-current solver using an independent impedance method for transcranial magnetic stimulation.

    Science.gov (United States)

    De Geeter, Nele; Crevecoeur, Guillaume; Dupre, Luc

    2011-02-01

    In many important bioelectromagnetic problem settings, eddy-current simulations are required. Examples are the reduction of eddy-current artifacts in magnetic resonance imaging and techniques, whereby the eddy currents interact with the biological system, like the alteration of the neurophysiology due to transcranial magnetic stimulation (TMS). TMS has become an important tool for the diagnosis and treatment of neurological diseases and psychiatric disorders. A widely applied method for simulating the eddy currents is the impedance method (IM). However, this method has to contend with an ill conditioned problem and consequently a long convergence time. When dealing with optimal design problems and sensitivity control, the convergence rate becomes even more crucial since the eddy-current solver needs to be evaluated in an iterative loop. Therefore, we introduce an independent IM (IIM), which improves the conditionality and speeds up the numerical convergence. This paper shows how IIM is based on IM and what are the advantages. Moreover, the method is applied to the efficient simulation of TMS. The proposed IIM achieves superior convergence properties with high time efficiency, compared to the traditional IM and is therefore a useful tool for accurate and fast TMS simulations.

  5. Brillouin-zone integration schemes: an efficiency study for the phonon frequency moments of the harmonic, solid, one-component plasma

    International Nuclear Information System (INIS)

    Albers, R.C.; Gubernatis, J.E.

    1981-01-01

    The efficiency of four different Brillouin-zone integration schemes including the uniform mesh, special point method, special directions method, and Holas method are compared for calculating moments of the harmonic phonon frequencies of the solid one-component plasma. Very accurate values for the moments are also presented. The Holas method for which weights and integration points can easily be generated has roughly the same efficiency as the special directions method, which is much superior to the uniform mesh and special point methods for this problem

  6. Reliability for systems of degrading components with distinct component shock sets

    International Nuclear Information System (INIS)

    Song, Sanling; Coit, David W.; Feng, Qianmei

    2014-01-01

    This paper studies reliability for multi-component systems subject to dependent competing risks of degradation wear and random shocks, with distinct shock sets. In practice, many systems are exposed to distinct and different types of shocks that can be categorized according to their sizes, function, affected components, etc. Previous research primarily focuses on simple systems with independent failure processes, systems with independent component time-to-failure, or components that share the same shock set or type of shocks. In our new model, we classify random shocks into different sets based on their sizes or function. Shocks with specific sizes or function can selectively affect one or more components in the system but not necessarily all components. Additionally the shocks from the different shock sets can arrive at different rates and have different relative magnitudes. Preventive maintenance (PM) optimization is conducted for the system with different component shock sets. Decision variables for two different maintenance scheduling problems, the PM replacement time interval, and the PM inspection time interval, are determined by minimizing a defined system cost rate. Sensitivity analysis is performed to provide insight into the behavior of the proposed maintenance policies. These models can be applied directly or customized for many complex systems that experience dependent competing failure processes with different component shock sets. A MEMS (Micro-electro mechanical systems) oscillator is a typical system subject to dependent and competing failure processes, and it is used as a numerical example to illustrate our new reliability and maintenance models

  7. Quantifying motor recovery after stroke using independent vector analysis and graph-theoretical analysis

    Directory of Open Access Journals (Sweden)

    Jonathan Laney

    2015-01-01

    Full Text Available The assessment of neuroplasticity after stroke through functional magnetic resonance imaging (fMRI analysis is a developing field where the objective is to better understand the neural process of recovery and to better target rehabilitation interventions. The challenge in this population stems from the large amount of individual spatial variability and the need to summarize entire brain maps by generating simple, yet discriminating features to highlight differences in functional connectivity. Independent vector analysis (IVA has been shown to provide superior performance in preserving subject variability when compared with widely used methods such as group independent component analysis. Hence, in this paper, graph-theoretical (GT analysis is applied to IVA-generated components to effectively exploit the individual subjects' connectivity to produce discriminative features. The analysis is performed on fMRI data collected from individuals with chronic stroke both before and after a 6-week arm and hand rehabilitation intervention. Resulting GT features are shown to capture connectivity changes that are not evident through direct comparison of the group t-maps. The GT features revealed increased small worldness across components and greater centrality in key motor networks as a result of the intervention, suggesting improved efficiency in neural communication. Clinically, these results bring forth new possibilities as a means to observe the neural processes underlying improvements in motor function.

  8. Empirical usability testing in a component-based environment : improving test efficiency with component-specific usability measures

    NARCIS (Netherlands)

    Brinkman, W.P.; Haakma, R.; Bouwhuis, D.G.; Bastide, R.; Palanque, P.; Roth, J.

    2005-01-01

    This paper addresses the issue of usability testing in a component-based software engineering environment, specifically measuring the usability of different versions of a component in a more powerful manner than other, more holistic, usability methods. Three component-specific usability measures are

  9. Independent component and pathway-based analysis of miRNA-regulated gene expression in a model of type 1 diabetes

    Directory of Open Access Journals (Sweden)

    Hagedorn Peter H

    2011-02-01

    Full Text Available Abstract Background Several approaches have been developed for miRNA target prediction, including methods that incorporate expression profiling. However the methods are still in need of improvements due to a high false discovery rate. So far, none of the methods have used independent component analysis (ICA. Here, we developed a novel target prediction method based on ICA that incorporates both seed matching and expression profiling of miRNA and mRNA expressions. The method was applied on a cellular model of type 1 diabetes. Results Microrray profiling identified eight miRNAs (miR-124/128/192/194/204/375/672/708 with differential expression. Applying ICA on the mRNA profiling data revealed five significant independent components (ICs correlating to the experimental conditions. The five ICs also captured the miRNA expressions by explaining >97% of their variance. By using ICA, seven of the eight miRNAs showed significant enrichment of sequence predicted targets, compared to only four miRNAs when using simple negative correlation. The ICs were enriched for miRNA targets that function in diabetes-relevant pathways e.g. type 1 and type 2 diabetes and maturity onset diabetes of the young (MODY. Conclusions In this study, ICA was applied as an attempt to separate the various factors that influence the mRNA expression in order to identify miRNA targets. The results suggest that ICA is better at identifying miRNA targets than negative correlation. Additionally, combining ICA and pathway analysis constitutes a means for prioritizing between the predicted miRNA targets. Applying the method on a model of type 1 diabetes resulted in identification of eight miRNAs that appear to affect pathways of relevance to disease mechanisms in diabetes.

  10. Independent random sampling methods

    CERN Document Server

    Martino, Luca; Míguez, Joaquín

    2018-01-01

    This book systematically addresses the design and analysis of efficient techniques for independent random sampling. Both general-purpose approaches, which can be used to generate samples from arbitrary probability distributions, and tailored techniques, designed to efficiently address common real-world practical problems, are introduced and discussed in detail. In turn, the monograph presents fundamental results and methodologies in the field, elaborating and developing them into the latest techniques. The theory and methods are illustrated with a varied collection of examples, which are discussed in detail in the text and supplemented with ready-to-run computer code. The main problem addressed in the book is how to generate independent random samples from an arbitrary probability distribution with the weakest possible constraints or assumptions in a form suitable for practical implementation. The authors review the fundamental results and methods in the field, address the latest methods, and emphasize the li...

  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. Detection of independent functional networks during music listening using electroencephalogram and sLORETA-ICA.

    Science.gov (United States)

    Jäncke, Lutz; Alahmadi, Nsreen

    2016-04-13

    The measurement of brain activation during music listening is a topic that is attracting increased attention from many researchers. Because of their high spatial accuracy, functional MRI measurements are often used for measuring brain activation in the context of music listening. However, this technique faces the issues of contaminating scanner noise and an uncomfortable experimental environment. Electroencephalogram (EEG), however, is a neural registration technique that allows the measurement of neurophysiological activation in silent and more comfortable experimental environments. Thus, it is optimal for recording brain activations during pleasant music stimulation. Using a new mathematical approach to calculate intracortical independent components (sLORETA-IC) on the basis of scalp-recorded EEG, we identified specific intracortical independent components during listening of a musical piece and scales, which differ substantially from intracortical independent components calculated from the resting state EEG. Most intracortical independent components are located bilaterally in perisylvian brain areas known to be involved in auditory processing and specifically in music perception. Some intracortical independent components differ between the music and scale listening conditions. The most prominent difference is found in the anterior part of the perisylvian brain region, with stronger activations seen in the left-sided anterior perisylvian regions during music listening, most likely indicating semantic processing during music listening. A further finding is that the intracortical independent components obtained for the music and scale listening are most prominent in higher frequency bands (e.g. beta-2 and beta-3), whereas the resting state intracortical independent components are active in lower frequency bands (alpha-1 and theta). This new technique for calculating intracortical independent components is able to differentiate independent neural networks associated

  13. Hand classification of fMRI ICA noise components.

    Science.gov (United States)

    Griffanti, Ludovica; Douaud, Gwenaëlle; Bijsterbosch, Janine; Evangelisti, Stefania; Alfaro-Almagro, Fidel; Glasser, Matthew F; Duff, Eugene P; Fitzgibbon, Sean; Westphal, Robert; Carone, Davide; Beckmann, Christian F; Smith, Stephen M

    2017-07-01

    We present a practical "how-to" guide to help determine whether single-subject fMRI independent components (ICs) characterise structured noise or not. Manual identification of signal and noise after ICA decomposition is required for efficient data denoising: to train supervised algorithms, to check the results of unsupervised ones or to manually clean the data. In this paper we describe the main spatial and temporal features of ICs and provide general guidelines on how to evaluate these. Examples of signal and noise components are provided from a wide range of datasets (3T data, including examples from the UK Biobank and the Human Connectome Project, and 7T data), together with practical guidelines for their identification. Finally, we discuss how the data quality, data type and preprocessing can influence the characteristics of the ICs and present examples of particularly challenging datasets. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

  14. Sandia_HighTemperatureComponentEvaluation_2015

    Energy Technology Data Exchange (ETDEWEB)

    Cashion, Avery T. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2015-03-01

    The objective of this project is to perform independent evaluation of high temperature components to determine their suitability for use in high temperature geothermal tools. Development of high temperature components has been increasing rapidly due to demand from the high temperature oil and gas exploration and aerospace industries. Many of these new components are at the late prototype or first production stage of development and could benefit from third party evaluation of functionality and lifetime at elevated temperatures. In addition to independent testing of new components, this project recognizes that there is a paucity of commercial-off-the-shelf COTS components rated for geothermal temperatures. As such, high-temperature circuit designers often must dedicate considerable time and resources to determine if a component exists that they may be able to knead performance out of to meet their requirements. This project aids tool developers by characterization of select COTS component performances beyond published temperature specifications. The process for selecting components includes public announcements of project intent (e.g., FedBizOps), direct discussions with candidate manufacturers,and coordination with other DOE funded programs.

  15. Risk management and market efficiency on the Midwest Independent System Operator electricity exchange

    Science.gov (United States)

    Jones, Kevin

    Midwest Independent Transmission System Operator, Inc. (MISO) is a non-profit regional transmission organization (RTO) that oversees electricity production and transmission across thirteen states and one Canadian province. MISO also operates an electronic exchange for buying and selling electricity for each of its five regional hubs. MISO oversees two types of markets. The forward market, which is referred to as the day-ahead (DA) market, allows market participants to place demand bids and supply offers on electricity to be delivered at a specified hour the following day. The equilibrium price, known as the locational marginal price (LMP), is determined by MISO after receiving sale offers and purchase bids from market participants. MISO also coordinates a spot market, which is known as the real-time (RT) market. Traders in the real-time market must submit bids and offers by thirty minutes prior to the hour for which the trade will be executed. After receiving purchase and sale offers for a given hour in the real time market, MISO then determines the LMP for that particular hour. The existence of the DA and RT markets allows producers and retailers to hedge against the large fluctuations that are common in electricity prices. Hedge ratios on the MISO exchange are estimated using various techniques. No hedge ratio technique examined consistently outperforms the unhedged portfolio in terms of variance reduction. Consequently, none of the hedge ratio methods in this study meet the general interpretation of FASB guidelines for a highly effective hedge. One of the major goals of deregulation is to bring about competition and increased efficiency in electricity markets. Previous research suggests that electricity exchanges may not be weak-form market efficient. A simple moving average trading rule is found to produce statistically and economically significant profits on the MISO exchange. This could call the long-term survivability of the MISO exchange into question.

  16. Characterizing speed-independence of high-level designs

    DEFF Research Database (Denmark)

    Kishinevsky, Michael; Staunstrup, Jørgen

    1994-01-01

    This paper characterizes the speed-independence of high-level designs. The characterization is a condition on the design description ensuring that the behavior of the design is independent of the speeds of its components. The behavior of a circuit is modeled as a transition system, that allows data...... types, and internal as well as external non-determinism. This makes it possible to verify the speed-independence of a design without providing an explicit realization of the environment. The verification can be done mechanically. A number of experimental designs have been verified including a speed-independent...

  17. REPEATABILITY OF SPITZER/IRAC EXOPLANETARY ECLIPSES WITH INDEPENDENT COMPONENT ANALYSIS

    Energy Technology Data Exchange (ETDEWEB)

    Morello, G.; Waldmann, I. P.; Tinetti, G., E-mail: giuseppe.morello.11@ucl.ac.uk [Department of Physics and Astronomy, University College London, Gower Street, WC1E6BT (United Kingdom)

    2016-04-01

    The research of effective and reliable detrending methods for Spitzer data is of paramount importance for the characterization of exoplanetary atmospheres. To date, the totality of exoplanetary observations in the mid- and far-infrared, at wavelengths >3 μm, have been taken with Spitzer. In some cases, in past years, repeated observations and multiple reanalyses of the same data sets led to discrepant results, raising questions about the accuracy and reproducibility of such measurements. Morello et al. (2014, 2015) proposed a blind-source separation method based on the Independent Component Analysis of pixel time series (pixel-ICA) to analyze InfraRed Array Camera (IRAC) data, obtaining coherent results when applied to repeated transit observations previously debated in the literature. Here we introduce a variant to the pixel-ICA through the use of wavelet transform, wavelet pixel-ICA, which extends its applicability to low-signal-to-noise-ratio cases. We describe the method and discuss the results obtained over 12 eclipses of the exoplanet XO3b observed during the “Warm Spitzer” era in the 4.5 μm band. The final results are reported, in part, also in Ingalls et al. (2016), together with results obtained with other detrending methods, and over 10 synthetic eclipses that were analyzed for the “IRAC Data Challenge 2015.” Our results are consistent within 1σ with the ones reported in Wong et al. (2014) and with most of the results reported in Ingalls et al. (2016), which appeared on arXiv while this paper was under review. Based on many statistical tests discussed in Ingalls et al. (2016), the wavelet pixel-ICA method performs as well as or better than other state-of-art methods recently developed by other teams to analyze Spitzer/IRAC data, and, in particular, it appears to be the most repeatable and the most reliable, while reaching the photon noise limit, at least for the particular data set analyzed. Another strength of the ICA approach is its highest

  18. REPEATABILITY OF SPITZER/IRAC EXOPLANETARY ECLIPSES WITH INDEPENDENT COMPONENT ANALYSIS

    International Nuclear Information System (INIS)

    Morello, G.; Waldmann, I. P.; Tinetti, G.

    2016-01-01

    The research of effective and reliable detrending methods for Spitzer data is of paramount importance for the characterization of exoplanetary atmospheres. To date, the totality of exoplanetary observations in the mid- and far-infrared, at wavelengths >3 μm, have been taken with Spitzer. In some cases, in past years, repeated observations and multiple reanalyses of the same data sets led to discrepant results, raising questions about the accuracy and reproducibility of such measurements. Morello et al. (2014, 2015) proposed a blind-source separation method based on the Independent Component Analysis of pixel time series (pixel-ICA) to analyze InfraRed Array Camera (IRAC) data, obtaining coherent results when applied to repeated transit observations previously debated in the literature. Here we introduce a variant to the pixel-ICA through the use of wavelet transform, wavelet pixel-ICA, which extends its applicability to low-signal-to-noise-ratio cases. We describe the method and discuss the results obtained over 12 eclipses of the exoplanet XO3b observed during the “Warm Spitzer” era in the 4.5 μm band. The final results are reported, in part, also in Ingalls et al. (2016), together with results obtained with other detrending methods, and over 10 synthetic eclipses that were analyzed for the “IRAC Data Challenge 2015.” Our results are consistent within 1σ with the ones reported in Wong et al. (2014) and with most of the results reported in Ingalls et al. (2016), which appeared on arXiv while this paper was under review. Based on many statistical tests discussed in Ingalls et al. (2016), the wavelet pixel-ICA method performs as well as or better than other state-of-art methods recently developed by other teams to analyze Spitzer/IRAC data, and, in particular, it appears to be the most repeatable and the most reliable, while reaching the photon noise limit, at least for the particular data set analyzed. Another strength of the ICA approach is its highest

  19. Principal Component Analysis as an Efficient Performance ...

    African Journals Online (AJOL)

    This paper uses the principal component analysis (PCA) to examine the possibility of using few explanatory variables (X's) to explain the variation in Y. It applied PCA to assess the performance of students in Abia State Polytechnic, Aba, Nigeria. This was done by estimating the coefficients of eight explanatory variables in a ...

  20. A quasi-independence model to estimate failure rates

    International Nuclear Information System (INIS)

    Colombo, A.G.

    1988-01-01

    The use of a quasi-independence model to estimate failure rates is investigated. Gate valves of nuclear plants are considered, and two qualitative covariates are taken into account: plant location and reactor system. Independence between the two covariates and an exponential failure model are assumed. The failure rate of the components of a given system and plant is assumed to be a constant, but it may vary from one system to another and from one plant to another. This leads to the analysis of a contingency table. A particular feature of the model is the different operating time of the components in the various cells which can also be equal to zero. The concept of independence of the covariates is then replaced by that of quasi-independence. The latter definition, however, is used in a broader sense than usual. Suitable statistical tests are discussed and a numerical example illustrates the use of the method. (author)

  1. Genetic parameters and expected responses to selection for components of feed efficiency in a Duroc pig line.

    Science.gov (United States)

    Sánchez, Juan P; Ragab, Mohamed; Quintanilla, Raquel; Rothschild, Max F; Piles, Miriam

    2017-12-01

    Improving feed efficiency ([Formula: see text]) is a key factor for any pig breeding company. Although this can be achieved by selection on an index of multi-trait best linear unbiased prediction of breeding values with optimal economic weights, considering deviations of feed intake from actual needs ([Formula: see text]) should be of value for further research on biological aspects of [Formula: see text]. Here, we present a random regression model that extends the classical definition of [Formula: see text] by including animal-specific needs in the model. Using this model, we explore the genetic determinism of several [Formula: see text] components: use of feed for growth ([Formula: see text]), use of feed for backfat deposition ([Formula: see text]), use of feed for maintenance ([Formula: see text]), and unspecific efficiency in the use of feed ([Formula: see text]). Expected response to alternative selection indexes involving different components is also studied. Based on goodness-of-fit to the available feed intake ([Formula: see text]) data, the model that assumes individual (genetic and permanent) variation in the use of feed for maintenance, [Formula: see text] and [Formula: see text] showed the best performance. Joint individual variation in feed allocation to maintenance, growth and backfat deposition comprised 37% of the individual variation of [Formula: see text]. The estimated heritabilities of [Formula: see text] using the model that accounts for animal-specific needs and the traditional [Formula: see text] model were 0.12 and 0.18, respectively. The estimated heritabilities for the regression coefficients were 0.44, 0.39 and 0.55 for [Formula: see text], [Formula: see text] and [Formula: see text], respectively. Estimates of genetic correlations of [Formula: see text] were positive with amount of feed used for [Formula: see text] and [Formula: see text] but negative for [Formula: see text]. Expected response in overall efficiency, reducing [Formula

  2. Independent and joint associations of TV viewing time and snack food consumption with the metabolic syndrome and its components; a cross-sectional study in Australian adults.

    Science.gov (United States)

    Thorp, Alicia A; McNaughton, Sarah A; Owen, Neville; Dunstan, David W

    2013-08-09

    Television (TV) viewing time is positively associated with the metabolic syndrome (MetS) in adults. However, the mechanisms through which TV viewing time is associated with MetS risk remain unclear. There is evidence that the consumption of energy-dense, nutrient poor snack foods increases during TV viewing time among adults, suggesting that these behaviors may jointly contribute towards MetS risk. While the association between TV viewing time and the MetS has previously been shown to be independent of adult's overall dietary intake, the specific influence of snack food consumption on the relationship is yet to be investigated. The purpose of this study was to examine the independent and joint associations of daily TV viewing time and snack food consumption with the MetS and its components in a sample of Australian adults. Population-based, cross-sectional study of 3,110 women and 2,572 men (>35 years) without diabetes or cardiovascular disease. Participants were recruited between May 1999 and Dec 2000 in the six states and the Northern Territory of Australia. Participants were categorised according to self-reported TV viewing time (low: 0-2 hr/d; high: >2 hr/d) and/or consumption of snack foods (low: 0-3 serves/d; high: >3 serves/d). Multivariate odds ratios [95% CI] for the MetS and its components were estimated using gender-specific, forced entry logistic regression. OR [95% CI] for the MetS was 3.59 [2.25, 5.74] (p≤0.001) in women and 1.45 [1.02, 3.45] (p = 0.04) in men who jointly reported high TV viewing time and high snack food consumption. Obesity, insulin resistance and hypertension (women only) were also jointly associated with high TV viewing time and high snack food consumption. Further adjustment for diet quality and central adiposity maintained the associations in women. High snack food consumption was also shown to be independently associated with MetS risk [OR: 1.94 (95% CI: 1.45, 2.60), p snack food consumption are independently and

  3. 2D surface temperature measurement of plasma facing components with modulated active pyrometry

    International Nuclear Information System (INIS)

    Amiel, S.; Loarer, T.; Pocheau, C.; Roche, H.; Gauthier, E.; Aumeunier, M.-H.; Courtois, X.; Jouve, M.; Balorin, C.; Moncada, V.; Le Niliot, C.; Rigollet, F.

    2014-01-01

    In nuclear fusion devices, such as Tore Supra, the plasma facing components (PFC) are in carbon. Such components are exposed to very high heat flux and the surface temperature measurement is mandatory for the safety of the device and also for efficient plasma scenario development. Besides this measurement is essential to evaluate these heat fluxes for a better knowledge of the physics of plasma-wall interaction, it is also required to monitor the fatigue of PFCs. Infrared system (IR) is used to manage to measure surface temperature in real time. For carbon PFCs, the emissivity is high and known (ε ∼ 0.8), therefore the contribution of the reflected flux from environment and collected by the IR cameras can be neglected. However, the future tokamaks such as WEST and ITER will be equipped with PFCs in metal (W and Be/W, respectively) with low and variable emissivities (ε ∼ 0.1–0.4). Consequently, the reflected flux will contribute significantly in the collected flux by IR camera. The modulated active pyrometry, using a bicolor camera, proposed in this paper allows a 2D surface temperature measurement independently of the reflected fluxes and the emissivity. Experimental results with Tungsten sample are reported and compared with simultaneous measurement performed with classical pyrometry (monochromatic and bichromatic) with and without reflective flux demonstrating the efficiency of this method for surface temperature measurement independently of the reflected flux and the emissivity

  4. Quantifying biological samples using Linear Poisson Independent Component Analysis for MALDI-ToF mass spectra

    Science.gov (United States)

    Deepaisarn, S; Tar, P D; Thacker, N A; Seepujak, A; McMahon, A W

    2018-01-01

    Abstract Motivation Matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI) facilitates the analysis of large organic molecules. However, the complexity of biological samples and MALDI data acquisition leads to high levels of variation, making reliable quantification of samples difficult. We present a new analysis approach that we believe is well-suited to the properties of MALDI mass spectra, based upon an Independent Component Analysis derived for Poisson sampled data. Simple analyses have been limited to studying small numbers of mass peaks, via peak ratios, which is known to be inefficient. Conventional PCA and ICA methods have also been applied, which extract correlations between any number of peaks, but we argue makes inappropriate assumptions regarding data noise, i.e. uniform and Gaussian. Results We provide evidence that the Gaussian assumption is incorrect, motivating the need for our Poisson approach. The method is demonstrated by making proportion measurements from lipid-rich binary mixtures of lamb brain and liver, and also goat and cow milk. These allow our measurements and error predictions to be compared to ground truth. Availability and implementation Software is available via the open source image analysis system TINA Vision, www.tina-vision.net. Contact paul.tar@manchester.ac.uk Supplementary information Supplementary data are available at Bioinformatics online. PMID:29091994

  5. Efficient and genotype-independent Agrobacterium--mediated tomato transformation.

    Science.gov (United States)

    Park, Sung Hun; Morris, Jay L; Park, Jung Eun; Hirschi, Kendal D; Smith, Roberta H

    2003-10-01

    An efficient method to transform five cultivars of tomato (Lycopersicon esculentum), Micro-Tom, Red Cherry, Rubion, Piedmont, and E6203 is reported. A comparison was made of leaf, cotyledon, and hypocotyl explants on 7 different regeneration media without Agrobacterium tumefaciens cocultivation and on 11 different media with cocultivation. Although all cultivars and explants formed callus and regenerated on the initial 7 media, cocultivation with A. tumefaciens significantly reduced the callus induction and regeneration. From these experiments, a transformation methodology using either hypocotyls or cotyledons cultured for one day on BA 1 mgL-1, NAA 0.1 mgL-1 and 3 days cocultivation with the Agrobacterium on this same medium followed by a transfer to a medium with zeatin 2 mgL-1 and IAA 0.1 mgL-1 for 4-6 weeks resulted in a greater than 20% transformation frequency for all five cultivars tested. In this transformation method, no feeder layers of tobacco, petunia or tomato suspension cultures were used, and the subculture media was minimal. Stable integration and transmission of the transgene in T1 generation plants were confirmed by Southern blot analysis. This procedure represents a simple, efficient and general means of transforming tomato.

  6. Active components for integrated plasmonic circuits

    DEFF Research Database (Denmark)

    Krasavin, A.V.; Bolger, P.M.; Zayats, A.V.

    2009-01-01

    We present a comprehensive study of highly efficient and compact passive and active components for integrated plasmonic circuit based on dielectric-loaded surface plasmon polariton waveguides.......We present a comprehensive study of highly efficient and compact passive and active components for integrated plasmonic circuit based on dielectric-loaded surface plasmon polariton waveguides....

  7. A systematic approach for component-based software development

    NARCIS (Netherlands)

    Guareis de farias, Cléver; van Sinderen, Marten J.; Ferreira Pires, Luis

    2000-01-01

    Component-based software development enables the construction of software artefacts by assembling prefabricated, configurable and independently evolving building blocks, called software components. This paper presents an approach for the development of component-based software artefacts. This

  8. Latent physiological factors of complex human diseases revealed by independent component analysis of clinarrays

    Directory of Open Access Journals (Sweden)

    Chen David P

    2010-10-01

    Full Text Available Abstract Background Diagnosis and treatment of patients in the clinical setting is often driven by known symptomatic factors that distinguish one particular condition from another. Treatment based on noticeable symptoms, however, is limited to the types of clinical biomarkers collected, and is prone to overlooking dysfunctions in physiological factors not easily evident to medical practitioners. We used a vector-based representation of patient clinical biomarkers, or clinarrays, to search for latent physiological factors that underlie human diseases directly from clinical laboratory data. Knowledge of these factors could be used to improve assessment of disease severity and help to refine strategies for diagnosis and monitoring disease progression. Results Applying Independent Component Analysis on clinarrays built from patient laboratory measurements revealed both known and novel concomitant physiological factors for asthma, types 1 and 2 diabetes, cystic fibrosis, and Duchenne muscular dystrophy. Serum sodium was found to be the most significant factor for both type 1 and type 2 diabetes, and was also significant in asthma. TSH3, a measure of thyroid function, and blood urea nitrogen, indicative of kidney function, were factors unique to type 1 diabetes respective to type 2 diabetes. Platelet count was significant across all the diseases analyzed. Conclusions The results demonstrate that large-scale analyses of clinical biomarkers using unsupervised methods can offer novel insights into the pathophysiological basis of human disease, and suggest novel clinical utility of established laboratory measurements.

  9. Differential recruitment of theory of mind brain network across three tasks: An independent component analysis.

    Science.gov (United States)

    Thye, Melissa D; Ammons, Carla J; Murdaugh, Donna L; Kana, Rajesh K

    2018-07-16

    Social neuroscience research has focused on an identified network of brain regions primarily associated with processing Theory of Mind (ToM). However, ToM is a broad cognitive process, which encompasses several sub-processes, such as mental state detection and intentional attribution, and the connectivity of brain regions underlying the broader ToM network in response to paradigms assessing these sub-processes requires further characterization. Standard fMRI analyses which focus only on brain activity cannot capture information about ToM processing at a network level. An alternative method, independent component analysis (ICA), is a data-driven technique used to isolate intrinsic connectivity networks, and this approach provides insight into network-level regional recruitment. In this fMRI study, three complementary, but distinct ToM tasks assessing mental state detection (e.g. RMIE: Reading the Mind in the Eyes; RMIV: Reading the Mind in the Voice) and intentional attribution (Causality task) were each analyzed using ICA in order to separately characterize the recruitment and functional connectivity of core nodes in the ToM network in response to the sub-processes of ToM. Based on visual comparison of the derived networks for each task, the spatiotemporal network patterns were similar between the RMIE and RMIV tasks, which elicited mentalizing about the mental states of others, and these networks differed from the network derived for the Causality task, which elicited mentalizing about goal-directed actions. The medial prefrontal cortex, precuneus, and right inferior frontal gyrus were seen in the components with the highest correlation with the task condition for each of the tasks highlighting the role of these regions in general ToM processing. Using a data-driven approach, the current study captured the differences in task-related brain response to ToM in three distinct ToM paradigms. The findings of this study further elucidate the neural mechanisms associated

  10. Magnetospheric particle detection efficiency of a conical telescope

    International Nuclear Information System (INIS)

    Miah, M.A.; Mitchell, J.W.; Wefel, J.P.

    1989-01-01

    A semianalytic program has been developed to map the pitch angles of magnetospheric particles onto a detector telescope acceptance cone. The telescope fractional efficiency is defined as the fraction of the pitch angle cone in common with the telescope cone multiplied by the fractional perpendicular component of the exposed detector area, and normalized by 2π. Calculations have been performed as a function of the satellite's location, orbital inclination and the zenith angle of the telescope axis, both in dipole and real geomagnetic field models. At the dipole equator, the peak efficiency occurs at 90 0 pitch angle. In the real geomagnetic field model, the average value of the pitch angle for maximum efficiency is ≅ 88 0 . The efficiency function depends strongly upon latitude and is independent of longitude in a dipole field, but depends on longitude in the real field model. In either field model, altitude, angle of tilt and orbital inclination have little effect upon efficiency. The efficiency function calculated at the dipole equator can be used at the minimum magnetic field equator with little error, but not for points away from the B min position. The results are applied to calculate the absolute flux of magnetospheric particles observed near the equator. (orig.)

  11. Applying Different Independent Component Analysis Algorithms and Support Vector Regression for IT Chain Store Sales Forecasting

    Science.gov (United States)

    Dai, Wensheng

    2014-01-01

    Sales forecasting is one of the most important issues in managing information technology (IT) chain store sales since an IT chain store has many branches. Integrating feature extraction method and prediction tool, such as support vector regression (SVR), is a useful method for constructing an effective sales forecasting scheme. Independent component analysis (ICA) is a novel feature extraction technique and has been widely applied to deal with various forecasting problems. But, up to now, only the basic ICA method (i.e., temporal ICA model) was applied to sale forecasting problem. In this paper, we utilize three different ICA methods including spatial ICA (sICA), temporal ICA (tICA), and spatiotemporal ICA (stICA) to extract features from the sales data and compare their performance in sales forecasting of IT chain store. Experimental results from a real sales data show that the sales forecasting scheme by integrating stICA and SVR outperforms the comparison models in terms of forecasting error. The stICA is a promising tool for extracting effective features from branch sales data and the extracted features can improve the prediction performance of SVR for sales forecasting. PMID:25165740

  12. Applying different independent component analysis algorithms and support vector regression for IT chain store sales forecasting.

    Science.gov (United States)

    Dai, Wensheng; Wu, Jui-Yu; Lu, Chi-Jie

    2014-01-01

    Sales forecasting is one of the most important issues in managing information technology (IT) chain store sales since an IT chain store has many branches. Integrating feature extraction method and prediction tool, such as support vector regression (SVR), is a useful method for constructing an effective sales forecasting scheme. Independent component analysis (ICA) is a novel feature extraction technique and has been widely applied to deal with various forecasting problems. But, up to now, only the basic ICA method (i.e., temporal ICA model) was applied to sale forecasting problem. In this paper, we utilize three different ICA methods including spatial ICA (sICA), temporal ICA (tICA), and spatiotemporal ICA (stICA) to extract features from the sales data and compare their performance in sales forecasting of IT chain store. Experimental results from a real sales data show that the sales forecasting scheme by integrating stICA and SVR outperforms the comparison models in terms of forecasting error. The stICA is a promising tool for extracting effective features from branch sales data and the extracted features can improve the prediction performance of SVR for sales forecasting.

  13. Applying Different Independent Component Analysis Algorithms and Support Vector Regression for IT Chain Store Sales Forecasting

    Directory of Open Access Journals (Sweden)

    Wensheng Dai

    2014-01-01

    Full Text Available Sales forecasting is one of the most important issues in managing information technology (IT chain store sales since an IT chain store has many branches. Integrating feature extraction method and prediction tool, such as support vector regression (SVR, is a useful method for constructing an effective sales forecasting scheme. Independent component analysis (ICA is a novel feature extraction technique and has been widely applied to deal with various forecasting problems. But, up to now, only the basic ICA method (i.e., temporal ICA model was applied to sale forecasting problem. In this paper, we utilize three different ICA methods including spatial ICA (sICA, temporal ICA (tICA, and spatiotemporal ICA (stICA to extract features from the sales data and compare their performance in sales forecasting of IT chain store. Experimental results from a real sales data show that the sales forecasting scheme by integrating stICA and SVR outperforms the comparison models in terms of forecasting error. The stICA is a promising tool for extracting effective features from branch sales data and the extracted features can improve the prediction performance of SVR for sales forecasting.

  14. Organization and control of independent work of students

    Directory of Open Access Journals (Sweden)

    Kaydalova L.G.

    2010-01-01

    Full Text Available The theoretical methodical aspects of independent work of students, organization and control, educational methodical providing, forms and types of independent work are examined. Efficiency of independent work is provided high-quality educational literature. The basic forms of control is: current, result and module, examinations, term papers, diploma works, licensed computer-integrated examinations, state attestation. Control can be conducted in a kind: expressquestioning, interview. Control is an information generator for a teacher about motion of independent capture the student of educational by material.

  15. π-Bridge-Independent 2-(Benzo[c][1,2,5]thiadiazol-4-ylmethylene)malononitrile-Substituted Nonfullerene Acceptors for Efficient Solar Cells

    KAUST Repository

    Wang, Kai

    2016-02-25

    Molecular acceptors are promising alternatives to fullerenes (e.g. PC61/71BM) in the fabrication of high-efficiency bulk-heterojunction (BHJ) solar cells. While solution-processed polymer-fullerene BHJ devices have recently met the 10% efficiency threshold, molecular acceptors have yet to prove comparably efficient with polymer donors. At this point in time, it is important to forge a better understanding of the design parameters that directly impact small-molecule (SM) acceptor performance in BHJ solar cells. In this report, we show that 2-(benzo[c][1,2,5]thiadiazol-4-ylmethylene)malononitrile (BM)-terminated SM acceptors can achieve efficiencies as high as 5.3% in BHJ solar cells with the polymer donor PCE10. Through systematic device optimization and characterization studies, we find that the nonfull-erene analogues (FBM, CBM and CDTBM) all perform comparably well, independent of the molecular structure and electronics of the π-bridge that links the two electron-deficient BM end groups. With estimated electron affinities within range of those of common fullerenes (4.0-4.3 eV), and a wider range of ionization potentials (6.2-5.6 eV), the SM acceptors absorb in the visible spectrum and effectively contribute to the BHJ device photocurrent. BM-substituted SM acceptors are promising alterna-tives to fullerenes in solution-processed BHJ solar cells.

  16. π-Bridge-Independent 2-(Benzo[c][1,2,5]thiadiazol-4-ylmethylene)malononitrile-Substituted Nonfullerene Acceptors for Efficient Solar Cells

    KAUST Repository

    Wang, Kai; Firdaus, Yuliar; Babics, Maxime; Cruciani, Federico; Saleem, Qasim; El Labban, Abdulrahman; Alamoudi, Maha; Marszalek, Tomasz; Pisula, Wojciech; Laquai, Fré dé ric; Beaujuge, Pierre

    2016-01-01

    Molecular acceptors are promising alternatives to fullerenes (e.g. PC61/71BM) in the fabrication of high-efficiency bulk-heterojunction (BHJ) solar cells. While solution-processed polymer-fullerene BHJ devices have recently met the 10% efficiency threshold, molecular acceptors have yet to prove comparably efficient with polymer donors. At this point in time, it is important to forge a better understanding of the design parameters that directly impact small-molecule (SM) acceptor performance in BHJ solar cells. In this report, we show that 2-(benzo[c][1,2,5]thiadiazol-4-ylmethylene)malononitrile (BM)-terminated SM acceptors can achieve efficiencies as high as 5.3% in BHJ solar cells with the polymer donor PCE10. Through systematic device optimization and characterization studies, we find that the nonfull-erene analogues (FBM, CBM and CDTBM) all perform comparably well, independent of the molecular structure and electronics of the π-bridge that links the two electron-deficient BM end groups. With estimated electron affinities within range of those of common fullerenes (4.0-4.3 eV), and a wider range of ionization potentials (6.2-5.6 eV), the SM acceptors absorb in the visible spectrum and effectively contribute to the BHJ device photocurrent. BM-substituted SM acceptors are promising alterna-tives to fullerenes in solution-processed BHJ solar cells.

  17. Systems with randomly failing repairable components

    DEFF Research Database (Denmark)

    Der Kiureghian, Armen; Ditlevsen, Ove Dalager; Song, Junho

    2005-01-01

    Closed-form expressions are derived for the steady-state availability, mean rate of failure, mean duration of downtime and reliability of a general system with randomly and independently failing repairable components. Component failures are assumed to be homogeneous Poisson events in time and rep...

  18. Deregulation of shopping hours: The impact on independent retailers and chain stores

    OpenAIRE

    Wenzel, Tobias

    2010-01-01

    This paper studies shopping hour decisions by retail chains and independent competitors. We use a Salop-type model where retailers compete in prices and shopping hours. Our results depend significantly on efficiency differences between retail chain and independent retailer. If the efficiency difference is small, the independent retailer may choose longer shopping hours than the retail chain and may gain from deregulation at the expense of the retail chain. The opposite result emerges when the...

  19. Opening A New Independent Pharmacy 101

    Directory of Open Access Journals (Sweden)

    Azam Elabed

    2016-02-01

    Full Text Available Opening an independent pharmacy is a process that involves multiple components. The rationale of this project is to discuss different issues that must be investigated prior to opening a new independency pharmacy. This includes the location, structure of the corporation, start-up cost, picking a wholesaler, fulfilling state board requirements and Philadelphia requirements, having a valid license, making professional relationships, and knowing basic marketing research. Methods used include using the knowledge and expertise from an independent pharmacy owner, visiting pharmacies, and interviewing neighbors for basic marketing research. Many aspects of opening an independent pharmacy differ significantly from a retail pharmacy, as there are various issues within the pharmacy and outside the pharmacy that must be extensively researched prior to opening in order to be successful.   Type: Student Project

  20. Brain network of semantic integration in sentence reading: insights from independent component analysis and graph theoretical analysis.

    Science.gov (United States)

    Ye, Zheng; Doñamayor, Nuria; Münte, Thomas F

    2014-02-01

    A set of cortical and sub-cortical brain structures has been linked with sentence-level semantic processes. However, it remains unclear how these brain regions are organized to support the semantic integration of a word into sentential context. To look into this issue, we conducted a functional magnetic resonance imaging (fMRI) study that required participants to silently read sentences with semantically congruent or incongruent endings and analyzed the network properties of the brain with two approaches, independent component analysis (ICA) and graph theoretical analysis (GTA). The GTA suggested that the whole-brain network is topologically stable across conditions. The ICA revealed a network comprising the supplementary motor area (SMA), left inferior frontal gyrus, left middle temporal gyrus, left caudate nucleus, and left angular gyrus, which was modulated by the incongruity of sentence ending. Furthermore, the GTA specified that the connections between the left SMA and left caudate nucleus as well as that between the left caudate nucleus and right thalamus were stronger in response to incongruent vs. congruent endings. Copyright © 2012 Wiley Periodicals, Inc.

  1. Driven Factors Analysis of China’s Irrigation Water Use Efficiency by Stepwise Regression and Principal Component Analysis

    Directory of Open Access Journals (Sweden)

    Renfu Jia

    2016-01-01

    Full Text Available This paper introduces an integrated approach to find out the major factors influencing efficiency of irrigation water use in China. It combines multiple stepwise regression (MSR and principal component analysis (PCA to obtain more realistic results. In real world case studies, classical linear regression model often involves too many explanatory variables and the linear correlation issue among variables cannot be eliminated. Linearly correlated variables will cause the invalidity of the factor analysis results. To overcome this issue and reduce the number of the variables, PCA technique has been used combining with MSR. As such, the irrigation water use status in China was analyzed to find out the five major factors that have significant impacts on irrigation water use efficiency. To illustrate the performance of the proposed approach, the calculation based on real data was conducted and the results were shown in this paper.

  2. An efficient modeling of fine air-gaps in tokamak in-vessel components for electromagnetic analyses

    International Nuclear Information System (INIS)

    Oh, Dong Keun; Pak, Sunil; Jhang, Hogun

    2012-01-01

    Highlights: ► A simple and efficient modeling technique is introduced to avoid undesirable massive air mesh which is usually encountered at the modeling of fine structures in tokamak in-vessel component. ► This modeling method is based on the decoupled nodes at the boundary element mocking the air gaps. ► We demonstrated the viability and efficacy, comparing this method with brute force modeling of air-gaps and effective resistivity approximation instead of detail modeling. ► Application of the method to the ITER machine was successfully carried out without sacrificing computational resources and speed. - Abstract: A simple and efficient modeling technique is presented for a proper analysis of complicated eddy current flows in conducting structures with fine air gaps. It is based on the idea of replacing a slit with the decoupled boundary of finite elements. The viability and efficacy of the technique is demonstrated in a simple problem. Application of the method to electromagnetic load analyses during plasma disruptions in ITER has been successfully carried out without sacrificing computational resources and speed. This shows the proposed method is applicable to a practical system with complicated geometrical structures.

  3. A proposed centralised distribution model for the South African automotive component industry

    Directory of Open Access Journals (Sweden)

    Micheline J. Naude

    2009-12-01

    Full Text Available Purpose: This article explores the possibility of developing a distribution model, similar to the model developed and implemented by the South African pharmaceutical industry, which could be implemented by automotive component manufacturers for supply to independent retailers. Problem Investigated: The South African automotive components distribution chain is extensive with a number of players of varying sizes, from the larger spares distribution groups to a number of independent retailers. Distributing to the smaller independent retailers is costly for the automotive component manufacturers. Methodology: This study is based on a preliminary study of an explorative nature. Interviews were conducted with a senior staff member from a leading automotive component manufacturer in KwaZulu Natal and nine participants at a senior management level at five of their main customers (aftermarket retailers. Findings: The findings from the empirical study suggest that the aftermarket component industry is mature with the role players well established. The distribution chain to the independent retailer is expensive in terms of transaction and distribution costs for the automotive component manufacturer. A proposed centralised distribution model for supply to independent retailers has been developed which should reduce distribution costs for the automotive component manufacturer in terms of (1 the lowest possible freight rate; (2 timely and controlled delivery; and (3 reduced congestion at the customer's receiving dock. Originality: This research is original in that it explores the possibility of implementing a centralised distribution model for independent retailers in the automotive component industry. Furthermore, there is a dearth of published research on the South African automotive component industry particularly addressing distribution issues. Conclusion: The distribution model as suggested is a practical one and should deliver added value to automotive

  4. Independent and joint associations of TV viewing time and snack food consumption with the metabolic syndrome and its components; a cross-sectional study in Australian adults

    Science.gov (United States)

    2013-01-01

    Background Television (TV) viewing time is positively associated with the metabolic syndrome (MetS) in adults. However, the mechanisms through which TV viewing time is associated with MetS risk remain unclear. There is evidence that the consumption of energy-dense, nutrient poor snack foods increases during TV viewing time among adults, suggesting that these behaviors may jointly contribute towards MetS risk. While the association between TV viewing time and the MetS has previously been shown to be independent of adult’s overall dietary intake, the specific influence of snack food consumption on the relationship is yet to be investigated. The purpose of this study was to examine the independent and joint associations of daily TV viewing time and snack food consumption with the MetS and its components in a sample of Australian adults. Methods Population-based, cross-sectional study of 3,110 women and 2,572 men (>35 years) without diabetes or cardiovascular disease. Participants were recruited between May 1999 and Dec 2000 in the six states and the Northern Territory of Australia. Participants were categorised according to self-reported TV viewing time (low: 0-2 hr/d; high: >2 hr/d) and/or consumption of snack foods (low: 0-3 serves/d; high: >3 serves/d). Multivariate odds ratios [95% CI] for the MetS and its components were estimated using gender-specific, forced entry logistic regression. Results OR [95% CI] for the MetS was 3.59 [2.25, 5.74] (p≤0.001) in women and 1.45 [1.02, 3.45] (p = 0.04) in men who jointly reported high TV viewing time and high snack food consumption. Obesity, insulin resistance and hypertension (women only) were also jointly associated with high TV viewing time and high snack food consumption. Further adjustment for diet quality and central adiposity maintained the associations in women. High snack food consumption was also shown to be independently associated with MetS risk [OR: 1.94 (95% CI: 1.45, 2.60), p snack food

  5. Task-evoked brain functional magnetic susceptibility mapping by independent component analysis (χICA).

    Science.gov (United States)

    Chen, Zikuan; Calhoun, Vince D

    2016-03-01

    Conventionally, independent component analysis (ICA) is performed on an fMRI magnitude dataset to analyze brain functional mapping (AICA). By solving the inverse problem of fMRI, we can reconstruct the brain magnetic susceptibility (χ) functional states. Upon the reconstructed χ dataspace, we propose an ICA-based brain functional χ mapping method (χICA) to extract task-evoked brain functional map. A complex division algorithm is applied to a timeseries of fMRI phase images to extract temporal phase changes (relative to an OFF-state snapshot). A computed inverse MRI (CIMRI) model is used to reconstruct a 4D brain χ response dataset. χICA is implemented by applying a spatial InfoMax ICA algorithm to the reconstructed 4D χ dataspace. With finger-tapping experiments on a 7T system, the χICA-extracted χ-depicted functional map is similar to the SPM-inferred functional χ map by a spatial correlation of 0.67 ± 0.05. In comparison, the AICA-extracted magnitude-depicted map is correlated with the SPM magnitude map by 0.81 ± 0.05. The understanding of the inferiority of χICA to AICA for task-evoked functional map is an ongoing research topic. For task-evoked brain functional mapping, we compare the data-driven ICA method with the task-correlated SPM method. In particular, we compare χICA with AICA for extracting task-correlated timecourses and functional maps. χICA can extract a χ-depicted task-evoked brain functional map from a reconstructed χ dataspace without the knowledge about brain hemodynamic responses. The χICA-extracted brain functional χ map reveals a bidirectional BOLD response pattern that is unavailable (or different) from AICA. Copyright © 2016 Elsevier B.V. All rights reserved.

  6. The Research of Multiple Attenuation Based on Feedback Iteration and Independent Component Analysis

    Science.gov (United States)

    Xu, X.; Tong, S.; Wang, L.

    2017-12-01

    How to solve the problem of multiple suppression is a difficult problem in seismic data processing. The traditional technology for multiple attenuation is based on the principle of the minimum output energy of the seismic signal, this criterion is based on the second order statistics, and it can't achieve the multiple attenuation when the primaries and multiples are non-orthogonal. In order to solve the above problems, we combine the feedback iteration method based on the wave equation and the improved independent component analysis (ICA) based on high order statistics to suppress the multiple waves. We first use iterative feedback method to predict the free surface multiples of each order. Then, in order to predict multiples from real multiple in amplitude and phase, we design an expanded pseudo multi-channel matching filtering method to get a more accurate matching multiple result. Finally, we present the improved fast ICA algorithm which is based on the maximum non-Gauss criterion of output signal to the matching multiples and get better separation results of the primaries and the multiples. The advantage of our method is that we don't need any priori information to the prediction of the multiples, and can have a better separation result. The method has been applied to several synthetic data generated by finite-difference model technique and the Sigsbee2B model multiple data, the primaries and multiples are non-orthogonal in these models. The experiments show that after three to four iterations, we can get the perfect multiple results. Using our matching method and Fast ICA adaptive multiple subtraction, we can not only effectively preserve the effective wave energy in seismic records, but also can effectively suppress the free surface multiples, especially the multiples related to the middle and deep areas.

  7. Validation of RNAi Silencing Efficiency Using Gene Array Data shows 18.5% Failure Rate across 429 Independent Experiments

    Directory of Open Access Journals (Sweden)

    Gyöngyi Munkácsy

    2016-01-01

    Full Text Available No independent cross-validation of success rate for studies utilizing small interfering RNA (siRNA for gene silencing has been completed before. To assess the influence of experimental parameters like cell line, transfection technique, validation method, and type of control, we have to validate these in a large set of studies. We utilized gene chip data published for siRNA experiments to assess success rate and to compare methods used in these experiments. We searched NCBI GEO for samples with whole transcriptome analysis before and after gene silencing and evaluated the efficiency for the target and off-target genes using the array-based expression data. Wilcoxon signed-rank test was used to assess silencing efficacy and Kruskal–Wallis tests and Spearman rank correlation were used to evaluate study parameters. All together 1,643 samples representing 429 experiments published in 207 studies were evaluated. The fold change (FC of down-regulation of the target gene was above 0.7 in 18.5% and was above 0.5 in 38.7% of experiments. Silencing efficiency was lowest in MCF7 and highest in SW480 cells (FC = 0.59 and FC = 0.30, respectively, P = 9.3E−06. Studies utilizing Western blot for validation performed better than those with quantitative polymerase chain reaction (qPCR or microarray (FC = 0.43, FC = 0.47, and FC = 0.55, respectively, P = 2.8E−04. There was no correlation between type of control, transfection method, publication year, and silencing efficiency. Although gene silencing is a robust feature successfully cross-validated in the majority of experiments, efficiency remained insufficient in a significant proportion of studies. Selection of cell line model and validation method had the highest influence on silencing proficiency.

  8. Reliability prediction of engineering systems with competing failure modes due to component degradation

    International Nuclear Information System (INIS)

    Son, Young Kap

    2011-01-01

    Reliability of an engineering system depends on two reliability metrics: the mechanical reliability, considering component failures, that a functional system topology is maintained and the performance reliability of adequate system performance in each functional configuration. Component degradation explains not only the component aging processes leading to failure in function, but also system performance change over time. Multiple competing failure modes for systems with degrading components in terms of system functionality and system performance are considered in this paper with the assumption that system functionality is not independent of system performance. To reduce errors in system reliability prediction, this paper tries to extend system performance reliability prediction methods in open literature through combining system mechanical reliability from component reliabilities and system performance reliability. The extended reliability prediction method provides a useful way to compare designs as well as to determine effective maintenance policy for efficient reliability growth. Application of the method to an electro-mechanical system, as an illustrative example, is explained in detail, and the prediction results are discussed. Both mechanical reliability and performance reliability are compared to total system reliability in terms of reliability prediction errors

  9. Go Pink! The Effect of Secondary Quanta on Detective Quantum Efficiency

    Energy Technology Data Exchange (ETDEWEB)

    Watson, Scott [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2017-09-05

    Photons are never directly observable. Consequently, we often use photoelectric detectors (eg CCDs) to record associated photoelectrons statistically. Nonetheless, it is an implicit goal of radiographic detector designers to achieve the maximum possible detector efficiency1. In part the desire for ever higher efficiency has been due to the fact that detectors are far less expensive than associated accelerator facilities (e.g. DARHT and PHERMEX2). In addition, higher efficiency detectors often have better spatial resolution. Consequently, the optimization of the detector, not the accelerator, is the system component with the highest leverage per dollar. In recent years, imaging scientists have adopted the so-called Detective Quantum Efficiency, or DQE as a summary measure of detector performance. Unfortunately, owing to the complex nature of the trade-space associated with detector components, and the natural desire for simplicity and low(er) cost, there has been a recent trend in Los Alamos to focus only on the zerofrequency efficiency, or DQE(0), when designing such systems. This narrow focus leads to system designs that neglect or even ignore the importance of high-spatial-frequency image components. In this paper we demonstrate the significant negative impact of these design choices on the Noise Power Spectrum1 (NPS) and recommend a more holistic approach to detector design. Here we present a statistical argument which indicates that a very large number (>20) of secondary quanta (typically visible light and/or recorded photo-electrons) are needed to take maximum advantage of the primary quanta (typically x-rays or protons) which are available to form an image. Since secondary particles come in bursts, they are not independent. In short, we want to maximize the pink nature of detector noise at DARHT.

  10. Utilization of independent component analysis for accurate pathological ripple detection in intracranial EEG recordings recorded extra- and intra-operatively.

    Science.gov (United States)

    Shimamoto, Shoichi; Waldman, Zachary J; Orosz, Iren; Song, Inkyung; Bragin, Anatol; Fried, Itzhak; Engel, Jerome; Staba, Richard; Sharan, Ashwini; Wu, Chengyuan; Sperling, Michael R; Weiss, Shennan A

    2018-01-01

    To develop and validate a detector that identifies ripple (80-200 Hz) events in intracranial EEG (iEEG) recordings in a referential montage and utilizes independent component analysis (ICA) to eliminate or reduce high-frequency artifact contamination. Also, investigate the correspondence of detected ripples and the seizure onset zone (SOZ). iEEG recordings from 16 patients were first band-pass filtered (80-600 Hz) and Infomax ICA was next applied to derive the first independent component (IC1). IC1 was subsequently pruned, and an artifact index was derived to reduce the identification of high-frequency events introduced by the reference electrode signal. A Hilbert detector identified ripple events in the processed iEEG recordings using amplitude and duration criteria. The identified ripple events were further classified and characterized as true or false ripple on spikes, or ripples on oscillations by utilizing a topographical analysis to their time-frequency plot, and confirmed by visual inspection. The signal to noise ratio was improved by pruning IC1. The precision of the detector for ripple events was 91.27 ± 4.3%, and the sensitivity of the detector was 79.4 ± 3.0% (N = 16 patients, 5842 ripple events). The sensitivity and precision of the detector was equivalent in iEEG recordings obtained during sleep or intra-operatively. Across all the patients, true ripple on spike rates and also the rates of false ripple on spikes, that were generated due to filter ringing, classified the seizure onset zone (SOZ) with an area under the receiver operating curve (AUROC) of >76%. The magnitude and spectral content of true ripple on spikes generated in the SOZ was distinct as compared with the ripples generated in the NSOZ (p ripple rates and properties defined using this approach may accurately delineate the seizure onset zone. Strategies to improve the spatial resolution of intracranial EEG and reduce artifact can help improve the clinical utility of

  11. From independence to expansion and back again

    DEFF Research Database (Denmark)

    Christiani, Tobias Lybecker; Pagh, Rasmus; Thorup, Mikkel

    2015-01-01

    We consider the following fundamental problems: • Constructing k-independent hash functions with a spacetime tradeoff close to Siegel’s lower bound. • Constructing representations of unbalanced expander graphs having small size and allowing fast computation of the neighbor function. It is not hard...... to show that these problems are intimately connected in the sense that a good solution to one of them leads to a good solution to the other one. In this paper we exploit this connection to present efficient, recursive constructions of k-independent hash functions (and hence expanders with a small...... representation). While the previously most efficient construction (Thorup, FOCS 2013) needed time quasipolynomial in Siegel’s lower bound, our time bound is just a logarithmic factor from the lower bound....

  12. Effect of linear and non-linear components in the temperature dependences of thermoelectric properties on the energy conversion efficiency

    International Nuclear Information System (INIS)

    Yamashita, Osamu

    2009-01-01

    The new thermal rate equations were built up by taking the linear and non-linear components in the temperature dependences of the Seebeck coefficient α, the electrical resistivity ρ and thermal conductivity κ of a thermoelectric (TE) material into the thermal rate equations on the assumption that their temperature dependences are expressed by a quadratic function of temperature T. The energy conversion efficiency η for a single TE element was formulated using the new thermal rate ones proposed here. By applying it to the high-performance half-Heusler compound, the non-linear component in the temperature dependence of α among those of the TE properties has the greatest effect on η, so that η/η 0 was increased by 11% under the condition of T = 510 K and ΔT = 440 K, where η 0 is a well-known conventional energy conversion efficiency. It was thus found that the temperature dependences of TE properties have a significant influence on η. When one evaluates the accurate achievement rate of η exp obtained experimentally for a TE generator, therefore, η exp should be compared with η the estimated from the theoretical expression proposed here, not with η 0 , particularly when there is a strong non-linearity in the temperature dependence of TE properties.

  13. Application of independent component analysis to ac dipole based optics measurement and correction at the Relativistic Heavy Ion Collider

    Directory of Open Access Journals (Sweden)

    X. Shen

    2013-11-01

    Full Text Available Correction of beta-beat is of great importance for performance improvement of high energy accelerators, like the Relativistic Hadron Ion Collider (RHIC. At RHIC, using the independent component analysis method, linear optical functions are extracted from the turn by turn beam position data of the ac dipole driven betatron oscillation. Despite the constraint of a limited number of available quadrupole correctors at RHIC, a global beta-beat correction scheme using a beta-beat response matrix method was developed and experimentally demonstrated. In both rings, a factor of 2 or better reduction of beta-beat was achieved within available beam time. At the same time, a new scheme of using horizontal closed orbit bump at sextupoles to correct beta-beat in the arcs was demonstrated in the Yellow ring of RHIC at beam energy of 255 GeV, and a peak beta-beat of approximately 7% was achieved.

  14. Comparison of conventional filtering and independent component analysis for artifact reduction in simultaneous gastric EMG and magnetogastrography from porcines.

    Science.gov (United States)

    Irimia, Andrei; Richards, William O; Bradshaw, L Alan

    2009-11-01

    In this study, we perform a comparative study of independent component analysis (ICA) and conventional filtering (CF) for the purpose of artifact reduction from simultaneous gastric EMG and magnetogastrography (MGG). EMG/MGG data were acquired from ten anesthetized pigs by obtaining simultaneous recordings using serosal electrodes (EMG) as well as with a superconducting quantum interference device biomagnetometer (MGG). The analysis of MGG waveforms using ICA and CF indicates that ICA is superior to the CF method in its ability to extract respiration and cardiac artifacts from MGG recordings. A signal frequency analysis of ICA- and CF-processed data was also undertaken using waterfall plots, and it was determined that the two methods produce qualitatively comparable results. Through the use of simultaneous EMG/MGG, we were able to demonstrate the accuracy and trustworthiness of our results by comparison and cross-validation within the framework of a porcine model.

  15. Efficient scattering-angle enrichment for a nonlinear inversion of the background and perturbations components of a velocity model

    KAUST Repository

    Wu, Zedong

    2017-07-04

    Reflection-waveform inversion (RWI) can help us reduce the nonlinearity of the standard full-waveform inversion (FWI) by inverting for the background velocity model using the wave-path of a single scattered wavefield to an image. However, current RWI implementations usually neglect the multi-scattered energy, which will cause some artifacts in the image and the update of the background. To improve existing RWI implementations in taking multi-scattered energy into consideration, we split the velocity model into background and perturbation components, integrate them directly in the wave equation, and formulate a new optimization problem for both components. In this case, the perturbed model is no longer a single-scattering model, but includes all scattering. Through introducing a new cheap implementation of scattering angle enrichment, the separation of the background and perturbation components can be implemented efficiently. We optimize both components simultaneously to produce updates to the velocity model that is nonlinear with respect to both the background and the perturbation. The newly introduced perturbation model can absorb the non-smooth update of the background in a more consistent way. We apply the proposed approach on the Marmousi model with data that contain frequencies starting from 5 Hz to show that this method can converge to an accurate velocity starting from a linearly increasing initial velocity. Also, our proposed method works well when applied to a field data set.

  16. A Layered Searchable Encryption Scheme with Functional Components Independent of Encryption Methods

    Science.gov (United States)

    Luo, Guangchun; Qin, Ke

    2014-01-01

    Searchable encryption technique enables the users to securely store and search their documents over the remote semitrusted server, which is especially suitable for protecting sensitive data in the cloud. However, various settings (based on symmetric or asymmetric encryption) and functionalities (ranked keyword query, range query, phrase query, etc.) are often realized by different methods with different searchable structures that are generally not compatible with each other, which limits the scope of application and hinders the functional extensions. We prove that asymmetric searchable structure could be converted to symmetric structure, and functions could be modeled separately apart from the core searchable structure. Based on this observation, we propose a layered searchable encryption (LSE) scheme, which provides compatibility, flexibility, and security for various settings and functionalities. In this scheme, the outputs of the core searchable component based on either symmetric or asymmetric setting are converted to some uniform mappings, which are then transmitted to loosely coupled functional components to further filter the results. In such a way, all functional components could directly support both symmetric and asymmetric settings. Based on LSE, we propose two representative and novel constructions for ranked keyword query (previously only available in symmetric scheme) and range query (previously only available in asymmetric scheme). PMID:24719565

  17. Connected Component Model for Multi-Object Tracking.

    Science.gov (United States)

    He, Zhenyu; Li, Xin; You, Xinge; Tao, Dacheng; Tang, Yuan Yan

    2016-08-01

    In multi-object tracking, it is critical to explore the data associations by exploiting the temporal information from a sequence of frames rather than the information from the adjacent two frames. Since straightforwardly obtaining data associations from multi-frames is an NP-hard multi-dimensional assignment (MDA) problem, most existing methods solve this MDA problem by either developing complicated approximate algorithms, or simplifying MDA as a 2D assignment problem based upon the information extracted only from adjacent frames. In this paper, we show that the relation between associations of two observations is the equivalence relation in the data association problem, based on the spatial-temporal constraint that the trajectories of different objects must be disjoint. Therefore, the MDA problem can be equivalently divided into independent subproblems by equivalence partitioning. In contrast to existing works for solving the MDA problem, we develop a connected component model (CCM) by exploiting the constraints of the data association and the equivalence relation on the constraints. Based upon CCM, we can efficiently obtain the global solution of the MDA problem for multi-object tracking by optimizing a sequence of independent data association subproblems. Experiments on challenging public data sets demonstrate that our algorithm outperforms the state-of-the-art approaches.

  18. Quantitative evaluation of deep and shallow tissue layers' contribution to fNIRS signal using multi-distance optodes and independent component analysis.

    Science.gov (United States)

    Funane, Tsukasa; Atsumori, Hirokazu; Katura, Takusige; Obata, Akiko N; Sato, Hiroki; Tanikawa, Yukari; Okada, Eiji; Kiguchi, Masashi

    2014-01-15

    To quantify the effect of absorption changes in the deep tissue (cerebral) and shallow tissue (scalp, skin) layers on functional near-infrared spectroscopy (fNIRS) signals, a method using multi-distance (MD) optodes and independent component analysis (ICA), referred to as the MD-ICA method, is proposed. In previous studies, when the signal from the shallow tissue layer (shallow signal) needs to be eliminated, it was often assumed that the shallow signal had no correlation with the signal from the deep tissue layer (deep signal). In this study, no relationship between the waveforms of deep and shallow signals is assumed, and instead, it is assumed that both signals are linear combinations of multiple signal sources, which allows the inclusion of a "shared component" (such as systemic signals) that is contained in both layers. The method also assumes that the partial optical path length of the shallow layer does not change, whereas that of the deep layer linearly increases along with the increase of the source-detector (S-D) distance. Deep- and shallow-layer contribution ratios of each independent component (IC) are calculated using the dependence of the weight of each IC on the S-D distance. Reconstruction of deep- and shallow-layer signals are performed by the sum of ICs weighted by the deep and shallow contribution ratio. Experimental validation of the principle of this technique was conducted using a dynamic phantom with two absorbing layers. Results showed that our method is effective for evaluating deep-layer contributions even if there are high correlations between deep and shallow signals. Next, we applied the method to fNIRS signals obtained on a human head with 5-, 15-, and 30-mm S-D distances during a verbal fluency task, a verbal working memory task (prefrontal area), a finger tapping task (motor area), and a tetrametric visual checker-board task (occipital area) and then estimated the deep-layer contribution ratio. To evaluate the signal separation

  19. INDICATORS AND DIAGNOSTICS OF INDEPENDENT WORK CULTURE FORMATION IN FUTURE MATHEMATICS TEACHERS

    Directory of Open Access Journals (Sweden)

    Олена Соя

    2015-09-01

    Full Text Available The article highlights the results of research of formation the culture of independent work of future mathematics teachers, indicating the effectiveness of selected theoretically grounded and practically implemented pedagogical conditions of its formation. Its semantic components that are interconnected and interdependent unity of cognitive, procedural, technological and motivational components were singled out on the basis of definition of independent work culture of future mathematics teachers. The system of indicators, which assessed the degree of mastering by students the culture of independent work by value-orientation, content-effective, reflective, constructive and operationally-activity criteria is reviewed.

  20. Unsupervised neural spike sorting for high-density microelectrode arrays with convolutive independent component analysis.

    Science.gov (United States)

    Leibig, Christian; Wachtler, Thomas; Zeck, Günther

    2016-09-15

    Unsupervised identification of action potentials in multi-channel extracellular recordings, in particular from high-density microelectrode arrays with thousands of sensors, is an unresolved problem. While independent component analysis (ICA) achieves rapid unsupervised sorting, it ignores the convolutive structure of extracellular data, thus limiting the unmixing to a subset of neurons. Here we present a spike sorting algorithm based on convolutive ICA (cICA) to retrieve a larger number of accurately sorted neurons than with instantaneous ICA while accounting for signal overlaps. Spike sorting was applied to datasets with varying signal-to-noise ratios (SNR: 3-12) and 27% spike overlaps, sampled at either 11.5 or 23kHz on 4365 electrodes. We demonstrate how the instantaneity assumption in ICA-based algorithms has to be relaxed in order to improve the spike sorting performance for high-density microelectrode array recordings. Reformulating the convolutive mixture as an instantaneous mixture by modeling several delayed samples jointly is necessary to increase signal-to-noise ratio. Our results emphasize that different cICA algorithms are not equivalent. Spike sorting performance was assessed with ground-truth data generated from experimentally derived templates. The presented spike sorter was able to extract ≈90% of the true spike trains with an error rate below 2%. It was superior to two alternative (c)ICA methods (≈80% accurately sorted neurons) and comparable to a supervised sorting. Our new algorithm represents a fast solution to overcome the current bottleneck in spike sorting of large datasets generated by simultaneous recording with thousands of electrodes. Copyright © 2016 Elsevier B.V. All rights reserved.

  1. The Institutional Component of the Efficient Economic Policy of the State

    Directory of Open Access Journals (Sweden)

    Mykytas Viktoriia V

    2016-01-01

    Full Text Available The article substantiates the necessity of institutional accompanying the economic policy of the State, establishing an efficient system of institutions. Challenges of the contemporary globalization require changes in the State influence on economy, redefining quality parameters and principles of an efficient economic policy. Complexity of the State policy in a global environment is determined not only by importance of the tasks of establishing an efficient market against the background of increasing influences of exogenous uncertainty, but also by seeking ways of entering the global space, thus implementing the best interests of national economic development. The article deduces parameters of the concept of «efficient institution». The author believes that institutions precisely should act as the link through which social and economic development would become unseparated in order to form a stable efficient socio-economic development

  2. Hybrid polylingual object model: an efficient and seamless integration of Java and native components on the Dalvik virtual machine.

    Science.gov (United States)

    Huang, Yukun; Chen, Rong; Wei, Jingbo; Pei, Xilong; Cao, Jing; Prakash Jayaraman, Prem; Ranjan, Rajiv

    2014-01-01

    JNI in the Android platform is often observed with low efficiency and high coding complexity. Although many researchers have investigated the JNI mechanism, few of them solve the efficiency and the complexity problems of JNI in the Android platform simultaneously. In this paper, a hybrid polylingual object (HPO) model is proposed to allow a CAR object being accessed as a Java object and as vice in the Dalvik virtual machine. It is an acceptable substitute for JNI to reuse the CAR-compliant components in Android applications in a seamless and efficient way. The metadata injection mechanism is designed to support the automatic mapping and reflection between CAR objects and Java objects. A prototype virtual machine, called HPO-Dalvik, is implemented by extending the Dalvik virtual machine to support the HPO model. Lifespan management, garbage collection, and data type transformation of HPO objects are also handled in the HPO-Dalvik virtual machine automatically. The experimental result shows that the HPO model outweighs the standard JNI in lower overhead on native side, better executing performance with no JNI bridging code being demanded.

  3. Prior-knowledge-independent equalization to improve battery uniformity with energy efficiency and time efficiency for lithium-ion battery

    International Nuclear Information System (INIS)

    Zhang, Shumei; Qiang, Jiaxi; Yang, Lin; Zhao, Xiaowei

    2016-01-01

    To improve battery uniformity as well as energy efficiency and time efficiency, a SOC (state of charge)-based equalization by AGA (adaptive genetic algorithm) is proposed on basis of two-stage DC/DC converters. The simulation results indicate that compared with FLC (fuzzy logic controller) equalization, the standard deviation of final SOC is improved by 78.7% while energy efficiency is improved by 6.01% and equalization time is decreased by 20% for AGA equalization of extreme dispersion. Additionally, AGA improves the battery uniformity by 30.77% with shortening equalization time by 16.29% and saving energy loss by 1.51% compared with FLC for equalization of regular dispersion. For further validation, the equalization optimization is verified by experiment based on the data-driven parameter identification method which is used to enhance the real-time capability of AGA. For AGA equalization of extreme dispersion, the standard deviation of final SOC is just 0.41% while equalization time prolongs only 14 min and energy efficiency is decreased by 0.81% compared with simulation results. Moreover, not only the standard deviation of final SOC is just 0.28% but also the energy efficiency is decreased by 0.69% and equalization time prolongs by 10.4 min compared with the simulation results for equalization of regular dispersion. - Highlights: • Issues of over equalization, time consumption and energy loss are addressed. • A SOC-based equalization is proposed based on adaptive genetic algorithm. • The equalization aims to improve battery uniformity, efficiency of energy and time. • Data-driven parameter identification is used to enhance the real-time capability.

  4. Resting State EEG in Children With Learning Disabilities: An Independent Component Analysis Approach.

    Science.gov (United States)

    Jäncke, Lutz; Alahmadi, Nsreen

    2016-01-01

    In this study, the neurophysiological underpinnings of learning disabilities (LD) in children are examined using resting state EEG. We were particularly interested in the neurophysiological differences between children with learning disabilities not otherwise specified (LD-NOS), learning disabilities with verbal disabilities (LD-Verbal), and healthy control (HC) children. We applied 2 different approaches to examine the differences between the different groups. First, we calculated theta/beta and theta/alpha ratios in order to quantify the relationship between slow and fast EEG oscillations. Second, we used a recently developed method for analyzing spectral EEG, namely the group independent component analysis (gICA) model. Using these measures, we identified substantial differences between LD and HC children and between LD-NOS and LD-Verbal children in terms of their spectral EEG profiles. We obtained the following findings: (a) theta/beta and theta/alpha ratios were substantially larger in LD than in HC children, with no difference between LD-NOS and LD-Verbal children; (b) there was substantial slowing of EEG oscillations, especially for gICs located in frontal scalp positions, with LD-NOS children demonstrating the strongest slowing; (c) the estimated intracortical sources of these gICs were mostly located in brain areas involved in the control of executive functions, attention, planning, and language; and (d) the LD-Verbal children demonstrated substantial differences in EEG oscillations compared with LD-NOS children, and these differences were localized in language-related brain areas. The general pattern of atypical neurophysiological activation found in LD children suggests that they suffer from neurophysiological dysfunction in brain areas involved with the control of attention, executive functions, planning, and language functions. LD-Verbal children also demonstrate atypical activation, especially in language-related brain areas. These atypical

  5. Suppression of the µ rhythm during speech and non-speech discrimination revealed by independent component analysis: implications for sensorimotor integration in speech processing.

    Science.gov (United States)

    Bowers, Andrew; Saltuklaroglu, Tim; Harkrider, Ashley; Cuellar, Megan

    2013-01-01

    Constructivist theories propose that articulatory hypotheses about incoming phonetic targets may function to enhance perception by limiting the possibilities for sensory analysis. To provide evidence for this proposal, it is necessary to map ongoing, high-temporal resolution changes in sensorimotor activity (i.e., the sensorimotor μ rhythm) to accurate speech and non-speech discrimination performance (i.e., correct trials.). Sixteen participants (15 female and 1 male) were asked to passively listen to or actively identify speech and tone-sweeps in a two-force choice discrimination task while the electroencephalograph (EEG) was recorded from 32 channels. The stimuli were presented at signal-to-noise ratios (SNRs) in which discrimination accuracy was high (i.e., 80-100%) and low SNRs producing discrimination performance at chance. EEG data were decomposed using independent component analysis and clustered across participants using principle component methods in EEGLAB. ICA revealed left and right sensorimotor µ components for 14/16 and 13/16 participants respectively that were identified on the basis of scalp topography, spectral peaks, and localization to the precentral and postcentral gyri. Time-frequency analysis of left and right lateralized µ component clusters revealed significant (pFDRspeech discrimination trials relative to chance trials following stimulus offset. Findings are consistent with constructivist, internal model theories proposing that early forward motor models generate predictions about likely phonemic units that are then synthesized with incoming sensory cues during active as opposed to passive processing. Future directions and possible translational value for clinical populations in which sensorimotor integration may play a functional role are discussed.

  6. Mixing efficiency inside micro-droplets coalesced by two components in cross-structure

    Science.gov (United States)

    Ren, Yanlin; Liu, Zhaomiao; Pang, Yan

    2017-11-01

    The mixing of micro-droplets is used in analytical chemistry, medicine production and material synthesis owing to its advantages including the encapsulation and narrow time residence distribution. In this work, droplets are coalesced by two dispersed phase with different flow rates, generated in cross-structure and mixed in planar serpentine structure. The mixing efficiency of micro-droplets under control characters including the width of entrance and the flow rate of dispersed phases have been investigated by experiments and numerical simulations. The UDS (user-defined scalar) as dimensionless concentration of the solution is adopted in simulation, and is used to calculate the concentration and the mixing effect. By changing the flow rates and the entrances` width, the changing rules of the mixing characters have been obtained. The asymmetry distributions of components make rapid mixing process in half part of each droplet when travel through a straight channel. Increasing of the ratio of entrance width result into larger droplet and weaken the chaotic mixing effect. Meanwhile, the coalesced mechanism can be performed by ranging the ratio of flow rates, the ranges are also determined by the widths of entrances. The authors gratefully acknowledge the support of National Natural Science Foundation of China (Grant No. 11572013).

  7. Attenuation of artifacts in EEG signals measured inside an MRI scanner using constrained independent component analysis

    International Nuclear Information System (INIS)

    Rasheed, Tahir; Lee, Young-Koo; Lee, Soo Yeol; Kim, Tae-Seong

    2009-01-01

    Integration of electroencephalography (EEG) and functional magnetic imaging (fMRI) resonance will allow analysis of the brain activities at superior temporal and spatial resolution. However simultaneous acquisition of EEG and fMRI is hindered by the enhancement of artifacts in EEG, the most prominent of which are ballistocardiogram (BCG) and electro-oculogram (EOG) artifacts. The situation gets even worse if the evoked potentials are measured inside MRI for their minute responses in comparison to the spontaneous brain responses. In this study, we propose a new method of attenuating these artifacts from the spontaneous and evoked EEG data acquired inside an MRI scanner using constrained independent component analysis with a priori information about the artifacts as constraints. With the proposed techniques of reference function generation for the BCG and EOG artifacts as constraints, our new approach performs significantly better than the averaged artifact subtraction (AAS) method. The proposed method could be an alternative to the conventional ICA method for artifact attenuation, with some advantages. As a performance measure we have achieved much improved normalized power spectrum ratios (INPS) for continuous EEG and correlation coefficient (cc) values with outside MRI visual evoked potentials for visual evoked EEG, as compared to those obtained with the AAS method. The results show that our new approach is more effective than the conventional methods, almost fully automatic, and no extra ECG signal measurements are involved

  8. Attribution of emotions to body postures: an independent component analysis study of functional connectivity in autism.

    Science.gov (United States)

    Libero, Lauren E; Stevens, Carl E; Kana, Rajesh K

    2014-10-01

    The ability to interpret others' body language is a vital skill that helps us infer their thoughts and emotions. However, individuals with autism spectrum disorder (ASD) have been found to have difficulty in understanding the meaning of people's body language, perhaps leading to an overarching deficit in processing emotions. The current fMRI study investigates the functional connectivity underlying emotion and action judgment in the context of processing body language in high-functioning adolescents and young adults with autism, using an independent components analysis (ICA) of the fMRI time series. While there were no reliable group differences in brain activity, the ICA revealed significant involvement of occipital and parietal regions in processing body actions; and inferior frontal gyrus, superior medial prefrontal cortex, and occipital cortex in body expressions of emotions. In a between-group analysis, participants with autism, relative to typical controls, demonstrated significantly reduced temporal coherence in left ventral premotor cortex and right superior parietal lobule while processing emotions. Participants with ASD, on the other hand, showed increased temporal coherence in left fusiform gyrus while inferring emotions from body postures. Finally, a positive predictive relationship was found between empathizing ability and the brain areas underlying emotion processing in ASD participants. These results underscore the differential role of frontal and parietal brain regions in processing emotional body language in autism. Copyright © 2014 Wiley Periodicals, Inc.

  9. Empirical validation of the triple-code model of numerical processing for complex math operations using functional MRI and group Independent Component Analysis of the mental addition and subtraction of fractions.

    Science.gov (United States)

    Schmithorst, Vincent J; Brown, Rhonda Douglas

    2004-07-01

    The suitability of a previously hypothesized triple-code model of numerical processing, involving analog magnitude, auditory verbal, and visual Arabic codes of representation, was investigated for the complex mathematical task of the mental addition and subtraction of fractions. Functional magnetic resonance imaging (fMRI) data from 15 normal adult subjects were processed using exploratory group Independent Component Analysis (ICA). Separate task-related components were found with activation in bilateral inferior parietal, left perisylvian, and ventral occipitotemporal areas. These results support the hypothesized triple-code model corresponding to the activated regions found in the individual components and indicate that the triple-code model may be a suitable framework for analyzing the neuropsychological bases of the performance of complex mathematical tasks. Copyright 2004 Elsevier Inc.

  10. An efficient ASIC implementation of 16-channel on-line recursive ICA processor for real-time EEG system.

    Science.gov (United States)

    Fang, Wai-Chi; Huang, Kuan-Ju; Chou, Chia-Ching; Chang, Jui-Chung; Cauwenberghs, Gert; Jung, Tzyy-Ping

    2014-01-01

    This is a proposal for an efficient very-large-scale integration (VLSI) design, 16-channel on-line recursive independent component analysis (ORICA) processor ASIC for real-time EEG system, implemented with TSMC 40 nm CMOS technology. ORICA is appropriate to be used in real-time EEG system to separate artifacts because of its highly efficient and real-time process features. The proposed ORICA processor is composed of an ORICA processing unit and a singular value decomposition (SVD) processing unit. Compared with previous work [1], this proposed ORICA processor has enhanced effectiveness and reduced hardware complexity by utilizing a deeper pipeline architecture, shared arithmetic processing unit, and shared registers. The 16-channel random signals which contain 8-channel super-Gaussian and 8-channel sub-Gaussian components are used to analyze the dependence of the source components, and the average correlation coefficient is 0.95452 between the original source signals and extracted ORICA signals. Finally, the proposed ORICA processor ASIC is implemented with TSMC 40 nm CMOS technology, and it consumes 15.72 mW at 100 MHz operating frequency.

  11. Separating spectral mixtures in hyperspectral image data using independent component analysis: validation with oral cancer tissue sections

    Science.gov (United States)

    Duann, Jeng-Ren; Jan, Chia-Ing; Ou-Yang, Mang; Lin, Chia-Yi; Mo, Jen-Feng; Lin, Yung-Jiun; Tsai, Ming-Hsui; Chiou, Jin-Chern

    2013-12-01

    Recently, hyperspectral imaging (HSI) systems, which can provide 100 or more wavelengths of emission autofluorescence measures, have been used to delineate more complete spectral patterns associated with certain molecules relevant to cancerization. Such a spectral fingerprint may reliably correspond to a certain type of molecule and thus can be treated as a biomarker for the presence of that molecule. However, the outcomes of HSI systems can be a complex mixture of characteristic spectra of a variety of molecules as well as optical interferences due to reflection, scattering, and refraction. As a result, the mixed nature of raw HSI data might obscure the extraction of consistent spectral fingerprints. Here we present the extraction of the characteristic spectra associated with keratinized tissues from the HSI data of tissue sections from 30 oral cancer patients (31 tissue samples in total), excited at two different wavelength ranges (330 to 385 and 470 to 490 nm), using independent and principal component analysis (ICA and PCA) methods. The results showed that for both excitation wavelength ranges, ICA was able to resolve much more reliable spectral fingerprints associated with the keratinized tissues for all the oral cancer tissue sections with significantly higher mean correlation coefficients as compared to PCA (p<0.001).

  12. Coordination of Energy Efficiency and Demand Response

    Energy Technology Data Exchange (ETDEWEB)

    Goldman, Charles; Reid, Michael; Levy, Roger; Silverstein, Alison

    2010-01-29

    This paper reviews the relationship between energy efficiency and demand response and discusses approaches and barriers to coordinating energy efficiency and demand response. The paper is intended to support the 10 implementation goals of the National Action Plan for Energy Efficiency's Vision to achieve all cost-effective energy efficiency by 2025. Improving energy efficiency in our homes, businesses, schools, governments, and industries - which consume more than 70 percent of the nation's natural gas and electricity - is one of the most constructive, cost-effective ways to address the challenges of high energy prices, energy security and independence, air pollution, and global climate change. While energy efficiency is an increasingly prominent component of efforts to supply affordable, reliable, secure, and clean electric power, demand response is becoming a valuable tool in utility and regional resource plans. The Federal Energy Regulatory Commission (FERC) estimated the contribution from existing U.S. demand response resources at about 41,000 megawatts (MW), about 5.8 percent of 2008 summer peak demand (FERC, 2008). Moreover, FERC recently estimated nationwide achievable demand response potential at 138,000 MW (14 percent of peak demand) by 2019 (FERC, 2009).2 A recent Electric Power Research Institute study estimates that 'the combination of demand response and energy efficiency programs has the potential to reduce non-coincident summer peak demand by 157 GW' by 2030, or 14-20 percent below projected levels (EPRI, 2009a). This paper supports the Action Plan's effort to coordinate energy efficiency and demand response programs to maximize value to customers. For information on the full suite of policy and programmatic options for removing barriers to energy efficiency, see the Vision for 2025 and the various other Action Plan papers and guides available at www.epa.gov/eeactionplan.

  13. Male pre- and post-pubertal castration effect on live weight, components of empty body weight, estimated nitrogen excretion and efficiency in Piemontese hypertrofic cattle

    Directory of Open Access Journals (Sweden)

    Davide Biagini

    2011-04-01

    Full Text Available To evaluate the effect of sexual neutering and age of castration on empty body weight (EBW components and estimated nitrogen excretion and efficiency, a trial was carried out on 3 groups of double-muscled Piemontese calves: early castrated (EC, 5th month of age, late castrated (LC, 12th month of age and intact males (IM, control group. Animals were fed at the same energy and protein level and slaughtered at 18th month of age. Live and slaughtering performances and EBW components were recorded, whereas N excretion was calculated by difference between diet and weight gain N content. In live and slaughtering performances, IM showed higher final, carcass and total meat weight than EC and LC (P<0.01. In EBW components, IM showed higher blood and head weight than EC and LC (P<0.01 and 0.05 respectively, and differences were found between EC and LC for head weights (P<0.01. IM showed higher body crude protein (BCP than EC and LC (P<0.01 and 0.05 respectively, but BCP/EBW ratio was higher only in IM than EC (P<0.05. Estimated N daily gain was higher in IM than EC and LC (P<0.01. Only LC showed higher excretion than IM (P<0.05, and N efficiency was higher in IM than EC and LC (P<0.05 and 0.01 respectively. In conclusion, for the Piemontese hypertrophied cattle castration significantly increases N excretion (+7% and reduces N efficiency (-15%, leading to a lower level of sustainability.

  14. DEVELOPMENT OF METHODOLOGY FOR DESIGNING TESTABLE COMPONENT STRUCTURE OF DISCIPLINARY COMPETENCE

    Directory of Open Access Journals (Sweden)

    Vladimir I. Freyman

    2014-01-01

    Full Text Available The aim of the study is to present new methods of quality results assessment of the education corresponding to requirements of Federal State Educational Standards (FSES of the Third Generation developed for the higher school. The urgency of search of adequate tools for quality competency measurement and its elements formed in the course of experts’ preparation are specified. Methods. It is necessary to consider interference of competency components such as knowledge, abilities, possession in order to make procedures of assessment of students’ achievements within the limits of separate discipline or curriculum section more convenient, effective and exact. While modeling of component structure of the disciplinary competence the testable design of components is used; the approach borrowed from technical diagnostics. Results. The research outcomes include the definition and analysis of general iterative methodology for testable designing component structure of the disciplinary competence. Application of the proposed methodology is illustrated as the example of an abstract academic discipline with specified data and index of labour requirement. Methodology restrictions are noted; practical recommendations are given. Scientific novelty. Basic data and a detailed step-by-step implementation phase of the proposed common iterative approach to the development of disciplinary competence testable component structure are considered. Tests and diagnostic tables for different options of designing are proposed. Practical significance. The research findings can help promoting learning efficiency increase, a choice of adequate control devices, accuracy of assessment, and also efficient use of personnel, temporal and material resources of higher education institutions. Proposed algorithms, methods and approaches to procedure of control results organization and realization of developed competences and its components can be used as methodical base while

  15. Gauge origin independent calculations of molecular magnetisabilities in relativistic four-component theory

    DEFF Research Database (Denmark)

    Iliaš, M.; Jensen, Hans Jørgen Aagaard; Bast, R.

    2013-01-01

    of the four-component relativistic linear response method at the self-consistent field single reference level. Benefits of employing the London atomic orbitals in relativistic calculations are illustrated with Hartree-Fock wave functions on the XF3 (X = N, P, As, Sb, Bi) series of molecules. Significantly...

  16. Hybrid PolyLingual Object Model: An Efficient and Seamless Integration of Java and Native Components on the Dalvik Virtual Machine

    Directory of Open Access Journals (Sweden)

    Yukun Huang

    2014-01-01

    Full Text Available JNI in the Android platform is often observed with low efficiency and high coding complexity. Although many researchers have investigated the JNI mechanism, few of them solve the efficiency and the complexity problems of JNI in the Android platform simultaneously. In this paper, a hybrid polylingual object (HPO model is proposed to allow a CAR object being accessed as a Java object and as vice in the Dalvik virtual machine. It is an acceptable substitute for JNI to reuse the CAR-compliant components in Android applications in a seamless and efficient way. The metadata injection mechanism is designed to support the automatic mapping and reflection between CAR objects and Java objects. A prototype virtual machine, called HPO-Dalvik, is implemented by extending the Dalvik virtual machine to support the HPO model. Lifespan management, garbage collection, and data type transformation of HPO objects are also handled in the HPO-Dalvik virtual machine automatically. The experimental result shows that the HPO model outweighs the standard JNI in lower overhead on native side, better executing performance with no JNI bridging code being demanded.

  17. An Efficient Connected Component Labeling Architecture for Embedded Systems

    Directory of Open Access Journals (Sweden)

    Fanny Spagnolo

    2018-03-01

    Full Text Available Connected component analysis is one of the most fundamental steps used in several image processing systems. This technique allows for distinguishing and detecting different objects in images by assigning a unique label to all pixels that refer to the same object. Most of the previous published algorithms have been designed for implementation by software. However, due to the large number of memory accesses and compare, lookup, and control operations when executed on a general-purpose processor, they do not satisfy the speed performance required by the next generation high performance computer vision systems. In this paper, we present the design of a new Connected Component Labeling hardware architecture suitable for high performance heterogeneous image processing of embedded designs. When implemented on a Zynq All Programmable-System on Chip (AP-SOC 7045 chip, the proposed design allows a throughput rate higher of 220 Mpixels/s to be reached using less than 18,000 LUTs and 5000 FFs, dissipating about 620 μJ.

  18. Efficient secretion of small proteins in mammalian cells relies on Sec62-dependent posttranslational translocation

    Science.gov (United States)

    Lakkaraju, Asvin K. K.; Thankappan, Ratheeshkumar; Mary, Camille; Garrison, Jennifer L.; Taunton, Jack; Strub, Katharina

    2012-01-01

    Mammalian cells secrete a large number of small proteins, but their mode of translocation into the endoplasmic reticulum is not fully understood. Cotranslational translocation was expected to be inefficient due to the small time window for signal sequence recognition by the signal recognition particle (SRP). Impairing the SRP pathway and reducing cellular levels of the translocon component Sec62 by RNA interference, we found an alternate, Sec62-dependent translocation path in mammalian cells required for the efficient translocation of small proteins with N-terminal signal sequences. The Sec62-dependent translocation occurs posttranslationally via the Sec61 translocon and requires ATP. We classified preproteins into three groups: 1) those that comprise ≤100 amino acids are strongly dependent on Sec62 for efficient translocation; 2) those in the size range of 120–160 amino acids use the SRP pathway, albeit inefficiently, and therefore rely on Sec62 for efficient translocation; and 3) those larger than 160 amino acids depend on the SRP pathway to preserve a transient translocation competence independent of Sec62. Thus, unlike in yeast, the Sec62-dependent translocation pathway in mammalian cells serves mainly as a fail-safe mechanism to ensure efficient secretion of small proteins and provides cells with an opportunity to regulate secretion of small proteins independent of the SRP pathway. PMID:22648169

  19. Cooling systems for efficient operation of induction heating installations; Kuehlsysteme fuer den effizienten Betrieb von Induktionsschmelzanlagen

    Energy Technology Data Exchange (ETDEWEB)

    Doetsch, Erwin; Schmidt, Juergen [ABP Induction Systems GmbH, Dortmund (Germany)

    2009-12-15

    Electrical and thermal losses in the system components of induction melting systems are mainly carried off by the cooling water. The design and maintenance of the corresponding cooling systems play a decisive role in the operating reliability of induction installations. Due to the differing requirements made on water quality, cooling of the furnace and the electrical components is generally accomplished by means of two independent cooling circuits, which are described below. The article also examines utilization of waste-heat, which has a particular significance for energy-efficiency, since more than a fourth of the furnace power, in the case of melting of ferrous materials, and more than half, in the case of non-ferrous materials, is lost. (orig.)

  20. Productive performance and efficiency of utilization of the diet components in dairy cows fed castor meal treated with calcium oxide

    Directory of Open Access Journals (Sweden)

    Juliana Variz Cobianchi

    2012-10-01

    Full Text Available The effect of replacing of 0; 0.33; 0.67 and 1.0 (kg/kg of soybean meal (SBM by undecorticated castor seed meal treated with calcium oxide (CMT - 60 g/kg was evaluated on performance and efficiency of nutrient utilization in dairy cows. Sixteen Holstein and crossbred cows were distributed in four 4 × 4 latin squares. Animals received concentrated feed at a ratio of 1 kg for 3 kg of milk produced, in the natural matter. The diets had the same amount of nitrogen (150.4 g crude protein/kg DM, containing 325.6 g of concentrated feed/kg DM. There was no effect on the serum concentration of transaminase and the animals showed no clinical symptoms of intoxication by ricin. The intake of DM, crude protein (CP and non-fibrous carbohydrates (NFC reduced from 0.67 replacement of SBM by CMT. The intake of neutral detergent fibers corrected for ash and protein (NDFap increased from 0.33 replacement of SBM with CMT. Although the digestibility of dietary components decreased from 0.33 replacement, the intake of digestible components only reduced from 0.67 replacement. Because of the reduction of digestible energy, the synthesis of microbial CP and the utilization efficiency of rumen-degradable protein for the synthesis of microbial CP reduced with full replacement of SBM by CMT. Milk yield, milk composition, daily variation of body weight and the efficiency of utilization of the nutrients for the synthesis of N in milk reduced from 0.67 replacement of SBM by CMT. Castor seed meal treated with calcium oxide can replace up to 0.33 of SBM (50 g/kg DM diet DM in the diet of dairy cows with an average milk production of 20 kg/day.

  1. Optimization of high-efficiency components; Optimieren auf hohem Niveau

    Energy Technology Data Exchange (ETDEWEB)

    Neumann, Eva

    2009-07-01

    High efficiency is a common feature of modern current inverters and is not a unique selling proposition. Other factors that influence the buyer's decision are cost reduction, reliability and service, optimum grid integration, and the challenges of the competitive thin film technology. (orig.)

  2. Effect of Mycorrhiza Symbiosis on Yield, Yield Components and Water Use Efficiency of Sesame (Sesamum indicum L. Affected by Different Irrigation Regimes in Mashhad Condition

    Directory of Open Access Journals (Sweden)

    A Koocheki

    2016-02-01

    Full Text Available Introduction Plant association with mycorrhiza has been considered as one of the options to improve input efficiency particularly for water and nutrient - (Allen and Musik, 1993; Bolan, 1991. This has been due to kncreasing the absorbing area of the root and therefore better contact with water and nutrients. Inoculation with mycorrhiza enhances nutrient uptake with low immobility such as phosphorus and solphur-, improve association and could be an option to drought and other environmental abnormalities such as salinity (Rice et al., 2002. Moreover, higher water use efficiency (WUE for crops -has been reported in the literatures (Sekhara and Reddy, 1993.The sustainable use of scarce water resources in Iran is a priority for agricultural development. The pressure of using water in agriculture sector is increasing, so creating ways to improve water-use efficiency and taking a full advantage of available water are crucial. Water stress reduce crop yield by impairing the growth of crop canopy and biomass. Scheduling water application is very crucial for efficient use of drip irrigation system, as excessive irrigation reduces yield, while inadequate irrigation causes water stress and reduces production. The aim of present study was to evaluate the symbiotic effect of mycorrhiza on yield, yield components and water use efficiency of sesame under different irrigation regimes in Mashhad. Material and Methods In order to investigate the impact of inoculation with two species of Arbuscular mycorrhiza fungi on yield, yield components and water use efficiency (WUE of sesame (Sesamum indicum L. under different irrigation regimes, an experiment was conducted as split plot based on a randomized complete block design with three replications during two growing seasons 2009-2010 and 2010-2011 at the Agricultural Research Station, College of Agriculture, Ferdowsi University of Mashhad.. The experimental factors were three irrigation regimes include 2000, 3000 and

  3. Availability, reliability and downtime of systems with repairable components

    DEFF Research Database (Denmark)

    Kiureghian, Armen Der; Ditlevsen, Ove Dalager; Song, J.

    2007-01-01

    Closed-form expressions are derived for the steady-state availability, mean rate of failure, mean duration of downtime and lower bound reliability of a general system with randomly and independently failing repairable components. Component failures are assumed to be homogeneous Poisson events in ...

  4. MANAGEMENT CONTROL SYSTEMS: A REVIEW OF THEIR COMPONENTS AND THEIR UNDERLYING INDEPENDENCE

    Directory of Open Access Journals (Sweden)

    Boghean Florin

    2013-07-01

    The organization of the internal control system in a manner that is divergent with the principles of planned economy has led managers to believe that control activities are discretionary, and the subsequent lack of management responsibility has weakened the efficiency of internal control systems during the first years after 1989.

  5. Making Judges Independent – Some Proposals Regarding the Judiciary

    OpenAIRE

    Lars P. Feld; Stefan Voigt

    2004-01-01

    It is argued that an independent judiciary is a necessary condition for both individual liberty and economic prosperity. After having surveyed the literature dealing with how to arrange for an independent judiciary, the authors derive some additional policy implications by drawing on two indicators of judicial independence (JI) recently introduced by them. De facto JI has a robust and highly significant impact on economic growth. Individual components of both de jure and de facto JI on econom...

  6. Evidence for modality-independent order coding in working memory.

    Science.gov (United States)

    Depoorter, Ann; Vandierendonck, André

    2009-03-01

    The aim of the present study was to investigate the representation of serial order in working memory, more specifically whether serial order is coded by means of a modality-dependent or a modality-independent order code. This was investigated by means of a series of four experiments based on a dual-task methodology in which one short-term memory task was embedded between the presentation and recall of another short-term memory task. Two aspects were varied in these memory tasks--namely, the modality of the stimulus materials (verbal or visuo-spatial) and the presence of an order component in the task (an order or an item memory task). The results of this study showed impaired primary-task recognition performance when both the primary and the embedded task included an order component, irrespective of the modality of the stimulus materials. If one or both of the tasks did not contain an order component, less interference was found. The results of this study support the existence of a modality-independent order code.

  7. Board Size and Board Independence: A Quantitative Study on Banking Industry in Pakistan

    Directory of Open Access Journals (Sweden)

    Kashif Rashid

    2014-12-01

    Full Text Available This paper aims to investigate the relationship of board independence and board size with productivity and efficiency of the listed banks on the Karachi Stock Exchange, Pakistan. There is a lack of consensus regarding impact of corporate governance practices in correspondence to number of board members and board independence in banking sector. The derived results of the study show that there is a positive relationship between board independence and bank profitability and efficiency. Independent directors play a crucial role in providing genuine advice during executive decision making process which is an important source for improving overall corporate governance. Moreover, results regarding the role of control variables suggest a positive relationship of the total assets and deposits of the firm with the firm’s performance supporting stewardship theory in the market.

  8. Shifted Independent Component Analysis

    DEFF Research Database (Denmark)

    Mørup, Morten; Madsen, Kristoffer Hougaard; Hansen, Lars Kai

    2007-01-01

    Delayed mixing is a problem of theoretical interest and practical importance, e.g., in speech processing, bio-medical signal analysis and financial data modelling. Most previous analyses have been based on models with integer shifts, i.e., shifts by a number of samples, and have often been carried...

  9. Imprecise system reliability and component importance based on survival signature

    International Nuclear Information System (INIS)

    Feng, Geng; Patelli, Edoardo; Beer, Michael; Coolen, Frank P.A.

    2016-01-01

    The concept of the survival signature has recently attracted increasing attention for performing reliability analysis on systems with multiple types of components. It opens a new pathway for a structured approach with high computational efficiency based on a complete probabilistic description of the system. In practical applications, however, some of the parameters of the system might not be defined completely due to limited data, which implies the need to take imprecisions of component specifications into account. This paper presents a methodology to include explicitly the imprecision, which leads to upper and lower bounds of the survival function of the system. In addition, the approach introduces novel and efficient component importance measures. By implementing relative importance index of each component without or with imprecision, the most critical component in the system can be identified depending on the service time of the system. Simulation method based on survival signature is introduced to deal with imprecision within components, which is precise and efficient. Numerical example is presented to show the applicability of the approach for systems. - Highlights: • Survival signature is a novel way for system reliability and component importance • High computational efficiency based on a complete description of system. • Include explicitly the imprecision, which leads to bounds of the survival function. • A novel relative importance index is proposed as importance measure. • Allows to identify critical components depending on the service time of the system.

  10. An efficient synthesis of β-amino ketone compounds through one-pot three-component Mannich-type reactions using bismuth nitrate as catalyst

    Directory of Open Access Journals (Sweden)

    S. Sheik Mansoor

    2015-07-01

    Full Text Available Three components one-pot Mannich reaction of aromatic ketone, aromatic aldehyde and aromatic amines has been efficiently catalyzed by recyclable bismuth nitrate (Bi(NO33, BN at ambient temperature to give various β-amino carbonyl compounds in high yields. This method has advantages of mild condition, no environmental pollution, and simple work-up procedures. Most importantly, β-amino carbonyl compounds with ortho-substituted aromatic amines are obtained in acceptable to moderate yields by this methodology.

  11. Speeding up Coarse Point Cloud Registration by Threshold-Independent Baysac Match Selection

    Science.gov (United States)

    Kang, Z.; Lindenbergh, R.; Pu, S.

    2016-06-01

    This paper presents an algorithm for the automatic registration of terrestrial point clouds by match selection using an efficiently conditional sampling method -- threshold-independent BaySAC (BAYes SAmpling Consensus) and employs the error metric of average point-to-surface residual to reduce the random measurement error and then approach the real registration error. BaySAC and other basic sampling algorithms usually need to artificially determine a threshold by which inlier points are identified, which leads to a threshold-dependent verification process. Therefore, we applied the LMedS method to construct the cost function that is used to determine the optimum model to reduce the influence of human factors and improve the robustness of the model estimate. Point-to-point and point-to-surface error metrics are most commonly used. However, point-to-point error in general consists of at least two components, random measurement error and systematic error as a result of a remaining error in the found rigid body transformation. Thus we employ the measure of the average point-to-surface residual to evaluate the registration accuracy. The proposed approaches, together with a traditional RANSAC approach, are tested on four data sets acquired by three different scanners in terms of their computational efficiency and quality of the final registration. The registration results show the st.dev of the average point-to-surface residuals is reduced from 1.4 cm (plain RANSAC) to 0.5 cm (threshold-independent BaySAC). The results also show that, compared to the performance of RANSAC, our BaySAC strategies lead to less iterations and cheaper computational cost when the hypothesis set is contaminated with more outliers.

  12. Rapid discrimination of plastic packaging materials using MIR spectroscopy coupled with independent components analysis (ICA).

    Science.gov (United States)

    Kassouf, Amine; Maalouly, Jacqueline; Rutledge, Douglas N; Chebib, Hanna; Ducruet, Violette

    2014-11-01

    Plastic packaging wastes increased considerably in recent decades, raising a major and serious public concern on political, economical and environmental levels. Dealing with this kind of problems is generally done by landfilling and energy recovery. However, these two methods are becoming more and more expensive, hazardous to the public health and the environment. Therefore, recycling is gaining worldwide consideration as a solution to decrease the growing volume of plastic packaging wastes and simultaneously reduce the consumption of oil required to produce virgin resin. Nevertheless, a major shortage is encountered in recycling which is related to the sorting of plastic wastes. In this paper, a feasibility study was performed in order to test the potential of an innovative approach combining mid infrared (MIR) spectroscopy with independent components analysis (ICA), as a simple and fast approach which could achieve high separation rates. This approach (MIR-ICA) gave 100% discrimination rates in the separation of all studied plastics: polyethylene terephthalate (PET), polyethylene (PE), polypropylene (PP), polystyrene (PS) and polylactide (PLA). In addition, some more specific discriminations were obtained separating plastic materials belonging to the same polymer family e.g. high density polyethylene (HDPE) from low density polyethylene (LDPE). High discrimination rates were obtained despite the heterogeneity among samples especially differences in colors, thicknesses and surface textures. The reproducibility of the proposed approach was also tested using two spectrometers with considerable differences in their sensitivities. Discrimination rates were not affected proving that the developed approach could be extrapolated to different spectrometers. MIR combined with ICA is a promising tool for plastic waste separation that can help improve performance in this field; however further technological improvements and developments are required before it can be applied

  13. Graviton propagator from background-independent quantum gravity.

    Science.gov (United States)

    Rovelli, Carlo

    2006-10-13

    We study the graviton propagator in Euclidean loop quantum gravity. We use spin foam, boundary-amplitude, and group-field-theory techniques. We compute a component of the propagator to first order, under some approximations, obtaining the correct large-distance behavior. This indicates a way for deriving conventional spacetime quantities from a background-independent theory.

  14. THE EFFICIENCY AND WAVELENGTH DEPENDENCE OF NEAR-INFRARED INTERSTELLAR POLARIZATION TOWARD THE GALACTIC CENTER

    Energy Technology Data Exchange (ETDEWEB)

    Hatano, Hirofumi; Kurita, Mikio; Kanai, Saori; Sato, Shuji [Department of Astrophysics, Nagoya University, Chikusa-ku, Nagoya 464-8602 (Japan); Nishiyama, Shogo; Nakajima, Yasushi; Tamura, Motohide; Kandori, Ryo [National Astronomical Observatory of Japan, Mitaka, Tokyo 181-8858 (Japan); Nagata, Tetsuya; Yoshikawa, Tatsuhito [Department of Astronomy, Kyoto University, Sakyo-ku, Kyoto 606-8502 (Japan); Kato, Daisuke [Department of Astronomy, School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033 (Japan); Sato, Yaeko; Suenaga, Takuya, E-mail: hattan@z.phys.nagoya-u.ac.jp, E-mail: shogo.nishiyama@nao.ac.jp [Department of Astronomical Sciences, Graduate University for Advanced Studies (Sokendai), Mitaka, Tokyo 181-8858 (Japan)

    2013-04-15

    Near-infrared polarimetric imaging observations toward the Galactic center (GC) have been carried out to examine the efficiency and wavelength dependence of interstellar polarization. A total area of about 5.7 deg{sup 2} is covered in the J, H, and K{sub S} bands. We examined the polarization efficiency, defined as the ratio of the degree of polarization to color excess. The interstellar medium between the GC and us shows a polarization efficiency lower than that in the Galactic disk by a factor of three. Moreover we investigated the spatial variation of the polarization efficiency by comparing it with that of the color excess, degree of polarization, and position angle. The spatial variations of color excess and degree of polarization depend on the Galactic latitude, while the polarization efficiency varies independently of the Galactic structure. Position angles are nearly parallel to the Galactic plane, indicating a longitudinal magnetic field configuration between the GC and us. The polarization efficiency anticorrelates with dispersions of position angles. The low polarization efficiency and its spatial variation can be explained by the differences in the magnetic field directions along the line of sight. From the lower polarization efficiency, we suggest a higher strength of a random component relative to a uniform component of the magnetic field between the GC and us. We also derived the ratios of degree of polarization p{sub H} /p{sub J} = 0.581 {+-} 0.004 and p{sub K{sub S}}/p{sub H} = 0.620 {+-} 0.002. The power-law indices of the wavelength dependence of polarization are {beta}{sub JH} = 2.08 {+-} 0.02 and {beta}{sub HK{sub S}} = 1.76 {+-} 0.01. Therefore, the wavelength dependence of interstellar polarization exhibits flattening toward longer wavelengths in the range of 1.25-2.14 {mu}m. The flattening would be caused by aligned large-size dust grains.

  15. Ceric ammonium nitrate catalysed three component one-pot efficient ...

    Indian Academy of Sciences (India)

    Wintec

    heterocyclic compounds. 26 here, we present a simple, mild and efficient protocol for synthesis of 2,4,5- triaryl-1H-imidazoles using CAN catalyst. 2. Experimental. 1. H NMR spectra were recorded on a 400 MHz Var- ian-Gemini spectrometer and are reported as parts per million (ppm) downfield from a tetramethylsi- ...

  16. Time–energy high-dimensional one-side device-independent quantum key distribution

    International Nuclear Information System (INIS)

    Bao Hai-Ze; Bao Wan-Su; Wang Yang; Chen Rui-Ke; Ma Hong-Xin; Zhou Chun; Li Hong-Wei

    2017-01-01

    Compared with full device-independent quantum key distribution (DI-QKD), one-side device-independent QKD (1sDI-QKD) needs fewer requirements, which is much easier to meet. In this paper, by applying recently developed novel time–energy entropic uncertainty relations, we present a time–energy high-dimensional one-side device-independent quantum key distribution (HD-QKD) and provide the security proof against coherent attacks. Besides, we connect the security with the quantum steering. By numerical simulation, we obtain the secret key rate for Alice’s different detection efficiencies. The results show that our protocol can performance much better than the original 1sDI-QKD. Furthermore, we clarify the relation among the secret key rate, Alice’s detection efficiency, and the dispersion coefficient. Finally, we simply analyze its performance in the optical fiber channel. (paper)

  17. Impact test of components

    International Nuclear Information System (INIS)

    Borsoi, L.; Buland, P.; Labbe, P.

    1987-01-01

    Stops with gaps are currently used to support components and piping: it is simple, low cost, efficient and permits free thermal expansion. In order to keep the nonlinear nature of stops, such design is often modeled by beam elements (for the component) and nonlinear springs (for the stops). This paper deals with the validity and the limits of these models through the comparison of computational and experimental results. The experimental results come from impact laboratory tests on a simplified mockup. (orig.)

  18. Incorporating diffuse radiation into a light use efficiency and evapotranspiration model: An 11-year study in a high latitude deciduous forest

    DEFF Research Database (Denmark)

    Wang, Sheng; Ibrom, Andreas; Bauer-Gottwein, Peter

    2018-01-01

    set were used to statistically explore the independent and joint effects of diffuse PAR on GPP, ET, incident light use efficiency (LUE), evaporative fraction (EF) and ecosystem water use efficiency (WUE). The independent and joint effects of CI were compared from global sensitivity analysis...... pressure saturation deficit played a major role for the joint influence of CI on LUE and EF. In the growing season from May to October, variation in CI accounts for 11.9%, 3.0% and 7.8% of the total variation of GPP, ET and transpiration, respectively. As the influence of CI on GPP is larger than...... PAR with plant canopies, the largest model improvements using CI for GPP and ET occurred during the growing season and for the transpiration component, as suggested by comparisons to sap flow measurements. Furthermore, our study suggests a potential biophysical mechanism, not considered in other...

  19. A novel high efficiency solar photovoltalic pump

    NARCIS (Netherlands)

    Diepens, J.F.L.; Smulders, P.T.; Vries, de D.A.

    1993-01-01

    The daily average overall efficiency of a solar pump system is not only influenced by the maximum efficiency of the components of the system, but just as much by the correct matching of the components to the local irradiation pattern. Normally centrifugal pumps are used in solar pump systems. The

  20. Are Independent Probes Truly Independent?

    Science.gov (United States)

    Camp, Gino; Pecher, Diane; Schmidt, Henk G.; Zeelenberg, Rene

    2009-01-01

    The independent cue technique has been developed to test traditional interference theories against inhibition theories of forgetting. In the present study, the authors tested the critical criterion for the independence of independent cues: Studied cues not presented during test (and unrelated to test cues) should not contribute to the retrieval…

  1. Efficient numerical methods for simulating surface tension of multi-component mixtures with the gradient theory of fluid interfaces

    KAUST Repository

    Kou, Jisheng

    2015-08-01

    Surface tension significantly impacts subsurface flow and transport, and it is the main cause of capillary effect, a major immiscible two-phase flow mechanism for systems with a strong wettability preference. In this paper, we consider the numerical simulation of the surface tension of multi-component mixtures with the gradient theory of fluid interfaces. Major numerical challenges include that the system of the Euler-Lagrange equations is solved on the infinite interval and the coefficient matrix is not positive definite. We construct a linear transformation to reduce the Euler-Lagrange equations, and naturally introduce a path function, which is proven to be a monotonic function of the spatial coordinate variable. By using the linear transformation and the path function, we overcome the above difficulties and develop the efficient methods for calculating the interface and its interior compositions. Moreover, the computation of the surface tension is also simplified. The proposed methods do not need to solve the differential equation system, and they are easy to be implemented in practical applications. Numerical examples are tested to verify the efficiency of the proposed methods. © 2014 Elsevier B.V.

  2. Memory attacks on device-independent quantum cryptography.

    Science.gov (United States)

    Barrett, Jonathan; Colbeck, Roger; Kent, Adrian

    2013-01-04

    Device-independent quantum cryptographic schemes aim to guarantee security to users based only on the output statistics of any components used, and without the need to verify their internal functionality. Since this would protect users against untrustworthy or incompetent manufacturers, sabotage, or device degradation, this idea has excited much interest, and many device-independent schemes have been proposed. Here we identify a critical weakness of device-independent protocols that rely on public communication between secure laboratories. Untrusted devices may record their inputs and outputs and reveal information about them via publicly discussed outputs during later runs. Reusing devices thus compromises the security of a protocol and risks leaking secret data. Possible defenses include securely destroying or isolating used devices. However, these are costly and often impractical. We propose other more practical partial defenses as well as a new protocol structure for device-independent quantum key distribution that aims to achieve composable security in the case of two parties using a small number of devices to repeatedly share keys with each other (and no other party).

  3. Cortical networks involved in visual awareness independent of visual attention.

    Science.gov (United States)

    Webb, Taylor W; Igelström, Kajsa M; Schurger, Aaron; Graziano, Michael S A

    2016-11-29

    It is now well established that visual attention, as measured with standard spatial attention tasks, and visual awareness, as measured by report, can be dissociated. It is possible to attend to a stimulus with no reported awareness of the stimulus. We used a behavioral paradigm in which people were aware of a stimulus in one condition and unaware of it in another condition, but the stimulus drew a similar amount of spatial attention in both conditions. The paradigm allowed us to test for brain regions active in association with awareness independent of level of attention. Participants performed the task in an MRI scanner. We looked for brain regions that were more active in the aware than the unaware trials. The largest cluster of activity was obtained in the temporoparietal junction (TPJ) bilaterally. Local independent component analysis (ICA) revealed that this activity contained three distinct, but overlapping, components: a bilateral, anterior component; a left dorsal component; and a right dorsal component. These components had brain-wide functional connectivity that partially overlapped the ventral attention network and the frontoparietal control network. In contrast, no significant activity in association with awareness was found in the banks of the intraparietal sulcus, a region connected to the dorsal attention network and traditionally associated with attention control. These results show the importance of separating awareness and attention when testing for cortical substrates. They are also consistent with a recent proposal that awareness is associated with ventral attention areas, especially in the TPJ.

  4. High-throughput shadow mask printing of passive electrical components on paper by supersonic cluster beam deposition

    Energy Technology Data Exchange (ETDEWEB)

    Caruso, Francesco; Bellacicca, Andrea; Milani, Paolo, E-mail: pmilani@mi.infn.it [CIMaINa and Dipartimento di Fisica, Università degli Studi di Milano, Via Celoria 16, 20133 Milano (Italy)

    2016-04-18

    We report the rapid prototyping of passive electrical components (resistors and capacitors) on plain paper by an additive and parallel technology consisting of supersonic cluster beam deposition (SCBD) coupled with shadow mask printing. Cluster-assembled films have a growth mechanism substantially different from that of atom-assembled ones providing the possibility of a fine tuning of their electrical conduction properties around the percolative conduction threshold. Exploiting the precise control on cluster beam intensity and shape typical of SCBD, we produced, in a one-step process, batches of resistors with resistance values spanning a range of two orders of magnitude. Parallel plate capacitors with paper as the dielectric medium were also produced with capacitance in the range of tens of picofarads. Compared to standard deposition technologies, SCBD allows for a very efficient use of raw materials and the rapid production of components with different shape and dimensions while controlling independently the electrical characteristics. Discrete electrical components produced by SCBD are very robust against deformation and bending, and they can be easily assembled to build circuits with desired characteristics. The availability of large batches of these components enables the rapid and cheap prototyping and integration of electrical components on paper as building blocks of more complex systems.

  5. Codon optimization of the HIV-1 vpu and vif genes stabilizes their mRNA and allows for highly efficient Rev-independent expression

    International Nuclear Information System (INIS)

    Nguyen, Kim-Lien; Llano, Manuel; Akari, Hirofumi; Miyagi, Eri; Poeschla, Eric M.; Strebel, Klaus; Bour, Stephan

    2004-01-01

    Two HIV-1 accessory proteins, Vpu and Vif, are notoriously difficult to express autonomously in the absence of the viral Tat and Rev proteins. We examined whether the codon bias observed in the vpu and vif genes relative to highly expressed human genes contributes to the Rev dependence and low expression level outside the context of the viral genome. The entire vpu gene as well as the 5' half of the vif gene were codon optimized and the resulting open reading frames (ORFs) (vphu and hvif, respectively) were cloned in autonomous expression vectors under the transcriptional control of the CMV promoter. Codon optimization efficiently removed the expression block observed in the native genes and allowed high levels of Rev- and Tat-independent expression of Vpu and Vif. Most of the higher protein levels detected are accounted for by enhanced steady-state levels of the mRNA encoding the optimized species. Nuclear run-on experiments show for the first time that codon optimization has no effect on the rate of transcriptional initiation or elongation of the vphu mRNA. Instead, optimization of the vpu gene was found to stabilize the vphu mRNA in the nucleus and enhance its export to the cytoplasm. This was achieved by allowing the optimized mRNA to use a new CRM1-independent nuclear export pathway. This work provides a better understanding of the molecular mechanisms underlying the process of codon optimization and introduces novel tools to study the biological functions of the Vpu and Vif proteins independently of other viral proteins

  6. Component Structure of Individual Differences in True and False Recognition of Faces

    Science.gov (United States)

    Bartlett, James C.; Shastri, Kalyan K.; Abdi, Herve; Neville-Smith, Marsha

    2009-01-01

    Principal-component analyses of 4 face-recognition studies uncovered 2 independent components. The first component was strongly related to false-alarm errors with new faces as well as to facial "conjunctions" that recombine features of previously studied faces. The second component was strongly related to hits as well as to the conjunction/new…

  7. Recent progresses of neural network unsupervised learning: I. Independent component analyses generalizing PCA

    Science.gov (United States)

    Szu, Harold H.

    1999-03-01

    The early vision principle of redundancy reduction of 108 sensor excitations is understandable from computer vision viewpoint toward sparse edge maps. It is only recently derived using a truly unsupervised learning paradigm of artificial neural networks (ANN). In fact, the biological vision, Hubel- Wiesel edge maps, is reproduced seeking the underlying independent components analyses (ICA) among 102 image samples by maximizing the ANN output entropy (partial)H(V)/(partial)[W] equals (partial)[W]/(partial)t. When a pair of newborn eyes or ears meet the bustling and hustling world without supervision, they seek ICA by comparing 2 sensory measurements (x1(t), x2(t))T equalsV X(t). Assuming a linear and instantaneous mixture model of the external world X(t) equals [A] S(t), where both the mixing matrix ([A] equalsV [a1, a2] of ICA vectors and the source percentages (s1(t), s2(t))T equalsV S(t) are unknown, we seek the independent sources approximately equals [I] where the approximated sign indicates that higher order statistics (HOS) may not be trivial. Without a teacher, the ANN weight matrix [W] equalsV [w1, w2] adjusts the outputs V(t) equals tanh([W]X(t)) approximately equals [W]X(t) until no desired outputs except the (Gaussian) 'garbage' (neither YES '1' nor NO '-1' but at linear may-be range 'origin 0') defined by Gaussian covariance G equals [I] equals [W][A] the internal knowledge representation [W], as the inverse of the external world matrix [A]-1. To unify IC, PCA, ANN & HOS theories since 1991 (advanced by Jutten & Herault, Comon, Oja, Bell-Sejnowski, Amari-Cichocki, Cardoso), the LYAPONOV function L(v1,...,vn, w1,...wn,) equals E(v1,...,vn) - H(w1,...wn) is constructed as the HELMHOTZ free energy to prove both convergences of supervised energy E and unsupervised entropy H learning. Consequently, rather using the faithful but dumb computer: 'GARBAGE-IN, GARBAGE-OUT,' the smarter neurocomputer will be equipped with an unsupervised learning that extracts

  8. Phonemes as short time cognitive components

    DEFF Research Database (Denmark)

    Feng, Ling; Hansen, Lars Kai

    2006-01-01

    are the smallest contrastive unit in the sound system of a language. Generalizable components were found deriving from phonemes based on homomorphic filtering features with basic time scale (20 msec). We sparsified the features based on energy as a preprocessing means to eliminate the intrinsic noise. Independent...

  9. Hemispheric connectivity and the visual-spatial divergent-thinking component of creativity.

    Science.gov (United States)

    Moore, Dana W; Bhadelia, Rafeeque A; Billings, Rebecca L; Fulwiler, Carl; Heilman, Kenneth M; Rood, Kenneth M J; Gansler, David A

    2009-08-01

    Divergent thinking is an important measurable component of creativity. This study tested the postulate that divergent thinking depends on large distributed inter- and intra-hemispheric networks. Although preliminary evidence supports increased brain connectivity during divergent thinking, the neural correlates of this characteristic have not been entirely specified. It was predicted that visuospatial divergent thinking would correlate with right hemisphere white matter volume (WMV) and with the size of the corpus callosum (CC). Volumetric magnetic resonance imaging (MRI) analyses and the Torrance Tests of Creative Thinking (TTCT) were completed among 21 normal right-handed adult males. TTCT scores correlated negatively with the size of the CC and were not correlated with right or, incidentally, left WMV. Although these results were not predicted, perhaps, as suggested by Bogen and Bogen (1988), decreased callosal connectivity enhances hemispheric specialization, which benefits the incubation of ideas that are critical for the divergent-thinking component of creativity, and it is the momentary inhibition of this hemispheric independence that accounts for the illumination that is part of the innovative stage of creativity. Alternatively, decreased CC size may reflect more selective developmental pruning, thereby facilitating efficient functional connectivity.

  10. Application of independent component analysis for speech-music separation using an efficient score function estimation

    Science.gov (United States)

    Pishravian, Arash; Aghabozorgi Sahaf, Masoud Reza

    2012-12-01

    In this paper speech-music separation using Blind Source Separation is discussed. The separating algorithm is based on the mutual information minimization where the natural gradient algorithm is used for minimization. In order to do that, score function estimation from observation signals (combination of speech and music) samples is needed. The accuracy and the speed of the mentioned estimation will affect on the quality of the separated signals and the processing time of the algorithm. The score function estimation in the presented algorithm is based on Gaussian mixture based kernel density estimation method. The experimental results of the presented algorithm on the speech-music separation and comparing to the separating algorithm which is based on the Minimum Mean Square Error estimator, indicate that it can cause better performance and less processing time

  11. The efficacy and efficiency of Disability Management in job-retention and job-reintegration. A systematic review.

    Science.gov (United States)

    Lefever, Marlies; Decuman, Saskia; Perl, François; Braeckman, Lutgart; Van de Velde, Dominique

    2018-01-01

    Disability management (DM) is a systematic method to ensure job-retention and job-reintegration in competitive employment for individuals with a disability. There is evidence that 'returning to work' has a positive impact on the individual, the company and on the society. However, a clear overview of the efficacy and efficiency of the DM programs is scarce. To systematically review the efficacy and efficiency of the disability management programs. Cochrane, PubMed, Google Scholar, and Web of Science were searched from 1994 to 2015. Two reviewers independently evaluated the articles on title, abstract, and full text. The data extraction and results are documented according to the study designs. Twenty-eight articles were included in the review. These 28 articles consisted of 7 systematic reviews, 3 randomized controlled trials, 9 clinical trials, 4 mixed-method studies and 5 qualitative studies. The DM program has shown to be effective and efficient. A consensus about the DM components is still not reached. Nevertheless, some components are emphasized more than others; job accommodation, facilitation of transitional duty, communication between all stakeholders, health care provider advice, early intervention, and acceptance, goodwill and trust in the stakeholders, in the organization, and in the disability management process.

  12. Design and Implementation of a High Efficiency, Low Component Voltage Stress, Single-Switch High Step-Up Voltage Converter for Vehicular Green Energy Systems

    Directory of Open Access Journals (Sweden)

    Yu-En Wu

    2016-09-01

    Full Text Available In this study, a novel, non-isolated, cascade-type, single-switch, high step-up DC/DC converter was developed for green energy systems. An integrated coupled inductor and voltage lift circuit were applied to simplify the converter structure and satisfy the requirements of high efficiency and high voltage gain ratios. In addition, the proposed structure is controllable with a single switch, which effectively reduces the circuit cost and simplifies the control circuit. With the leakage inductor energy recovery function and active voltage clamp characteristics being present, the circuit yields optimizable conversion efficiency and low component voltage stress. After the operating principles of the proposed structure and characteristics of a steady-state circuit were analyzed, a converter prototype with 450 W, 40 V of input voltage, 400 V of output voltage, and 95% operating efficiency was fabricated. The Renesas MCU RX62T was employed to control the circuits. Experimental results were analyzed to validate the feasibility and effectiveness of the proposed system.

  13. Instrument-independent analysis of music by means of the continuous wavelet transform

    Science.gov (United States)

    Olmo, Gabriella; Dovis, Fabio; Benotto, Paolo; Calosso, Claudio; Passaro, Pierluigi

    1999-10-01

    This paper deals with the problem of automatic recognition of music. Segments of digitized music are processed by means of a Continuous Wavelet Transform, properly chosen so as to match the spectral characteristics of the signal. In order to achieve a good time-scale representation of the signal components a novel wavelet has been designed suited to the musical signal features. particular care has been devoted towards an efficient implementation, which operates in the frequency domain, and includes proper segmentation and aliasing reduction techniques to make the analysis of long signals feasible. The method achieves very good performance in terms of both time and frequency selectivity, and can yield the estimate and the localization in time of both the fundamental frequency and the main harmonics of each tone. The analysis is used as a preprocessing step for a recognition algorithm, which we show to be almost independent on the instrument reproducing the sounds. Simulations are provided to demonstrate the effectiveness of the proposed method.

  14. Quantitative Efficiency Evaluation Method for Transportation Networks

    Directory of Open Access Journals (Sweden)

    Jin Qin

    2014-11-01

    Full Text Available An effective evaluation of transportation network efficiency/performance is essential to the establishment of sustainable development in any transportation system. Based on a redefinition of transportation network efficiency, a quantitative efficiency evaluation method for transportation network is proposed, which could reflect the effects of network structure, traffic demands, travel choice, and travel costs on network efficiency. Furthermore, the efficiency-oriented importance measure for network components is presented, which can be used to help engineers identify the critical nodes and links in the network. The numerical examples show that, compared with existing efficiency evaluation methods, the network efficiency value calculated by the method proposed in this paper can portray the real operation situation of the transportation network as well as the effects of main factors on network efficiency. We also find that the network efficiency and the importance values of the network components both are functions of demands and network structure in the transportation network.

  15. Mass-flux subgrid-scale parameterization in analogy with multi-component flows: a formulation towards scale independence

    Directory of Open Access Journals (Sweden)

    J.-I. Yano

    2012-11-01

    Full Text Available A generalized mass-flux formulation is presented, which no longer takes a limit of vanishing fractional areas for subgrid-scale components. The presented formulation is applicable to a~situation in which the scale separation is still satisfied, but fractional areas occupied by individual subgrid-scale components are no longer small. A self-consistent formulation is presented by generalizing the mass-flux formulation under the segmentally-constant approximation (SCA to the grid–scale variabilities. The present formulation is expected to alleviate problems arising from increasing resolutions of operational forecast models without invoking more extensive overhaul of parameterizations.

    The present formulation leads to an analogy of the large-scale atmospheric flow with multi-component flows. This analogy allows a generality of including any subgrid-scale variability into the mass-flux parameterization under SCA. Those include stratiform clouds as well as cold pools in the boundary layer.

    An important finding under the present formulation is that the subgrid-scale quantities are advected by the large-scale velocities characteristic of given subgrid-scale components (large-scale subcomponent flows, rather than by the total large-scale flows as simply defined by grid-box average. In this manner, each subgrid-scale component behaves as if like a component of multi-component flows. This formulation, as a result, ensures the lateral interaction of subgrid-scale variability crossing the grid boxes, which are missing in the current parameterizations based on vertical one-dimensional models, and leading to a reduction of the grid-size dependencies in its performance. It is shown that the large-scale subcomponent flows are driven by large-scale subcomponent pressure gradients. The formulation, as a result, furthermore includes a self-contained description of subgrid-scale momentum transport.

    The main purpose of the present paper

  16. Efficient coding of spectrotemporal binaural sounds leads to emergence of the auditory space representation

    Science.gov (United States)

    Młynarski, Wiktor

    2014-01-01

    To date a number of studies have shown that receptive field shapes of early sensory neurons can be reproduced by optimizing coding efficiency of natural stimulus ensembles. A still unresolved question is whether the efficient coding hypothesis explains formation of neurons which explicitly represent environmental features of different functional importance. This paper proposes that the spatial selectivity of higher auditory neurons emerges as a direct consequence of learning efficient codes for natural binaural sounds. Firstly, it is demonstrated that a linear efficient coding transform—Independent Component Analysis (ICA) trained on spectrograms of naturalistic simulated binaural sounds extracts spatial information present in the signal. A simple hierarchical ICA extension allowing for decoding of sound position is proposed. Furthermore, it is shown that units revealing spatial selectivity can be learned from a binaural recording of a natural auditory scene. In both cases a relatively small subpopulation of learned spectrogram features suffices to perform accurate sound localization. Representation of the auditory space is therefore learned in a purely unsupervised way by maximizing the coding efficiency and without any task-specific constraints. This results imply that efficient coding is a useful strategy for learning structures which allow for making behaviorally vital inferences about the environment. PMID:24639644

  17. Judicious use of custom development in an open source component architecture

    Science.gov (United States)

    Bristol, S.; Latysh, N.; Long, D.; Tekell, S.; Allen, J.

    2014-12-01

    Modern software engineering is not as much programming from scratch as innovative assembly of existing components. Seamlessly integrating disparate components into scalable, performant architecture requires sound engineering craftsmanship and can often result in increased cost efficiency and accelerated capabilities if software teams focus their creativity on the edges of the problem space. ScienceBase is part of the U.S. Geological Survey scientific cyberinfrastructure, providing data and information management, distribution services, and analysis capabilities in a way that strives to follow this pattern. ScienceBase leverages open source NoSQL and relational databases, search indexing technology, spatial service engines, numerous libraries, and one proprietary but necessary software component in its architecture. The primary engineering focus is cohesive component interaction, including construction of a seamless Application Programming Interface (API) across all elements. The API allows researchers and software developers alike to leverage the infrastructure in unique, creative ways. Scaling the ScienceBase architecture and core API with increasing data volume (more databases) and complexity (integrated science problems) is a primary challenge addressed by judicious use of custom development in the component architecture. Other data management and informatics activities in the earth sciences have independently resolved to a similar design of reusing and building upon established technology and are working through similar issues for managing and developing information (e.g., U.S. Geoscience Information Network; NASA's Earth Observing System Clearing House; GSToRE at the University of New Mexico). Recent discussions facilitated through the Earth Science Information Partners are exploring potential avenues to exploit the implicit relationships between similar projects for explicit gains in our ability to more rapidly advance global scientific cyberinfrastructure.

  18. A Combined Methodology to Eliminate Artifacts in Multichannel Electrogastrogram Based on Independent Component Analysis and Ensemble Empirical Mode Decomposition.

    Science.gov (United States)

    Sengottuvel, S; Khan, Pathan Fayaz; Mariyappa, N; Patel, Rajesh; Saipriya, S; Gireesan, K

    2018-06-01

    Cutaneous measurements of electrogastrogram (EGG) signals are heavily contaminated by artifacts due to cardiac activity, breathing, motion artifacts, and electrode drifts whose effective elimination remains an open problem. A common methodology is proposed by combining independent component analysis (ICA) and ensemble empirical mode decomposition (EEMD) to denoise gastric slow-wave signals in multichannel EGG data. Sixteen electrodes are fixed over the upper abdomen to measure the EGG signals under three gastric conditions, namely, preprandial, postprandial immediately, and postprandial 2 h after food for three healthy subjects and a subject with a gastric disorder. Instantaneous frequencies of intrinsic mode functions that are obtained by applying the EEMD technique are analyzed to individually identify and remove each of the artifacts. A critical investigation on the proposed ICA-EEMD method reveals its ability to provide a higher attenuation of artifacts and lower distortion than those obtained by the ICA-EMD method and conventional techniques, like bandpass and adaptive filtering. Characteristic changes in the slow-wave frequencies across the three gastric conditions could be determined from the denoised signals for all the cases. The results therefore encourage the use of the EEMD-based technique for denoising gastric signals to be used in clinical practice.

  19. Fabrication of the polarization independent spectral beam combining grating

    Science.gov (United States)

    Liu, Quan; Jin, Yunxia; Wu, Jianhong; Guo, Peiliang

    2016-03-01

    Owing to damage, thermal issues, and nonlinear optical effects, the output power of fiber laser has been proven to be limited. Beam combining techniques are the attractive solutions to achieve high-power high-brightness fiber laser output. The spectral beam combining (SBC) is a promising method to achieve high average power output without influencing the beam quality. A polarization independent spectral beam combining grating is one of the key elements in the SBC. In this paper the diffraction efficiency of the grating is investigated by rigorous coupled-wave analysis (RCWA). The theoretical -1st order diffraction efficiency of the grating is more than 95% from 1010nm to 1080nm for both TE and TM polarizations. The fabrication tolerance is analyzed. The polarization independent spectral beam combining grating with the period of 1.04μm has been fabricated by holographic lithography - ion beam etching, which are within the fabrication tolerance.

  20. Effectiveness and Cost Efficiency of Different Surveillance Components for Proving Freedom and Early Detection of Disease: Bluetongue Serotype 8 in Cattle as Case Study for Belgium, France and the Netherlands.

    Science.gov (United States)

    Welby, S; van Schaik, G; Veldhuis, A; Brouwer-Middelesch, H; Peroz, C; Santman-Berends, I M; Fourichon, C; Wever, P; Van der Stede, Y

    2017-12-01

    Quick detection and recovery of country's freedom status remain a constant challenge in animal health surveillance. The efficacy and cost efficiency of different surveillance components in proving the absence of infection or (early) detection of bluetongue serotype 8 in cattle populations within different countries (the Netherlands, France, Belgium) using surveillance data from years 2006 and 2007 were investigated using an adapted scenario tree model approach. First, surveillance components (sentinel, yearly cross-sectional and passive clinical reporting) within each country were evaluated in terms of efficacy for substantiating freedom of infection. Yearly cross-sectional survey and passive clinical reporting performed well within each country with sensitivity of detection values ranging around 0.99. The sentinel component had a sensitivity of detection around 0.7. Secondly, how effective the components were for (early) detection of bluetongue serotype 8 and whether syndromic surveillance on reproductive performance, milk production and mortality data available from the Netherlands and Belgium could be of added value were evaluated. Epidemic curves were used to estimate the timeliness of detection. Sensitivity analysis revealed that expected within-herd prevalence and number of herds processed were the most influential parameters for proving freedom and early detection. Looking at the assumed direct costs, although total costs were low for sentinel and passive clinical surveillance components, passive clinical surveillance together with syndromic surveillance (based on reproductive performance data) turned out most cost-efficient for the detection of bluetongue serotype 8. To conclude, for emerging or re-emerging vectorborne disease that behaves such as bluetongue serotype 8, it is recommended to use passive clinical and syndromic surveillance as early detection systems for maximum cost efficiency and sensitivity. Once an infection is detected and eradicated

  1. Definition and discussion of the intrinsic efficiency of winglets

    Directory of Open Access Journals (Sweden)

    Dieter SCHOLZ

    2018-03-01

    Full Text Available Three simple equations are derived to define the “Intrinsic Aerodynamic Efficiency of Winglets” independent of the horizontal extension of the winglet and independent of the winglet’s (relative height. This Intrinsic Aerodynamic Efficiency allows a quick comparison of purely the aerodynamic shape of winglets independent of the selected size chosen for a certain aircraft installation. The Intrinsic Aerodynamic Efficiency is calculated in 3 steps: STEP 1: The relative total drag reduction due to the winglet is converted into an assumed contribution of the winglet only on the span efficiency factor. STEP 2: If the winglet also increases span, its performance is converted into one without the effect of span increase. STEP 3: The winglet’s reduction in induced drag is compared to a horizontal wing extension. If the winglet needs e.g. to be three times longer than the horizontal extension to achieve the same induced drag reduction, its Intrinsic Aerodynamic Efficiency is the inverse or 1/3. Winglet metrics as defined are calculated from literature inputs. In order to evaluate winglets further, the mass increase due to winglets is estimated in addition to the reduction of drag on aircraft level and fuel burn.

  2. Failure characteristic analysis of a component on standby state

    International Nuclear Information System (INIS)

    Shin, Sungmin; Kang, Hyungook

    2013-01-01

    Periodic operations for a specific type of component, however, can accelerate aging effects which increase component unavailability. For the other type of components, the aging effect caused by operation can be ignored. Therefore frequent operations can decrease component unavailability. Thus, to get optimum unavailability proper operation period and method should be studied considering the failure characteristics of each component. The information of component failure is given according to the main causes of failure depending on time flow. However, to get the optimal unavailability, proper interval of operation for inspection should be decided considering the time dependent and independent causes together. According to this study, gradually shorter operation interval for inspection is better to get the optimal component unavailability than that of specific period

  3. Effect of facade components on energy efficiency in office buildings

    International Nuclear Information System (INIS)

    Ihara, Takeshi; Gustavsen, Arild; Jelle, Bjørn Petter

    2015-01-01

    Highlights: • Investigation of facade properties for energy efficiency of Tokyo office buildings. • Higher reflectance for opaque parts may slightly reduce energy demand. • Lower window U-value and solar heat gain coefficient are potential solutions. • Decreased heating due to insulation did not always compensate increased cooling. • Fundamental data for adjustment of facade properties of buildings are provided. - Abstract: Properties of facade materials should be considered to determine which of them strongly affect building energy performance, regardless of the building shapes, scales, ideal locations, and building types, and thus may be able to promote energy efficiency in buildings. In this study, the effects of four fundamental facade properties related to the energy efficiency of office buildings in Tokyo, Japan, were investigated with the purpose of reducing the heating and cooling energy demands. Some fundamental design factors such as volume and shape were also considered. It was found that the reduction in both the solar heat gain coefficient and window U-value and increase in the solar reflectance of the opaque parts are promising measures for reducing the energy demand. Conversely, the reduction in the U-value of the opaque parts decreased the heating energy demand, and this was accompanied by an increase in the cooling energy demand in some cases because the total energy demands were predominantly for cooling. The above-mentioned promising measures for reducing building energy demands are thus recommended for use, and an appropriate U-value should be applied to the opaque parts based on careful considerations. This study provides some fundamental ideas to adjust the facade properties of buildings.

  4. Signaling added response-independent reinforcement to assess Pavlovian processes in resistance to change and relapse.

    Science.gov (United States)

    Podlesnik, Christopher A; Fleet, James D

    2014-09-01

    Behavioral momentum theory asserts Pavlovian stimulus-reinforcer relations govern the persistence of operant behavior. Specifically, resistance to conditions of disruption (e.g., extinction, satiation) reflects the relation between discriminative stimuli and the prevailing reinforcement conditions. The present study assessed whether Pavlovian stimulus-reinforcer relations govern resistance to disruption in pigeons by arranging both response-dependent and -independent food reinforcers in two components of a multiple schedule. In one component, discrete-stimulus changes preceded response-independent reinforcers, paralleling methods that reduce Pavlovian conditioned responding to contextual stimuli. Compared to the control component with no added stimuli preceding response-independent reinforcement, response rates increased as discrete-stimulus duration increased (0, 5, 10, and 15 s) across conditions. Although resistance to extinction decreased as stimulus duration increased in the component with the added discrete stimulus, further tests revealed no effect of discrete stimuli, including other disrupters (presession food, intercomponent food, modified extinction) and reinstatement designed to control for generalization decrement. These findings call into question a straightforward conception that the stimulus-reinforcer relations governing resistance to disruption reflect the same processes as Pavlovian conditioning, as asserted by behavioral momentum theory. © Society for the Experimental Analysis of Behavior.

  5. Influence of microemulsion chirality on chromatographic figures of merit in EKC: results with novel three-chiral-component microemulsions and comparison with one- and two-chiral-component microemulsions.

    Science.gov (United States)

    Kahle, Kimberly A; Foley, Joe P

    2007-08-01

    Novel microemulsion formulations containing all chiral components are described for the enantioseparation of six pairs of pharmaceutical enantiomers (atenolol, ephedrine, metoprolol, N-methyl ephedrine, pseudoephedrine, and synephrine). The chiral surfactant dodecoxycarbonylvaline (DDCV, R- and S-), the chiral cosurfactant S-2-hexanol, and the chiral oil diethyl tartrate (R- and S-) were combined to create four different chiral microemulsions, three of which were stable. Results obtained for enantioselectivity, efficiency, and resolution were compared for the triple-chirality systems and the single-chirality system that contained chiral surfactant only. Improvements in enantioselectivity and resolution were achieved by simultaneously incorporating three chiral components into the aggregate. The one-chiral-component microemulsion provided better efficiencies. Enantioselective synergies were identified for the three-chiral-component nanodroplets using a thermodynamic model. Additionally, two types of dual-chirality systems, chiral surfactant/chiral cosurfactant and chiral surfactant/chiral oil, were examined in terms of chromatographic figures of merit, with the former providing much better resolution. The two varieties of two-chiral-component microemulsions gave similar values for enantioselectivity and efficiency. Lastly, the microemulsion formulations were divided into categories based on the number of chiral microemulsion reagents and the average results for each pair of enantiomers were analyzed for trends. In general, enantioselectivity and resolution were enhanced while efficiency was decreased as more chiral components were used to create the pseudostationary phase (PSP).

  6. Estimates of variance components for postweaning feed intake and ...

    African Journals Online (AJOL)

    Feed efficiency is of major economic importance in beef production. The objective of this work was to evaluate alternative measures of feed efficiency for use in genetic evaluation. To meet this objective, genetic parameters were estimated for the components of efficiency. These parameters were then used in multiple-trait ...

  7. The future of the independent Egyptian music in the digital era

    OpenAIRE

    Maraghah, Mohammad

    2013-01-01

    Master's thesis in music management - University of Agder 2013 This thesis is investigating the impact of the digital era with its technological advanced components and revolutionized information platforms on shaping the future of the independent Egyptian music. The author investigated this impact through conducting fifteen semi structured qualitative interviews between the 15th of December 2012 to 25th of January 2013 with the relevant Independent Egyptian Music stakeholders who gave the ...

  8. Bismuth nitrate as an efficient recyclable catalyst for the one-pot multi component synthesis of 1,4-dihydropyridine derivatives through unsymmetrical Hantzsch reaction

    Directory of Open Access Journals (Sweden)

    S. Sheik Mansoor

    2016-09-01

    Full Text Available Bismuth nitrate catalyzed efficient Hantzsch reaction via four-component coupling reactions of aromatic aldehydes, 5,5-dimethyl-1,3-cyclohexanedione (dimedone, ethyl acetoacetate and ammonium acetate at 80 °C temperature was described as the preparation of 1,4-dihydropyridine derivatives. 2-Amino-4-phenyl-3-cyano-7,7-dimethyl-5-oxo-1,4,5,6,7,8-hexahydroquinoline derivatives are also prepared under the same experimental conditions using aldehydes, dimedone, malononitrile and ammonium acetate in good yield. The higher catalytic activity of Bi(NO3·5H2O is ascribed to its high acidity, thermal stability and water tolerance. The process presented here is operationally simple, environmentally benign and has excellent yield. Furthermore, the catalyst can be recovered conveniently and reused efficiently.

  9. Retrieval of spheroid particle size distribution from spectral extinction data in the independent mode using PCA approach

    International Nuclear Information System (INIS)

    Tang, Hong; Lin, Jian-Zhong

    2013-01-01

    An improved anomalous diffraction approximation (ADA) method is presented for calculating the extinction efficiency of spheroids firstly. In this approach, the extinction efficiency of spheroid particles can be calculated with good accuracy and high efficiency in a wider size range by combining the Latimer method and the ADA theory, and this method can present a more general expression for calculating the extinction efficiency of spheroid particles with various complex refractive indices and aspect ratios. Meanwhile, the visible spectral extinction with varied spheroid particle size distributions and complex refractive indices is surveyed. Furthermore, a selection principle about the spectral extinction data is developed based on PCA (principle component analysis) of first derivative spectral extinction. By calculating the contribution rate of first derivative spectral extinction, the spectral extinction with more significant features can be selected as the input data, and those with less features is removed from the inversion data. In addition, we propose an improved Tikhonov iteration method to retrieve the spheroid particle size distributions in the independent mode. Simulation experiments indicate that the spheroid particle size distributions obtained with the proposed method coincide fairly well with the given distributions, and this inversion method provides a simple, reliable and efficient method to retrieve the spheroid particle size distributions from the spectral extinction data. -- Highlights: ► Improved ADA is presented for calculating the extinction efficiency of spheroids. ► Selection principle about spectral extinction data is developed based on PCA. ► Improved Tikhonov iteration method is proposed to retrieve the spheroid PSD.

  10. Multifractal analysis of managed and independent float exchange rates

    Science.gov (United States)

    Stošić, Darko; Stošić, Dusan; Stošić, Tatijana; Stanley, H. Eugene

    2015-06-01

    We investigate multifractal properties of daily price changes in currency rates using the multifractal detrended fluctuation analysis (MF-DFA). We analyze managed and independent floating currency rates in eight countries, and determine the changes in multifractal spectrum when transitioning between the two regimes. We find that after the transition from managed to independent float regime the changes in multifractal spectrum (position of maximum and width) indicate an increase in market efficiency. The observed changes are more pronounced for developed countries that have a well established trading market. After shuffling the series, we find that the multifractality is due to both probability density function and long term correlations for managed float regime, while for independent float regime multifractality is in most cases caused by broad probability density function.

  11. Walking beam pumping unit system efficiency measurements

    International Nuclear Information System (INIS)

    Kilgore, J.J.; Tripp, H.A.; Hunt, C.L. Jr.

    1991-01-01

    The cost of electricity used by walking beam pumping units is a major expense in producing crude oil. However, only very limited information is available on the efficiency of beam pumping systems and less is known about the efficiency of the various components of the pumping units. This paper presents and discusses measurements that have been made on wells at several Shell locations and on a specially designed walking beam pump test stand at Lufkin Industries. These measurements were made in order to determine the overall system efficiency and efficiency of individual components. The results of this work show that the overall beam pumping system efficiency is normally between 48 and 58 percent. This is primarily dependent on the motor size, motor type, gearbox size, system's age, production, pump size, tubing size, and rod sizes

  12. Layout Optimization Model for the Production Planning of Precast Concrete Building Components

    Directory of Open Access Journals (Sweden)

    Dong Wang

    2018-05-01

    Full Text Available Precast concrete comprises the basic components of modular buildings. The efficiency of precast concrete building component production directly impacts the construction time and cost. In the processes of precast component production, mold setting has a significant influence on the production efficiency and cost, as well as reducing the resource consumption. However, the development of mold setting plans is left to the experience of production staff, with outcomes dependent on the quality of human skill and experience available. This can result in sub-optimal production efficiencies and resource wastage. Accordingly, in order to improve the efficiency of precast component production, this paper proposes an optimization model able to maximize the average utilization rate of pallets used during the molding process. The constraints considered were the order demand, the size of the pallet, layout methods, and the positional relationship of components. A heuristic algorithm was used to identify optimization solutions provided by the model. Through empirical analysis, and as exemplified in the case study, this research is significant in offering a prefabrication production planning model which improves pallet utilization rates, shortens component production time, reduces production costs, and improves the resource utilization. The results clearly demonstrate that the proposed method can facilitate the precast production plan providing strong practical implications for production planners.

  13. I-SG : Interactive Search Grouping - Search result grouping using Independent Component Analysis

    DEFF Research Database (Denmark)

    Lauritsen, Thomas; Kolenda, Thomas

    2002-01-01

    We present a computational simple and efficient approach to unsupervised grouping the search result from any search engine. Along with each group a set of keywords are found to annotate the contents. This approach leads to an interactive search trough a hierarchial structure that is build online....... It is the users task to improve the search, trough expanding the search query using the topic keywords representing the desired groups. In doing so the search engine limits the space of possible search results, virtually moving down in the search hierarchy, and so refines the search....

  14. Efficient training of multilayer perceptrons using principal component analysis

    International Nuclear Information System (INIS)

    Bunzmann, Christoph; Urbanczik, Robert; Biehl, Michael

    2005-01-01

    A training algorithm for multilayer perceptrons is discussed and studied in detail, which relates to the technique of principal component analysis. The latter is performed with respect to a correlation matrix computed from the example inputs and their target outputs. Typical properties of the training procedure are investigated by means of a statistical physics analysis in models of learning regression and classification tasks. We demonstrate that the procedure requires by far fewer examples for good generalization than traditional online training. For networks with a large number of hidden units we derive the training prescription which achieves, within our model, the optimal generalization behavior

  15. An efficient and fair solution for communication graph games

    NARCIS (Netherlands)

    van den Brink, René; Khmelnitskaya, Anna Borisovna; van der Laan, Gerard

    We introduce an efficient solution for games with communication graph structures and show that it is characterized by efficiency, fairness and a new axiom called component balancedness. This latter axiom compares for every component in the communication graph the total payo to the players of this

  16. Study of efficiency indicators of urban public transportation systems. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Tomazinis, A.R.

    1977-01-01

    This report presents the efforts of a research project on efficiency problems of urban public transportation systems (UPTS). Three test regions were selected in an effort to discover, clarify, and understand the efficiency relationships within UPTS. The test regions vary from a small one-mode region to a large multi-mode region. The UPTS are first divided into three major system components, i.e., primary services, support functions, and the network. Then each system is divided by mode, and each component by each distinct function carried within the system component. The inputs to the system are also divided by type, i.e., labor, capital, and energy, and according to the contributor, i.e., the operator, the direct user, the society at large, and the government at all levels. Input units are also traced in terms of money costs (Fiscal Inputs Matrix) and physical units (Physical Inputs Matrix). System outputs are also separated by the receiver and the nature of the outputs. Efficiency analysis is then explored in a hierarchical manner exploring three types of relationships, i.e., system inputs vs. system outputs; component inputs vs. component inputs; and component outputs vs. component outputs. Efficiency indicators are then discussed as to the type of useful service they may offer in various types of efficiency analysis problems.

  17. A New Efficient Algorithm for the All Sorting Reversals Problem with No Bad Components.

    Science.gov (United States)

    Wang, Biing-Feng

    2016-01-01

    The problem of finding all reversals that take a permutation one step closer to a target permutation is called the all sorting reversals problem (the ASR problem). For this problem, Siepel had an O(n (3))-time algorithm. Most complications of his algorithm stem from some peculiar structures called bad components. Since bad components are very rare in both real and simulated data, it is practical to study the ASR problem with no bad components. For the ASR problem with no bad components, Swenson et al. gave an O (n(2))-time algorithm. Very recently, Swenson found that their algorithm does not always work. In this paper, a new algorithm is presented for the ASR problem with no bad components. The time complexity is O(n(2)) in the worst case and is linear in the size of input and output in practice.

  18. Efficient coding of spectrotemporal binaural sounds leads to emergence of the auditory space representation

    Directory of Open Access Journals (Sweden)

    Wiktor eMlynarski

    2014-03-01

    Full Text Available To date a number of studies have shown that receptive field shapes of early sensory neurons can be reproduced by optimizing coding efficiency of natural stimulus ensembles. A still unresolved question is whether the efficientcoding hypothesis explains formation of neurons which explicitly represent environmental features of different functional importance. This paper proposes that the spatial selectivity of higher auditory neurons emerges as a direct consequence of learning efficient codes for natural binaural sounds. Firstly, it is demonstrated that a linear efficient coding transform - Independent Component Analysis (ICA trained on spectrograms of naturalistic simulated binaural sounds extracts spatial information present in the signal. A simple hierarchical ICA extension allowing for decoding of sound position is proposed. Furthermore, it is shown that units revealing spatial selectivity can be learned from a binaural recording of a natural auditory scene. In both cases a relatively small subpopulation of learned spectrogram features suffices to perform accurate sound localization. Representation of the auditory space is therefore learned in a purely unsupervised way by maximizing the coding efficiency and without any task-specific constraints. This results imply that efficient coding is a useful strategy for learning structures which allow for making behaviorally vital inferences about the environment.

  19. Endocytic crosstalk: cavins, caveolins, and caveolae regulate clathrin-independent endocytosis.

    Directory of Open Access Journals (Sweden)

    Natasha Chaudhary

    2014-04-01

    Full Text Available Several studies have suggested crosstalk between different clathrin-independent endocytic pathways. However, the molecular mechanisms and functional relevance of these interactions are unclear. Caveolins and cavins are crucial components of caveolae, specialized microdomains that also constitute an endocytic route. Here we show that specific caveolar proteins are independently acting negative regulators of clathrin-independent endocytosis. Cavin-1 and Cavin-3, but not Cavin-2 or Cavin-4, are potent inhibitors of the clathrin-independent carriers/GPI-AP enriched early endosomal compartment (CLIC/GEEC endocytic pathway, in a process independent of caveola formation. Caveolin-1 (CAV1 and CAV3 also inhibit the CLIC/GEEC pathway upon over-expression. Expression of caveolar protein leads to reduction in formation of early CLIC/GEEC carriers, as detected by quantitative electron microscopy analysis. Furthermore, the CLIC/GEEC pathway is upregulated in cells lacking CAV1/Cavin-1 or with reduced expression of Cavin-1 and Cavin-3. Inhibition by caveolins can be mimicked by the isolated caveolin scaffolding domain and is associated with perturbed diffusion of lipid microdomain components, as revealed by fluorescence recovery after photobleaching (FRAP studies. In the absence of cavins (and caveolae CAV1 is itself endocytosed preferentially through the CLIC/GEEC pathway, but the pathway loses polarization and sorting attributes with consequences for membrane dynamics and endocytic polarization in migrating cells and adult muscle tissue. We also found that noncaveolar Cavin-1 can act as a modulator for the activity of the key regulator of the CLIC/GEEC pathway, Cdc42. This work provides new insights into the regulation of noncaveolar clathrin-independent endocytosis by specific caveolar proteins, illustrating multiple levels of crosstalk between these pathways. We show for the first time a role for specific cavins in regulating the CLIC/GEEC pathway, provide

  20. EPICS: operating system independent device/driver support

    International Nuclear Information System (INIS)

    Kraimer, M.R.

    2003-01-01

    Originally EPICS input/output controllers (IOCs) were only supported on VME-based systems running the vxWorks operating system. Now IOCs are supported on many systems: vxWorks, RTEMS, Solaris, HPUX, Linux, WIN32, and Darwin. A challenge is to provide operating-system-independent device and driver support. This paper presents some techniques for providing such support. EPICS (Experimental Physics and Industrial Control System) is a set of software tools, libraries, and applications developed collaboratively and used worldwide to create distributed, real-time control systems for scientific instruments such as particle accelerators, telescopes, and other large scientific experiments. An important component of all EPICS-based control systems is a collection of input/output controllers (IOCs). An IOC has three primary components: (1) a real-time database; (2) channel access, which provides network access to the database; and (3) device/driver support for interfacing to equipment. This paper describes some projects related to providing device/driver support on non-vxWorks systems. In order to support IOCs on platforms other than vxWorks, operating-system-independent (OSI) application program interfaces (APIs) were defined for threads, semaphores, timers, etc. Providing support for a new platform consists of providing an operating-system-dependent implementation of the OSI APIs.

  1. Validation by theoretical approach to the experimental estimation of efficiency for gamma spectrometry of gas in 100 ml standard flask

    International Nuclear Information System (INIS)

    Mohan, V.; Chudalayandi, K.; Sundaram, M.; Krishnamony, S.

    1996-01-01

    Estimation of gaseous activity forms an important component of air monitoring at Madras Atomic Power Station (MAPS). The gases of importance are argon 41 an air activation product and fission product noble gas xenon 133. For estimating the concentration, the experimental method is used in which a grab sample is collected in a 100 ml volumetric standard flask. The activity of gas is then computed by gamma spectrometry using a predetermined efficiency estimated experimentally. An attempt is made using theoretical approach to validate the experimental method of efficiency estimation. Two analytical models named relative flux model and absolute activity model were developed independently of each other. Attention is focussed on the efficiencies for 41 Ar and 133 Xe. Results show that the present method of sampling and analysis using 100 ml volumetric flask is adequate and acceptable. (author). 5 refs., 2 tabs

  2. Prototype nickel component demonstration. Final report

    International Nuclear Information System (INIS)

    Boss, D.E.

    1994-01-01

    We have been developing a process to produce high-purity nickel structures from nickel carbonyl using chemical vapor deposition (CVD). The prototype demonstration effort had been separated into a number of independent tasks to allow Los Alamos National Laboratory (LANL) the greatest flexibility in tailoring the project to their needs. LANL selected three of the proposed tasks to be performed--Task 1- system modification and demonstration, Task 2-stainless steel mandrel trials, and Task 4-manufacturing study. Task 1 focused on converting the CVD system from a hot-wall to a cold-wall configuration and demonstrating the improved efficiency of the reactor type by depositing a 0.01-inch-thick nickel coating on a cylindrical substrate. Since stainless steel substrates were preferred because of their low α-emitter levels, Task 2 evaluated mandrel configurations which would allow removal of the nickel tube from the substrate. The manufacturing study was performed to develop strategies and system designs for manufacturing large quantities of the components needed for the Sudbury Nuetrino Observatory (SNO) program. Each of these tasks was successfully completed. During these efforts, BIRL successfully produced short lengths of 2-inch-diameter tubing and 6-inch-wide foil with levels of α-radiation emitting contaminants lower than either conventional nickel alloys or electroplated materials. We have produced both the tubing and foil using hot-substrate, cold-wall reactors and clearly demonstrated the advantages of higher precursor efficiency and deposition rate associated with this configuration. We also demonstrated a novel mandrel design which allowed easy removal of the nickel tubing and should dramatically simplify the production of 1.5-meter-long tubes in the production phase of the program

  3. Group Independent Component Analysis (gICA) and Current Source Density (CSD) in the study of EEG in ADHD adults.

    Science.gov (United States)

    Ponomarev, Valery A; Mueller, Andreas; Candrian, Gian; Grin-Yatsenko, Vera A; Kropotov, Juri D

    2014-01-01

    To investigate the performance of the spectral analysis of resting EEG, Current Source Density (CSD) and group independent components (gIC) in diagnosing ADHD adults. Power spectra of resting EEG, CSD and gIC (19 channels, linked ears reference, eyes open/closed) from 96 ADHD and 376 healthy adults were compared between eyes open and eyes closed conditions, and between groups of subjects. Pattern of differences in gIC and CSD spectral power between conditions was approximately similar, whereas it was more widely spatially distributed for EEG. Size effect (Cohen's d) of differences in gIC and CSD spectral power between groups of subjects was considerably greater than in the case of EEG. Significant reduction of gIC and CSD spectral power depending on conditions was found in ADHD patients. Reducing power in a wide frequency range in the fronto-central areas is a common phenomenon regardless of whether the eyes were open or closed. Spectral power of local EEG activity isolated by gICA or CSD in the fronto-central areas may be a suitable marker for discrimination of ADHD and healthy adults. Spectral analysis of gIC and CSD provides better sensitivity to discriminate ADHD and healthy adults. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

  4. Principal component analysis to assess the efficiency and mechanism for enhanced coagulation of natural algae-laden water using a novel dual coagulant system.

    Science.gov (United States)

    Ou, Hua-Se; Wei, Chao-Hai; Deng, Yang; Gao, Nai-Yun; Ren, Yuan; Hu, Yun

    2014-02-01

    A novel dual coagulant system of polyaluminum chloride sulfate (PACS) and polydiallyldimethylammonium chloride (PDADMAC) was used to treat natural algae-laden water from Meiliang Gulf, Lake Taihu. PACS (Aln(OH)mCl3n-m-2k(SO4)k) has a mass ratio of 10 %, a SO4 (2-)/Al3 (+) mole ratio of 0.0664, and an OH/Al mole ratio of 2. The PDADMAC ([C8H16NCl]m) has a MW which ranges from 5 × 10(5) to 20 × 10(5) Da. The variations of contaminants in water samples during treatments were estimated in the form of principal component analysis (PCA) factor scores and conventional variables (turbidity, DOC, etc.). Parallel factor analysis determined four chromophoric dissolved organic matters (CDOM) components, and PCA identified four integrated principle factors. PCA factor 1 had significant correlations with chlorophyll-a (r=0.718), protein-like CDOM C1 (0.689), and C2 (0.756). Factor 2 correlated with UV254 (0.672), humic-like CDOM component C3 (0.716), and C4 (0.758). Factors 3 and 4 had correlations with NH3-N (0.748) and T-P (0.769), respectively. The variations of PCA factors scores revealed that PACS contributed less aluminum dissolution than PAC to obtain equivalent removal efficiency of contaminants. This might be due to the high cationic charge and pre-hydrolyzation of PACS. Compared with PACS coagulation (20 mg L(-1)), the removal of PCA factors 1, 2, and 4 increased 45, 33, and 12 %, respectively, in combined PACS-PDADMAC treatment (0.8 mg L(-1) +20 mg L(-1)). Since PAC contained more Al (0.053 g/1 g) than PACS (0.028 g/1 g), the results indicated that PACS contributed less Al dissolution into the water to obtain equivalent removal efficiency.

  5. Are Independent Fiscal Institutions Really Independent?

    Directory of Open Access Journals (Sweden)

    Slawomir Franek

    2015-08-01

    Full Text Available In the last decade the number of independent fiscal institutions (known also as fiscal councils has tripled. They play an important oversight role over fiscal policy-making in democratic societies, especially as they seek to restore public finance stability in the wake of the recent financial crisis. Although common functions of such institutions include a role in analysis of fiscal policy, forecasting, monitoring compliance with fiscal rules or costing of spending proposals, their roles, resources and structures vary considerably across countries. The aim of the article is to determine the degree of independence of such institutions based on the analysis of the independence index of independent fiscal institutions. The analysis of this index values may be useful to determine the relations between the degree of independence of fiscal councils and fiscal performance of particular countries. The data used to calculate the index values will be derived from European Commission and IMF, which collect sets of information about characteristics of activity of fiscal councils.

  6. Reform of Kosovo Tax System after independence and its key functions

    OpenAIRE

    Dr.Sc. Bedri Peci

    2013-01-01

    In this paper we have analyzed the initial circumstances which characterize tax system in Kosovo after independence. After the Declaration of Independence, it is of the paramount importance that Kosovo has undergone through a reform of policy and tax system by exploring more seriously the economic functions. However, policy and tax system of Kosovo should be more in function of economic development by achieving equilibrium between direct and indirect taxes, increasing efficiency of public ...

  7. Foundations of cumulative culture in apes: improved foraging efficiency through relinquishing and combining witnessed behaviours in chimpanzees (Pan troglodytes).

    Science.gov (United States)

    Davis, Sarah J; Vale, Gillian L; Schapiro, Steven J; Lambeth, Susan P; Whiten, Andrew

    2016-10-24

    A vital prerequisite for cumulative culture, a phenomenon often asserted to be unique to humans, is the ability to modify behaviour and flexibly switch to more productive or efficient alternatives. Here, we first established an inefficient solution to a foraging task in five captive chimpanzee groups (N = 19). Three groups subsequently witnessed a conspecific using an alternative, more efficient, solution. When participants could successfully forage with their established behaviours, most individuals did not switch to this more efficient technique; however, when their foraging method became substantially less efficient, nine chimpanzees with socially-acquired information (four of whom witnessed additional human demonstrations) relinquished their old behaviour in favour of the more efficient one. Only a single chimpanzee in control groups, who had not witnessed a knowledgeable model, discovered this. Individuals who switched were later able to combine components of their two learned techniques to produce a more efficient solution than their extensively used, original foraging method. These results suggest that, although chimpanzees show a considerable degree of conservatism, they also have an ability to combine independent behaviours to produce efficient compound action sequences; one of the foundational abilities (or candidate mechanisms) for human cumulative culture.

  8. The Efficient Windows Collaborative

    Energy Technology Data Exchange (ETDEWEB)

    Petermann, Nils

    2006-03-31

    The Efficient Windows Collaborative (EWC) is a coalition of manufacturers, component suppliers, government agencies, research institutions, and others who partner to expand the market for energy efficient window products. Funded through a cooperative agreement with the U.S. Department of Energy, the EWC provides education, communication and outreach in order to transform the residential window market to 70% energy efficient products by 2005. Implementation of the EWC is managed by the Alliance to Save Energy, with support from the University of Minnesota and Lawrence Berkeley National Laboratory.

  9. What is the effect of optimum independent parameters on solar heating systems?

    International Nuclear Information System (INIS)

    Kaçan, Erkan; Ulgen, Koray; Kaçan, Erdal

    2015-01-01

    Highlights: • The efficiency effect of 4 independent parameters over the solar heating system are examined. • 3 of 4 independent parameters are found as decisive parameter for system design. • Maximum exergetic efficiency exceeded 11% at optimized process. • Maximum environmental efficiency reached up to 95% at optimized process. • The optimum outside temperature and solar radiation are found as 22 °C and 773 W/m"2 for all responses. - Abstract: Researchers are rather closely involved in Solar Combisystems recently, but there is lack of study that presents the optimum design parameters. Therefore, in this study the influence of the four major variables, namely; outside, inside temperature, solar radiation on horizontal surface and instantaneous efficiency of solar collector on the energetic, exergetic and environmental efficiencies of Solar Combisystems are investigated and system optimization is done by a combination of response surface methodology. Measured parameters and energetic–exergetic and environmental performance curves are found and statistical model is created parallel with the actual data. It is found that statistical model is significant and all “lack-of-fit” values are non-significant. Thus, it is proved that statistical model strongly represents the design model. Outside temperature, solar radiation on horizontal surface and instantaneous efficiency of solar collector are the decisive parameters for all responses but instantaneous efficiency of solar collector is not for environmental efficiency. Maximum exergetic efficiency exceeded 11%, maximum environmental efficiency reached up to 95% at optimized process. The optimum value of the outside temperature and solar radiation are found as 22 °C and 773 W/m"2 for all responses, on the other hand optimum collector efficiency is found around 60% for energetic and exergetic efficiency values. Inside temperature is not a decisive parameter for all responses.

  10. Anisotropic magnetoresistance components in (Ga,Mn)As.

    Science.gov (United States)

    Rushforth, A W; Výborný, K; King, C S; Edmonds, K W; Campion, R P; Foxon, C T; Wunderlich, J; Irvine, A C; Vasek, P; Novák, V; Olejník, K; Sinova, Jairo; Jungwirth, T; Gallagher, B L

    2007-10-05

    We explore the basic physical origins of the noncrystalline and crystalline components of the anisotropic magnetoresistance (AMR) in (Ga,Mn)As. The sign of the noncrystalline AMR is found to be determined by the form of spin-orbit coupling in the host band and by the relative strengths of the nonmagnetic and magnetic contributions to the Mn impurity potential. We develop experimental methods yielding directly the noncrystalline and crystalline AMR components which are then analyzed independently. We report the observation of an AMR dominated by a large uniaxial crystalline component and show that AMR can be modified by local strain relaxation. Generic implications of our findings for other dilute moment systems are discussed.

  11. Principal components analysis in clinical studies.

    Science.gov (United States)

    Zhang, Zhongheng; Castelló, Adela

    2017-09-01

    In multivariate analysis, independent variables are usually correlated to each other which can introduce multicollinearity in the regression models. One approach to solve this problem is to apply principal components analysis (PCA) over these variables. This method uses orthogonal transformation to represent sets of potentially correlated variables with principal components (PC) that are linearly uncorrelated. PCs are ordered so that the first PC has the largest possible variance and only some components are selected to represent the correlated variables. As a result, the dimension of the variable space is reduced. This tutorial illustrates how to perform PCA in R environment, the example is a simulated dataset in which two PCs are responsible for the majority of the variance in the data. Furthermore, the visualization of PCA is highlighted.

  12. Functional connectivity analysis of the neural bases of emotion regulation: A comparison of independent component method with density-based k-means clustering method.

    Science.gov (United States)

    Zou, Ling; Guo, Qian; Xu, Yi; Yang, Biao; Jiao, Zhuqing; Xiang, Jianbo

    2016-04-29

    Functional magnetic resonance imaging (fMRI) is an important tool in neuroscience for assessing connectivity and interactions between distant areas of the brain. To find and characterize the coherent patterns of brain activity as a means of identifying brain systems for the cognitive reappraisal of the emotion task, both density-based k-means clustering and independent component analysis (ICA) methods can be applied to characterize the interactions between brain regions involved in cognitive reappraisal of emotion. Our results reveal that compared with the ICA method, the density-based k-means clustering method provides a higher sensitivity of polymerization. In addition, it is more sensitive to those relatively weak functional connection regions. Thus, the study concludes that in the process of receiving emotional stimuli, the relatively obvious activation areas are mainly distributed in the frontal lobe, cingulum and near the hypothalamus. Furthermore, density-based k-means clustering method creates a more reliable method for follow-up studies of brain functional connectivity.

  13. Energy-efficient neural information processing in individual neurons and neuronal networks.

    Science.gov (United States)

    Yu, Lianchun; Yu, Yuguo

    2017-11-01

    Brains are composed of networks of an enormous number of neurons interconnected with synapses. Neural information is carried by the electrical signals within neurons and the chemical signals among neurons. Generating these electrical and chemical signals is metabolically expensive. The fundamental issue raised here is whether brains have evolved efficient ways of developing an energy-efficient neural code from the molecular level to the circuit level. Here, we summarize the factors and biophysical mechanisms that could contribute to the energy-efficient neural code for processing input signals. The factors range from ion channel kinetics, body temperature, axonal propagation of action potentials, low-probability release of synaptic neurotransmitters, optimal input and noise, the size of neurons and neuronal clusters, excitation/inhibition balance, coding strategy, cortical wiring, and the organization of functional connectivity. Both experimental and computational evidence suggests that neural systems may use these factors to maximize the efficiency of energy consumption in processing neural signals. Studies indicate that efficient energy utilization may be universal in neuronal systems as an evolutionary consequence of the pressure of limited energy. As a result, neuronal connections may be wired in a highly economical manner to lower energy costs and space. Individual neurons within a network may encode independent stimulus components to allow a minimal number of neurons to represent whole stimulus characteristics efficiently. This basic principle may fundamentally change our view of how billions of neurons organize themselves into complex circuits to operate and generate the most powerful intelligent cognition in nature. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  14. Cooking for Independence: Middle School Students Gain Skills While Cooking

    Science.gov (United States)

    Mixon, Gloria

    2011-01-01

    Middle school students with intellectual disabilities often have difficulties achieving independence with instrumental activities of daily living (IADLs); therefore, these skills must be taught in school. IADLs are a complex component of skills that require a higher level of cognitive reasoning such as community mobility, shopping, meal…

  15. Dysfunctional default mode network and executive control network in people with Internet gaming disorder: Independent component analysis under a probability discounting task.

    Science.gov (United States)

    Wang, L; Wu, L; Lin, X; Zhang, Y; Zhou, H; Du, X; Dong, G

    2016-04-01

    The present study identified the neural mechanism of risky decision-making in Internet gaming disorder (IGD) under a probability discounting task. Independent component analysis was used on the functional magnetic resonance imaging data from 19 IGD subjects (22.2 ± 3.08 years) and 21 healthy controls (HC, 22.8 ± 3.5 years). For the behavioral results, IGD subjects prefer the risky to the fixed options and showed shorter reaction time compared to HC. For the imaging results, the IGD subjects showed higher task-related activity in default mode network (DMN) and less engagement in the executive control network (ECN) than HC when making the risky decisions. Also, we found the activities of DMN correlate negatively with the reaction time and the ECN correlate positively with the probability discounting rates. The results suggest that people with IGD show altered modulation in DMN and deficit in executive control function, which might be the reason for why the IGD subjects continue to play online games despite the potential negative consequences. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

  16. Gauge origin independent calculations of nuclear magnetic shieldings in relativistic four-component theory

    DEFF Research Database (Denmark)

    Ilias, Miroslav; Saue, Trond; Enevoldsen, Thomas

    2009-01-01

    The use of perturbation-dependent London atomic orbitals, also called gauge including atomic orbitals, has proven efficient for calculations of NMR shielding constants and other magnetic properties in the nonrelativistic framework. In this paper, the theory of London atomic orbitals for NMR...... calculates the diamagnetic contribution as an expectation value, leads to significant errors and is not recommended. (C) 2009 American Institute of Physics. [doi:10.1063/1.3240198]...

  17. Rapid discrimination of plastic packaging materials using MIR spectroscopy coupled with independent components analysis (ICA)

    International Nuclear Information System (INIS)

    Kassouf, Amine; Maalouly, Jacqueline; Rutledge, Douglas N.; Chebib, Hanna; Ducruet, Violette

    2014-01-01

    Highlights: • An innovative technique, MIR-ICA, was applied to plastic packaging separation. • This study was carried out on PE, PP, PS, PET and PLA plastic packaging materials. • ICA was applied to discriminate plastics and 100% separation rates were obtained. • Analyses performed on two spectrometers proved the reproducibility of the method. • MIR-ICA is a simple and fast technique allowing plastic identification/classification. - Abstract: Plastic packaging wastes increased considerably in recent decades, raising a major and serious public concern on political, economical and environmental levels. Dealing with this kind of problems is generally done by landfilling and energy recovery. However, these two methods are becoming more and more expensive, hazardous to the public health and the environment. Therefore, recycling is gaining worldwide consideration as a solution to decrease the growing volume of plastic packaging wastes and simultaneously reduce the consumption of oil required to produce virgin resin. Nevertheless, a major shortage is encountered in recycling which is related to the sorting of plastic wastes. In this paper, a feasibility study was performed in order to test the potential of an innovative approach combining mid infrared (MIR) spectroscopy with independent components analysis (ICA), as a simple and fast approach which could achieve high separation rates. This approach (MIR-ICA) gave 100% discrimination rates in the separation of all studied plastics: polyethylene terephthalate (PET), polyethylene (PE), polypropylene (PP), polystyrene (PS) and polylactide (PLA). In addition, some more specific discriminations were obtained separating plastic materials belonging to the same polymer family e.g. high density polyethylene (HDPE) from low density polyethylene (LDPE). High discrimination rates were obtained despite the heterogeneity among samples especially differences in colors, thicknesses and surface textures. The reproducibility of

  18. Rapid discrimination of plastic packaging materials using MIR spectroscopy coupled with independent components analysis (ICA)

    Energy Technology Data Exchange (ETDEWEB)

    Kassouf, Amine, E-mail: amine.kassouf@agroparistech.fr [ER004 “Lebanese Food Packaging”, Faculty of Sciences II, Lebanese University, 90656 Jdeideth El Matn, Fanar (Lebanon); INRA, UMR1145 Ingénierie Procédés Aliments, 1 Avenue des Olympiades, 91300 Massy (France); AgroParisTech, UMR1145 Ingénierie Procédés Aliments, 16 rue Claude Bernard, 75005 Paris (France); Maalouly, Jacqueline, E-mail: j_maalouly@hotmail.com [ER004 “Lebanese Food Packaging”, Faculty of Sciences II, Lebanese University, 90656 Jdeideth El Matn, Fanar (Lebanon); Rutledge, Douglas N., E-mail: douglas.rutledge@agroparistech.fr [INRA, UMR1145 Ingénierie Procédés Aliments, 1 Avenue des Olympiades, 91300 Massy (France); AgroParisTech, UMR1145 Ingénierie Procédés Aliments, 16 rue Claude Bernard, 75005 Paris (France); Chebib, Hanna, E-mail: hchebib@hotmail.com [ER004 “Lebanese Food Packaging”, Faculty of Sciences II, Lebanese University, 90656 Jdeideth El Matn, Fanar (Lebanon); Ducruet, Violette, E-mail: violette.ducruet@agroparistech.fr [INRA, UMR1145 Ingénierie Procédés Aliments, 1 Avenue des Olympiades, 91300 Massy (France); AgroParisTech, UMR1145 Ingénierie Procédés Aliments, 16 rue Claude Bernard, 75005 Paris (France)

    2014-11-15

    Highlights: • An innovative technique, MIR-ICA, was applied to plastic packaging separation. • This study was carried out on PE, PP, PS, PET and PLA plastic packaging materials. • ICA was applied to discriminate plastics and 100% separation rates were obtained. • Analyses performed on two spectrometers proved the reproducibility of the method. • MIR-ICA is a simple and fast technique allowing plastic identification/classification. - Abstract: Plastic packaging wastes increased considerably in recent decades, raising a major and serious public concern on political, economical and environmental levels. Dealing with this kind of problems is generally done by landfilling and energy recovery. However, these two methods are becoming more and more expensive, hazardous to the public health and the environment. Therefore, recycling is gaining worldwide consideration as a solution to decrease the growing volume of plastic packaging wastes and simultaneously reduce the consumption of oil required to produce virgin resin. Nevertheless, a major shortage is encountered in recycling which is related to the sorting of plastic wastes. In this paper, a feasibility study was performed in order to test the potential of an innovative approach combining mid infrared (MIR) spectroscopy with independent components analysis (ICA), as a simple and fast approach which could achieve high separation rates. This approach (MIR-ICA) gave 100% discrimination rates in the separation of all studied plastics: polyethylene terephthalate (PET), polyethylene (PE), polypropylene (PP), polystyrene (PS) and polylactide (PLA). In addition, some more specific discriminations were obtained separating plastic materials belonging to the same polymer family e.g. high density polyethylene (HDPE) from low density polyethylene (LDPE). High discrimination rates were obtained despite the heterogeneity among samples especially differences in colors, thicknesses and surface textures. The reproducibility of

  19. Systematic review of reviews of intervention components associated with increased effectiveness in dietary and physical activity interventions

    Directory of Open Access Journals (Sweden)

    Evans Philip H

    2011-02-01

    Full Text Available Abstract Background To develop more efficient programmes for promoting dietary and/or physical activity change (in order to prevent type 2 diabetes it is critical to ensure that the intervention components and characteristics most strongly associated with effectiveness are included. The aim of this systematic review of reviews was to identify intervention components that are associated with increased change in diet and/or physical activity in individuals at risk of type 2 diabetes. Methods MEDLINE, EMBASE, CINAHL, PsycInfo, and the Cochrane Library were searched for systematic reviews of interventions targeting diet and/or physical activity in adults at risk of developing type 2 diabetes from 1998 to 2008. Two reviewers independently selected reviews and rated methodological quality. Individual analyses from reviews relating effectiveness to intervention components were extracted, graded for evidence quality and summarised. Results Of 3856 identified articles, 30 met the inclusion criteria and 129 analyses related intervention components to effectiveness. These included causal analyses (based on randomisation of participants to different intervention conditions and associative analyses (e.g. meta-regression. Overall, interventions produced clinically meaningful weight loss (3-5 kg at 12 months; 2-3 kg at 36 months and increased physical activity (30-60 mins/week of moderate activity at 12-18 months. Based on causal analyses, intervention effectiveness was increased by engaging social support, targeting both diet and physical activity, and using well-defined/established behaviour change techniques. Increased effectiveness was also associated with increased contact frequency and using a specific cluster of "self-regulatory" behaviour change techniques (e.g. goal-setting, self-monitoring. No clear relationships were found between effectiveness and intervention setting, delivery mode, study population or delivery provider. Evidence on long

  20. Efficient real time OD matrix estimation based on principal component analysis

    NARCIS (Netherlands)

    Djukic, T.; Flötteröd, G.; Van Lint, H.; Hoogendoorn, S.P.

    2012-01-01

    In this paper we explore the idea of dimensionality reduction and approximation of OD demand based on principal component analysis (PCA). First, we show how we can apply PCA to linearly transform the high dimensional OD matrices into the lower dimensional space without significant loss of accuracy.

  1. Independent Living Services and the Educational Motivation of Foster Youth

    Science.gov (United States)

    Eriamiatoe, Osarumen Rachel

    2011-01-01

    The purpose of this qualitative study was to examine the components of independent living training and services to determine their effectiveness in preparing foster youth in Tennessee for adulthood, and whether the youth's perceived effectiveness of these services affected their educational motivation. Support factors (i.e., family, financial,…

  2. Final report of the UMTRA independent technical review of TAC audit programs

    International Nuclear Information System (INIS)

    1994-10-01

    This report details the findings of an Independent Technical Review (ITR) of practices and procedures for the Uranium Mill Tailings Remedial Action (UMTRA) Project audit program. The audit program is conducted by Jacobs Engineering Group Inc., the Technical Assistance Contractor (TAC) for the UMTRA Project. The purpose of the ITR was to ensure that the TAC audit program is effective and is conducted efficiently. The ITR was conducted from May 16-20, 1994. A review team observed audit practices in the field, reviewed the TAC audit program's documentation, and discussed the program with TAC staff and management. The format of this report has been developed around EPA guidelines; they comprise most of the major section headings. Each section begins by identifying the criteria that the TAC program is measured against, then describing the approach used by the ITR team to measure each TAC audit program against the criteria. An assessment of each type of audit is then summarized for each component in the following order: Radiological audit summary; Health and safety audit summary; Environmental audit summary; Quality assurance audit summary

  3. Modeling Energy Efficiency As A Green Logistics Component In Vehicle Assembly Line

    Science.gov (United States)

    Oumer, Abduaziz; Mekbib Atnaw, Samson; Kie Cheng, Jack; Singh, Lakveer

    2016-11-01

    This paper uses System Dynamics (SD) simulation to investigate the concept green logistics in terms of energy efficiency in automotive industry. The car manufacturing industry is considered to be one of the highest energy consuming industries. An efficient decision making model is proposed that capture the impacts of strategic decisions on energy consumption and environmental sustainability. The sources of energy considered in this research are electricity and fuel; which are the two main types of energy sources used in a typical vehicle assembly plant. The model depicts the performance measurement for process- specific energy measures of painting, welding, and assembling processes. SD is the chosen simulation method and the main green logistics issues considered are Carbon Dioxide (CO2) emission and energy utilization. The model will assist decision makers acquire an in-depth understanding of relationship between high level planning and low level operation activities on production, environmental impacts and costs associated. The results of the SD model signify the existence of positive trade-offs between green practices of energy efficiency and the reduction of CO2 emission.

  4. Calcium-dependent and -independent binding of the pentraxin serum amyloid P component to glycosaminoglycans and amyloid proteins

    DEFF Research Database (Denmark)

    Danielsen, B; Sørensen, I J; Nybo, Mads

    1997-01-01

    precursor protein beta2M was observed. This binding was also enhanced at slightly acid pH, most pronounced at pH 5.0. The results of this study indicate that SAP can exhibit both Ca2(+)-dependent and -independent binding to ligands involved in amyloid fibril formation and that the binding is enhanced under...... and beta2M) by ELISA. An increase in the dose-dependent binding of SAP to heparan sulfate, AA-protein and beta2M was observed as the pH decreased from 8.0 to 5.0. Furthermore, a lower, but significant Ca2(+)-independent binding of SAP to heparan sulfate, dermatan sulfate, AA protein and the amyloid...

  5. Model-independent confirmation of the $Z(4430)^-$ state

    CERN Document Server

    Aaij, Roel; Adinolfi, Marco; Affolder, Anthony; Ajaltouni, Ziad; Albrecht, Johannes; Alessio, Federico; Alexander, Michael; Ali, Suvayu; Alkhazov, Georgy; Alvarez Cartelle, Paula; Alves Jr, Antonio; Amato, Sandra; Amerio, Silvia; Amhis, Yasmine; An, Liupan; Anderlini, Lucio; Anderson, Jonathan; Andreassen, Rolf; Andreotti, Mirco; Andrews, Jason; Appleby, Robert; Aquines Gutierrez, Osvaldo; Archilli, Flavio; Artamonov, Alexander; Artuso, Marina; Aslanides, Elie; Auriemma, Giulio; Baalouch, Marouen; Bachmann, Sebastian; Back, John; Badalov, Alexey; Balagura, Vladislav; Baldini, Wander; Barlow, Roger; Barschel, Colin; Barsuk, Sergey; Barter, William; Batozskaya, Varvara; Bauer, Thomas; Bay, Aurelio; Beaucourt, Leo; Beddow, John; Bedeschi, Franco; Bediaga, Ignacio; Belogurov, Sergey; Belous, Konstantin; Belyaev, Ivan; Ben-Haim, Eli; Bencivenni, Giovanni; Benson, Sean; Benton, Jack; Berezhnoy, Alexander; Bernet, Roland; Bettler, Marc-Olivier; van Beuzekom, Martinus; Bien, Alexander; Bifani, Simone; Bird, Thomas; Bizzeti, Andrea; Bjørnstad, Pål Marius; Blake, Thomas; Blanc, Frédéric; Blouw, Johan; Blusk, Steven; Bocci, Valerio; Bondar, Alexander; Bondar, Nikolay; Bonivento, Walter; Borghi, Silvia; Borgia, Alessandra; Borsato, Martino; Bowcock, Themistocles; Bowen, Espen Eie; Bozzi, Concezio; Brambach, Tobias; van den Brand, Johannes; Bressieux, Joël; Brett, David; Britsch, Markward; Britton, Thomas; Brodzicka, Jolanta; Brook, Nicholas; Brown, Henry; Bursche, Albert; Busetto, Giovanni; Buytaert, Jan; Cadeddu, Sandro; Calabrese, Roberto; Calvi, Marta; Calvo Gomez, Miriam; Camboni, Alessandro; Campana, Pierluigi; Campora Perez, Daniel; Carbone, Angelo; Carboni, Giovanni; Cardinale, Roberta; Cardini, Alessandro; Carranza-Mejia, Hector; Carson, Laurence; Carvalho Akiba, Kazuyoshi; Casse, Gianluigi; Cassina, Lorenzo; Castillo Garcia, Lucia; Cattaneo, Marco; Cauet, Christophe; Cenci, Riccardo; Charles, Matthew; Charpentier, Philippe; Chen, Shanzhen; Cheung, Shu-Faye; Chiapolini, Nicola; Chrzaszcz, Marcin; Ciba, Krzystof; Cid Vidal, Xabier; Ciezarek, Gregory; Clarke, Peter; Clemencic, Marco; Cliff, Harry; Closier, Joel; Coco, Victor; Cogan, Julien; Cogneras, Eric; Collins, Paula; Comerma-Montells, Albert; Contu, Andrea; Cook, Andrew; Coombes, Matthew; Coquereau, Samuel; Corti, Gloria; Corvo, Marco; Counts, Ian; Couturier, Benjamin; Cowan, Greig; Craik, Daniel Charles; Cruz Torres, Melissa Maria; Cunliffe, Samuel; Currie, Robert; D'Ambrosio, Carmelo; Dalseno, Jeremy; David, Pascal; David, Pieter; Davis, Adam; De Bruyn, Kristof; De Capua, Stefano; De Cian, Michel; De Miranda, Jussara; De Paula, Leandro; De Silva, Weeraddana; De Simone, Patrizia; Decamp, Daniel; Deckenhoff, Mirko; Del Buono, Luigi; Déléage, Nicolas; Derkach, Denis; Deschamps, Olivier; Dettori, Francesco; Di Canto, Angelo; Dijkstra, Hans; Donleavy, Stephanie; Dordei, Francesca; Dorigo, Mirco; Dosil Suárez, Alvaro; Dossett, David; Dovbnya, Anatoliy; Dujany, Giulio; Dupertuis, Frederic; Durante, Paolo; Dzhelyadin, Rustem; Dziurda, Agnieszka; Dzyuba, Alexey; Easo, Sajan; Egede, Ulrik; Egorychev, Victor; Eidelman, Semen; Eisenhardt, Stephan; Eitschberger, Ulrich; Ekelhof, Robert; Eklund, Lars; El Rifai, Ibrahim; Elsasser, Christian; Ely, Scott; Esen, Sevda; Evans, Timothy; Falabella, Antonio; Färber, Christian; Farinelli, Chiara; Farley, Nathanael; Farry, Stephen; Ferguson, Dianne; Fernandez Albor, Victor; Ferreira Rodrigues, Fernando; Ferro-Luzzi, Massimiliano; Filippov, Sergey; Fiore, Marco; Fiorini, Massimiliano; Firlej, Miroslaw; Fitzpatrick, Conor; Fiutowski, Tomasz; Fontana, Marianna; Fontanelli, Flavio; Forty, Roger; Francisco, Oscar; Frank, Markus; Frei, Christoph; Frosini, Maddalena; Fu, Jinlin; Furfaro, Emiliano; Gallas Torreira, Abraham; Galli, Domenico; Gallorini, Stefano; Gambetta, Silvia; Gandelman, Miriam; Gandini, Paolo; Gao, Yuanning; Garofoli, Justin; Garra Tico, Jordi; Garrido, Lluis; Gaspar, Clara; Gauld, Rhorry; Gavardi, Laura; Gersabeck, Evelina; Gersabeck, Marco; Gershon, Timothy; Ghez, Philippe; Gianelle, Alessio; Giani', Sebastiana; Gibson, Valerie; Giubega, Lavinia-Helena; Gligorov, Vladimir; Göbel, Carla; Golubkov, Dmitry; Golutvin, Andrey; Gomes, Alvaro; Gordon, Hamish; Gotti, Claudio; Grabalosa Gándara, Marc; Graciani Diaz, Ricardo; Granado Cardoso, Luis Alberto; Graugés, Eugeni; Graziani, Giacomo; Grecu, Alexandru; Greening, Edward; Gregson, Sam; Griffith, Peter; Grillo, Lucia; Grünberg, Oliver; Gui, Bin; Gushchin, Evgeny; Guz, Yury; Gys, Thierry; Hadjivasiliou, Christos; Haefeli, Guido; Haen, Christophe; Haines, Susan; Hall, Samuel; Hamilton, Brian; Hampson, Thomas; Han, Xiaoxue; Hansmann-Menzemer, Stephanie; Harnew, Neville; Harnew, Samuel; Harrison, Jonathan; Hartmann, Thomas; He, Jibo; Head, Timothy; Heijne, Veerle; Hennessy, Karol; Henrard, Pierre; Henry, Louis; Hernando Morata, Jose Angel; van Herwijnen, Eric; Heß, Miriam; Hicheur, Adlène; Hill, Donal; Hoballah, Mostafa; Hombach, Christoph; Hulsbergen, Wouter; Hunt, Philip; Hussain, Nazim; Hutchcroft, David; Hynds, Daniel; Idzik, Marek; Ilten, Philip; Jacobsson, Richard; Jaeger, Andreas; Jalocha, Pawel; Jans, Eddy; Jaton, Pierre; Jawahery, Abolhassan; Jezabek, Marek; Jing, Fanfan; John, Malcolm; Johnson, Daniel; Jones, Christopher; Joram, Christian; Jost, Beat; Jurik, Nathan; Kaballo, Michael; Kandybei, Sergii; Kanso, Walaa; Karacson, Matthias; Karbach, Moritz; Kelsey, Matthew; Kenyon, Ian; Ketel, Tjeerd; Khanji, Basem; Khurewathanakul, Chitsanu; Klaver, Suzanne; Kochebina, Olga; Kolpin, Michael; Komarov, Ilya; Koopman, Rose; Koppenburg, Patrick; Korolev, Mikhail; Kozlinskiy, Alexandr; Kravchuk, Leonid; Kreplin, Katharina; Kreps, Michal; Krocker, Georg; Krokovny, Pavel; Kruse, Florian; Kucharczyk, Marcin; Kudryavtsev, Vasily; Kurek, Krzysztof; Kvaratskheliya, Tengiz; La Thi, Viet Nga; Lacarrere, Daniel; Lafferty, George; Lai, Adriano; Lambert, Dean; Lambert, Robert W; Lanciotti, Elisa; Lanfranchi, Gaia; Langenbruch, Christoph; Langhans, Benedikt; Latham, Thomas; Lazzeroni, Cristina; Le Gac, Renaud; van Leerdam, Jeroen; Lees, Jean-Pierre; Lefèvre, Regis; Leflat, Alexander; Lefrançois, Jacques; Leo, Sabato; Leroy, Olivier; Lesiak, Tadeusz; Leverington, Blake; Li, Yiming; Liles, Myfanwy; Lindner, Rolf; Linn, Christian; Lionetto, Federica; Liu, Bo; Liu, Guoming; Lohn, Stefan; Longstaff, Iain; Lopes, Jose; Lopez-March, Neus; Lowdon, Peter; Lu, Haiting; Lucchesi, Donatella; Luo, Haofei; Lupato, Anna; Luppi, Eleonora; Lupton, Oliver; Machefert, Frederic; Machikhiliyan, Irina V; Maciuc, Florin; Maev, Oleg; Malde, Sneha; Manca, Giulia; Mancinelli, Giampiero; Manzali, Matteo; Maratas, Jan; Marchand, Jean François; Marconi, Umberto; Marin Benito, Carla; Marino, Pietro; Märki, Raphael; Marks, Jörg; Martellotti, Giuseppe; Martens, Aurelien; Martín Sánchez, Alexandra; Martinelli, Maurizio; Martinez Santos, Diego; Martinez Vidal, Fernando; Martins Tostes, Danielle; Massafferri, André; Matev, Rosen; Mathe, Zoltan; Matteuzzi, Clara; Mazurov, Alexander; McCann, Michael; McCarthy, James; McNab, Andrew; McNulty, Ronan; McSkelly, Ben; Meadows, Brian; Meier, Frank; Meissner, Marco; Merk, Marcel; Milanes, Diego Alejandro; Minard, Marie-Noelle; Moggi, Niccolò; Molina Rodriguez, Josue; Monteil, Stephane; Moran, Dermot; Morandin, Mauro; Morawski, Piotr; Mordà, Alessandro; Morello, Michael Joseph; Moron, Jakub; Morris, Adam Benjamin; Mountain, Raymond; Muheim, Franz; Müller, Katharina; Muresan, Raluca; Mussini, Manuel; Muster, Bastien; Naik, Paras; Nakada, Tatsuya; Nandakumar, Raja; Nasteva, Irina; Needham, Matthew; Neri, Nicola; Neubert, Sebastian; Neufeld, Niko; Neuner, Max; Nguyen, Anh Duc; Nguyen, Thi-Dung; Nguyen-Mau, Chung; Nicol, Michelle; Niess, Valentin; Niet, Ramon; Nikitin, Nikolay; Nikodem, Thomas; Novoselov, Alexey; Oblakowska-Mucha, Agnieszka; Obraztsov, Vladimir; Oggero, Serena; Ogilvy, Stephen; Okhrimenko, Oleksandr; Oldeman, Rudolf; Onderwater, Gerco; Orlandea, Marius; Otalora Goicochea, Juan Martin; Owen, Patrick; Oyanguren, Maria Arantza; Pal, Bilas Kanti; Palano, Antimo; Palombo, Fernando; Palutan, Matteo; Panman, Jacob; Papanestis, Antonios; Pappagallo, Marco; Parkes, Christopher; Parkinson, Christopher John; Passaleva, Giovanni; Patel, Girish; Patel, Mitesh; Patrignani, Claudia; Pazos Alvarez, Antonio; Pearce, Alex; Pellegrino, Antonio; Pepe Altarelli, Monica; Perazzini, Stefano; Perez Trigo, Eliseo; Perret, Pascal; Perrin-Terrin, Mathieu; Pescatore, Luca; Pesen, Erhan; Petridis, Konstantin; Petrolini, Alessandro; Picatoste Olloqui, Eduardo; Pietrzyk, Boleslaw; Pilař, Tomas; Pinci, Davide; Pistone, Alessandro; Playfer, Stephen; Plo Casasus, Maximo; Polci, Francesco; Poluektov, Anton; Polycarpo, Erica; Popov, Alexander; Popov, Dmitry; Popovici, Bogdan; Potterat, Cédric; Powell, Andrew; Prisciandaro, Jessica; Pritchard, Adrian; Prouve, Claire; Pugatch, Valery; Puig Navarro, Albert; Punzi, Giovanni; Qian, Wenbin; Rachwal, Bartolomiej; Rademacker, Jonas; Rakotomiaramanana, Barinjaka; Rama, Matteo; Rangel, Murilo; Raniuk, Iurii; Rauschmayr, Nathalie; Raven, Gerhard; Reichert, Stefanie; Reid, Matthew; dos Reis, Alberto; Ricciardi, Stefania; Richards, Alexander; Rihl, Mariana; Rinnert, Kurt; Rives Molina, Vincente; Roa Romero, Diego; Robbe, Patrick; Rodrigues, Ana Barbara; Rodrigues, Eduardo; Rodriguez Perez, Pablo; Roiser, Stefan; Romanovsky, Vladimir; Romero Vidal, Antonio; Rotondo, Marcello; Rouvinet, Julien; Ruf, Thomas; Ruffini, Fabrizio; Ruiz, Hugo; Ruiz Valls, Pablo; Sabatino, Giovanni; Saborido Silva, Juan Jose; Sagidova, Naylya; Sail, Paul; Saitta, Biagio; Salustino Guimaraes, Valdir; Sanchez Mayordomo, Carlos; Sanmartin Sedes, Brais; Santacesaria, Roberta; Santamarina Rios, Cibran; Santovetti, Emanuele; Sapunov, Matvey; Sarti, Alessio; Satriano, Celestina; Satta, Alessia; Savrie, Mauro; Savrina, Darya; Schiller, Manuel; Schindler, Heinrich; Schlupp, Maximilian; Schmelling, Michael; Schmidt, Burkhard; Schneider, Olivier; Schopper, Andreas; Schune, Marie Helene; Schwemmer, Rainer; Sciascia, Barbara; Sciubba, Adalberto; Seco, Marcos; Semennikov, Alexander; Senderowska, Katarzyna; Sepp, Indrek; Serra, Nicola; Serrano, Justine; Sestini, Lorenzo; Seyfert, Paul; Shapkin, Mikhail; Shapoval, Illya; Shcheglov, Yury; Shears, Tara; Shekhtman, Lev; Shevchenko, Vladimir; Shires, Alexander; Silva Coutinho, Rafael; Simi, Gabriele; Sirendi, Marek; Skidmore, Nicola; Skwarnicki, Tomasz; Smith, Anthony; Smith, Edmund; Smith, Eluned; Smith, Jackson; Smith, Mark; Snoek, Hella; Sokoloff, Michael; Soler, Paul; Soomro, Fatima; Souza, Daniel; Souza De Paula, Bruno; Spaan, Bernhard; Sparkes, Ailsa; Spinella, Franco; Spradlin, Patrick; Stagni, Federico; Stahl, Sascha; Steinkamp, Olaf; Stenyakin, Oleg; Stevenson, Scott; Stoica, Sabin; Stone, Sheldon; Storaci, Barbara; Stracka, Simone; Straticiuc, Mihai; Straumann, Ulrich; Stroili, Roberto; Subbiah, Vijay Kartik; Sun, Liang; Sutcliffe, William; Swientek, Krzysztof; Swientek, Stefan; Syropoulos, Vasileios; Szczekowski, Marek; Szczypka, Paul; Szilard, Daniela; Szumlak, Tomasz; T'Jampens, Stephane; Teklishyn, Maksym; Tellarini, Giulia; Teubert, Frederic; Thomas, Christopher; Thomas, Eric; van Tilburg, Jeroen; Tisserand, Vincent; Tobin, Mark; Tolk, Siim; Tomassetti, Luca; Tonelli, Diego; Topp-Joergensen, Stig; Torr, Nicholas; Tournefier, Edwige; Tourneur, Stephane; Tran, Minh Tâm; Tresch, Marco; Tsaregorodtsev, Andrei; Tsopelas, Panagiotis; Tuning, Niels; Ubeda Garcia, Mario; Ukleja, Artur; Ustyuzhanin, Andrey; Uwer, Ulrich; Vagnoni, Vincenzo; Valenti, Giovanni; Vallier, Alexis; Vazquez Gomez, Ricardo; Vazquez Regueiro, Pablo; Vázquez Sierra, Carlos; Vecchi, Stefania; Velthuis, Jaap; Veltri, Michele; Veneziano, Giovanni; Vesterinen, Mika; Viaud, Benoit; Vieira, Daniel; Vieites Diaz, Maria; Vilasis-Cardona, Xavier; Vollhardt, Achim; Volyanskyy, Dmytro; Voong, David; Vorobyev, Alexey; Vorobyev, Vitaly; Voß, Christian; Voss, Helge; de Vries, Jacco; Waldi, Roland; Wallace, Charlotte; Wallace, Ronan; Walsh, John; Wandernoth, Sebastian; Wang, Jianchun; Ward, David; Watson, Nigel; Websdale, David; Whitehead, Mark; Wicht, Jean; Wiedner, Dirk; Wilkinson, Guy; Williams, Matthew; Williams, Mike; Wilson, Fergus; Wimberley, Jack; Wishahi, Julian; Wislicki, Wojciech; Witek, Mariusz; Wormser, Guy; Wotton, Stephen; Wright, Simon; Wu, Suzhi; Wyllie, Kenneth; Xie, Yuehong; Xing, Zhou; Xu, Zhirui; Yang, Zhenwei; Yuan, Xuhao; Yushchenko, Oleg; Zangoli, Maria; Zavertyaev, Mikhail; Zhang, Feng; Zhang, Liming; Zhang, Wen Chao; Zhang, Yanxi; Zhelezov, Alexey; Zhokhov, Anatoly; Zhong, Liang; Zvyagin, Alexander

    2015-01-01

    The decay $B^0\\to \\psi(2S) K^+\\pi^-$ is analyzed using $\\rm 3~fb^{-1}$ of $pp$ collision data collected with the LHCb detector. A model-independent description of the $\\psi(2S) \\pi$ mass spectrum is obtained, using as input the $K\\pi$ mass spectrum and angular distribution derived directly from data, without requiring a theoretical description of resonance shapes or their interference. The hypothesis that the $\\psi(2S)\\pi$ mass spectrum can be described in terms of $K\\pi$ reflections alone is rejected with more than 8$\\sigma$ significance. This provides confirmation, in a model-independent way, of the need for an additional resonant component in the mass region of the $Z(4430)^-$ exotic state.

  6. The Total Energy Efficiency Index for machine tools

    International Nuclear Information System (INIS)

    Schudeleit, Timo; Züst, Simon; Weiss, Lukas; Wegener, Konrad

    2016-01-01

    Energy efficiency in industries is one of the dominating challenges of the 21st century. Since the release of the eco-design directive 2005/32/EC in 2005, great research effort has been spent on the energy efficiency assessment for energy using products. The ISO (International Organization for Standardization) standardization body (ISO/TC 39 WG 12) currently works on the ISO 14955 series in order to enable the assessment of energy efficient design of machine tools. A missing piece for completion of the ISO 14955 series is a metric to quantify the design of machine tools regarding energy efficiency based on the respective assembly of components. The metric needs to take into account each machine tool components' efficiency and the need-oriented utilization in combination with the other components while referring to efficiency limits. However, a state of the art review reveals that none of the existing metrics is feasible to adequately match this goal. This paper presents a metric that matches all these criteria to promote the development of the ISO 14955 series. The applicability of the metric is proven in a practical case study on a turning machine. - Highlights: • Study for pushing forward the standardization work on the ISO 14955 series. • Review of existing energy efficiency indicators regarding three basic strategies to foster sustainability. • Development of a metric comprising the three basic strategies to foster sustainability. • Metric application for quantifying the energy efficiency of a turning machine.

  7. Spatio temporal media components for neurofeedback

    DEFF Research Database (Denmark)

    Jensen, Camilla Birgitte Falk; Petersen, Michael Kai; Larsen, Jakob Eg

    2013-01-01

    A class of Brain Computer Interfaces (BCI) involves interfaces for neurofeedback training, where a user can learn to self-regulate brain activity based on real-time feedback. These particular interfaces are constructed from audio-visual components and temporal settings, which appear to have...... a strong influence on the ability to control brain activity. Therefore, identifying the different interface components and exploring their individual effects might be key for constructing new interfaces that support more efficient neurofeedback training. We discuss experiments involving two different...

  8. Certification and brand identity for energy efficiency in competitive energy services markets

    Energy Technology Data Exchange (ETDEWEB)

    Prindle, W.R.; Wiser, R.

    1998-07-01

    Resource commitments for energy efficiency from electricity companies are disappearing rapidly as the regulated Integrated Resource Planning and Demand-Side Management paradigms that fostered them give way to competitive power markets in a restructuring electricity industry. While free-market advocates claim that energy efficiency needs will be taken care of by competitive energy service providers, there is no assurance that efficiency will compete effectively with the panoply of other energy-related (and non-energy-related) services that are beginning to appear in early market offerings. This paper reports the results of a feasibility study for a certification and brand identity program for energy efficiency geared to competitive power markets. Funded by the Energy Foundation, this study involved a survey and personal interviews with stakeholders, plus a workshop to further the discussion. Stakeholders include independent power marketers and energy service companies, utility affiliate power marketers and energy service companies, government agencies, trade associations, non-profit organizations, equipment manufacturers, and consultants. The paper summarizes the study's findings on such key issues as: Whether a brand identity concept has a critical mass of interest and support; how qualification and certification could work in such a program; how a brand identity could be positioned in the market; how an efficiency brand identity could co-brand with renewable power branding programs and other green marketing efforts; and the resources and components needed to make such a program work on a national scale.

  9. Robustness analysis of the efficiency in PV inverters

    DEFF Research Database (Denmark)

    Pigazo, Alberto; Liserre, Marco; Blaabjerg, Frede

    2013-01-01

    topology and control strategy but also on the characteristics of the employed components. The aim of this paper is evaluate the effect of physical variations associated to the main components on the overall efficiency of PV inverters. It is concluded that a statistical evaluation of the power converter......During last years an increasing attention has been paid to the efficiency of grid-connected PV inverters. They are manufactured from a number of discrete components and by using a certain topology and control strategy. Hence, the performance of a certain PV inverter not only depends on the selected...

  10. Structured Performance Analysis for Component Based Systems

    OpenAIRE

    Salmi , N.; Moreaux , Patrice; Ioualalen , M.

    2012-01-01

    International audience; The Component Based System (CBS) paradigm is now largely used to design software systems. In addition, performance and behavioural analysis remains a required step for the design and the construction of efficient systems. This is especially the case of CBS, which involve interconnected components running concurrent processes. % This paper proposes a compositional method for modeling and structured performance analysis of CBS. Modeling is based on Stochastic Well-formed...

  11. Independent Subspace Analysis of the Sea Surface Temperature Variability: Non-Gaussian Sources and Sensitivity to Sampling and Dimensionality

    Directory of Open Access Journals (Sweden)

    Carlos A. L. Pires

    2017-01-01

    Full Text Available We propose an expansion of multivariate time-series data into maximally independent source subspaces. The search is made among rotations of prewhitened data which maximize non-Gaussianity of candidate sources. We use a tensorial invariant approximation of the multivariate negentropy in terms of a linear combination of squared coskewness and cokurtosis. By solving a high-order singular value decomposition problem, we extract the axes associated with most non-Gaussianity. Moreover, an estimate of the Gaussian subspace is provided by the trailing singular vectors. The independent subspaces are obtained through the search of “quasi-independent” components within the estimated non-Gaussian subspace, followed by the identification of groups with significant joint negentropies. Sources result essentially from the coherency of extremes of the data components. The method is then applied to the global sea surface temperature anomalies, equatorward of 65°, after being tested with non-Gaussian surrogates consistent with the data anomalies. The main emerging independent components and subspaces, supposedly generated by independent forcing, include different variability modes, namely, The East-Pacific, the Central Pacific, and the Atlantic Niños, the Atlantic Multidecadal Oscillation, along with the subtropical dipoles in the Indian, South Pacific, and South-Atlantic oceans. Benefits and usefulness of independent subspaces are then discussed.

  12. Polish Foundation for Energy Efficiency

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1995-12-31

    The Polish Foundation for Energy Efficiency (FEWE) was established in Poland at the end of 1990. FEWE, as an independent and non-profit organization, has the following objectives: to strive towards an energy efficient national economy, and to show the way and methods by use of which energy efficiency can be increased. The activity of the Foundation covers the entire territory of Poland through three regional centers: in Warsaw, Katowice and Cracow. FEWE employs well-known and experienced specialists within thermal and power engineering, civil engineering, economy and applied sciences. The organizer of the Foundation has been Battelle Memorial Institute - Pacific Northwest Laboratories from the USA.

  13. MDM2 Associates with Polycomb Repressor Complex 2 and Enhances Stemness-Promoting Chromatin Modifications Independent of p53.

    Science.gov (United States)

    Wienken, Magdalena; Dickmanns, Antje; Nemajerova, Alice; Kramer, Daniela; Najafova, Zeynab; Weiss, Miriam; Karpiuk, Oleksandra; Kassem, Moustapha; Zhang, Yanping; Lozano, Guillermina; Johnsen, Steven A; Moll, Ute M; Zhang, Xin; Dobbelstein, Matthias

    2016-01-07

    The MDM2 oncoprotein ubiquitinates and antagonizes p53 but may also carry out p53-independent functions. Here we report that MDM2 is required for the efficient generation of induced pluripotent stem cells (iPSCs) from murine embryonic fibroblasts, in the absence of p53. Similarly, MDM2 depletion in the context of p53 deficiency also promoted the differentiation of human mesenchymal stem cells and diminished clonogenic survival of cancer cells. Most of the MDM2-controlled genes also responded to the inactivation of the Polycomb Repressor Complex 2 (PRC2) and its catalytic component EZH2. MDM2 physically associated with EZH2 on chromatin, enhancing the trimethylation of histone 3 at lysine 27 and the ubiquitination of histone 2A at lysine 119 (H2AK119) at its target genes. Removing MDM2 simultaneously with the H2AK119 E3 ligase Ring1B/RNF2 further induced these genes and synthetically arrested cell proliferation. In conclusion, MDM2 supports the Polycomb-mediated repression of lineage-specific genes, independent of p53. Copyright © 2016 Elsevier Inc. All rights reserved.

  14. INTERACTION’S EFFECT OF ORGANIC MATERIAL AND AGGREGATION ON EXTRACTION EFFICIENCY OF TPHS FROM PETROLEUM CONTAMINATED SOILS WITH MAE

    Directory of Open Access Journals (Sweden)

    H. Ganjidoust and Gh. Naghizadeh

    2005-10-01

    Full Text Available Microwave-Assisted Extraction (MAE is a type of low-temperature thermal desorption process that its numerous advantages have caused a wide spread use of it. Microwave heating is a potentially attractive technique as it provides volumetric heating process to improve heating efficiencies as compared with conventional techniques. The ability to rapidly heat the sample solvent mixture is inherent to MAE and the main advantage of this technique. Presently MAE has been shown to be one of the best technologies for removing environmental pollutants specially PAHs, phenols and PCBs from soils and sediments. Five different mixtures and types of aggregation (Sand, Top soil, Kaolinite besides three concentrations of crude oil as a contaminant (1000, 5000 and 10000 mg/L were considered. The results indicated that regardless of aggregation, the presence of humus component in soil reduces the efficiency. Minimum and maximum efficiencies were for sandy soil (containing organic components and kaolinite (without any organic content, respectively. According to the results of this research when some amount of humus and organic materials are available in the matrix, it causes the extraction efficiency to perform as a function of just humus materials but not aggregation. Increasing the concentration of crude oil reduced the efficiency with a sharp steep for higher concentration (5000-10000 mg/L and less steeper for lower concentration (1000-5000 mg/L. The concentration of the contaminant, works just as an independent function with extraction time and aggregation factors. The extraction period of 10 min. can be suggested as an optimum extraction time in FMAE for PAHs contaminated soils.

  15. Emotional stability components of human performance problems

    International Nuclear Information System (INIS)

    Wexler, R.H.

    1987-01-01

    Over half of all significant events that occur in nuclear plants involve human performance problems. There is increasing worldwide recognition that human performance problems have a significant impact on the safety, cost, and efficiency of nuclear plant operations. Emotional stability components have an important direct and indirect impact on human performance problems. This paper examines emotional stability components that are currently incorporated into human performance evaluation systems (HPES) in nuclear plants. It describes HPES programs being developed around the world, the emotional stability components that are currently referred to in these programs, and suggestions for improving HPES programs through a greater understanding of emotion stability components. A review of emotional stability components that may hinder or promote a plant environment that encourages the voluntary reporting and correction of human error is also presented

  16. The Influence of Alertness on Spatial and Nonspatial Components of Visual Attention

    Science.gov (United States)

    Matthias, Ellen; Bublak, Peter; Muller, Hermann J.; Schneider, Werner X.; Krummenacher, Joseph; Finke, Kathrin

    2010-01-01

    Three experiments investigated whether spatial and nonspatial components of visual attention would be influenced by changes in (healthy, young) subjects' level of alertness and whether such effects on separable components would occur independently of each other. The experiments used a no-cue/alerting-cue design with varying cue-target stimulus…

  17. Energy Independence and Security Act of 2007: A Summary of Major Provisions

    National Research Council Canada - National Science Library

    Sissine, Fred

    2007-01-01

    The Energy Independence and Security Act (P.L. 110-140, H.R. 6) is an omnibus energy policy law that consists mainly of provisions designed to increase energy efficiency and the availability of renewable energy...

  18. Efficient three-dimensional resist profile-driven source mask optimization optical proximity correction based on Abbe-principal component analysis and Sylvester equation

    Science.gov (United States)

    Lin, Pei-Chun; Yu, Chun-Chang; Chen, Charlie Chung-Ping

    2015-01-01

    As one of the critical stages of a very large scale integration fabrication process, postexposure bake (PEB) plays a crucial role in determining the final three-dimensional (3-D) profiles and lessening the standing wave effects. However, the full 3-D chemically amplified resist simulation is not widely adopted during the postlayout optimization due to the long run-time and huge memory usage. An efficient simulation method is proposed to simulate the PEB while considering standing wave effects and resolution enhancement techniques, such as source mask optimization and subresolution assist features based on the Sylvester equation and Abbe-principal component analysis method. Simulation results show that our algorithm is 20× faster than the conventional Gaussian convolution method.

  19. Independently Controlled Wing Stroke Patterns in the Fruit Fly Drosophila melanogaster

    Czech Academy of Sciences Publication Activity Database

    Chakraborty, Soma; Bartussek, Jan; Fry, S.N.; Zápotocký, Martin

    2015-01-01

    Roč. 10, č. 2 (2015), e0116813 E-ISSN 1932-6203 R&D Projects: GA ČR(CZ) GBP304/12/G069 Institutional support: RVO:67985823 Keywords : motor control * wing kinematics * independent component analysis Subject RIV: ED - Physiology Impact factor: 3.057, year: 2015

  20. Sadness and ruminative thinking independently depress people's moods.

    Science.gov (United States)

    Jahanitabesh, Azra; Cardwell, Brittany A; Halberstadt, Jamin

    2017-11-02

    Depression and rumination often co-occur in clinical populations, but it is not clear which causes which, or if both are manifestations of an underlying pathology. Does rumination simply exacerbate whatever affect a person is experiencing, or is it a negative experience in and of itself? In two experiments we answer this question by independently manipulating emotion and rumination. Participants were allocated to sad or neutral (in Experiment 1), or sad, neutral or happy (Experiment 2) mood conditions, via a combination of emotionally evocative music and autobiographical recall. Afterwards, in both studies, participants either ruminated by thinking about self-relevant statements or, in a control group, thought about self-irrelevant statements. Taken together, our data show that, independent of participants' mood, ruminators reported more negative affect relative to controls. The findings are consistent with theories suggesting that self-focus is itself unpleasant, and illustrate that depressive rumination comprises both affective and ruminative components, which could be targeted independently in clinical samples. © 2017 International Union of Psychological Science.

  1. The loss of essential oil components induced by the Purge Time in the Pressurized Liquid Extraction (PLE) procedure of Cupressus sempervirens.

    Science.gov (United States)

    Dawidowicz, Andrzej L; Czapczyńska, Natalia B; Wianowska, Dorota

    2012-05-30

    The influence of different Purge Times on the effectiveness of Pressurized Liquid Extraction (PLE) of volatile oil components from cypress plant matrix (Cupressus sempervirens) was investigated, applying solvents of diverse extraction efficiencies. The obtained results show the decrease of the mass yields of essential oil components as a result of increased Purge Time. The loss of extracted components depends on the extrahent type - the greatest mass yield loss occurred in the case of non-polar solvents, whereas the smallest was found in polar extracts. Comparisons of the PLE method with Sea Sand Disruption Method (SSDM), Matrix Solid-Phase Dispersion Method (MSPD) and Steam Distillation (SD) were performed to assess the method's accuracy. Independent of the solvent and Purge Time applied in the PLE process, the total mass yield was lower than the one obtained for simple, short and relatively cheap low-temperature matrix disruption procedures - MSPD and SSDM. Thus, in the case of volatile oils analysis, the application of these methods is advisable. Copyright © 2012 Elsevier B.V. All rights reserved.

  2. Efficient Adjoint Computation of Hybrid Systems of Differential Algebraic Equations with Applications in Power Systems

    Energy Technology Data Exchange (ETDEWEB)

    Abhyankar, Shrirang [Argonne National Lab. (ANL), Argonne, IL (United States); Anitescu, Mihai [Argonne National Lab. (ANL), Argonne, IL (United States); Constantinescu, Emil [Argonne National Lab. (ANL), Argonne, IL (United States); Zhang, Hong [Argonne National Lab. (ANL), Argonne, IL (United States)

    2016-03-31

    Sensitivity analysis is an important tool to describe power system dynamic behavior in response to parameter variations. It is a central component in preventive and corrective control applications. The existing approaches for sensitivity calculations, namely, finite-difference and forward sensitivity analysis, require a computational effort that increases linearly with the number of sensitivity parameters. In this work, we investigate, implement, and test a discrete adjoint sensitivity approach whose computational effort is effectively independent of the number of sensitivity parameters. The proposed approach is highly efficient for calculating trajectory sensitivities of larger systems and is consistent, within machine precision, with the function whose sensitivity we are seeking. This is an essential feature for use in optimization applications. Moreover, our approach includes a consistent treatment of systems with switching, such as DC exciters, by deriving and implementing the adjoint jump conditions that arise from state and time-dependent discontinuities. The accuracy and the computational efficiency of the proposed approach are demonstrated in comparison with the forward sensitivity analysis approach.

  3. Word Recognition Processing Efficiency as a Component of Second Language Listening

    Science.gov (United States)

    Joyce, Paul

    2013-01-01

    This study investigated the application of the speeded lexical decision task to L2 aural processing efficiency. One-hundred and twenty Japanese university students completed an aural word/nonword task. When the variation of lexical decision time (CV) was correlated with reaction time (RT), the results suggested that the single-word recognition…

  4. Composing simulations using persistent software components

    Energy Technology Data Exchange (ETDEWEB)

    Holland, J.V.; Michelsen, R.E.; Powell, D.R.; Upton, S.C.; Thompson, D.R.

    1999-03-01

    The traditional process for developing large-scale simulations is cumbersome, time consuming, costly, and in some cases, inadequate. The topics of software components and component-based software engineering are being explored by software professionals in academic and industrial settings. A component is a well-delineated, relatively independent, and replaceable part of a software system that performs a specific function. Many researchers have addressed the potential to derive a component-based approach to simulations in general, and a few have focused on military simulations in particular. In a component-based approach, functional or logical blocks of the simulation entities are represented as coherent collections of components satisfying explicitly defined interface requirements. A simulation is a top-level aggregate comprised of a collection of components that interact with each other in the context of a simulated environment. A component may represent a simulation artifact, an agent, or any entity that can generated events affecting itself, other simulated entities, or the state of the system. The component-based approach promotes code reuse, contributes to reducing time spent validating or verifying models, and promises to reduce the cost of development while still delivering tailored simulations specific to analysis questions. The Integrated Virtual Environment for Simulation (IVES) is a composition-centered framework to achieve this potential. IVES is a Java implementation of simulation composition concepts developed at Los Alamos National Laboratory for use in several application domains. In this paper, its use in the military domain is demonstrated via the simulation of dismounted infantry in an urban environment.

  5. Do efficiency scores depend on input mix?

    DEFF Research Database (Denmark)

    Asmild, Mette; Hougaard, Jens Leth; Kronborg, Dorte

    2013-01-01

    In this paper we examine the possibility of using the standard Kruskal-Wallis (KW) rank test in order to evaluate whether the distribution of efficiency scores resulting from Data Envelopment Analysis (DEA) is independent of the input (or output) mix of the observations. Since the DEA frontier...... is estimated, many standard assumptions for evaluating the KW test statistic are violated. Therefore, we propose to explore its statistical properties by the use of simulation studies. The simulations are performed conditional on the observed input mixes. The method, unlike existing approaches...... the assumption of mix independence is rejected the implication is that it, for example, is impossible to determine whether machine intensive project are more or less efficient than labor intensive projects....

  6. Collective fluctuations in networks of noisy components

    International Nuclear Information System (INIS)

    Masuda, Naoki; Kawamura, Yoji; Kori, Hiroshi

    2010-01-01

    Collective dynamics result from interactions among noisy dynamical components. Examples include heartbeats, circadian rhythms and various pattern formations. Because of noise in each component, collective dynamics inevitably involve fluctuations, which may crucially affect the functioning of the system. However, the relation between the fluctuations in isolated individual components and those in collective dynamics is not clear. Here, we study a linear dynamical system of networked components subjected to independent Gaussian noise and analytically show that the connectivity of networks determines the intensity of fluctuations in the collective dynamics. Remarkably, in general directed networks including scale-free networks, the fluctuations decrease more slowly with system size than the standard law stated by the central limit theorem. They even remain finite for a large system size when global directionality of the network exists. Moreover, such non-trivial behavior appears even in undirected networks when nonlinear dynamical systems are considered. We demonstrate it with a coupled oscillator system.

  7. Inorganic Biominerals in Crustaceans are Structurally Independent of Organic Framework

    Science.gov (United States)

    Mergelsberg, S. T.; Michel, F. M.; Mukhopadhyay, B.; Dove, P. M.

    2015-12-01

    Biomineralization of calcium carbonate (CaCO3) as crystalline calcite or amorphous CaCO3 (ACC) occurs in the exoskeletons of all crustaceans. These cuticles are complex composites of inorganic mineral and organic macromolecules with highly divergent morphologies that are adapted to the extreme variations in environmental pressures within their diverse ecological niches. The remarkable variations and adaptations that form, infer a highly efficient and regulated mechanism for biomineralization that is most likely orchestrated by a myriad of biomacromolecules (Ziegler A 2012). The roles of these peptides and organic metabolites during CaCO3 biomineralization are not well understood. In part, this is due to a lack of knowledge of crustacean homeostasis. In a step toward understanding cuticle mineralization in crustaceans, this study asks: Which molecules affect biomineralization? Do the biomineral-active molecules vary greatly between species and body parts? Recent studies of polysaccharide controls on mineralization also raise the question of whether small heterogeneities in chitin, the most abundant biopolymer of the composite, could be primarily responsible for differences in CaCO3 crystallinity. This study used a novel spectroscopic approach to characterize the mineral and organic components of exoskeletons from three Malacostraca organisms — American Lobster (Homarus americanus), Dungeness Crab (Metacarcinus magister), and Red Rock Crab (Cancer productus). Using high-energy x-ray diffraction and Raman spectroscopy, the cuticles of three major body parts from these organisms were analyzed for the structure and bulk chemistry of its chitin and CaCO3 components. The findings indicate that Raman spectroscopy provides adequate resolution to show that crystallinity of chitin and the CaCO3 mineral component are chemically independent of each other, although their crystallinities co-vary for Brachyura species (Dungeness and Red Rock Crabs). Insights from this study

  8. Weighted Components of i-Government Enterprise Architecture

    Science.gov (United States)

    Budiardjo, E. K.; Firmansyah, G.; Hasibuan, Z. A.

    2017-01-01

    Lack of government performance, among others due to the lack of coordination and communication among government agencies. Whilst, Enterprise Architecture (EA) in the government can be use as a strategic planning tool to improve productivity, efficiency, and effectivity. However, the existence components of Government Enterprise Architecture (GEA) do not show level of importance, that cause difficulty in implementing good e-government for good governance. This study is to explore the weight of GEA components using Principal Component Analysis (PCA) in order to discovered an inherent structure of e-government. The results show that IT governance component of GEA play a major role in the GEA. The rest of components that consist of e-government system, e-government regulation, e-government management, and application key operational, contributed more or less the same. Beside that GEA from other countries analyzes using comparative base on comon enterprise architecture component. These weighted components use to construct i-Government enterprise architecture. and show the relative importance of component in order to established priorities in developing e-government.

  9. Enhanced dynamic wedge and independent monitor unit verification

    International Nuclear Information System (INIS)

    Howlett, SJ.

    2005-01-01

    Some serious radiation accidents have occurred around the world during the delivery of radiotherapy treatment. The regrettable incident in Panama clearly indicated the need for independent monitor unit (MU) verification. Indeed the International Atomic Energy Agency (IAEA), after investigating the incident, made specific recommendations for radiotherapy centres which included an independent monitor unit check for all treatments. Independent monitor unit verification is practiced in many radiotherapy centres in developed countries around the world. It is mandatory in USA but not yet in Australia. This paper describes development of an independent MU program, concentrating on the implementation of the Enhanced Dynamic Wedge (EDW) component. The difficult case of non centre of field (COF) calculation points under the EDW was studied in some detail. Results of a survey of Australasian centres regarding the use of independent MU check systems is also presented. The system was developed with reference to MU calculations made by Pinnacle 3 D Radiotherapy Treatment Planning (RTP) system (ADAC - Philips) for 4MV, 6MV and 18MV X-ray beams used at the Newcastle Mater Misericordiae Hospital (NMMH) in the clinical environment. A small systematic error was detected in the equation used for the EDW calculations. Results indicate that COF equations may be used in the non COF situation with similar accuracy to that achieved with profile corrected methods. Further collaborative work with other centres is planned to extend these findings

  10. An ensemble training scheme for machine-learning classification of Hyperion satellite imagery with independent hyperspectral libraries

    Science.gov (United States)

    Friedel, Michael; Buscema, Massimo

    2016-04-01

    A training scheme is proposed for the real-time classification of soil and vegetation (landscape) components in EO-1 Hyperion hyperspectral images. First, an auto-contractive map is used to compute connectivity of reflectance values for spectral bands (N=200) from independent laboratory spectral library components. Second, a minimum spanning tree is used to identify optimal grouping of training components from connectivity values. Third, the reflectance values for optimal landscape component signatures are sorted. Fourth, empirical distribution functions (EDF) are computed for each landscape component. Fifth, the Monte-Carlo technique is used to generate realizations (N=30) for each landscape EDF. The correspondence of component realizations to original signatures validates the stochastic procedure. Presentation of the realizations to the self-organizing map (SOM) is done using three different map sizes: 14x10, 28x20, and 40 x 30. In each case, the SOM training proceeds first with a rough phase (20 iterations using a Gaussian neighborhood with an initial and final radius of 11 units and 3 units) and then fine phase (400 iterations using a Gaussian neighborhood with an initial and final radius of 3 units and 1 unit). The initial and final learning rates of 0.5 and 0.05 decay linearly down to 10-5, and the Gaussian neighborhood function decreases exponentially (decay rate of 10-3 iteration-1) providing reasonable convergence. Following training of the three networks, each corresponding SOM is used to independently classify the original spectral library signatures. In comparing the different SOM networks, the 28x20 map size is chosen for independent reproducibility and processing speed. The corresponding universal distance matrix reveals separation of the seven component classes for this map size thereby supporting it use as a Hyperion classifier.

  11. The integration of emotional and symbolic components in multimodal communication

    Directory of Open Access Journals (Sweden)

    Marc eMehu

    2015-07-01

    Full Text Available Human multimodal communication can be said to serve two main purposes: information transfer and social influence. In this paper, I argue that different components of multimodal signals play different roles in the processes of information transfer and social influence. Although the symbolic components of communication (e.g. verbal and denotative signals are well suited to transfer conceptual information, emotional components (e.g. nonverbal signals that are difficult to manipulate voluntarily likely take a function that is closer to social influence. I suggest that emotion should be considered a property of communicative signals, rather than an entity that is transferred as content by nonverbal signals. In this view, the effect of emotional processes on communication serve to change the quality of social signals to make them more efficient at producing responses in perceivers, whereas symbolic components increase the signals’ efficiency at interacting with the cognitive processes dedicated to the assessment of relevance. The interaction between symbolic and emotional components will be discussed in relation to the need for perceivers to evaluate the reliability of multimodal signals.

  12. The integration of emotional and symbolic components in multimodal communication

    Science.gov (United States)

    Mehu, Marc

    2015-01-01

    Human multimodal communication can be said to serve two main purposes: information transfer and social influence. In this paper, I argue that different components of multimodal signals play different roles in the processes of information transfer and social influence. Although the symbolic components of communication (e.g., verbal and denotative signals) are well suited to transfer conceptual information, emotional components (e.g., non-verbal signals that are difficult to manipulate voluntarily) likely take a function that is closer to social influence. I suggest that emotion should be considered a property of communicative signals, rather than an entity that is transferred as content by non-verbal signals. In this view, the effect of emotional processes on communication serve to change the quality of social signals to make them more efficient at producing responses in perceivers, whereas symbolic components increase the signals’ efficiency at interacting with the cognitive processes dedicated to the assessment of relevance. The interaction between symbolic and emotional components will be discussed in relation to the need for perceivers to evaluate the reliability of multimodal signals. PMID:26217280

  13. Sex-dependent components of the analgesia produced by athletic competition.

    Science.gov (United States)

    Sternberg, W F; Bokat, C; Kass, L; Alboyadjian, A; Gracely, R H

    2001-02-01

    Competing in various athletic events (track meet, basketball game, or fencing match) can produce analgesia to cold pressor stimuli in male and female college athletes compared with baseline assessments. This competition-induced analgesia has been attributed to the stress associated with competition, which has components related to both physical exercise and the cognitive aspects of competing. This study evaluated the analgesic effect of exercise-related stress, and that caused by the cognitively stressful components of competing independent of exercise. Cold pressor pain ratings were assessed after competition in a track meet and after treadmill exercise or sedentary video game competition in both athletes and nonathletes. As expected, competing in athletics resulted in a decrease in cold pressor ratings in both male and female athletes. Independent of athletic status, treadmill running induced analgesia in women, but not in males, whereas sedentary video game competition produced analgesia in men, but not in women. These findings suggest that different components of the competitive athletic experience might be responsible for the analgesic effects in a sex-dependent manner.

  14. ORGANIZATION OF INDEPENDENT STUDENT WORK BASED ON STUDENT BLOGGING ACTIVITY

    Directory of Open Access Journals (Sweden)

    A. A. Gareyev

    2018-01-01

    Full Text Available Introduction. Today, the students’ personality traits and increasing their motivation to self-development are the most complex and urgent problems in foreign language training at higher technical university and in the system of higher education in general. According to the authors, the technology of student blogging is a means for addressing these issues, despite the lack of research on its methodology. In that regard, there is a need for further studies on information and communication technologies (ICT application by promoting independent student work. The aim of this paper is to present the developed model of organization of bachelors’ independent work through educational blogging; to fulfill educational potential and to prove the efficiency of ICTs application in education taking into consideration professional foreign language competence development of future specialists in tool making. Methodology and research methods. When designing the model, the basic considerations of the following methodological approaches were considered: competency-based, personal-oriented, activity-based, thesaurus, and qualimetric; the listed above approaches enable to realize the principles of individualization, professional orientation, integrity, self-organization and interactivity in the performed work. The method of group expert assessment, as the leading one in pedagogical qualimetry, was chosen as the main method in the research undertaken. The methods of modeling and pedagogical experiment were involved. Results and scientific novelty. The structure of professional foreign language competence (including communicative, cognitive and subject components of future toolmaking bachelors is identified. The development of the competence formation model among students is described in detail: having studied independently the subject topic, the students post the material. Pedagogical conditions and didactic guidelines for the model realization are formulated

  15. Aerolization During Boron Nanoparticle Multi-Component Fuel Group Burning Studies

    Science.gov (United States)

    2014-02-03

    overall energy density of the multi-component fuel mixture. Boron nanoparticle- doped multi-component hydrocarbon fuels represent a potential high...addressed, Boron nanoparticle- doped multi-component hydrocarbon fuels represent a potential high-efficiency, tactical fuel that could increase thrust...and micron-sized aluminum particles. Combustion and Flame 158(2): 354-368. Gan, Y., Y. S. Lim, and L. Qiao. 2012. Combustion of nanofluid fuels

  16. Two Independent Mushroom Body Output Circuits Retrieve the Six Discrete Components of Drosophila Aversive Memory

    Directory of Open Access Journals (Sweden)

    Emna Bouzaiane

    2015-05-01

    Full Text Available Understanding how the various memory components are encoded and how they interact to guide behavior requires knowledge of the underlying neural circuits. Currently, aversive olfactory memory in Drosophila is behaviorally subdivided into four discrete phases. Among these, short- and long-term memories rely, respectively, on the γ and α/β Kenyon cells (KCs, two distinct subsets of the ∼2,000 neurons in the mushroom body (MB. Whereas V2 efferent neurons retrieve memory from α/β KCs, the neurons that retrieve short-term memory are unknown. We identified a specific pair of MB efferent neurons, named M6, that retrieve memory from γ KCs. Moreover, our network analysis revealed that six discrete memory phases actually exist, three of which have been conflated in the past. At each time point, two distinct memory components separately recruit either V2 or M6 output pathways. Memory retrieval thus features a dramatic convergence from KCs to MB efferent neurons.

  17. Highly efficient one-pot/one-step synthesis of multiblock copolymers from three-component polymerization of carbon dioxide, epoxide and lactone.

    Science.gov (United States)

    Li, Yang; Hong, Jiali; Wei, Renjian; Zhang, Yingying; Tong, Zaizai; Zhang, Xinghong; Du, Binyang; Xu, Junting; Fan, Zhiqiang

    2015-02-01

    It is a long-standing challenge to combine mixed monomers into multiblock copolymer (MBC) in a one-pot/one-step polymerization manner. We report the first example of MBC with biodegradable polycarbonate and polyester blocks that were synthesized from highly efficient one-pot/one-step polymerization of cyclohexene oxide (CHO), CO 2 and ε-caprolactone (ε-CL) in the presence of zinc-cobalt double metal cyanide complex and stannous octoate. In this protocol, two cross-chain exchange reactions (CCER) occurred at dual catalysts respectively and connected two independent chain propagation procedures ( i.e. , polycarbonate formation and polyester formation) simultaneously in a block-by-block manner, affording MBC without tapering structure. The multiblock structure of MBC was determined by the rate ratio of CCER to the two chain propagations and could be simply tuned by various kinetic factors. This protocol is also of significance due to partial utilization of renewable CO 2 and improved mechanical properties of the resultant MBC.

  18. Efficient Use of Exogenous Isoprenols for Protein Isoprenylation by MDA-MB-231 Cells Is Regulated Independently of the Mevalonate Pathway*

    Science.gov (United States)

    Onono, Fredrick; Subramanian, Thangaiah; Sunkara, Manjula; Subramanian, Karunai Leela; Spielmann, H. Peter; Morris, Andrew J.

    2013-01-01

    Mammalian cells can use exogenous isoprenols to generate isoprenoid diphosphate substrates for protein isoprenylation, but the mechanism, efficiency, and biological importance of this process are not known. We developed mass spectrometry-based methods using chemical probes and newly synthesized stable isotope-labeled tracers to quantitate incorporation of exogenously provided farnesol, geranylgeraniol, and unnatural analogs of these isoprenols containing an aniline group into isoprenoid diphosphates and protein isoprenylcysteines by cultured human cancer cell lines. We found that at exogenous isoprenol concentrations >10 μm, this process can generate as much as 50% of the cellular isoprenoid diphosphate pool used for protein isoprenylation. Mutational activation of p53 in MDA-MB-231 breast cancer cells up-regulates the mevalonate pathway to promote tumor invasiveness. p53 silencing or pharmacological inhibition of HMG-CoA reductase in these cells decreases protein isoprenylation from endogenously synthesized isoprenoids but enhances the use of exogenous isoprenols for this purpose, indicating that this latter process is regulated independently of the mevalonate pathway. Our observations suggest unique opportunities for design of cancer cell-directed therapies and may provide insights into mechanisms underlying pleiotropic therapeutic benefits and unwanted side effects of mevalonate pathway inhibition. PMID:23908355

  19. Principal Component Analysis In Radar Polarimetry

    Directory of Open Access Journals (Sweden)

    A. Danklmayer

    2005-01-01

    Full Text Available Second order moments of multivariate (often Gaussian joint probability density functions can be described by the covariance or normalised correlation matrices or by the Kennaugh matrix (Kronecker matrix. In Radar Polarimetry the application of the covariance matrix is known as target decomposition theory, which is a special application of the extremely versatile Principle Component Analysis (PCA. The basic idea of PCA is to convert a data set, consisting of correlated random variables into a new set of uncorrelated variables and order the new variables according to the value of their variances. It is important to stress that uncorrelatedness does not necessarily mean independent which is used in the much stronger concept of Independent Component Analysis (ICA. Both concepts agree for multivariate Gaussian distribution functions, representing the most random and least structured distribution. In this contribution, we propose a new approach in applying the concept of PCA to Radar Polarimetry. Therefore, new uncorrelated random variables will be introduced by means of linear transformations with well determined loading coefficients. This in turn, will allow the decomposition of the original random backscattering target variables into three point targets with new random uncorrelated variables whose variances agree with the eigenvalues of the covariance matrix. This allows a new interpretation of existing decomposition theorems.

  20. Distribution of Independent Boutique Hotels on Secondary and Tertiary Markets in Germany

    OpenAIRE

    Dambach, Marie-Theres

    2016-01-01

    Boutique hotels are a recent trend in the hospitality industry. As they are receiving more and more attention independent operators on secondary and tertiary markets need to find ways to reach and sell to their customer in order to stay competitive. Therefore, the question is raised whether the way independent German boutique hoteliers distribute their products matches the way their guests prefer or would prefer to buy them. Moreover, it was evaluated if soft brands are an efficient tool to s...

  1. Digital hologram transformations for RGB color holographic display with independent image magnification and translation in 3D.

    Science.gov (United States)

    Makowski, Piotr L; Zaperty, Weronika; Kozacki, Tomasz

    2018-01-01

    A new framework for in-plane transformations of digital holograms (DHs) is proposed, which provides improved control over basic geometrical features of holographic images reconstructed optically in full color. The method is based on a Fourier hologram equivalent of the adaptive affine transformation technique [Opt. Express18, 8806 (2010)OPEXFF1094-408710.1364/OE.18.008806]. The solution includes four elementary geometrical transformations that can be performed independently on a full-color 3D image reconstructed from an RGB hologram: (i) transverse magnification; (ii) axial translation with minimized distortion; (iii) transverse translation; and (iv) viewing angle rotation. The independent character of transformations (i) and (ii) constitutes the main result of the work and plays a double role: (1) it simplifies synchronization of color components of the RGB image in the presence of mismatch between capture and display parameters; (2) provides improved control over position and size of the projected image, particularly the axial position, which opens new possibilities for efficient animation of holographic content. The approximate character of the operations (i) and (ii) is examined both analytically and experimentally using an RGB circular holographic display system. Additionally, a complex animation built from a single wide-aperture RGB Fourier hologram is presented to demonstrate full capabilities of the developed toolset.

  2. Parallel ICA identifies sub-components of resting state networks that covary with behavioral indices.

    Science.gov (United States)

    Meier, Timothy B; Wildenberg, Joseph C; Liu, Jingyu; Chen, Jiayu; Calhoun, Vince D; Biswal, Bharat B; Meyerand, Mary E; Birn, Rasmus M; Prabhakaran, Vivek

    2012-01-01

    Parallel Independent Component Analysis (para-ICA) is a multivariate method that can identify complex relationships between different data modalities by simultaneously performing Independent Component Analysis on each data set while finding mutual information between the two data sets. We use para-ICA to test the hypothesis that spatial sub-components of common resting state networks (RSNs) covary with specific behavioral measures. Resting state scans and a battery of behavioral indices were collected from 24 younger adults. Group ICA was performed and common RSNs were identified by spatial correlation to publically available templates. Nine RSNs were identified and para-ICA was run on each network with a matrix of behavioral measures serving as the second data type. Five networks had spatial sub-components that significantly correlated with behavioral components. These included a sub-component of the temporo-parietal attention network that differentially covaried with different trial-types of a sustained attention task, sub-components of default mode networks that covaried with attention and working memory tasks, and a sub-component of the bilateral frontal network that split the left inferior frontal gyrus into three clusters according to its cytoarchitecture that differentially covaried with working memory performance. Additionally, we demonstrate the validity of para-ICA in cases with unbalanced dimensions using simulated data.

  3. Commonwealth of the independent states - the new formof interethnic integration

    Directory of Open Access Journals (Sweden)

    Ф У Айбазова

    2008-06-01

    Full Text Available In clause on a concrete historical material the new independent sovereign states are analyzed which have been formed after disintegration of the USSR. Forms of their integration in economic, military, cultural and social integration are shown. Conclusions are done and the offers directed on the further efficiency of their cooperation are formulated.

  4. Efficiency assessment of a wind pumping system

    International Nuclear Information System (INIS)

    Lara, David D.; Merino, Gabriel G.; Pavez, Boris J.; Tapia, Juan A.

    2011-01-01

    The combined efficiency of the components determines overall system performance in electric wind pumping systems. We evaluated a system composed of a 3 kW wind generator feeding a battery bank of 48 V/880 Ah by means of a non-controlled 6-pulse rectifier. Connected to this battery bank was a 1.5 kW inverter that generated 220 V at 50 Hz, which powers a 1.1 kW single-phase electric pump. At the University of Concepcion, Chile, energy losses in each electrical component was determined using a data collection system configured to measure electrical variables in real time. The electrical power generated by the wind generator for different wind speeds averaged 38% lower than the power curve provided by the manufacturer. Electromechanical tests performed in a lab showed the operation efficiency of the electric generator of the wind turbine averaged 80%. This information, along with the electrical power output, and the wind velocity measured during field operation allowed us to determine the rotor's power coefficient C p , which had a maximum value of 35%. For the stored energy components measured data indicated that the rectifier, the battery bank, and the inverter operated with average efficiencies of 95%, 78% and 86% respectively. The combined component efficiencies showed a maximum of 17% of the wind energy would be available for water pumping. Since a large amount of wind energy was dissipated during the energy conversion process, new configurations should be analyzed that could avoid such losses in wind pumping systems.

  5. Efficiency assessment of a wind pumping system

    Energy Technology Data Exchange (ETDEWEB)

    Lara, David D.; Merino, Gabriel G. [Department of Mechanization and Energy, University of Concepcion, Avenida Vicente Mendez 595, Chillan (Chile); Pavez, Boris J. [Department of Electrical Engineering, University of La Frontera, Casilla 54-D, Temuco (Chile); Tapia, Juan A. [Department of Electrical Engineering, University of Concepcion, Casilla 160-C, Concepcion (Chile)

    2011-02-15

    The combined efficiency of the components determines overall system performance in electric wind pumping systems. We evaluated a system composed of a 3 kW wind generator feeding a battery bank of 48 V/880 Ah by means of a non-controlled 6-pulse rectifier. Connected to this battery bank was a 1.5 kW inverter that generated 220 V at 50 Hz, which powers a 1.1 kW single-phase electric pump. At the University of Concepcion, Chile, energy losses in each electrical component was determined using a data collection system configured to measure electrical variables in real time. The electrical power generated by the wind generator for different wind speeds averaged 38% lower than the power curve provided by the manufacturer. Electromechanical tests performed in a lab showed the operation efficiency of the electric generator of the wind turbine averaged 80%. This information, along with the electrical power output, and the wind velocity measured during field operation allowed us to determine the rotor's power coefficient C{sub p}, which had a maximum value of 35%. For the stored energy components measured data indicated that the rectifier, the battery bank, and the inverter operated with average efficiencies of 95%, 78% and 86% respectively. The combined component efficiencies showed a maximum of 17% of the wind energy would be available for water pumping. Since a large amount of wind energy was dissipated during the energy conversion process, new configurations should be analyzed that could avoid such losses in wind pumping systems. (author)

  6. EDITORIAL: Special section on gaze-independent brain-computer interfaces Special section on gaze-independent brain-computer interfaces

    Science.gov (United States)

    Treder, Matthias S.

    2012-08-01

    Restoring the ability to communicate and interact with the environment in patients with severe motor disabilities is a vision that has been the main catalyst of early brain-computer interface (BCI) research. The past decade has brought a diversification of the field. BCIs have been examined as a tool for motor rehabilitation and their benefit in non-medical applications such as mental-state monitoring for improved human-computer interaction and gaming has been confirmed. At the same time, the weaknesses of some approaches have been pointed out. One of these weaknesses is gaze-dependence, that is, the requirement that the user of a BCI system voluntarily directs his or her eye gaze towards a visual target in order to efficiently operate a BCI. This not only contradicts the main doctrine of BCI research, namely that BCIs should be independent of muscle activity, but it can also limit its real-world applicability both in clinical and non-medical settings. It is only in a scenario devoid of any motor activity that a BCI solution is without alternative. Gaze-dependencies have surfaced at two different points in the BCI loop. Firstly, a BCI that relies on visual stimulation may require users to fixate on the target location. Secondly, feedback is often presented visually, which implies that the user may have to move his or her eyes in order to perceive the feedback. This special section was borne out of a BCI workshop on gaze-independent BCIs held at the 2011 Society for Applied Neurosciences (SAN) Conference and has then been extended with additional contributions from other research groups. It compiles experimental and methodological work that aims toward gaze-independent communication and mental-state monitoring. Riccio et al review the current state-of-the-art in research on gaze-independent BCIs [1]. Van der Waal et al present a tactile speller that builds on the stimulation of the fingers of the right and left hand [2]. H¨ohne et al analyze the ergonomic aspects

  7. Heavy steel casting components for power plants 'mega-components' made of high Cr-steels

    Energy Technology Data Exchange (ETDEWEB)

    Hanus, Reinhold [voestalpine Giesserei Linz GmbH, Linz (Austria)

    2010-07-01

    Steel castings of creep resistant steels play a key role in fossil fuel fired power plants for highly loaded components in the high and intermediate pressure section of the turbines. Inner and outer casings, valve casings, inlet connections and elbows are examples of such critical components. The most important characteristic in a power plant is the efficiency, which mainly drives the CO2-emission. As a consequence of steadily improving power plant efficiencies and ever stricter emission standards, steam parameters become more critical and the creep resistance of the cast materials must also be constantly improved. The foundries voestalpine Giesserei Linz and voestalpine Giesserei Traisen participated in the development of the new 9-10% Cr-steels for application up to 625 C/650 C and in the THERMIE project where Ni-base alloys for 700 C-power plants were developed. Beside the material development in the European research projects the commercial production had to be established for industrial processes and the newly developed materials have to be transferred from research into the commercial production of heavy cast components. After selecting the most promising alloy from the laboratory melts, welding tests were performed - mostly with matching electrodes also produced within COST/THERMIE. Base material and welds were investigated in respect of microstructure, creep resistance, mechanical properties and weldability. Heat treatment investigations were also necessary for optimization of the mechanical properties. Based on the results of these studies, pilot components and plates for testing welding processes were cast in order to verify the castability and weldability of larger parts and to make any necessary adjustments to chemical composition, heat treatment or welding parameters. Parallel to the ongoing creep tests within COST/THERMIE-program, the newly developed steel grades were introduced into the commercial production of large components. This involved finding

  8. Reliability analysis of a repairable k-out-of-n system with some components being suspended when the system is down

    International Nuclear Information System (INIS)

    Li Xiaohu; Zuo, Ming J.; Yam, Richard C.M.

    2006-01-01

    A k-out-of-n system with independent exponential components is investigated. It is assumed that some working components are suspended as soon as the system is down, repair starts immediately when a component fails and repair times are independent and exponentially distributed. Formulas for various reliability indices of the system including mean time between failures, mean working time in a failure-repair cycle, and mean down time in a failure-repair cycle are derived

  9. Application and Evaluation of Independent Component Analysis Methods to Generalized Seizure Disorder Activities Exhibited in the Brain.

    Science.gov (United States)

    George, S Thomas; Balakrishnan, R; Johnson, J Stanly; Jayakumar, J

    2017-07-01

    EEG records the spontaneous electrical activity of the brain using multiple electrodes placed on the scalp, and it provides a wealth of information related to the functions of brain. Nevertheless, the signals from the electrodes cannot be directly applied to a diagnostic tool like brain mapping as they undergo a "mixing" process because of the volume conduction effect in the scalp. A pervasive problem in neuroscience is determining which regions of the brain are active, given voltage measurements at the scalp. Because of which, there has been a surge of interest among the biosignal processing community to investigate the process of mixing and unmixing to identify the underlying active sources. According to the assumptions of independent component analysis (ICA) algorithms, the resultant mixture obtained from the scalp can be closely approximated by a linear combination of the "actual" EEG signals emanating from the underlying sources of electrical activity in the brain. As a consequence, using these well-known ICA techniques in preprocessing of the EEG signals prior to clinical applications could result in development of diagnostic tool like quantitative EEG which in turn can assist the neurologists to gain noninvasive access to patient-specific cortical activity, which helps in treating neuropathologies like seizure disorders. The popular and proven ICA schemes mentioned in various literature and applications were selected (which includes Infomax, JADE, and SOBI) and applied on generalized seizure disorder samples using EEGLAB toolbox in MATLAB environment to see their usefulness in source separations; and they were validated by the expert neurologist for clinical relevance in terms of pathologies on brain functionalities. The performance of Infomax method was found to be superior when compared with other ICA schemes applied on EEG and it has been established based on the validations carried by expert neurologist for generalized seizure and its clinical

  10. Monitoring changes in economy-wide energy efficiency: From energy-GDP ratio to composite efficiency index

    International Nuclear Information System (INIS)

    Ang, B.W.

    2006-01-01

    Since the 1973 world oil crisis, monitoring trends in energy efficiency at the economy-wide level has been an important component of energy strategy in many countries. To support this effort, various energy efficiency-related indicators have been developed. We examine some classical indicators which are often found in national and international energy studies in the 1970s and 1980s. We then describe the recent developments in using the index decomposition analysis to give an economy-wide composite energy efficiency index based on a bottom-up approach. This composite index is superior to the classical indicators as an economy-wide energy efficiency measure and has lately been adopted by a growing number of countries for national energy efficiency trend monitoring

  11. Energy Efficiency, Water Efficiency, and Renewable Energy Site Assessment: Mendenhall Glacier Visitor Center, Juneau, Alaska

    Energy Technology Data Exchange (ETDEWEB)

    Salasovich, James [National Renewable Energy Lab. (NREL), Golden, CO (United States); LoVullo, David [National Renewable Energy Lab. (NREL), Golden, CO (United States); Kandt, Alicen [National Renewable Energy Lab. (NREL), Golden, CO (United States)

    2016-01-21

    This report summarizes results from the energy efficiency, water efficiency, and renewable energy site assessment of the Mendenhall Glacier Visitor Center and site in Juneau, Alaska. The assessment is an American Society of Heating, Refrigerating, and Air-Conditioning Engineers Level 2 audit and meets Energy Independence and Security Act requirements. A team led by the U.S. Department of Energy's National Renewable Energy Laboratory conducted the assessment with U.S. Forest Service personnel August 19-20, 2015, as part of ongoing efforts by USFS to reduce energy and water use.

  12. Application of heterocyclic aldehydes as components in Ugi–Smiles couplings

    Directory of Open Access Journals (Sweden)

    Katelynn M. Mason

    2016-09-01

    Full Text Available Efficient one-pot Ugi–Smiles couplings are reported for the use of furyl-substituted aldehyde components. In the presence of these heterocyclic aldehydes, reactions tolerated variations in amine components and led to either isolated N-arylamide Ugi–Smiles adducts or N-arylepoxyisoindolines, products of tandem Ugi–Smiles Diels–Alder cyclizations, in moderate yields. A thienyl-substituted aldehyde was also a competent component for Ugi–Smiles adduct formation.

  13. Components of Standing Postural Control Evaluated in Pediatric Balance Measures: A Scoping Review.

    Science.gov (United States)

    Sibley, Kathryn M; Beauchamp, Marla K; Van Ooteghem, Karen; Paterson, Marie; Wittmeier, Kristy D

    2017-10-01

    To identify measures of standing balance validated in pediatric populations, and to determine the components of postural control captured in each tool. Electronic searches of MEDLINE, Embase, and CINAHL databases using key word combinations of postural balance/equilibrium, psychometrics/reproducibility of results/predictive value of tests, and child/pediatrics; gray literature; and hand searches. Inclusion criteria were measures with a stated objective to assess balance, with pediatric (≤18y) populations, with at least 1 psychometric evaluation, with at least 1 standing task, with a standardized protocol and evaluation criteria, and published in English. Two reviewers independently identified studies for inclusion. There were 21 measures included. Two reviewers extracted descriptive characteristics, and 2 investigators independently coded components of balance in each measure using a systems perspective for postural control, an established framework for balance in pediatric populations. Components of balance evaluated in measures were underlying motor systems (100% of measures), anticipatory postural control (72%), static stability (62%), sensory integration (52%), dynamic stability (48%), functional stability limits (24%), cognitive influences (24%), verticality (9%), and reactive postural control (0%). Assessing children's balance with valid and comprehensive measures is important for ensuring development of safe mobility and independence with functional tasks. Balance measures validated in pediatric populations to date do not comprehensively assess standing postural control and omit some key components for safe mobility and independence. Existing balance measures, that have been validated in adult populations and address some of the existing gaps in pediatric measures, warrant consideration for validation in children. Copyright © 2017 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

  14. On the importance of the long-term seasonal component in day-ahead electricity price forecasting

    International Nuclear Information System (INIS)

    Nowotarski, Jakub; Weron, Rafał

    2016-01-01

    In day-ahead electricity price forecasting (EPF) the daily and weekly seasonalities are always taken into account, but the long-term seasonal component (LTSC) is believed to add unnecessary complexity to the already parameter-rich models and is generally ignored. Conducting an extensive empirical study involving state-of-the-art time series models we show that (i) decomposing a series of electricity prices into a LTSC and a stochastic component, (ii) modeling them independently and (iii) combining their forecasts can bring – contrary to a common belief – an accuracy gain compared to an approach in which a given time series model is calibrated to the prices themselves. - Highlights: • A new class of Seasonal Component AutoRegressive (SCAR) models is introduced. • Electricity prices are decomposed into a trend-seasonal and a stochastic component. • Both components are modeled independently, their forecasts are combined. • Significant accuracy gains can be achieved compared to commonly used approaches.

  15. A 3D multi-mode geometry-independent RMP optimization method and its application to TCV

    International Nuclear Information System (INIS)

    Rossel, J X; Moret, J-M; Martin, Y

    2010-01-01

    Resonant magnetic perturbation (RMP) and error field correction (EFC) produced by toroidally and poloidally distributed coil systems can be optimized if each coil is powered with an independent power supply. A 3D multi-mode geometry-independent Lagrange method has been developed and appears to be an efficient way to minimize the parasitic spatial modes of the magnetic perturbation and the coil current requirements while imposing the amplitude and phase of a number of target modes. A figure of merit measuring the quality of a perturbation spectrum with respect to RMP independently of the considered coil system or plasma equilibrium is proposed. To ease the application of the Lagrange method, a spectral characterization of the system, based on a generalized discrete Fourier transform applied in current space, is performed to determine how spectral degeneracy and side-band creation limit the set of simultaneously controllable target modes. This characterization is also useful to quantify the efficiency of the coil system in each toroidal mode number and to know whether optimization is possible for a given number of target modes. The efficiency of the method is demonstrated in the special case of a multi-purpose saddle coil system proposed as part of a future upgrade of Tokamak a Configuration Variable (TCV). This system consists of three rows of eight internal coils, each coil having independent power supplies, and provides simultaneously EFC, RMP and fast vertical position control.

  16. BAYESIAN SEMI-BLIND COMPONENT SEPARATION FOR FOREGROUND REMOVAL IN INTERFEROMETRIC 21 cm OBSERVATIONS

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Le; Timbie, Peter T. [Department of Physics, University of Wisconsin, Madison, WI 53706 (United States); Bunn, Emory F. [Physics Department, University of Richmond, Richmond, VA 23173 (United States); Karakci, Ata; Korotkov, Andrei; Tucker, Gregory S. [Department of Physics, Brown University, 182 Hope Street, Providence, RI 02912 (United States); Sutter, P. M. [Center for Cosmology and Astro-Particle Physics, Ohio State University, Columbus, OH 43210 (United States); Wandelt, Benjamin D., E-mail: lzhang263@wisc.edu [Department of Physics, University of Illinois at Urbana-Champaign, 1110 W Green Street, Urbana, IL 61801 (United States)

    2016-01-15

    In this paper, we present a new Bayesian semi-blind approach for foreground removal in observations of the 21 cm signal measured by interferometers. The technique, which we call H i Expectation–Maximization Independent Component Analysis (HIEMICA), is an extension of the Independent Component Analysis technique developed for two-dimensional (2D) cosmic microwave background maps to three-dimensional (3D) 21 cm cosmological signals measured by interferometers. This technique provides a fully Bayesian inference of power spectra and maps and separates the foregrounds from the signal based on the diversity of their power spectra. Relying only on the statistical independence of the components, this approach can jointly estimate the 3D power spectrum of the 21 cm signal, as well as the 2D angular power spectrum and the frequency dependence of each foreground component, without any prior assumptions about the foregrounds. This approach has been tested extensively by applying it to mock data from interferometric 21 cm intensity mapping observations under idealized assumptions of instrumental effects. We also discuss the impact when the noise properties are not known completely. As a first step toward solving the 21 cm power spectrum analysis problem, we compare the semi-blind HIEMICA technique to the commonly used Principal Component Analysis. Under the same idealized circumstances, the proposed technique provides significantly improved recovery of the power spectrum. This technique can be applied in a straightforward manner to all 21 cm interferometric observations, including epoch of reionization measurements, and can be extended to single-dish observations as well.

  17. Path Analysis of Grain Yield and Yield Components and Some Agronomic Traits in Bread Wheat

    Directory of Open Access Journals (Sweden)

    Mohsen Janmohammadi

    2014-01-01

    Full Text Available Development of new bread wheat cultivars needs efficient tools to monitor trait association in a breeding program. This investigation was aimed to characterize grain yield components and some agronomic traits related to bread wheat grain yield. The efficiency of a breeding program depends mainly on the direction of the correlation between different traits and the relative importance of each component involved in contributing to grain yield. Correlation and path analysis were carried out in 56 bread wheat genotypes grown under field conditions of Maragheh, Iran. Observations were recorded on 18 wheat traits and correlation coefficient analysis revealed grain yield was positively correlated with stem diameter, spike length, floret number, spikelet number, grain diameter, grain length and 1000 seed weight traits. According to the variance inflation factor (VIF and tolerance as multicollinearity statistics, there are inconsistent relationships among the variables and all traits could be considered as first-order variables (Model I with grain yield as the response variable due to low multicollinearity of all measured traits. In the path coefficient analysis, grain yield represented the dependent variable and the spikelet number and 1000 seed weight traits were the independent ones. Our results indicated that the number of spikelets per spikes and leaf width and 1000 seed weight traits followed by the grain length, grain diameter and grain number per spike were the traits related to higher grain yield. The above mentioned traits along with their indirect causal factors should be considered simultaneously as an effective selection criteria evolving high yielding genotype because of their direct positive contribution to grain yield.

  18. Decoding the encoding of functional brain networks: An fMRI classification comparison of non-negative matrix factorization (NMF), independent component analysis (ICA), and sparse coding algorithms.

    Science.gov (United States)

    Xie, Jianwen; Douglas, Pamela K; Wu, Ying Nian; Brody, Arthur L; Anderson, Ariana E

    2017-04-15

    Brain networks in fMRI are typically identified using spatial independent component analysis (ICA), yet other mathematical constraints provide alternate biologically-plausible frameworks for generating brain networks. Non-negative matrix factorization (NMF) would suppress negative BOLD signal by enforcing positivity. Spatial sparse coding algorithms (L1 Regularized Learning and K-SVD) would impose local specialization and a discouragement of multitasking, where the total observed activity in a single voxel originates from a restricted number of possible brain networks. The assumptions of independence, positivity, and sparsity to encode task-related brain networks are compared; the resulting brain networks within scan for different constraints are used as basis functions to encode observed functional activity. These encodings are then decoded using machine learning, by using the time series weights to predict within scan whether a subject is viewing a video, listening to an audio cue, or at rest, in 304 fMRI scans from 51 subjects. The sparse coding algorithm of L1 Regularized Learning outperformed 4 variations of ICA (pcoding algorithms. Holding constant the effect of the extraction algorithm, encodings using sparser spatial networks (containing more zero-valued voxels) had higher classification accuracy (pcoding algorithms suggests that algorithms which enforce sparsity, discourage multitasking, and promote local specialization may capture better the underlying source processes than those which allow inexhaustible local processes such as ICA. Negative BOLD signal may capture task-related activations. Copyright © 2017 Elsevier B.V. All rights reserved.

  19. Speeding up coarse point cloud registration by threshold-independent baysac match selection

    NARCIS (Netherlands)

    Kang, Z.; Lindenbergh, R.C.; Pu, S

    2016-01-01

    This paper presents an algorithm for the automatic registration of terrestrial point clouds by match selection using an efficiently conditional sampling method - Threshold-independent BaySAC (BAYes SAmpling Consensus) and employs the error metric of average point- To-surface residual to reduce

  20. Interoperability in practice: case study of the Slovenian independence war of 1991

    Directory of Open Access Journals (Sweden)

    Vladimir Prebilič

    2015-08-01

    Full Text Available The paper will examine the theory of the interoperability of armed forces through the case of he Slovenian Independence War of 1991. Although defense system interoperability is a well-established concept, there are many obstacles to its implementation. Some defense systems do not deliberately support the idea of interoperability. One such example is the total defense system in SFR Yugoslavia, which is comprised of two defense components: the Yugoslav People’s Army (YPA and territorial defense structures organized by the federal republic. The question of interoperability is highly relevant since the war was fought between the YPA and the defense forces of the newly proclaimed independent state, Slovenia, who were partners in the total defense concept. Due to the clear asymmetry, interoperability offered a great advantage in the independence war. The Slovenian defense forces were combined into three structures: the former militia as an internal security element, the territorial defense as a military component, and the national protection forces as a “civil” defense element. Although each structure had its own command and organizational structure, during the Slovenian War they were combined into a well-structured and organized defense element that achieved victory against a much stronger, better equipped, and better supported army.

  1. Sequential recovery of macromolecular components of the nucleolus.

    Science.gov (United States)

    Bai, Baoyan; Laiho, Marikki

    2015-01-01

    The nucleolus is involved in a number of cellular processes of importance to cell physiology and pathology, including cell stress responses and malignancies. Studies of macromolecular composition of the nucleolus depend critically on the efficient extraction and accurate quantification of all macromolecular components (e.g., DNA, RNA, and protein). We have developed a TRIzol-based method that efficiently and simultaneously isolates these three macromolecular constituents from the same sample of purified nucleoli. The recovered and solubilized protein can be accurately quantified by the bicinchoninic acid assay and assessed by polyacrylamide gel electrophoresis or by mass spectrometry. We have successfully applied this approach to extract and quantify the responses of all three macromolecular components in nucleoli after drug treatments of HeLa cells, and conducted RNA-Seq analysis of the nucleolar RNA.

  2. PRINCIPAL COMPONENT ANALYSIS (PCA DAN APLIKASINYA DENGAN SPSS

    Directory of Open Access Journals (Sweden)

    Hermita Bus Umar

    2009-03-01

    Full Text Available PCA (Principal Component Analysis are statistical techniques applied to a single set of variables when the researcher is interested in discovering which variables in the setform coherent subset that are relativity independent of one another.Variables that are correlated with one another but largely independent of other subset of variables are combined into factors. The Coals of PCA to which each variables is explained by each dimension. Step in PCA include selecting and mean measuring a set of variables, preparing the correlation matrix, extracting a set offactors from the correlation matrixs. Rotating the factor to increase interpretabilitv and interpreting the result.

  3. Independent control of ion current and ion impact energy onto electrodes in dual frequency plasma devices

    International Nuclear Information System (INIS)

    Boyle, P C; Ellingboe, A R; Turner, M M

    2004-01-01

    Dual frequency capacitive discharges are designed to offer independent control of the flux and energy of ions impacting on an object immersed in a plasma. This is desirable in applications such as the processing of silicon wafers for microelectronics manufacturing. In such discharges, a low frequency component couples predominantly to the ions, while a high frequency component couples predominantly to electrons. Thus, the low frequency component controls the ion energy, while the high frequency component controls the plasma density. Clearly, this desired behaviour is not achieved for arbitrary configurations of the discharge, and in general one expects some unwanted coupling of ion flux and energy. In this paper we use computer simulations with the particle-in-cell method to show that the most important governing parameter is the ratio of the driving frequencies. If the ratio of the high and low frequencies is great enough, essentially independent control of the ion energy and flux is possible by manipulation of the high and low frequency power sources. Other operating parameters, such as pressure, discharge geometry, and absolute power, are of much less significance

  4. Electrical efficiency losses occurred by the air compressor for PEMFC

    International Nuclear Information System (INIS)

    Haubrock, J.; Heideck, G.; Styczynski, Z.

    2006-01-01

    Fuel Cells are characterised by a high efficiency and comparatively small emissions. Depending on their partial load behaviour and their high efficiency, Fuel Cells are well suited for net connected or isolated autonomous energy generators for thermal and electricity power production. Proton Exchange Membrane (PEM) Fuel Cell systems need several external components to produce electricity and thermal power. However, the high theoretical degree of efficiency of 83% is decreased by these components. To reach higher fuel utilisation it is necessary to reduce the energy consumption of these components. In this study, the influence of the air supply compressor on the fuel utilisation is investigated and an optimization strategy was developed. The results were reviewed by a real test set up using an autonomous PEM Fuel Cell system. (authors)

  5. Naive Bayes Bearing Fault Diagnosis Based on Enhanced Independence of Data.

    Science.gov (United States)

    Zhang, Nannan; Wu, Lifeng; Yang, Jing; Guan, Yong

    2018-02-05

    The bearing is the key component of rotating machinery, and its performance directly determines the reliability and safety of the system. Data-based bearing fault diagnosis has become a research hotspot. Naive Bayes (NB), which is based on independent presumption, is widely used in fault diagnosis. However, the bearing data are not completely independent, which reduces the performance of NB algorithms. In order to solve this problem, we propose a NB bearing fault diagnosis method based on enhanced independence of data. The method deals with data vector from two aspects: the attribute feature and the sample dimension. After processing, the classification limitation of NB is reduced by the independence hypothesis. First, we extract the statistical characteristics of the original signal of the bearings effectively. Then, the Decision Tree algorithm is used to select the important features of the time domain signal, and the low correlation features is selected. Next, the Selective Support Vector Machine (SSVM) is used to prune the dimension data and remove redundant vectors. Finally, we use NB to diagnose the fault with the low correlation data. The experimental results show that the independent enhancement of data is effective for bearing fault diagnosis.

  6. Naive Bayes Bearing Fault Diagnosis Based on Enhanced Independence of Data

    Science.gov (United States)

    Zhang, Nannan; Wu, Lifeng; Yang, Jing; Guan, Yong

    2018-01-01

    The bearing is the key component of rotating machinery, and its performance directly determines the reliability and safety of the system. Data-based bearing fault diagnosis has become a research hotspot. Naive Bayes (NB), which is based on independent presumption, is widely used in fault diagnosis. However, the bearing data are not completely independent, which reduces the performance of NB algorithms. In order to solve this problem, we propose a NB bearing fault diagnosis method based on enhanced independence of data. The method deals with data vector from two aspects: the attribute feature and the sample dimension. After processing, the classification limitation of NB is reduced by the independence hypothesis. First, we extract the statistical characteristics of the original signal of the bearings effectively. Then, the Decision Tree algorithm is used to select the important features of the time domain signal, and the low correlation features is selected. Next, the Selective Support Vector Machine (SSVM) is used to prune the dimension data and remove redundant vectors. Finally, we use NB to diagnose the fault with the low correlation data. The experimental results show that the independent enhancement of data is effective for bearing fault diagnosis. PMID:29401730

  7. Resting State Functional Connectivity in Mild Traumatic Brain Injury at the Acute Stage: Independent Component and Seed-Based Analyses

    Science.gov (United States)

    Iraji, Armin; Benson, Randall R.; Welch, Robert D.; O'Neil, Brian J.; Woodard, John L.; Imran Ayaz, Syed; Kulek, Andrew; Mika, Valerie; Medado, Patrick; Soltanian-Zadeh, Hamid; Liu, Tianming; Haacke, E. Mark

    2015-01-01

    Abstract Mild traumatic brain injury (mTBI) accounts for more than 1 million emergency visits each year. Most of the injured stay in the emergency department for a few hours and are discharged home without a specific follow-up plan because of their negative clinical structural imaging. Advanced magnetic resonance imaging (MRI), particularly functional MRI (fMRI), has been reported as being sensitive to functional disturbances after brain injury. In this study, a cohort of 12 patients with mTBI were prospectively recruited from the emergency department of our local Level-1 trauma center for an advanced MRI scan at the acute stage. Sixteen age- and sex-matched controls were also recruited for comparison. Both group-based and individual-based independent component analysis of resting-state fMRI (rsfMRI) demonstrated reduced functional connectivity in both posterior cingulate cortex (PCC) and precuneus regions in comparison with controls, which is part of the default mode network (DMN). Further seed-based analysis confirmed reduced functional connectivity in these two regions and also demonstrated increased connectivity between these regions and other regions of the brain in mTBI. Seed-based analysis using the thalamus, hippocampus, and amygdala regions further demonstrated increased functional connectivity between these regions and other regions of the brain, particularly in the frontal lobe, in mTBI. Our data demonstrate alterations of multiple brain networks at the resting state, particularly increased functional connectivity in the frontal lobe, in response to brain concussion at the acute stage. Resting-state functional connectivity of the DMN could serve as a potential biomarker for improved detection of mTBI in the acute setting. PMID:25285363

  8. Study on efficiency calibration of tritium in liquid scintillation spectrometry

    International Nuclear Information System (INIS)

    Zhai Xiufang; Wang Yaoqin; Li Weiping; Liang Wei; Xu Hui; Zhang Ruirong

    2014-01-01

    The method for efficiency calibration of tritium sample in liquid scintillation spectrometry was presented. The quenching effects from different chemical quenchers (Acidbase, CH_3NO_2, CCl_4, CH_3COCH_3) and color quencher (Na_2CrO_4) were studied. For each quencher, the methods of sample channel ratio (SCR), spectrum index of the sample (SIS) and spectral quenching parameter of the external standard (SQP (E)) were used for efficiency calibration respectively, and three methods were compared. The results show that the quenching from the various chemical quencher can be unified for one chemical quenching for efficiency calibration. There is great difference in the correction curves of chemical quenching and color quenching, and the fact is independent of the used efficiency calibration method. The SCR method is not advantageous for the tritium sample with low radioactivity or strong quenching. The SQP (E) method is independent of the sample count rate, and it is especially suitable for the efficiency calibration of low radioactivity tritium. The SIS method can be used for samples with high radioactivity. The accurate efficiency calibration for various quenching can be carried out by combining the SIS method and the SQP (E) method. (authors)

  9. Principal component regression for crop yield estimation

    CERN Document Server

    Suryanarayana, T M V

    2016-01-01

    This book highlights the estimation of crop yield in Central Gujarat, especially with regard to the development of Multiple Regression Models and Principal Component Regression (PCR) models using climatological parameters as independent variables and crop yield as a dependent variable. It subsequently compares the multiple linear regression (MLR) and PCR results, and discusses the significance of PCR for crop yield estimation. In this context, the book also covers Principal Component Analysis (PCA), a statistical procedure used to reduce a number of correlated variables into a smaller number of uncorrelated variables called principal components (PC). This book will be helpful to the students and researchers, starting their works on climate and agriculture, mainly focussing on estimation models. The flow of chapters takes the readers in a smooth path, in understanding climate and weather and impact of climate change, and gradually proceeds towards downscaling techniques and then finally towards development of ...

  10. Gaussian process based independent analysis for temporal source separation in fMRI

    DEFF Research Database (Denmark)

    Hald, Ditte Høvenhoff; Henao, Ricardo; Winther, Ole

    2017-01-01

    Functional Magnetic Resonance Imaging (fMRI) gives us a unique insight into the processes of the brain, and opens up for analyzing the functional activation patterns of the underlying sources. Task-inferred supervised learning with restrictive assumptions in the regression set-up, restricts...... the exploratory nature of the analysis. Fully unsupervised independent component analysis (ICA) algorithms, on the other hand, can struggle to detect clear classifiable components on single-subject data. We attribute this shortcoming to inadequate modeling of the fMRI source signals by failing to incorporate its...

  11. Dimension-independent likelihood-informed MCMC

    KAUST Repository

    Cui, Tiangang

    2015-10-08

    Many Bayesian inference problems require exploring the posterior distribution of high-dimensional parameters that represent the discretization of an underlying function. This work introduces a family of Markov chain Monte Carlo (MCMC) samplers that can adapt to the particular structure of a posterior distribution over functions. Two distinct lines of research intersect in the methods developed here. First, we introduce a general class of operator-weighted proposal distributions that are well defined on function space, such that the performance of the resulting MCMC samplers is independent of the discretization of the function. Second, by exploiting local Hessian information and any associated low-dimensional structure in the change from prior to posterior distributions, we develop an inhomogeneous discretization scheme for the Langevin stochastic differential equation that yields operator-weighted proposals adapted to the non-Gaussian structure of the posterior. The resulting dimension-independent and likelihood-informed (DILI) MCMC samplers may be useful for a large class of high-dimensional problems where the target probability measure has a density with respect to a Gaussian reference measure. Two nonlinear inverse problems are used to demonstrate the efficiency of these DILI samplers: an elliptic PDE coefficient inverse problem and path reconstruction in a conditioned diffusion.

  12. Dimension-independent likelihood-informed MCMC

    KAUST Repository

    Cui, Tiangang; Law, Kody; Marzouk, Youssef M.

    2015-01-01

    Many Bayesian inference problems require exploring the posterior distribution of high-dimensional parameters that represent the discretization of an underlying function. This work introduces a family of Markov chain Monte Carlo (MCMC) samplers that can adapt to the particular structure of a posterior distribution over functions. Two distinct lines of research intersect in the methods developed here. First, we introduce a general class of operator-weighted proposal distributions that are well defined on function space, such that the performance of the resulting MCMC samplers is independent of the discretization of the function. Second, by exploiting local Hessian information and any associated low-dimensional structure in the change from prior to posterior distributions, we develop an inhomogeneous discretization scheme for the Langevin stochastic differential equation that yields operator-weighted proposals adapted to the non-Gaussian structure of the posterior. The resulting dimension-independent and likelihood-informed (DILI) MCMC samplers may be useful for a large class of high-dimensional problems where the target probability measure has a density with respect to a Gaussian reference measure. Two nonlinear inverse problems are used to demonstrate the efficiency of these DILI samplers: an elliptic PDE coefficient inverse problem and path reconstruction in a conditioned diffusion.

  13. Principal component analysis for neural electron/jet discrimination in highly segmented calorimeters

    International Nuclear Information System (INIS)

    Vassali, M.R.; Seixas, J.M.

    2001-01-01

    A neural electron/jet discriminator based on calorimetry is developed for the second-level trigger system of the ATLAS detector. As preprocessing of the calorimeter information, a principal component analysis is performed on each segment of the two sections (electromagnetic and hadronic) of the calorimeter system, in order to reduce significantly the dimension of the input data space and fully explore the detailed energy deposition profile, which is provided by the highly-segmented calorimeter system. It is shown that projecting calorimeter data onto 33 segmented principal components, the discrimination efficiency of the neural classifier reaches 98.9% for electrons (with only 1% of false alarm probability). Furthermore, restricting data projection onto only 9 components, an electron efficiency of 99.1% is achieved (with 3% of false alarm), which confirms that a fast triggering system may be designed using few components

  14. Influence of the Structure of a Solid-Fuel Mixture on the Thermal Efficiency of the Combustion Chamber of an Engine System

    Science.gov (United States)

    Futko, S. I.; Koznacheev, I. A.; Ermolaeva, E. M.

    2014-11-01

    On the basis of thermodynamic calculations, the features of the combustion of a solid-fuel mixture based on the glycidyl azide polymer were investigated, the thermal cycle of the combustion chamber of a model engine system was analyzed, and the efficiency of this chamber was determined for a wide range of pressures in it and different ratios between the components of the combustible mixture. It was established that, when the pressure in the combustion chamber of an engine system increases, two maxima arise successively on the dependence of the thermal efficiency of the chamber on the weight fractions of the components of the combustible mixture and that the first maximum shifts to the side of smaller concentrations of the glycidyl azide polymer with increase in the pressure in the chamber; the position of the second maximum is independent of this pressure, coincides with the minimum on the dependence of the rate of combustion of the mixture, and corresponds to the point of its structural phase transition at which the mole fractions of the carbon and oxygen atoms in the mixture are equal. The results obtained were interpreted on the basis of the Le-Chatelier principle.

  15. Abrasion Testing of Critical Components of Hydrokinetic Devices

    Energy Technology Data Exchange (ETDEWEB)

    Worthington, Monty [ORPC Alaska; Ali, Muhammad [Ohio University; Ravens, Tom [University of Alaska Anchorage

    2013-12-06

    The objective of the Abrasion Testing of Critical Components of Hydrokinetic Devices (Project) was to test critical components of hydrokinetic devices in waters with high levels of suspended sediment – information that is widely applicable to the hydrokinetic industry. Tidal and river sites in Alaska typically have high suspended sediment concentrations. High suspended sediment also occurs in major rivers and estuaries throughout the world and throughout high latitude locations where glacial inputs introduce silt into water bodies. In assessing the vulnerability of technology components to sediment induced abrasion, one of the greatest concerns is the impact that the sediment may have on device components such as bearings and seals, failures of which could lead to both efficiency loss and catastrophic system failures.

  16. Precision cosmological measurements: Independent evidence for dark energy

    International Nuclear Information System (INIS)

    Bothun, Greg; Hsu, Stephen D.H.; Murray, Brian

    2008-01-01

    Using recent precision measurements of cosmological parameters, we re-examine whether these observations alone, independent of type Ia supernova surveys, are sufficient to imply the existence of dark energy. We find that best measurements of the age of the Universe t 0 , the Hubble parameter H 0 and the matter fraction Ω m strongly favor an equation of state defined by (w<-1/3). This result is consistent with the existence of a repulsive, acceleration-causing component of energy if the Universe is nearly flat

  17. Genomic selection for feed efficiency in dairy cattle

    NARCIS (Netherlands)

    Pryce, J.E.; Wales, W.J.; Haas, de Y.; Veerkamp, R.F.; Hayes, B.J.

    2014-01-01

    Feed is a major component of variable costs associated with dairy systems and is therefore an important consideration for breeding objectives. As a result, measures of feed efficiency are becoming popular traits for genetic analyses. Already, several countries account for feed efficiency in their

  18. Energy Efficient Hydraulic Hybrid Drives

    OpenAIRE

    Rydberg, Karl-Erik

    2009-01-01

    Energy efficiency of propulsion systems for cars, trucks and construction machineries has become one of the most important topics in today’s mobile system design, mainly because of increased fuel costs and new regulations about engine emissions, which is needed to save the environment. To meet the increased requirements on higher efficiency and better functionality, components and systems have been developed over the years. For the last ten years the development of hybrid systems can be divid...

  19. Basic separative power of multi-component isotopes separation in a gas centrifuge

    International Nuclear Information System (INIS)

    Jiang, Hongmin; Lei, Zengguang; Zhuge, Fu

    2008-01-01

    On condition that the overall separation factor per unit exists in centrifuge for multi-component isotopes separation, the relations between separative power of each component and molecular weight have been investigated in the paper while the value function and the separative power of binary-component separation are adopted. The separative power of each component is proportional to the square of the molecular weight difference between its molecular weight and the average molecular weight of other remnant components. In addition, these relations are independent on the number of the components and feed concentrations. The basic separative power and related expressions, suggested in the paper, can be used for estimating the separative power of each component and analyzing the separation characteristics. The most valuable application of the basic separative power is to evaluate the separative capacity of centrifuge for multi-component isotopes. (author)

  20. Selecting the right collaborative components in a construction project

    DEFF Research Database (Denmark)

    Bohnstedt, Kristian Ditlev; Wandahl, Søren

    2018-01-01

    Regardless of context and scope, collaboration is consistently attributed to be an essential determinant of success in construction projects. Researches have long been concerned with the issue of poor collaboration, but situational determination of collaborative components has been overlooked....... The questionnaire was distributed electronically to 440 respondents; after sorting a total of 288 valid responses were obtained. The result is a set of components in a model of structures of collaboration that facilitates a more efficient and effective situational collaboration (EESC), it is denoted as target areas...... structured in type of contract, party and component....

  1. Sunlight-Driven Forging of Amide/Ester Bonds from Three Independent Components: An Approach to Carbamates.

    Science.gov (United States)

    Zhao, Yating; Huang, Binbin; Yang, Chao; Chen, Qingqing; Xia, Wujiong

    2016-11-04

    A photoredox catalytic route to carbamates enabled by visible irradiation (or simply sunlight) has been developed. This process leads to a novel approach to the construction of heterocyclic rings wherein the amide or ester motifs of carbamates were assembled from three isolated components. Large-scale experiments were realized by employing continuous flow techniques, and reuse of photocatalyst demonstrated the green and sustainable aspects of this method.

  2. Research activities of MPA, Stuttgart University, for enhanced safety and reliability of components under complex load

    International Nuclear Information System (INIS)

    Herter, K.H.; Roos, E.; Schuler, X.; Maile, K.

    2004-01-01

    MPA research activities focus on fracture prevention and on the development of a generally applicable method of component integrity testing which, independent of the safety relevance of the components involved, is also part of ageing management. (orig.) [de

  3. Different cellular effects of four anti-inflammatory eye drops on human corneal epithelial cells: independent in active components

    OpenAIRE

    Qu, Mingli; Wang, Yao; Yang, Lingling; Zhou, Qingjun

    2011-01-01

    Purpose To evaluate and compare the cellular effects of four commercially available anti-inflammatory eye drops and their active components on human corneal epithelial cells (HCECs) in vitro. Methods The cellular effects of four eye drops (Bromfenac Sodium Hydrate Eye Drops, Pranoprofen Eye Drops, Diclofenac Sodium Eye Drops, and Tobramycin & Dex Eye Drops) and their corresponding active components were evaluated in an HCEC line with five in vitro assays. Cell proliferation and migration were...

  4. Slow component of VO2 kinetics: Mechanistic bases and practical applications

    DEFF Research Database (Denmark)

    Jones, Andrew M; Grassi, Bruno; Christensen, Peter Møller

    2011-01-01

    with the progressive recruitment of additional (type II) muscle fibers that are presumed to have lower efficiency. Recent studies, however, indicate that muscle efficiency is also lowered (resulting in a 'mirror-image'V¿O2 slow component) during fatiguing, high-intensity exercise in which additional fiber recruitment...

  5. Central Bank Independence, Transparency and Accountability Indexes: a Survey

    Directory of Open Access Journals (Sweden)

    Dumiter Florin Cornel

    2014-06-01

    Full Text Available Recently, the remarkable trend upon central bank independence and the efficient monetary policy were seriously highlighted in the monetary economics field. Starting from 1990s’ central bank independence was at the core of policy making and central banking problems, because of the widespread economical, political, personal and budgetary autonomy of the central bank. Nowadays, we can observe an increasing trend upon central bank transparency, for evaluating more accurate the central bank’s performances by the wide public, mass-media and financial markets. Consequently, a central bank must encompass a high degree of accountability and responsibility, because of the final liability in case of failure. In this paper we present, analyze and assess the construction of the most important indices regarding central bank independence, transparency and accountability in a chronological manner, presenting also the advantages and disadvantages of these indices related to actual practices of central banks. Moreover, we analyze the analytical results of the empirical testing of these indices with a considerable impact upon the developed and developing country group. In regard with the empirical results of different authors, we suggest the importance and the necessity for constructing an aggregate index for measuring central bank independence, transparency and accountability, based on de jure stipulations and the actual practices of the central banks.

  6. Initial Ada components evaluation

    Science.gov (United States)

    Moebes, Travis

    1989-01-01

    The SAIC has the responsibility for independent test and validation of the SSE. They have been using a mathematical functions library package implemented in Ada to test the SSE IV and V process. The library package consists of elementary mathematical functions and is both machine and accuracy independent. The SSE Ada components evaluation includes code complexity metrics based on Halstead's software science metrics and McCabe's measure of cyclomatic complexity. Halstead's metrics are based on the number of operators and operands on a logical unit of code and are compiled from the number of distinct operators, distinct operands, and total number of occurrences of operators and operands. These metrics give an indication of the physical size of a program in terms of operators and operands and are used diagnostically to point to potential problems. McCabe's Cyclomatic Complexity Metrics (CCM) are compiled from flow charts transformed to equivalent directed graphs. The CCM is a measure of the total number of linearly independent paths through the code's control structure. These metrics were computed for the Ada mathematical functions library using Software Automated Verification and Validation (SAVVAS), the SSE IV and V tool. A table with selected results was shown, indicating that most of these routines are of good quality. Thresholds for the Halstead measures indicate poor quality if the length metric exceeds 260 or difficulty is greater than 190. The McCabe CCM indicated a high quality of software products.

  7. Experience with an Independent Study Program in Pathophysiology for Doctor of Pharmacy Students.

    Science.gov (United States)

    Nahata, Milap C.

    1986-01-01

    A pharmacy doctoral program's independent-study component in pathophysiology, supported by computer-assisted instruction and self-evaluation, has the advantages of self-pacing, reduced faculty time commitment, and increased ability to work effectively with physicians. Disadvantages include student feeling of isolation, imbalanced content, and…

  8. Using Independent Research Projects to Foster Learning in the Comparative Vertebrate Anatomy Laboratory

    Science.gov (United States)

    Ghedotti, Michael J.; Fielitz, Christopher; Leonard, Daniel J.

    2005-01-01

    This paper presents a teaching methodology involving an independent research project component for use in undergraduate Comparative Vertebrate Anatomy laboratory courses. The proposed project introduces cooperative, active learning in a research context to comparative vertebrate anatomy. This project involves pairs or groups of three students…

  9. Developing Reusable and Reconfigurable Real-Time Software using Aspects and Components

    OpenAIRE

    Tešanović, Aleksandra

    2006-01-01

    Our main focus in this thesis is on providing guidelines, methods, and tools for design, configuration, and analysis of configurable and reusable real-time software, developed using a combination of aspect-oriented and component-based software development. Specifically, we define a reconfigurable real-time component model (RTCOM) that describes how a real-time component, supporting aspects and enforcing information hiding, could efficiently be designed and implemented. In this context, we out...

  10. Different cellular effects of four anti-inflammatory eye drops on human corneal epithelial cells: independent in active components.

    Science.gov (United States)

    Qu, Mingli; Wang, Yao; Yang, Lingling; Zhou, Qingjun

    2011-01-01

    To evaluate and compare the cellular effects of four commercially available anti-inflammatory eye drops and their active components on human corneal epithelial cells (HCECs) in vitro. The cellular effects of four eye drops (Bromfenac Sodium Hydrate Eye Drops, Pranoprofen Eye Drops, Diclofenac Sodium Eye Drops, and Tobramycin & Dex Eye Drops) and their corresponding active components were evaluated in an HCEC line with five in vitro assays. Cell proliferation and migration were measured using 3-(4,5)-dimethylthiahiazo (-z-y1)-3 5-di-phenytetrazoliumromide (MTT) assay and transwell migration assay. Cell damage was determined with the lactate dehydrogenase (LDH) assay. Cell viability and median lethal time (LT₅₀) were measured by 7-amino-actinomycin D (7-AAD) staining and flow cytometry analysis. Cellular effects after exposure of HCECs to the four anti-inflammatory eye drops were concentration dependent. The differences of cellular toxicity on cell proliferation became significant at lower concentrations (Eye Drops showed significant increasing effects on cell damage and viability when compared with the other three solutions. Tobramycin & Dex Eye Drops inhibited the migration of HCECs significantly. Tobramycin & Dex Eye Drops showed the quickest effect on cell viability: the LT₅₀ was 3.28, 9.23, 10.38, and 23.80 min for Tobramycin & Dex Eye Drops, Diclofenac Sodium Eye Drops, Pranoprofen Eye Drops, and Bromfenac Sodium Hydrate Eye Drops, respectively. However, the comparisons of cellular toxicity revealed significant differences between the eye drops and their active components under the same concentration. The corneal epithelial toxicity differences among the active components of the four eye drops became significant as higher concentration (>0.020%). The four anti-inflammatory eye drops showed different cellular effects on HCECs, and the toxicity was not related with their active components, which provides new reference for the clinical application and drug

  11. MultiComponent Exercise and theRApeutic lifeStyle (CERgAS) intervention to improve physical performance and maintain independent living among urban poor older people--a cluster randomised controlled trial.

    Science.gov (United States)

    Loh, Debbie Ann; Hairi, Noran Naqiah; Choo, Wan Yuen; Mohd Hairi, Farizah; Peramalah, Devi; Kandiben, Shathanapriya; Lee, Pek Ling; Gani, Norlissa; Madzlan, Mohamed Faris; Abd Hamid, Mohd Alif Idham; Akram, Zohaib; Chu, Ai Sean; Bulgiba, Awang; Cumming, Robert G

    2015-02-11

    The ability of older people to function independently is crucial as physical disability and functional limitation have profound impacts on health. Interventions that either delay the onset of frailty or attenuate its severity potentially have cascading benefits for older people, their families and society. This study aims to develop and evaluate the effectiveness of a multiComponent Exercise and theRApeutic lifeStyle (CERgAS) intervention program targeted at improving physical performance and maintaining independent living as compared to general health education among older people in an urban poor setting in Malaysia. This cluster randomised controlled trial will be a 6-week community-based intervention programme for older people aged 60 years and above from urban poor settings. A minimum of 164 eligible participants will be recruited from 8 clusters (low-cost public subsidised flats) and randomised to the intervention and control arm. This study will be underpinned by the Health Belief Model with an emphasis towards self-efficacy. The intervention will comprise multicomponent group exercise sessions, nutrition education, oral care education and on-going support and counselling. These will be complemented with a kit containing practical tips on exercise, nutrition and oral care after each session. Data will be collected over four time points; at baseline, immediately post-intervention, 3-months and 6-months follow-up. Findings from this trial will potentially provide valuable evidence to improve physical function and maintain independence among older people from low-resource settings. This will inform health policies and identify locally acceptable strategies to promote healthy aging, prevent and delay functional decline among older Malaysian adults. ISRCTN22749696.

  12. Probabilistic deletion of copies of linearly independent quantum states

    International Nuclear Information System (INIS)

    Feng Jian; Gao Yunfeng; Wang Jisuo; Zhan Mingsheng

    2002-01-01

    We show that each of two copies of the nonorthogonal states randomly selected from a certain set S can be probabilistically deleted by a general unitary-reduction operation if and only if the states are linearly independent. We derive a tight bound on the best possible deleting efficiencies. These results for 2→1 probabilistic deleting are also generalized into the case of N→M deleting (N,M positive integers and N>M)

  13. Sustainable Development in Indian Automotive Component Clusters

    Science.gov (United States)

    Bhaskaran, E.

    2013-01-01

    India is the world's second fastest growing auto market and boasts of the sixth largest automobile industry after China, the US, Germany, Japan and Brazil. The Indian auto component industry recorded its highest year-on-year growth of 34.2 % in 2010-2011, raking in revenue of US 39.9 billion; major contribution coming from exports at US five billion and fresh investment from the US at around US two billion. For inclusive growth and sustainable development most of the auto components manufacturers has adopted the cluster development approach. The objective is to study the technical efficiency (θ), peer weights (λ i ), input slacks (S-) and output slacks (S+) of four Auto Component Clusters (ACC) in India. The methodology adopted is using Data Envelopment Analysis of Input Oriented Banker Charnes Cooper Model by taking number of units and number of employments as inputs and sales and exports in crores as an outputs. The non-zero λ i 's represents the weights for efficient clusters. The S > 0 obtained for one ACC reveals the excess no. of units (S-) and employment (S-) and shortage in sales (S+) and exports (S+). However the variable returns to scale are increasing for three clusters, constant for one more cluster and with nil decrease. To conclude, for inclusive growth and sustainable development, the inefficient ACC should increase their turnover and exports, as decrease in no. of enterprises and employment is practically not possible. Moreover for sustainable development, the ACC should strengthen infrastructure interrelationships, technology interrelationships, procurement interrelationships, production interrelationships and marketing interrelationships to increase productivity and efficiency to compete in the world market.

  14. Software components for medical image visualization and surgical planning

    Science.gov (United States)

    Starreveld, Yves P.; Gobbi, David G.; Finnis, Kirk; Peters, Terence M.

    2001-05-01

    Purpose: The development of new applications in medical image visualization and surgical planning requires the completion of many common tasks such as image reading and re-sampling, segmentation, volume rendering, and surface display. Intra-operative use requires an interface to a tracking system and image registration, and the application requires basic, easy to understand user interface components. Rapid changes in computer and end-application hardware, as well as in operating systems and network environments make it desirable to have a hardware and operating system as an independent collection of reusable software components that can be assembled rapidly to prototype new applications. Methods: Using the OpenGL based Visualization Toolkit as a base, we have developed a set of components that implement the above mentioned tasks. The components are written in both C++ and Python, but all are accessible from Python, a byte compiled scripting language. The components have been used on the Red Hat Linux, Silicon Graphics Iris, Microsoft Windows, and Apple OS X platforms. Rigorous object-oriented software design methods have been applied to ensure hardware independence and a standard application programming interface (API). There are components to acquire, display, and register images from MRI, MRA, CT, Computed Rotational Angiography (CRA), Digital Subtraction Angiography (DSA), 2D and 3D ultrasound, video and physiological recordings. Interfaces to various tracking systems for intra-operative use have also been implemented. Results: The described components have been implemented and tested. To date they have been used to create image manipulation and viewing tools, a deep brain functional atlas, a 3D ultrasound acquisition and display platform, a prototype minimally invasive robotic coronary artery bypass graft planning system, a tracked neuro-endoscope guidance system and a frame-based stereotaxy neurosurgery planning tool. The frame-based stereotaxy module has been

  15. Novel method for detecting the hadronic component of extensive air showers

    International Nuclear Information System (INIS)

    Gromushkin, D. M.; Volchenko, V. I.; Petrukhin, A. A.; Stenkin, Yu. V.; Stepanov, V. I.; Shchegolev, O. B.; Yashin, I. I.

    2015-01-01

    A novel method for studying the hadronic component of extensive air showers (EAS) is proposed. The method is based on recording thermal neutrons accompanying EAS with en-detectors that are sensitive to two EAS components: an electromagnetic (e) component and a hadron component in the form of neutrons (n). In contrast to hadron calorimeters used in some arrays, the proposed method makes it possible to record the hadronic component over the whole area of the array. The efficiency of a prototype array that consists of 32 en-detectors was tested for a long time, and some parameters of the neutron EAS component were determined

  16. Life-time management for mechanical components; Lebensdauermanagement mechanischer Komponenten

    Energy Technology Data Exchange (ETDEWEB)

    Roos, E. [Stuttgart Univ. (DE). Materialpruefungsanstalt (MPA)

    2006-07-01

    The safety and economic efficiency of industrial systems depend on the quality of components and systems. In the field of power generation, power plants should be safe and have high availability and minimum specific generation cost. Life management is essential for this. Depending on the safety relevance of systems, structures and components (SSC), this includes proofs of integrity, time-oriented or condition-oriented preventive maintenance, or just failure-oriented maintenance. (orig.)

  17. Every Day We're Shufflin': Empowering Students during In-School Independent Reading

    Science.gov (United States)

    Hall, Katrina W.; Hedrick, Wanda B.; Williams, Lunetta M.

    2014-01-01

    Research in the field of literacy has identified choice as a key component affecting students' reading habits and their resulting literacy growth. This article discusses an in-school independent reading project in which students are provided the freedom to choose books, use ambient music, and engage in book talks. The children showed increased…

  18. Parameter estimation of component reliability models in PSA model of Krsko NPP

    International Nuclear Information System (INIS)

    Jordan Cizelj, R.; Vrbanic, I.

    2001-01-01

    In the paper, the uncertainty analysis of component reliability models for independent failures is shown. The present approach for parameter estimation of component reliability models in NPP Krsko is presented. Mathematical approaches for different types of uncertainty analyses are introduced and used in accordance with some predisposed requirements. Results of the uncertainty analyses are shown in an example for time-related components. As the most appropriate uncertainty analysis proved the Bayesian estimation with the numerical estimation of a posterior, which can be approximated with some appropriate probability distribution, in this paper with lognormal distribution.(author)

  19. Interdependency in Multimodel Climate Projections: Component Replication and Result Similarity

    Science.gov (United States)

    Boé, Julien

    2018-03-01

    Multimodel ensembles are the main way to deal with model uncertainties in climate projections. However, the interdependencies between models that often share entire components make it difficult to combine their results in a satisfactory way. In this study, how the replication of components (atmosphere, ocean, land, and sea ice) between climate models impacts the proximity of their results is quantified precisely, in terms of climatological means and future changes. A clear relationship exists between the number of components shared by climate models and the proximity of their results. Even the impact of a single shared component is generally visible. These conclusions are true at both the global and regional scales. Given available data, it cannot be robustly concluded that some components are more important than others. Those results provide ways to estimate model interdependencies a priori rather than a posteriori based on their results, in order to define independence weights.

  20. IMRT: Improvement in treatment planning efficiency using NTCP calculation independent of the dose-volume-histogram

    International Nuclear Information System (INIS)

    Grigorov, Grigor N.; Chow, James C.L.; Grigorov, Lenko; Jiang, Runqing; Barnett, Rob B.

    2006-01-01

    The normal tissue complication probability (NTCP) is a predictor of radiobiological effect for organs at risk (OAR). The calculation of the NTCP is based on the dose-volume-histogram (DVH) which is generated by the treatment planning system after calculation of the 3D dose distribution. Including the NTCP in the objective function for intensity modulated radiation therapy (IMRT) plan optimization would make the planning more effective in reducing the postradiation effects. However, doing so would lengthen the total planning time. The purpose of this work is to establish a method for NTCP determination, independent of a DVH calculation, as a quality assurance check and also as a mean of improving the treatment planning efficiency. In the study, the CTs of ten randomly selected prostate patients were used. IMRT optimization was performed with a PINNACLE3 V 6.2b planning system, using planning target volume (PTV) with margins in the range of 2 to 10 mm. The DVH control points of the PTV and OAR were adapted from the prescriptions of Radiation Therapy Oncology Group protocol P-0126 for an escalated prescribed dose of 82 Gy. This paper presents a new model for the determination of the rectal NTCP ( R NTCP). The method uses a special function, named GVN (from Gy, Volume, NTCP), which describes the R NTCP if 1 cm 3 of the volume of intersection of the PTV and rectum (R int ) is irradiated uniformly by a dose of 1 Gy. The function was 'geometrically' normalized using a prostate-prostate ratio (PPR) of the patients' prostates. A correction of the R NTCP for different prescribed doses, ranging from 70 to 82 Gy, was employed in our model. The argument of the normalized function is the R int , and parameters are the prescribed dose, prostate volume, PTV margin, and PPR. The R NTCPs of another group of patients were calculated by the new method and the resulting difference was <±5% in comparison to the NTCP calculated by the PINNACLE3 software where Kutcher's dose

  1. Age-related alterations of brain network underlying the retrieval of emotional autobiographical memories: an fMRI study using independent component analysis.

    Science.gov (United States)

    Ge, Ruiyang; Fu, Yan; Wang, Dahua; Yao, Li; Long, Zhiying

    2014-01-01

    Normal aging has been shown to modulate the neural underpinnings of autobiographical memory and emotion processing. Moreover, previous researches have suggested that aging produces a "positivity effect" in autobiographical memory. Although a few imaging studies have investigated the neural mechanism of the positivity effect, the neural substrates underlying the positivity effect in emotional autobiographical memory is unclear. To understand the age-related neural changes in emotional autobiographical memory that underlie the positivity effect, the present functional magnetic resonance imaging (fMRI) study used the independent component analysis (ICA) method to compare brain networks in younger and older adults as they retrieved positive and negative autobiographical events. Compared to their younger counterparts, older adults reported relatively higher positive feelings when retrieving emotional autobiographical events. Imaging data indicated an age-related reversal within the ventromedial prefrontal/anterior cingulate cortex (VMPFC/ACC) and the left amygdala of the brain networks that were engaged in the retrieval of autobiographical events with different valence. The retrieval of negative events compared to positive events induced stronger activity in the VMPFC/ACC and weaker activity in the amygdala for the older adults, whereas the younger adults showed a reversed pattern. Moreover, activity in the VMPFC/ACC within the task-related networks showed a negative correlation with the emotional valence intensity. These results may suggest that the positivity effect in older adults' autobiographical memories is potentially due to age-related changes in controlled emotional processing implemented by the VMPFC/ACC-amygdala circuit.

  2. Age-related alterations of brain network underlying the retrieval of emotional autobiographical memories: An fMRI study using independent component analysis

    Directory of Open Access Journals (Sweden)

    Ruiyang eGe

    2014-08-01

    Full Text Available Normal aging has been shown to modulate the neural underpinnings of autobiographical memory and emotion processing. Moreover, previous researches have suggested that aging produces a positivity effect in autobiographical memory. Although a few imaging studies have investigated the neural mechanism of the positivity effect, the neural substrates underlying the positivity effect in emotional autobiographical memory is unclear. To understand the age-related neural changes in emotional autobiographical memory that underlie the positivity effect, the present functional magnetic resonance imaging (fMRI study used the independent component analysis (ICA method to compare brain networks in younger and older adults as they retrieved positive and negative autobiographical events. Compared to their younger counterparts, older adults reported relatively higher positive feelings when retrieving emotional autobiographical events. Imaging data indicated an age-related reversal within the ventromedial prefrontal/anterior cingulate cortex (VMPFC/ACC and the left amygdala of the brain networks that were engaged in the retrieval of autobiographical events with different valence. The retrieval of negative events compared to positive events induced stronger activity in the VMPFC/ACC and weaker activity in the amygdala for the older adults, whereas the younger adults showed a reversed pattern. Moreover, activity in the VMPFC/ACC within the task-related networks showed a negative correlation with the emotional valence intensity. These results may suggest that the positivity effect in older adults’ autobiographical memories is potentially due to age-related changes in controlled emotional processing implemented by the VMPFC/ACC-amygdala circuit.

  3. Design Optimization Method for Composite Components Based on Moment Reliability-Sensitivity Criteria

    Science.gov (United States)

    Sun, Zhigang; Wang, Changxi; Niu, Xuming; Song, Yingdong

    2017-08-01

    In this paper, a Reliability-Sensitivity Based Design Optimization (RSBDO) methodology for the design of the ceramic matrix composites (CMCs) components has been proposed. A practical and efficient method for reliability analysis and sensitivity analysis of complex components with arbitrary distribution parameters are investigated by using the perturbation method, the respond surface method, the Edgeworth series and the sensitivity analysis approach. The RSBDO methodology is then established by incorporating sensitivity calculation model into RBDO methodology. Finally, the proposed RSBDO methodology is applied to the design of the CMCs components. By comparing with Monte Carlo simulation, the numerical results demonstrate that the proposed methodology provides an accurate, convergent and computationally efficient method for reliability-analysis based finite element modeling engineering practice.

  4. Analysis of Thermo-Mechanical Distortions in Sliding Components : An ALE Approach

    NARCIS (Netherlands)

    Owczarek, P.; Geijselaers, H.J.M.

    2008-01-01

    A numerical technique for analysis of heat transfer and thermal distortion in reciprocating sliding components is proposed. In this paper we utilize the Arbitrary Lagrangian Eulerian (ALE) description where the mesh displacement can be controlled independently from the material displacement. A

  5. Only low frequency event-related EEG activity is compromised in multiple sclerosis: insights from an independent component clustering analysis.

    Directory of Open Access Journals (Sweden)

    Hanni Kiiski

    Full Text Available Cognitive impairment (CI, often examined with neuropsychological tests such as the Paced Auditory Serial Addition Test (PASAT, affects approximately 65% of multiple sclerosis (MS patients. The P3b event-related potential (ERP, evoked when an infrequent target stimulus is presented, indexes cognitive function and is typically compared across subjects' scalp electroencephalography (EEG data. However, the clustering of independent components (ICs is superior to scalp-based EEG methods because it can accommodate the spatiotemporal overlap inherent in scalp EEG data. Event-related spectral perturbations (ERSPs; event-related mean power spectral changes and inter-trial coherence (ITCs; event-related consistency of spectral phase reveal a more comprehensive overview of EEG activity. Ninety-five subjects (56 MS patients, 39 controls completed visual and auditory two-stimulus P3b event-related potential tasks and the PASAT. MS patients were also divided into CI and non-CI groups (n = 18 in each based on PASAT scores. Data were recorded from 128-scalp EEG channels and 4 IC clusters in the visual, and 5 IC clusters in the auditory, modality were identified. In general, MS patients had significantly reduced ERSP theta power versus controls, and a similar pattern was observed for CI vs. non-CI MS patients. The ITC measures were also significantly different in the theta band for some clusters. The finding that MS patients had reduced P3b task-related theta power in both modalities is a reflection of compromised connectivity, likely due to demyelination, that may have disrupted early processes essential to P3b generation, such as orientating and signal detection. However, for posterior sources, MS patients had a greater decrease in alpha power, normally associated with enhanced cognitive function, which may reflect a compensatory mechanism in response to the compromised early cognitive processing.

  6. Transition I efficiency and victory in volleyball matches

    Directory of Open Access Journals (Sweden)

    Herbert Ugrinowitsch

    2014-03-01

    Full Text Available The present study investigated the correlation between Transition Iwith victory in volleyball matches. The 2002 South-American Youth Men's Championship was recorded and the Transition I was analyzed and classified as negative, null or positive. Results of the efficiency in Transition I was calculated using t test for independent samples and compared to the efficiency between teams during each set and matches. Spearman correlation assessed the relationship between efficiency in each set and results of the matches with the final ranking in the championship. The results showed that the winning teams exhibited higher efficiency in Transition I, as well as a positive relationship of higher efficiency in Transition I with all of their results. The higher efficiency in Transition I is related to victory in volleyball matches.

  7. Optimization of thermal efficiency of nuclear central power like as PWR

    International Nuclear Information System (INIS)

    Lapa, Nelbia da Silva

    2005-10-01

    The main purpose of this work is the definition of operational conditions for the steam and power conservation of Pressurized Water Reactor (PWR) plant in order to increase its system thermal efficiency without changing any component, based on the optimization of operational parameters of the plant. The thermal efficiency is calculated by a thermal balance program, based on conservation equations for homogeneous modeling. The circuit coefficients are estimated by an optimization tool, allowing a more realistic thermal balance for the plans under analysis, as well as others parameters necessary to some component models. With the operational parameter optimization, it is possible to get a level of thermal efficiency that increase capital gain, due to a better relationship between the electricity production and the amount of fuel used, without any need to change components plant. (author)

  8. Efficient and reliable 3D dose quality assurance for IMRT by combining independent dose calculations with measurements

    NARCIS (Netherlands)

    Visser, R.; Wauben, D. J. L.; de Groot, M.; Godart, J.; Langendijk, J. A.; van t Veld, Aart A.; Korevaar, E. W.

    Purpose: Advanced radiotherapy treatments require appropriate quality assurance (QA) to verify 3D dose distributions. Moreover, increase in patient numbers demand efficient QA-methods. In this study, a time efficient method that combines model-based QA and measurement-based QA was developed; i.e.,

  9. Comparing Server Energy Use and Efficiency Using Small Sample Sizes

    Energy Technology Data Exchange (ETDEWEB)

    Coles, Henry C.; Qin, Yong; Price, Phillip N.

    2014-11-01

    This report documents a demonstration that compared the energy consumption and efficiency of a limited sample size of server-type IT equipment from different manufacturers by measuring power at the server power supply power cords. The results are specific to the equipment and methods used. However, it is hoped that those responsible for IT equipment selection can used the methods described to choose models that optimize energy use efficiency. The demonstration was conducted in a data center at Lawrence Berkeley National Laboratory in Berkeley, California. It was performed with five servers of similar mechanical and electronic specifications; three from Intel and one each from Dell and Supermicro. Server IT equipment is constructed using commodity components, server manufacturer-designed assemblies, and control systems. Server compute efficiency is constrained by the commodity component specifications and integration requirements. The design freedom, outside of the commodity component constraints, provides room for the manufacturer to offer a product with competitive efficiency that meets market needs at a compelling price. A goal of the demonstration was to compare and quantify the server efficiency for three different brands. The efficiency is defined as the average compute rate (computations per unit of time) divided by the average energy consumption rate. The research team used an industry standard benchmark software package to provide a repeatable software load to obtain the compute rate and provide a variety of power consumption levels. Energy use when the servers were in an idle state (not providing computing work) were also measured. At high server compute loads, all brands, using the same key components (processors and memory), had similar results; therefore, from these results, it could not be concluded that one brand is more efficient than the other brands. The test results show that the power consumption variability caused by the key components as a

  10. Parallel PDE-Based Simulations Using the Common Component Architecture

    International Nuclear Information System (INIS)

    McInnes, Lois C.; Allan, Benjamin A.; Armstrong, Robert; Benson, Steven J.; Bernholdt, David E.; Dahlgren, Tamara L.; Diachin, Lori; Krishnan, Manoj Kumar; Kohl, James A.; Larson, J. Walter; Lefantzi, Sophia; Nieplocha, Jarek; Norris, Boyana; Parker, Steven G.; Ray, Jaideep; Zhou, Shujia

    2006-01-01

    The complexity of parallel PDE-based simulations continues to increase as multimodel, multiphysics, and multi-institutional projects become widespread. A goal of component based software engineering in such large-scale simulations is to help manage this complexity by enabling better interoperability among various codes that have been independently developed by different groups. The Common Component Architecture (CCA) Forum is defining a component architecture specification to address the challenges of high-performance scientific computing. In addition, several execution frameworks, supporting infrastructure, and general purpose components are being developed. Furthermore, this group is collaborating with others in the high-performance computing community to design suites of domain-specific component interface specifications and underlying implementations. This chapter discusses recent work on leveraging these CCA efforts in parallel PDE-based simulations involving accelerator design, climate modeling, combustion, and accidental fires and explosions. We explain how component technology helps to address the different challenges posed by each of these applications, and we highlight how component interfaces built on existing parallel toolkits facilitate the reuse of software for parallel mesh manipulation, discretization, linear algebra, integration, optimization, and parallel data redistribution. We also present performance data to demonstrate the suitability of this approach, and we discuss strategies for applying component technologies to both new and existing applications

  11. P.L. 110-140, "Energy Independence and Security Act of 2007", 2007

    Energy Technology Data Exchange (ETDEWEB)

    None

    2007-12-19

    The Energy Independence and Security Act of 2007 (EISA), signed into law on December 19, 2007, set forth an agenda for improving U.S. energy security across the entire economy. While industrial energy efficiency is specifically called out in Title IV, Subtitle D, other EISA provisions also apply to AMO activities.

  12. Efficient and reliable 3D dose quality assurance for IMRT by combining independent dose calculations with measurements

    International Nuclear Information System (INIS)

    Visser, R.; Wauben, D. J. L.; Godart, J.; Langendijk, J. A.; Veld, A. A. van't; Korevaar, E. W.; Groot, M. de

    2013-01-01

    Purpose: Advanced radiotherapy treatments require appropriate quality assurance (QA) to verify 3D dose distributions. Moreover, increase in patient numbers demand efficient QA-methods. In this study, a time efficient method that combines model-based QA and measurement-based QA was developed; i.e., the hybrid-QA. The purpose of this study was to determine the reliability of the model-based QA and to evaluate time efficiency of the hybrid-QA method. Methods: Accuracy of the model-based QA was determined by comparison of COMPASS calculated dose with Monte Carlo calculations for heterogeneous media. In total, 330 intensity modulated radiation therapy (IMRT) treatment plans were evaluated based on the mean gamma index (GI) with criteria of 3%/3mm and classification of PASS (GI ≤ 0.4), EVAL (0.4 0.6), and FAIL (GI ≥ 0.6). Agreement between model-based QA and measurement-based QA was determined for 48 treatment plans, and linac stability was verified for 15 months. Finally, time efficiency improvement of the hybrid-QA was quantified for four representative treatment plans. Results: COMPASS calculated dose was in agreement with Monte Carlo dose, with a maximum error of 3.2% in heterogeneous media with high density (2.4 g/cm 3 ). Hybrid-QA results for IMRT treatment plans showed an excellent PASS rate of 98% for all cases. Model-based QA was in agreement with measurement-based QA, as shown by a minimal difference in GI of 0.03 ± 0.08. Linac stability was high with an average GI of 0.28 ± 0.04. The hybrid-QA method resulted in a time efficiency improvement of 15 min per treatment plan QA compared to measurement-based QA. Conclusions: The hybrid-QA method is adequate for efficient and accurate 3D dose verification. It combines time efficiency of model-based QA with reliability of measurement-based QA and is suitable for implementation within any radiotherapy department.

  13. 77 FR 38743 - Energy Efficiency Program for Consumer Products: Energy Conservation Standards for Battery...

    Science.gov (United States)

    2012-06-29

    ... Efficiency Program for Consumer Products: Energy Conservation Standards for Battery Chargers and External Power Supplies AGENCY: Office of Energy Efficiency and Renewable Energy, Department of Energy. ACTION... Energy Efficiency and Renewable Energy, Building Technologies Program, EE-2J, 1000 Independence Avenue SW...

  14. Scaffolded Silent Reading (ScSR): Advocating a Policy for Adolescents' Independent Reading

    Science.gov (United States)

    Walker, Karen P.

    2013-01-01

    Structured independent reading among students is often a vital missing component in many school districts' literacy curriculum. The nationwide implementation of the Common Core State Standards (CCSS) requires districts to re-think their literacy curriculum and what instruction might entail in order for students to demonstrate proficiency in…

  15. Validated biomechanical model for efficiency and speed of rowing.

    Science.gov (United States)

    Pelz, Peter F; Vergé, Angela

    2014-10-17

    The speed of a competitive rowing crew depends on the number of crew members, their body mass, sex and the type of rowing-sweep rowing or sculling. The time-averaged speed is proportional to the rower's body mass to the 1/36th power, to the number of crew members to the 1/9th power and to the physiological efficiency (accounted for by the rower's sex) to the 1/3rd power. The quality of the rowing shell and propulsion system is captured by one dimensionless parameter that takes the mechanical efficiency, the shape and drag coefficient of the shell and the Froude propulsion efficiency into account. We derive the biomechanical equation for the speed of rowing by two independent methods and further validate it by successfully predicting race times. We derive the theoretical upper limit of the Froude propulsion efficiency for low viscous flows. This upper limit is shown to be a function solely of the velocity ratio of blade to boat speed (i.e., it is completely independent of the blade shape), a result that may also be of interes